阅读说明：本技术 至物联网的自动扶梯控制数据 (Escalator control data to internet of things ) 是由 D·O·帕尔克 于 2020-11-13 设计创作，主要内容包括：本发明涉及至物联网的自动扶梯控制数据。一种用于自动扶梯的监测系统包括：本地网关装置；分析引擎,其通过云计算网络与本地网关装置通信；感测设备,其通过短程无线协议与本地网关装置无线通信,感测设备包括：配置成检测自动扶梯的加速度数据的惯性测量单元传感器,其中,感测设备和本地网关装置中的至少一个配置成至少响应于加速度数据来确定自动扶梯的基于状况的监测(CBM)健康分数,并且其中本地网关配置成经由长程无线通信协议将自动扶梯的CBM健康分数以数据包的形式无线传输到云计算网络。(The invention relates to escalator control data of the Internet of things. A monitoring system for an escalator comprising: a local gateway device; an analysis engine in communication with a local gateway device over a cloud computing network; a sensing device that wirelessly communicates with a local gateway apparatus through a short-range wireless protocol, the sensing device comprising: an inertial measurement unit sensor configured to detect acceleration data of the escalator, wherein at least one of the sensing device and the local gateway device is configured to determine a condition-based monitoring (CBM) health score of the escalator at least in response to the acceleration data, and wherein the local gateway is configured to wirelessly transmit the CBM health score of the escalator in data packets to the cloud computing network via the long-range wireless communication protocol.)

1. A monitoring system for an escalator, the monitoring system comprising:

a local gateway device;

an analysis engine in communication with the local gateway device over a cloud computing network;

a sensing apparatus in wireless communication with the local gateway device over a short-range wireless protocol, the sensing apparatus comprising:

an inertial measurement unit sensor configured to detect acceleration data of the escalator,

wherein at least one of the sensing device and the local gateway device is configured to determine a condition-based monitoring (CBM) health score for the escalator at least in response to the acceleration data, and

wherein the local gateway is configured to wirelessly transmit the CBM health score of the escalator in data packets to the cloud computing network via a long-range wireless communication protocol.

2. The monitoring system of claim 1, further comprising:

a microphone configured to detect sound data of the escalator,

wherein the CBM health score is determined in response to at least one of the acceleration data and the sound data.

3. The monitoring system of claim 1, further comprising:

an application for a computing device in wireless communication with the network, the application configured to display the CBM health score of the escalator on a display device of the computing device.

4. The monitoring system of claim 3, wherein the application is configured to display a user input interface for adjusting the CBM health score via user input.

5. The monitoring system of claim 1, wherein the data packets are transmitted using MQTT data compression.

6. The monitoring system of claim 2, wherein the sensing device is configured to determine the CBM health score of the escalator in response to at least one of the acceleration data and the sound data.

7. The monitoring system of claim 2, wherein the sensing device is configured to transmit the acceleration data and the sound data to the local gateway device, and the local gateway device is configured to determine the CBM health score of the escalator in response to at least one of the acceleration data and the sound data.

8. The monitoring system of claim 1, wherein the sensing device is positioned within a handrail of the escalator and moves with the handrail.

9. The monitoring system of claim 1, wherein the sensing device is attached to and moves with a step chain of the escalator.

10. The monitoring system of claim 1, wherein the sensing device is stationary and positioned near a step chain of the escalator or a drive machine of the escalator.

11. The monitoring system of claim 1, wherein the sensing device is attached to a moving member of a drive machine of the escalator.

12. The monitoring system of claim 11, wherein the moving member of the drive machine is an output sheave that drives a step chain of the escalator.

13. The monitoring system of claim 1, wherein the sensing device uses the inertial measurement unit sensor to detect low frequency vibrations of less than 10 Hz.

14. The monitoring system of claim 2, wherein the sensing device uses the microphone to detect high frequency vibrations greater than 10 Hz.

15. A method of monitoring an escalator, the method comprising:

detecting acceleration data of the escalator using an inertial measurement unit sensor positioned in a sensing device;

determining a condition-based monitoring (CBM) health score in response to at least the acceleration data; and

wirelessly transmitting the CBM health score of the escalator in data packets to a cloud computing network via a long-range wireless communication protocol.

16. The method of claim 15, further comprising:

detecting sound data of the escalator using a microphone positioned in the sensing device, wherein the CBM health score is determined in response to at least one of the acceleration data and the sound data.

17. The method of claim 15, further comprising:

displaying the CBM health score of the escalator on a display device of a computing device, the computing device in wireless communication with the network.

18. The method of claim 17, further comprising:

displaying, using the application for the computing device, a user input interface for adjusting the CBM health score by user input.

19. The method of claim 18, further comprising:

receiving a user input to adjust the CBM health score; and

adjusting the CBM health score in response to the user input.

20. The method of claim 15, further comprising:

the data packets are compressed using MQTT data compression.

Technical Field

Embodiments herein relate to the field of conveying systems, and in particular to a method and apparatus for monitoring a conveying apparatus of a conveying system.

Background

The health of the transport equipment within a transport system, such as, for example, an elevator system, an escalator system, and a moving walkway, may be difficult and/or costly to determine.

