阅读说明：本技术 基于智能手环的触电紧急救护系统及其方法 (Electric shock emergency rescue system and method based on smart bracelet ) 是由 蔡怡晗 蔡梦洁 于 2019-10-15 设计创作，主要内容包括：本发明涉及一种基于智能手环的触电紧急救护系统,所述手环包括手环主体和带状手环；所述手环主体包括信号采集模块、滤波放大电路、A/D转换模块、中央处理单元、告警模块、GPS定位模块、无线模块和显示模块；所述信号采集模块依次通过滤波放大电路和A/D转换模块,将采集的信号输入至中央处理单元；所述中央处理单元还与GPS定位模块、无线模块、告警模块和显示模块分别连接；所述系统还设置有一电源模块用于提供电源。本发明能实时采集与监测作业人员心率状态、能快速判断心率异常并及时告警发信的紧急呼救系统,实现作业过程人员身体状况的全程跟踪,提高作业人员安全保障系数。(The invention relates to an electric shock emergency rescue system based on an intelligent bracelet, wherein the bracelet comprises a bracelet main body and a band-shaped bracelet; the bracelet main body comprises a signal acquisition module, a filtering amplification circuit, an A/D conversion module, a central processing unit, an alarm module, a GPS positioning module, a wireless module and a display module; the signal acquisition module inputs acquired signals to the central processing unit through the filtering amplification circuit and the A/D conversion module in sequence; the central processing unit is also connected with the GPS positioning module, the wireless module, the alarm module and the display module respectively; the system is also provided with a power supply module for supplying power. The invention can acquire and monitor the heart rate state of the operating personnel in real time, can quickly judge abnormal heart rate and alarm in time to send a message, realizes the whole-process tracking of the physical condition of the operating personnel, and improves the safety guarantee coefficient of the operating personnel.)

1. The utility model provides an electric shock emergency call system based on intelligence bracelet which characterized in that: the bracelet comprises a bracelet main body and a band bracelet; the bracelet main body comprises a signal acquisition module, a filtering amplification circuit, an A/D conversion module, a central processing unit, an alarm module, a GPS positioning module, a wireless module and a display module; the signal acquisition module inputs acquired signals to the central processing unit through the filtering amplification circuit and the A/D conversion module in sequence; the central processing unit is also connected with the GPS positioning module, the wireless module, the alarm module and the display module respectively; the system is also provided with a power supply module for supplying power.

2. The electric shock emergency call system based on the smart band of claim 1, wherein: the signal acquisition module adopts an SC0073 pulse sensor.

3. A control method of an electric shock emergency call system based on an intelligent bracelet is characterized by comprising the following steps:

step S1, turning on the power supply of the intelligent bracelet, initializing the system, collecting heart rate data by the collecting module through the SC0073 pulse sensor, and processing the collected signals by the signal collecting module accessing the filter amplifying circuit;

step S2: presetting data for 20s, after 20s, enabling the system to enter a normal real-time monitoring mode, transmitting acquired and processed heart rate data to a central processing unit by a signal acquisition module to serve as input data of a neural network analysis module arranged in the central processing unit, processing the data by the neural network analysis module, and judging whether the heart rate is in a normal range or not;

step S3: if the person heart rate data is suddenly changed or the gradual change range exceeds the normal heart rate range, the central processing unit judges that the person heart rate data is suddenly changed or the gradual change range exceeds the normal heart rate range, the alarm module sends out an alarm signal to start the sound alarm device, and sends out alarm information and person positioning information to the background monitoring terminal through the wireless module.

4. The control method of the electric shock emergency call system based on the smart band as claimed in claim 3, wherein: the judgment basis of the neural network analysis module comprises that heart rate data is taken as the basis, and if the heart rate data is in a normal range, the system only displays instantaneous heart rate data and average heart rate data within 1min on a display screen; if the gradual change range exceeds the normal heart rate range by 10%, judging that the physical condition of the person is abnormal, and outputting an alarm signal; the heart rate change rate is used as a basis, if the heart rate data is suddenly changed and the heart rate change rate exceeds a set value, the system immediately judges that the heart rate data is abnormal, and a high-level trigger alarm signal is output.

5. The control method of the electric shock emergency call system based on the smart band as claimed in claim 3, wherein: the neural network training data is specifically that the average value of the collected heart rate data is obtained within the preset time of the system

The supplemental training matrix is designed by (1) defining a function of (1/x),

(2) definition of g (x) ═ rand (),

6. the control method of the electric shock emergency call system based on the smart band as claimed in claim 3, wherein: the built-in neural network analysis module of the central processing unit is specifically constructed by the steps that an input node is 5, the neural network is 4 layers, and an activation function is selected

Technical Field

The invention relates to the field of power system safety, in particular to a touch emergency rescue system and method based on an intelligent bracelet.

