阅读说明：本技术 一种车载汽车衡故障检测系统 (Vehicle-mounted truck scale fault detection system ) 是由 许冠 林�发 林金田 于 2019-09-09 设计创作，主要内容包括：一种车载汽车衡故障检测系统,涉及故障检测领域,所述系统包括故障类别建立模块、样本库建立模块、样本输入输出序列确定模块、第样本故障辨识模块、运行数据采集模块、运行输入输出序列确定模块、运行故障辨识模块以及比对模块。本发明一方面,采用最小二乘法辨识系统参数,无需获知系统参数本身的物理意义,只需进行求解并与各种故障模式的系统参数进行对比,获知车载汽车衡故障的故障模式；另一方面,该检测系统简单,优化车载汽车衡故障检测系统,提高检测的速度,并实现能够直观检测出故障类型；可以广泛应用到车载汽车衡故障的检测。(The system comprises a fault category establishing module, a sample library establishing module, a sample input and output sequence determining module, a first sample fault identifying module, an operation data collecting module, an operation input and output sequence determining module, an operation fault identifying module and a comparing module. On one hand, the system parameters are identified by adopting a least square method, the physical significance of the system parameters is not required to be obtained, and the fault mode of the vehicle-mounted truck scale is obtained only by solving and comparing with the system parameters of various fault modes; on the other hand, the detection system is simple, the vehicle-mounted truck scale fault detection system is optimized, the detection speed is improved, and the fault type can be visually detected; the method can be widely applied to the detection of the faults of the vehicle-mounted truck scale.)

1. A vehicle-mounted truck scale fault detection system is characterized in that the vehicle-mounted truck scale comprises eight weighing sensors; the system comprises:

the fault type establishing module is used for determining that the number of the weighing sensors of the vehicle-mounted truck scale is eight, and determining that the fault type of the weighing sensors is as follows: short-circuit faults, open-circuit faults, zero faults and sensitivity faults, and determining the total fault number as the product of the number of the circuits and the number of the fault categories;

a sample library establishing module for acquiring first data Q of the weighing sensor sample in the failure mode respectively under the condition of controlling each weighing sensor to be in each failure category respectively in an experiment_(i,j)(ii) a The first data Q_(i,j)Comprises a first sensor output signal X_1(i,j)The second path of sensor output signal X_2(i,j)And the output signal X of the third sensor_3(i,j)And the fourth path of sensor output signal X_4(i,j)The fifth path of sensor output signal X_5(i,j)And the sixth path of sensor output signal X_6(i,j)And the seventh sensor output signal X_7(i,j)Output signal X by the eighth sensor_8(i,j)(ii) a The i is the total failure number; the j is the order of the first dataNumber, j is a positive integer;

a sample input/output sequence determining module for determining the first data Q_(i,j)Confirming the first output data column F_i(j)And a first input matrix phi_(i,j)(ii) a The first output data column F_i(j)＝(X_1(i,1) X_1(i,2)…X_1(i,j))^TThe first input matrix

A sample failure identification module for solving a first failure identification parameter eta corresponding to the weighing sensor sample of each failure mode_i(ii) a The first fault identification parameter η_iSatisfies the following conditions:

The operation data acquisition module is used for acquiring second data G of the faulty weighing sensor in real time in the actual detection process_(n)(ii) a The second data G_(n)Comprises a first sensor output signal X_1(n)The second path of sensor output signal X_2(n)And the output signal X of the third sensor_3(n)And the fourth path of sensor output signal X_4(n)The fifth path of sensor output signal X_5(n)The sixth path of sensor output signal X_6(n)The seventh sensor output signal X_7(n)Output signal X by the eighth sensor_8(n)(ii) a The n is the serial number of the fault mode, the n is the serial number of the second data, and the n is a positive integer;

a running input/output sequence determining module for determining the second data G according to the first data G_(n)Identifying the second output data column F (n) and the second input matrix phi_(n)(ii) a The above-mentionedThe second output data sequence f (n) ═ X₁₍₁₎ X₁₍₂₎…X_1(n))^TSaid second input matrix

The operation fault identification module is used for solving a second fault identification parameter omega of the faulty weighing sensor; the second fault identification parameter ω satisfies:

A comparison module for comparing the second fault identification parameter omega and the first fault identification parameter eta_iComparing to obtain a comparison value D_(i)Taking the contrast value D_(i)And determining the faults of the vehicle-mounted truck scale for the number of roadblocks corresponding to the minimum value and the fault type.