Disclosure of Invention

According to an embodiment, a monitoring system for an escalator is provided. The monitoring system includes: a local gateway device; an analysis engine in communication with a local gateway device over a cloud computing network; a sensing device that wirelessly communicates with a local gateway apparatus through a short-range wireless protocol, the sensing device comprising: an inertial measurement unit sensor configured to detect acceleration data of the escalator, wherein at least one of the sensing device and the local gateway device is configured to determine a condition-based monitoring (CBM) health score of the escalator at least in response to the acceleration data, and wherein the local gateway is configured to wirelessly transmit the CBM health score of the escalator in the form of data packets to the cloud computing network via the long-range wireless communication protocol.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: a microphone configured to detect sound data of the escalator, wherein the CBM health score is determined in response to at least one of the acceleration data and the sound data.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: an application for a computing device in wireless communication with a network, the application configured to display the CBM health score of the escalator on a display device of the computing device.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: the application is configured to display a user input interface for adjusting the CBM health score via user input.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: data packets are transmitted using MQTT data compression.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: the sensing device is configured to determine a CBM health score of the escalator responsive to at least one of the acceleration data and the sound data.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: the sensing device is configured to transmit the acceleration data and the sound data to the local gateway device, and the local gateway device is configured to determine a CBM health score for the escalator responsive to at least one of the acceleration data and the sound data.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: the sensing device is positioned within a handrail of the escalator and moves with the handrail.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: the sensing device is attached to and moves with a step chain of the escalator.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: the sensing device is stationary and positioned near a step chain of the escalator or a drive machine of the escalator.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: the sensing device is attached to a moving member of a drive machine of the escalator.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: the moving member of the drive machine is an output sheave that drives the step chain of the escalator.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: the sensing device uses inertial measurement unit sensors to detect low frequency vibrations of less than 10 Hz.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: the sensing device uses a microphone to detect high frequency vibrations above 10 Hz.

According to another embodiment, a method of monitoring an escalator is provided. The method comprises the following steps: detecting acceleration data of the escalator using inertial measurement unit sensors positioned in the sensing device; determining a condition-based monitoring (CBM) health score for the escalator in response to at least the acceleration data; and wirelessly transmitting the CBM health score of the escalator in the form of data packets to a cloud computing network via a long-range wireless communication protocol.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: detecting sound data of the escalator using a microphone positioned in the sensing device, wherein the CBM health score is determined in response to at least one of the acceleration data and the sound data.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: the CBM health score of the escalator is displayed on a display device of a computing device, and the computing device is in wireless communication with a network.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: an application for the computing device is used to display a user input interface for adjusting the CBM health score by user input.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: receiving user input to adjust the CBM health score; and adjusting the CBM health score in response to the user input.

In addition or as an alternative to one or more of the features described herein, further embodiments may include: data packets are compressed using MQTT data compression.

A technical effect of embodiments of the present disclosure includes monitoring an escalator using at least one of acceleration and sound to determine a health score, and transmitting the health score of the escalator in data packets to a cloud computing network via a long-range wireless communication protocol.

The foregoing features and elements may be combined in various combinations, not exclusively, unless explicitly indicated otherwise. These features and elements and their operation will become more apparent from the following description and the accompanying drawings. It is to be understood, however, that the following description and the accompanying drawings are intended to be illustrative and explanatory in nature, and not restrictive.

Drawings

The present disclosure is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements.

Fig. 1 is a schematic illustration of an escalator system and a monitoring system according to an embodiment of the present disclosure;

fig. 2 is a schematic illustration of a sensing device of the monitoring system of fig. 1, according to an embodiment of the present disclosure;

fig. 3 is a flow chart of a method of monitoring an escalator according to an embodiment of the present disclosure; and

fig. 4 is an illustration of a graphical user interface displaying condition-based monitored health scores for an escalator system, according to an embodiment of the present disclosure.

Detailed Description

Figure 1 illustrates an escalator 10. In the description that follows, it should become apparent that the present invention is applicable to other passenger conveyor systems, such as moving walkways. Escalator 10 generally includes a truss 12 extending between a lower landing 14 and an upper landing 16. A plurality of sequentially connected steps or treads 18 are connected to a step chain 20 and travel through a closed loop path within truss 12. The pair of balustrades 22 includes moving handrails 24. The drive machine 26 or drive system is typically positioned in a machine space 28 below the upper landing 16; however, an additional machine space 28' may be positioned below the lower landing 14. The drive machine 26 is configured to drive the tread plates 18 and/or the handrail 24 through the step chain 20. The drive machine 26 operates to move the pedals 18 in a selected direction at a desired speed under normal operating conditions.

The pedals 18 make a 180-degree change in the direction of travel in a turn zone 19 positioned below the lower landing 14 and the upper landing 16. The tread 18 is pivotally attached to the step chain 20 and follows the closed loop path of the step chain 20, running from one landing to another, and back again.

The drive machine 26 includes a first drive member 32, such as a motor output sheave, connected to a drive motor 34 by a belt reduction assembly 36, the belt reduction assembly 36 including a second drive member 38, such as an output sheave, driven by a tensioning member 39, such as an output belt. In some embodiments, the first drive component 32 is a drive component and the second drive component 38 is a driven component.

As used herein, in various embodiments, the first drive component 32 and/or the second drive component can be any type of rotating device, such as a sheave, pulley, gear, wheel, sprocket, cog, pinion, and the like. In various embodiments, the tensioning member 39 may be configured as a chain, belt, cable, strap, belt, strap, or any other similar device that operatively connects two elements to provide a driving force from one element to the other. For example, the tensioning member 39 may be any type of interconnecting member that extends between and operatively connects the first and second drive members 32, 38. In some embodiments, as shown in fig. 1, the first drive component 32 and the second drive component may provide belt deceleration. For example, the diameter of the first drive member 32 may be approximately 75 mm (2.95 inches), while the diameter of the second drive member 38 may be approximately 750 mm (29.53 inches). For example, belt deceleration allows sheave replacement to change speeds or different step speeds for 50 or 60 Hz mains power applications. However, in other embodiments, the second drive member 38 may be substantially similar to the first drive member 32.