Background

When the facilities of power switch cabinets such as a transformer substation, a ring main unit and a branch box are overhauled, the names and the numbers of intervals needing to be overhauled are mainly checked by personnel. In actual work, the power switch cabinets used in the same area are various in types, different in manufacturers and different in panel. Because the professional quality of field workers is not uniform, the familiarity of the field workers to equipment is not enough, and the field workers can maintain the field workers in the switch interval under the conditions that the energy of the field workers is not concentrated and safety measures are not in place, the field workers can easily mistakenly enter the electrified interval or open the electrified interval cover plate to touch the electrified equipment, so that electric shock is caused to cause accidents.

When existing electric power switch cabinet type facilities are overhauled, safety measures taken by workers are still manual mutual monitoring methods, potential safety hazards cannot be completely and thoroughly eradicated, and serious consequences can be caused when rescue is untimely due to lack of real-time monitoring and analysis on physical conditions of the workers in outdoor operation and small-sized decentralized operation work of an electric power system.

Disclosure of Invention

In view of the above, the present invention provides an electric shock emergency rescue system based on an intelligent bracelet and a method thereof, and the emergency call system can quickly determine abnormal heart rate and timely alarm for a signal, thereby realizing the whole-process tracking of the physical condition of the operator during the operation process and improving the safety protection coefficient of the operator.

In order to achieve the purpose, the invention adopts the following technical scheme:

an electric shock emergency call system based on an intelligent bracelet, wherein the bracelet comprises a bracelet main body and a band-shaped bracelet; the bracelet main body comprises a signal acquisition module, a filtering amplification circuit, an A/D conversion module, a central processing unit, an alarm module, a GPS positioning module, a wireless module and a display module; the signal acquisition module inputs acquired signals to the central processing unit through the filtering amplification circuit and the A/D conversion module in sequence; the central processing unit is also connected with the GPS positioning module, the wireless module, the alarm module and the display module respectively; the system is also provided with a power supply module for supplying power.

Further, the signal acquisition module adopts an SC0073 pulse sensor.

The control method of the electric shock emergency call system based on the smart bracelet comprises the following steps:

step S1, turning on the power supply of the intelligent bracelet, initializing the system, collecting heart rate data by the collecting module through the SC0073 pulse sensor, and processing the collected signals by the signal collecting module accessing the filter amplifying circuit;

step S2: presetting data for 20s, after 20s, enabling the system to enter a normal real-time monitoring mode, transmitting acquired and processed heart rate data to a central processing unit by a signal acquisition module to serve as input data of a neural network analysis module arranged in the central processing unit, processing the data by the neural network analysis module, and judging whether the heart rate is in a normal range or not;

step S3: if the person heart rate data is suddenly changed or the gradual change range exceeds the normal heart rate range, the central processing unit judges that the person heart rate data is suddenly changed or the gradual change range exceeds the normal heart rate range, the alarm module sends out an alarm signal to start the sound alarm device, and sends out alarm information and person positioning information to the background monitoring terminal through the wireless module.

Further, the judgment basis of the neural network analysis module comprises that the heart rate data is taken as the basis, and if the heart rate data is in a normal range, the system only displays the instantaneous heart rate data and the average heart rate data within 1min on a display screen; if the gradual change range exceeds the normal heart rate range by 10%, judging that the physical condition of the person is abnormal, and outputting an alarm signal; the heart rate change rate is used as a basis, if the heart rate data is suddenly changed and the heart rate change rate exceeds a set value, the system immediately judges that the heart rate data is abnormal, and a high-level trigger alarm signal is output.

Further, the neural network training data is specifically obtained by averaging the collected heart rate data within a preset time of the system

(times/min), so that the normal heart rate value of the subject ranges from

The training data core matrix is selected as

The remaining supplemental training matrices are designed as follows, (1) define f (x) as a 1/x function,b_n＝0.2+0.02*n，

d_n＝0.6+0.015*n

f_n＝0.9-0.0125*n，

h_n＝0.65-0.0225*n ，

n-1, 2, ·, 20; (2) definition of g (x) ═ rand (),

n＝1,2,···,100。

further, the neural network analysis module built in the central processing unit is specifically constructed in such a way that the input node is 5, the neural network is 4 layers, and the activation function is selected

The function, network weight parameter W, learning rate alpha is 0.8, the weight is updated by gradient descent method, and error e_k＝(t_k-o_k)²T is the target value, o is the output value,

through the simplified calculation, the method has the advantages that,

and obtaining a weight updating formula, thereby obtaining a weight coefficient matrix W of the neural network and obtaining a neural network analysis module.