As noted, the first drive member 32 is driven by the drive motor 34 and is therefore configured to drive the tensioning member 39 and the second drive member 38. In some embodiments, the second drive member 38 may be an idler gear or similar device that is driven by the operative connection between the first drive member 32 and the second drive member 38 via the tensioning member 39. The tensioning member 39 runs around a loop set by the first drive member 32 and the second drive member 38, which loop may be referred to as a small loop hereinafter. A small loop is provided for driving a larger loop, which consists of the step chain 20 and is driven by, for example, the output sheave 40. Under normal operating conditions, the tension members 39 and the step chain 20 move in unison based on the speed of movement of the first drive member 32 as driven by the drive motor 34.

The escalator 10 also includes a controller 115 in electronic communication with the drive motor 34. As shown, the controller 115 can be located in the machine space 28 of the escalator 10 and configured to control operation of the escalator 10. For example, the controller 115 may provide drive signals to the drive motor 34 to control acceleration, deceleration, stopping, etc. of the tread plates 18 via the step chain 20. The controller 115 may be an electronic controller that includes a processor and associated memory that includes computer-executable instructions that, when executed by the processor, cause the processor to perform various operations. The processor may be, but is not limited to, a single processor or a multi-processor system of any of a wide variety of possible architectures including Field Programmable Gate Arrays (FPGAs), Central Processing Units (CPUs), Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), or Graphics Processing Unit (GPU) hardware, arranged either homogeneously or heterogeneously. The memory may be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), or any other electronic, optical, magnetic, or any other computer readable medium.

Although described herein as a particular escalator drive system and particular components, this is merely exemplary and those skilled in the art will recognize that other escalator system configurations may operate with the invention disclosed herein.

The elements and components of the escalator 10 may be subject to fatigue, wear and tear or other damage that can compromise the health of the escalator 10. Embodiments disclosed herein seek to provide a monitoring system 200 for the escalator 10 of fig. 1.

In accordance with an embodiment of the present disclosure, a monitoring system 200 is illustrated in fig. 1. The monitoring system 200 includes one or more sensing devices 210 configured to: detects sensor data 202 of the escalator 10, processes the sensor data 202, and transmits the processed sensor data 202a (e.g., condition-based monitoring (CBM) health score 318) to the cloud-connected analysis engine 280. Alternatively, the sensor data 202 may be sent raw to at least one of the local gateway device 240 and the analytics engine 280, where the raw sensor data 202b will be processed. The processed sensor data 202a may simply be the CBM health score 318.

The raw sensor data 202b and/or the processed sensor data 202a may be transmitted between the local gateway device 240 and the network 250 in the form of data packets 207. The data packet 207 may be transmitted using a secure internet protocol (e.g., UDP, TCP) with payload and message encryption (e.g., AES 256). Data packet 207 may be transmitted at a selected frequency in an efficient manner. For example, packet 207 may be transmitted every 2 minutes to establish an uninterrupted connection using either a dynamic IP address or a static IP address. Data packet 207 may be transmitted using data compression (e.g., MQTT), necessitating bidirectional communication with network 250. Information such as, for example, heartbeat data, remote (intervention) commands, wireless updates of firmware, may be communicated. The heartbeat data may include information about the status of the escalator 10. The intervention commands may include commands that may be sent to the device to alter the operation of the device. In an embodiment, the data compression is MQTT data compression.

The sensor data 202 may include, but is not limited to, pressure data 314, vibration signature (i.e., vibration over a period of time) or acceleration data 312, and sound data 316. The acceleration data 312 may be a derivative or an integral of the acceleration data 312 of the escalator 10, such as, for example, position distance, speed, jerk. The sensor data 202 may also include light, humidity, and temperature data, or any other desired data parameter. It should be appreciated that although specific systems are defined separately in the schematic block diagram, each or any of the systems may be otherwise combined or separated via hardware and/or software. For example, the sensing device 210 may be a single sensor or may be a plurality of separate sensors.

The monitoring system 200 can include one or more sensing devices 210 positioned in various locations of the escalator 10. In one example, the sensing device 210 may be positioned to be attached to the armrest 24 or within the armrest 24 and move with the armrest 24. In another example, the sensing device 210 is stationary and positioned near the drive machine 26 or the step chain 20. In another example, the sensing device 210 can be attached to the step chain 20 and move with the moving step chain 20. In another example, the sensing device 210 may be attached to the pedal 18 and move with the pedal 18. In another example, the sensing device 210 may be attached to the drive machine 26 and move relative to the moving step chain 20. In another embodiment, sensing device 210 may be attached to a moving member of drive machine 26. The moving member of the drive machine 26 can be an output sheave 40 that drives the step chain 20 of the escalator 10.

In an embodiment, the sensing device 210 is configured to process the sensor data 202 by a processing method (such as, for example, edge processing) before transmitting the sensor data 202 to the analytics engine 280. Advantageously, utilizing edge processing helps to save energy by reducing the amount of data that needs to be transferred. In another embodiment, the sensing device 210 is configured to transmit raw and unprocessed raw sensor data 202b to the analysis engine 280 for processing.

The processing of the sensor data 202 may reveal data such as, for example, vibration characteristics, sound, temperature, acceleration of the escalator 10, deceleration of the escalator, escalator ride performance, emergency stops, and the like.

The analysis engine 280 may be a computing device, such as, for example, a desktop computer, a cloud-based computer, and/or a cloud-based Artificial Intelligence (AI) computing system. The analysis engine 280 may also be a computing device typically carried by a person, such as, for example, a smart phone, a PDA, a smart watch, a tablet, a laptop, and the like. The analysis engine 280 may also be two separate devices that are synchronized together, such as, for example, a cell phone and a desktop computer that are synchronized through an internet connection.

The analysis engine 280 may be an electronic controller that includes a processor 282 and associated memory 284, the memory 284 including computer-executable instructions that, when executed by the processor 282, cause the processor 282 to perform various operations. The processor 282 may be, but is not limited to, a single processor or a multi-processor system of any of a wide variety of possible architectures including Field Programmable Gate Arrays (FPGAs), Central Processing Units (CPUs), Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), or Graphics Processing Unit (GPU) hardware, arranged either homogeneously or heterogeneously. The memory 284 may be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), or any other electronic, optical, magnetic, or any other computer readable medium.

The sensing device 210 is configured to transmit the raw sensor data 202b or the processed sensor data 202a to the local gateway apparatus 240 via the short-range wireless protocol 203. The short-range wireless protocol 203 may include, but is not limited to, Bluetooth, BLE, Wi-Fi, LoRa, insignnu, enOcean, Sigfox, HaLow (801.11ah), zWave, ZigBee, wireless M-Bus, or other short-range wireless protocols known to those skilled in the art. In an embodiment, the local gateway device 240 may utilize message queue telemetry transport (MQTT or MQTT SN) to communicate with the sensing devices 210. Advantageously, MQTT minimizes network bandwidth and device resource requirements, which helps to reduce power consumption among the local gateway device 240 and the sensing devices 210, while helping to ensure reliability and message delivery. Using the short-range wireless protocol 203, the sensing device 210 is configured to transmit raw or processed sensor data 202 directly to the local gateway apparatus 240, and the local gateway apparatus 240 is configured to transmit the raw or processed sensor data 202 over the network 250 to the analytics engine 280 or to the controller 115. Network 250 may be a computing network such as, for example, a cloud computing network, a cellular network, or any other computing network known to those skilled in the art. Using the long-range wireless protocol 204, the sensing device 210 is configured to transmit the sensor data 202 to the analytics engine 280 over the network 250. The long-range wireless protocol 204 may include, but is not limited to, cellular, 3G, 4G, 5G, Cat M1, Weightless, LTE (NB-IoT, CAT M1), LoRa, Satellite, Ingeniu, or SigFox. The local gateway device 240 may communicate with the controller 115 over a hard-wired and/or wireless connection using the short-range wireless protocol 203.

The sensing device 210 may be configured to detect sensor data 202 including acceleration in any number of directions. In an embodiment, the sensing device 210 may detect the sensor data 202 including acceleration data 312 along three axes (X, Y, and Z axes). As illustrated in fig. 1, the X-axis and the Y-axis may form a plane parallel to the pedal 18, and the Z-axis is perpendicular to the pedal 18. The Z axis is parallel to the vertical or gravitational direction. X is parallel to the horizontal movement of the pedal 18 and the Y axis is perpendicular to the horizontal movement of the pedal 18.

Also shown in fig. 1 is a computing device 400. The computing device 400 can be part of an escalator mechanic operating on the escalator 10 or monitoring the escalator 10. Computing device 400 may be a computing device such as a desktop computer or a mobile computing device, such as, for example, a smartphone, PDA, smart watch, tablet, laptop, etc., typically carried by a person. The computing device 400 can include a display device 450 so that a mechanic can visually see the CBM health score 318 or sensor data 202 of the escalator 10. Computing device 400 may include a processor 420, memory 410, a communication module 430, and an application 440, as shown in fig. 1. Processor 420 may be any type or combination of computer processor, such as a microprocessor, microcontroller, digital signal processor, application specific integrated circuit, programmable logic device, and/or field programmable gate array. Memory 410 is an example of a non-transitory computer-readable storage medium tangibly embodied in computing device 400, including executable instructions stored therein, e.g., as firmware. The communication module 430 may implement one or more communication protocols, such as, for example, a short-range wireless protocol 203 and a long-range wireless protocol 204. The communication module 430 may be in communication with at least one of the controller 115, the sensing device 210, the network 250, and the analysis engine 280. In an embodiment, the communication module 430 may communicate with the analysis engine 280 over the network 250.

Communication module 430 is configured to receive CBM health score 318 and/or sensor data 202 from network 250 and analysis engine 280. Application 440 is configured to generate a graphical user interface on computing device 400 to display CBM health score 318. The application 440 may be computer software (e.g., software as a service) that is installed directly on the memory 410 of the computing device 400 and/or installed remotely and accessible through the computing device 400.

Fig. 2 illustrates a block diagram of the sensing device 210 of the monitoring system 200 of fig. 1. It should be appreciated that although specific systems are defined separately in the schematic block diagram of fig. 2, each or any of the systems may be otherwise combined or separated via hardware and/or software. As shown in fig. 2, the sensing device 210 may include a controller 212, a plurality of sensors 217 in communication with the controller 212, a communication module 220 in communication with the controller 212, and a power source 222 electrically connected to the controller 212.