Compared with the prior art, the invention has the following beneficial effects:

the emergency call-for-help system can acquire and monitor the heart rate state of the operating personnel in real time, can quickly judge abnormal heart rate and alarm in time to send a signal, realizes the whole-process tracking of the physical condition of the operating personnel, and improves the safety guarantee coefficient of the operating personnel.

Drawings

FIG. 1 is a block diagram of the system architecture of the present invention.

Detailed Description

The invention is further explained below with reference to the drawings and the embodiments.

Referring to fig. 1, the invention provides an electric shock emergency call system based on an intelligent bracelet, wherein the bracelet comprises a bracelet main body and a band-shaped bracelet; the bracelet main body comprises a signal acquisition module, a filtering amplification circuit, an A/D conversion module, a central processing unit, an alarm module, a GPS positioning module, a wireless module and a display module; the signal acquisition module inputs acquired signals to the central processing unit through the filtering amplification circuit and the A/D conversion module in sequence; the central processing unit is also connected with the GPS positioning module, the wireless module, the alarm module and the display module respectively; the system is also provided with a power supply module for supplying power.

In this embodiment, the signal acquisition module employs an SC0073 pulse sensor.

In this embodiment, the method for controlling the electric shock emergency call system based on the smart band includes the following steps:

step S1, turning on the power supply of the intelligent bracelet, initializing the system, collecting heart rate data by the collecting module through the SC0073 pulse sensor, and processing the collected signals by the signal collecting module accessing the filter amplifying circuit;

step S2: presetting data for 20s, after 20s, enabling the system to enter a normal real-time monitoring mode, transmitting acquired and processed heart rate data to a central processing unit by a signal acquisition module to serve as input data of a neural network analysis module arranged in the central processing unit, processing the data by the neural network analysis module, and judging whether the heart rate is in a normal range or not;

step S3: if the person heart rate data is suddenly changed or the gradual change range exceeds the normal heart rate range, the central processing unit judges that the person heart rate data is suddenly changed or the gradual change range exceeds the normal heart rate range, the alarm module sends out an alarm signal to start the sound alarm device, and sends out alarm information and person positioning information to the background monitoring terminal through the wireless module.

In this embodiment, the judgment basis of the neural network analysis module includes that the heart rate data is taken as the basis, if the heart rate data is in the normal range, firstly, the heart rate value exceeds the normal range by 10%, and the criterion setting is embodied in the selection of the training data; or the heart rate change rate (HRV) directly exceeds the normal level, namely, the heart rate is judged to be abnormal when the instantaneous heart rate change rate exceeds 25 times/min; when the two conditions meet one condition, the judgment is 1, the alarm module is triggered, and an alarm distress signal is sent out.

In this embodiment, the neural network training data is specifically obtained by averaging the collected heart rate data within a preset time of the system

(times/min), so that the normal heart rate value of the subject ranges fromThe training data core matrix is selected as

The remaining supplemental training matrices are designed as follows, (1) define f (x) as a 1/x function,

b_n＝0.2+0.02*n，

d_n＝0.6+0.015*nf_n＝0.9-0.0125*n，

h_n＝0.65-0.0225*n ，

n-1, 2, ·, 20; (2) definition of g (x) ═ rand (),n is 1,2, 100. The training data set comprehensively reflects the heart rate data normality of the individual, the output score is higher when the heart rate is closer to the average numerical value, otherwise, the output score is lower, linear exercise is avoided, and the neural network response is closer to the state of a real heart rate system of a human body.

In this embodiment, the neural network analysis module built in the central processing unit is specifically configured such that the input node is 5, the neural network is 4 layers, and the activation function is selected

The function, network weight parameter W, learning rate alpha is 0.8, the weight is updated by gradient descent method, and error e_k＝(t_k-o_k)²T is the target value, o is the output value,

through the simplified calculation, the method has the advantages that,

and obtaining a weight updating formula, thereby obtaining a weight coefficient matrix W of the neural network and obtaining a neural network analysis module.

The above description is only a preferred embodiment of the present invention, and all equivalent changes and modifications made in accordance with the claims of the present invention should be covered by the present invention.