The plurality of sensors 217 includes an Inertial Measurement Unit (IMU) sensor 218 configured to detect the sensor data 202 including the sensing device 210 and the acceleration data 312 of the escalator 10. The IMU sensor 218 may be a sensor such as, for example, an accelerometer, a gyroscope, or similar sensors known to those skilled in the art. The acceleration data 312 detected by the IMU sensor 218 may include acceleration as well as derivatives or integrals of acceleration, such as, for example, velocity, jerk. The IMU sensor 218 is in communication with the controller 212 of the sensing device 210.

The plurality of sensors 217 includes a pressure sensor 228 configured to detect sensor data 202 including pressure data 314, such as, for example, atmospheric pressure near the escalator 10. In two non-limiting examples, the pressure sensor 228 may be a pressure altimeter or a barometric altimeter. The pressure sensor 228 is in communication with the controller 212.

The plurality of sensors 217 includes a microphone 230 configured to detect sensor data 202 including sound data 316, such as, for example, audible sounds and sound levels. The microphone 230 may be a 2D (e.g., stereo) or 3D microphone. The microphone 230 is in communication with the controller 212.

The plurality of sensors 217 may also include additional sensors including, but not limited to, a light sensor 226, a pressure sensor 228, a humidity sensor 232, and a temperature sensor 234. The light sensor 226 is configured to detect sensor data 202 including exposure. The light sensor 226 is in communication with the controller 212. The humidity sensor 232 is configured to detect sensor data 202 including a humidity level. The humidity sensor 232 is in communication with the controller 212. The temperature sensor 234 is configured to detect the sensor data 202 including a temperature level. The temperature sensor 234 is in communication with the controller 212.

The plurality of sensors 217 of the sensing device 210 can be used to determine a plurality of operating modes of the escalator 10. Any one of a plurality of sensors 217 may be used to determine that the escalator 10 is operating. For example, the microphone 230 may detect a characteristic noise indicating that the escalator 10 is operating, or the IMU sensor 218 may detect a characteristic acceleration indicating that the escalator 10 is operating. The pressure sensor 228 can be used to determine the operating speed of the escalator 10. For example, if the sensing device 210 is positioned on the step chain 20 or tread 18, a continuous or constant change in air pressure may indicate movement of the step chain 20, and thus the operating speed may be determined in response to the change in air pressure. The IMU sensor 218 may be used to determine the height of the escalator 10. For example, if the sensing device 210 is positioned on the handrail 24 or the tread 18, a change in speed direction (e.g., the steps are moving upward and then moving abruptly downward) may indicate that the handrail 24 or the tread 18 has reached a maximum height. The IMU sensor 218 may be used to determine the stopping distance of the escalator 10. For example, if the sensing device 210 is positioned on the handrail 24, step chain 20, or tread 18, a second integral of the deceleration of the sensing device 210 may be calculated to determine the braking distance. The braking distance may be determined from acceleration data 312, which acceleration data 312 indicates an acceleration above a threshold value up to a first zero crossing of the filtered sensor data (the integrated velocity of the measured vibration from the acceleration data 312). The IMU sensor 218 may be used to determine the occupancy state of the escalator 10. For example, if the sensing device 210 is positioned on the step chain 20 or tread 18, the vibrations detected by the sensing device 210 using the IMU sensor 218 may indicate the entry of a passenger onto the escalator 10 or the exit of a passenger from the escalator 10.

The controller 212 of the sensing device 210 includes a processor 214 and associated memory 216, the memory 216 including computer-executable instructions that, when executed by the processor 214, cause the processor 214 to perform various operations, such as, for example, edge preprocessing or processing of sensor data 202 collected by the IMU sensor 218, the light sensor 226, the pressure sensor 228, the microphone 230, the humidity sensor 232, and the temperature sensor 234. In an embodiment, the controller 212 may process the acceleration data 312 and/or the pressure data 314 to determine the elevation (elevation) of the sensing device 210 (if the sensing device 210 is located on a member that is raised or lowered during operation of the escalator 10, such as, for example, on the handrail 24 and step chain 20). In an embodiment, the controller 212 of the sensing device 210 may utilize a Fast Fourier Transform (FFT) algorithm to process the sensor data 202.

The processor 214 may be, but is not limited to, a single processor or a multi-processor system of any of a wide variety of possible architectures including Field Programmable Gate Arrays (FPGAs), Central Processing Units (CPUs), Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), or Graphics Processing Unit (GPU) hardware, arranged either homogeneously or heterogeneously. The memory 216 may be a storage device such as, for example, a Random Access Memory (RAM), a Read Only Memory (ROM), or any other electronic, optical, magnetic, or any other computer readable medium.

The power source 222 of the sensing device 210 is configured to store electrical power and/or supply electrical power to the sensing device 210. The power source 222 may include an energy storage system, such as, for example, a battery system, a capacitor, or other energy storage systems known to those skilled in the art. The power source 222 may also generate electrical power for the sensing device 210. The power source 222 may also include an energy generation or power harvesting system, such as, for example, a synchronous generator, an induction generator, or other types of generators known to those skilled in the art. The power source 222 can also be a hard-wired power source that is hard-wired to and receives power from the power grid and/or escalator 10.

The sensing device 210 includes a communication module 220 configured to allow the controller 212 of the sensing device 210 to communicate with the local gateway apparatus 240 via the short-range wireless protocol 203. The communication module 220 may be configured to communicate with the local gateway device 240 using a short-range wireless protocol 203 such as: such as bluetooth, BLE, Wi-Fi, LoRa, insignnu, enOcean, Sigfox, HaLow (801.11ah), zWave, ZigBee, wireless M-Bus, or other short-range wireless protocols known to those skilled in the art. Using the short-range wireless protocol 203, the communication module 220 is configured to transmit the sensor data 202 to the local gateway device 240, and the local gateway device 240 is configured to transmit the sensor data 202 to the analytics engine 280 over the network 250, as described above.

The communication module 220 may also allow the sensing device 210 to communicate with other sensing devices 210 directly through the short-range wireless protocol 203 or indirectly through the local gateway apparatus 240 and/or the cloud computing network 250. Advantageously, this allows the sensing device 210 to coordinate the detection of the sensor data 202.

The sensing device 210 includes an elevation determination module 330 configured to determine the elevation or (i.e., height) of the sensing device 210, the sensing device 210 being positioned on a moving component of the escalator 10, such as, for example, the tread 18, step chain 20, and/or handrail 24. The elevation determination module 330 may utilize a variety of methods to determine the elevation or (i.e., height) of the sensing device 210. Altitude determination module 330 may be configured to determine the altitude of sensing device 210 using at least one of pressure altitude determination module 310 and acceleration altitude determination module 320.

The acceleration elevation determination module 320 is configured to determine a change in height of the sensing device in response to the acceleration of the sensing device 210 detected along the Z-axis. The sensing device 210 can detect acceleration along the Z axis, shown at 322, and can integrate the acceleration at 324 to obtain the vertical velocity of the sensing device. At 326, the sensing device 210 may also integrate the vertical velocity of the sensing device 210 to determine the vertical distance traveled by the sensing device 210 during the acceleration data 312 detected at 322. The direction of travel of the sensing device 210 may also be determined in response to the detected acceleration data 312. Altitude determination module 330 may then determine the altitude of sensing device 210 in response to the starting altitude and the distance traveled away from the starting altitude. The starting elevation may be based on tracking past operation and/or movement of the sensing device 210. An abnormal change in acceleration and/or speed of the escalator may indicate a poor CBM health score 318.

The pressure elevation determination module 310 is configured to detect atmospheric pressure while sensing device movement and/or being stationary using the pressure sensor 228. In two non-limiting embodiments, the pressure detected by pressure sensor 228 may be associated with the altitude by a lookup table or an altitude calculation using changes in atmospheric pressure. The direction of travel of the sensing device 210 may also be determined in response to changes in pressure detected via the pressure data 314. For example, a change in pressure may indicate that the sensing device 210 is moving up or down. The pressure sensor 228 may need to periodically detect the baseline pressure to account for changes in barometric pressure due to local weather conditions. For example, in non-limiting embodiments, it may be desirable to detect the baseline pressure daily, hourly, or weekly. In some embodiments, the baseline pressure may be detected whenever the sensing device is stationary, or during certain intervals when the sensing device 210 is stationary and/or at a known altitude. It may also be desirable to detect acceleration of the sensing device 210 to know when the sensing device 210 is stationary, and then when the sensing device 210 is stationary, the sensing device 210 may need to be offset to compensate for sensor drift and environmental drift.

In one embodiment, pressure elevation determination module 310 may be used to verify and/or modify the elevation of sensing device 210 determined by acceleration elevation determination module 320. In another embodiment, acceleration elevation determination module 320 may be used to verify and/or modify the elevation of the sensing device determined by pressure elevation determination module 310. In another embodiment, the pressure elevation determination module 310 may be prompted to determine the elevation of the sensing device 210 in response to the acceleration detected by the IMU sensor 218.

The health determination module 311 is configured to determine a CBM health score 318 for the escalator 10. The CBM health score 318 can be associated with a particular component of the escalator 10, or can be the CBM health score 318 for the escalator 10 as a whole. The health determination module 311 may be located in the analysis engine 280, the local gateway device 240, or the sensing apparatus 210. In an embodiment, the health determination module 311 is positioned in the sensing device 210 to perform edge processing. Health determination module 311 may process sensor data 202 using an FFT algorithm to determine CBM health score 318. In one embodiment, the health determination module 311 may process at least one of the sound data 316 detected by the microphone 230, the light detected by the light sensor 226, the humidity detected by the humidity sensor 232, the temperature data detected by the temperature sensor 234, the acceleration data 312 detected by the IMU sensor 218, and/or the pressure data 314 detected by the pressure sensor 228 to determine the CBM health score 318 for the escalator 10.

In an embodiment, the health determination module 311 may process at least one of the sound data 316 detected by the microphone 230 and the acceleration data 312 detected by the IMU sensor 218 to determine the CBM health score 318 for the escalator 10.

Different frequency ranges may be needed to detect different types of vibrations in the escalator 10, and different sensors of the sensing device 210 (e.g., microphone, IMU sensor 218.. etc.) may be better suited to detect different frequency ranges. In one example, the vibrations in the handrail 24 may consist of low frequency contributing vibrations less than 5 Hz and higher frequency vibrations induced at points in the handrail 24 where friction may occur. Low frequency vibrations may be best detected using the IMU sensor 218, while higher frequency vibrations (e.g., in the kHz region) may be best detected using the microphone 230, which has higher power efficiency. Advantageously, using the microphone to detect higher frequency vibrations and the IMU sensor 218 to detect lower frequency vibrations is more energy efficient. In an embodiment, the higher frequency may include a frequency greater than or equal to 10 Hz. In an embodiment, the lower frequency may comprise a frequency less than or equal to 10 Hz.

The sensing device 210 may be placed in a specific location to capture vibrations from different components. In an embodiment, the sensing device 210 may be placed in the handrail 24 (i.e., move with the handrail 24). When positioned in the armrest 24, the sensing device 210 may utilize the IMU sensor 218 to capture low frequency vibrations. Any change in low frequency vibrations from baseline may indicate a low CBM health score 318. Foreign objects (e.g., dirt, dust, pebbles) may become lodged in the handrail 24, thus causing increased vibration. In one example, low frequency oscillations may occur due to friction caused by dust or dirt. These low frequency oscillations can be identified using a low pass filter of less than 2 Hz. In another example, a single spike or noise may occur by dirt catching on the rails or wheels of the step chain 20. These single spikes or noise may be detected by identifying spikes in vibration greater than 100 mg.

In an embodiment, the sensing apparatus 210 may be attached to (e.g., in or on) the step chain 20 or tread plates 18 (i.e., move with the step chain 20 or tread plates 18). In another embodiment, sensing device 210 is positioned stationary near drive machine 26. When the sensing device 210 is attached to the drive machine 26, the temperature sensor 234 may best measure the temperature of the drive machine 26. The IMU sensor 218 may best measure acceleration when the sensing device 210 is attached to the output sheave 40 or the pedal 18. When attached to the step chain 20 or statically positioned near the drive machine 26, the sensing device 210 may utilize the IMU sensor 218 to capture low frequency vibrations that may indicate bearing issues with respect to the main pivot of the step chain 20, the step rollers of the step chain 20, or the handrail pivot of the handrail 24. Alternatively, the sensing device 210 may utilize the microphone 230 to capture high frequency vibrations that may indicate bearing problems when attached to the step chain 20 or statically positioned near the drive machine 26. An FFT algorithm may be used to help analyze the high frequency vibrations captured by the microphone. Advantageously, the FFT algorithm uses pre-defined special electronic hardware, resulting in an easy, low cost and low power consuming way to detect the deviation. When attached to the step chain 20 or positioned stationary near the drive machine 26, the sensing device 210 may utilize a temperature sensor 234 to measure temperature. An increase in temperature may indicate an increase in machine load or an increase in friction on drive machine 26. When attached to the step chain 20, the sensing device 210 may utilize the IMU sensors 218 to capture acceleration in multiple axes (e.g., X, Y, and Z axes) to determine the direction (e.g., up or down) of the tread plates 18, the 3D acceleration profile of the tread plates 18 to determine, among other things, when the tread plates 18 are turning, the tread plates 18 are misaligned, and the humps in the step chain 20 that may indicate foreign objects (dirt, pebbles, dust, etc.) in the step chain 20 or the tread plates 18. The combination of multiple sensor information from different sensors of the multiple sensors 217 results in the ability for the sensors within the sensing device to fuse, thus allowing the sensors to work in concert to confirm, adjust, or reject data readings. For example, an increase in acceleration values (at certain frequencies (FFT)) within acceleration data 312 may be associated with an increase in temperature detected by temperature sensor 234 (e.g., machine heat driving machine 26 due to higher loads) and an increase in relative humidity detected by humidity sensor 232 (excluding changes in friction due to external weather conditions).

The CBM health score 318 can be a graded scale that indicates the health of the escalator 10 and/or components of the escalator 10. In a non-limiting example, CBM health scores 318 may be ranked on a scale of one to ten, where a CBM health score 318 equivalent to one is the lowest CBM health score 318, and a CBM health score 318 equivalent to ten is the highest CBM health score 318. In another non-limiting example, the CBM health score 318 may be ranked on a one percent to one hundred percent scale, where a CBM health score 318 equivalent to one percent is the lowest CBM health score 318, and a CBM health score 318 equivalent to one hundred percent is the highest CBM health score 318. In another non-limiting example, CBM health scores 318 may be ranked on a scale of color, where a CBM health score 318 equivalent to red is the lowest CBM health score 318, and a CBM health score 318 equivalent to green is the highest CBM health score 318. The CBM health score 318 may be determined in response to at least one of the acceleration data 312, the pressure data 314, and/or the temperature data. For example, acceleration data 312 above a threshold acceleration (e.g., normal operating acceleration) on any of the X, Y, and Z axes may indicate a low CBM health score 318. In another example, elevated temperature data above a threshold temperature for a component may indicate a low CBM health score 318. In another example, elevated sound data 316 above a threshold sound level for a component may indicate a low CBM health score 318.

Reference is now made to fig. 3 and 4, with simultaneous reference to the components of fig. 1-2. Fig. 3 shows a flow chart of a method 500 of monitoring an escalator, according to an embodiment of the present disclosure. In an embodiment, the method 500 may be performed by at least one of the sensing device 210, the local gateway device 240, the application 440, and the analysis engine 280.

At block 504, the acceleration data 312 of the escalator 10 is detected using the inertial measurement unit sensor 218 positioned in the sensing device 210. In one embodiment, the sensing device 210 is positioned within the handrail 24 of the escalator 10 and moves with the handrail 24. In another embodiment, the sensing device 210 is attached to the step chain 20 of the escalator 10 and moves with the step chain 20. In another embodiment, the sensing device 210 is attached to the steps 18 of the escalator 10 and moves with the steps 18. In another embodiment, the sensing device 210 is stationary and positioned near the step chain 20 of the escalator 10 or the drive machine 26 of the escalator 10. At block 506, sound data 316 of the escalator 10 is detected using a microphone 230 positioned in the sensing device 210.

At block 508, a CBM health score 318 for the escalator 10 is determined in response to at least one of the acceleration data 312 and the sound data 316. Alternatively, the CBM health score 318 may be determined in response to at least the acceleration data 312. In one embodiment, the sensing device 210 is configured to determine an operating mode of the escalator 10 in response to at least one of the acceleration data 312 and the sound data 316.

In another embodiment, the acceleration data 312 and the sound data 316 are transmitted over the short-range wireless protocol 203 to a local gateway device 240 in wireless communication with the sensing device 210, and the local gateway device 240 is configured to determine the operating mode of the escalator 10 in response to at least one of the acceleration data 312 and the sound data 316.

In another embodiment, the acceleration data 312 and the sound data 316 are transmitted over the short-range wireless protocol 203 to a local gateway apparatus 240 in wireless communication with the sensing device 210, and the local gateway apparatus 240 transmits the acceleration data 312 and the sound data 316 over the cloud computing network 250 to the analysis engine 280. The analysis engine 280 is configured to determine an operating mode of the escalator 10 in response to at least one of the acceleration data 312 and the sound data 316.

In an embodiment, the inertial measurement unit sensor 218 is used to detect low frequency vibrations of less than 10 Hz. In another embodiment, a microphone 230 is used to detect high frequency vibrations greater than 10 Hz. In another embodiment, the dither is between 10 Hz and 1 kHz. In another embodiment, the dither is greater than 1 kHz.

At block 510, the CBM health score of the escalator 10 is wirelessly transmitted to a cloud computing network in the form of data packets 207 via a long-range wireless communication protocol. Method 500 may also include compressing data packet 207 using MQTT data compression.

Method 500 may also further include displaying CBM health score 318 on a display device. As illustrated in fig. 4, the display device may be the display device 450 of the computing device 400. The computing device 400 of fig. 4 may be part of an employee or operator of the escalator 10. Computing device 400 may be a desktop computer, a laptop computer, a smartphone, a tablet computer, a smart watch, or any other computing device known to those skilled in the art. In the example shown in fig. 4, computing device 400 is a touch screen smartphone. The computing device 400 includes an input device 452 such as, for example, a mouse, keyboard, touch screen, scroll wheel, roller ball, stylus, microphone, camera, or the like. In the example shown in fig. 4, since the computing device 400 is a touch screen smart phone, the display device 450 also serves as an input device 452. Fig. 4 illustrates a graphical user interface 470 generated on the display device 450 of the computing device 400. The user may interact with the graphical user interface 470 through user input, such as, for example, "click," "touch," spoken commands, gesture recognition, or any other input to the graphical user interface 470.

FIG. 4 illustrates a computing device 400 that generates a graphical user interface 470 for viewing CBM health scores 318 via a display device 450 through an application 440. The application 440 is configured to display the CBM health score 318 for the escalator 10 on the display device 450 of the computing device 400. As illustrated in FIG. 4, the CBM health score 318 may be displayed as a weighted scale from one to ten, but it is to be understood that the CBM health score 318 is not limited to being displayed as a weighted scale from one to ten, and that the CBM health score 318 may be displayed using a variety of other methods. The application 440 is also configured to display a user input interface 718 for adjusting the CBM health score 318 via user input. As illustrated in fig. 4, the user input interface 718 may be displayed as a weighted scale from one to ten adjusted by user input sliding the weighted scale left or right, but it is to be understood that the user input interface 718 is not limited to being displayed as a weighted scale from one to ten and that the user input interface 718 may be displayed using a variety of other methods.

While the description above has described the flow of fig. 3 in a particular order, it should be recognized that the ordering of the steps may be varied unless specifically claimed otherwise in the appended claims.

As described above, embodiments may take the form of processor-implemented processes and apparatuses (such as processors) for practicing those processes. Embodiments may also be in the form of computer program code (e.g., a computer program product) that: the computer program code contains instructions embodied in tangible media (e.g., non-transitory computer readable media), such as floppy diskettes, CD ROMs, hard drives, or any other non-transitory computer readable medium, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing the embodiments. Embodiments may also be in the form of computer program code for: for example, the computer program code is either stored in a storage medium, loaded into and/or executed by a computer, or transmitted over some transmission medium, such as over electrical wiring or cabling, through fiber optics, or via electromagnetic radiation, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing the exemplary embodiments. When implemented on a general-purpose microprocessor, the computer program code segments configure the microprocessor to create specific logic circuits.

The term "about" is intended to include a degree of error associated with measuring a particular quantity and/or manufacturing tolerance based on equipment available at the time of filing the present application.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, element components, and/or groups thereof.

Those skilled in the art will recognize that a variety of example embodiments are shown and described herein, each having certain features in specific embodiments, but the disclosure is not so limited. Rather, the disclosure can be modified to incorporate any number of variations, alterations, substitutions, combinations, sub-combinations or equivalent arrangements not heretofore described, but which are commensurate with the scope of the disclosure. Additionally, while various embodiments of the disclosure have been described, it is to be understood that aspects of the disclosure may include only some of the described embodiments. Accordingly, the disclosure is not to be seen as limited by the foregoing description, but is only limited by the scope of the appended claims.