2. The vehicle scale fault detection system of claim 1, wherein the comparison module further comprises:

a contrast value solving unit for solving the contrast value D_(i)(ii) a The contrast value D_(i)Satisfies the following conditions:

a minimum value selection unit for selecting the minimum value according to the solved contrast value D_(i)Selecting D_min＝min(D_(i))；

A fault determination unit for determining a fault according to D_minDetermining the failure mode of the faulty load cell.

3. The truck scale fault detection system of claim 1, wherein the first data Q_(i,j)And outputting voltage or current for each path of weighing sensor.

4. The vehicle scale fault detection system of claim 1, wherein in the sample construction stage, the load cells with faults are set to the corresponding road numbers for experiment.

Technical Field

The invention relates to the field of fault detection, in particular to a fault detection system for a vehicle-mounted truck scale.

Background

The traditional truck scale utilizes a parallel circuit connection mode, accumulates output signals of a plurality of paths of weighing sensors in an analog junction box to obtain a voltage signal proportional to the mass of a load to be measured, and transmits the voltage signal to a weighing instrument to finish weighing the load to be measured. The method causes the truck scale to lose the fault diagnosis function, and the weighing system is disabled when any sensor fails.

Therefore, fault detection is necessary for the faulty weighing sensor, and a detection system existing in the current market is complex, so that the fault type of the faulty weighing sensor is difficult to detect intuitively, and a fault solution cannot be specified at the first time.

Disclosure of Invention

In view of some of the above drawbacks in the prior art, the present invention provides a vehicle-mounted truck scale fault detection system, which is designed to optimize the vehicle-mounted truck scale fault detection system, improve the detection efficiency, and visually determine the fault type.

In order to achieve the above object, the present invention provides a vehicle-mounted truck scale fault detection system, including:

the fault type establishing module is used for determining that the number of the weighing sensors of the vehicle-mounted truck scale is eight, and determining that the fault type of the weighing sensors is as follows: short-circuit faults, open-circuit faults, zero faults and sensitivity faults, and determining the total fault number as the product of the number of the circuits and the number of the fault categories;

a sample library establishing module for acquiring first data Q of the weighing sensor sample in the failure mode respectively under the condition of controlling each weighing sensor to be in each failure category respectively in an experiment_(i,j)(ii) a The first data Q_(i,j)Comprises a first sensor output signal X_1(i,j)The second path of sensor output signal X_2(i,j)And the output signal X of the third sensor_3(i,j)And the fourth path of sensor output signal X_4(i,j)The fifth path of sensor output signal X_5(i,j)And the sixth path of sensor output signal X_6(i,j)And the seventh sensor output signal X_7(i,j)Output signal X by the eighth sensor_8(i,j)(ii) a The i is the total failure number; j is the serial number of the first data, and j is a positive integer;

a sample input/output sequence determining module for determining the first data Q_(i,j)Confirming the first output data column F_i(j)And a first input matrix phi_(i,j)(ii) a The first output data column F_i(j)＝(X_1(i,1) X_1(i,2) … X_1(i,j))^TThe first input matrix

A sample failure identification module for solving a first failure identification parameter eta corresponding to the weighing sensor sample of each failure mode_i(ii) a The first fault identification parameter η_iSatisfies the following conditions:wherein said eta_iIs a column vector of said η_iSeven sub-items are included; eta of_i＝[a_(i,1) a_(i,2) a_(i,3) a_(i,4) a_(i,5) a_(i,6) a_(i,7)]^T；

The operation data acquisition module is used for acquiring second data G of the faulty weighing sensor in real time in the actual detection process_(n)(ii) a The second data G_(n)Comprises a first sensor output signal X_1(n)The second path of sensor output signal X_2(n)And the output signal X of the third sensor_3(n)And the fourth path of sensor output signal X_4(n)The fifth path of sensor output signal X_5(n)The sixth path of sensor output signal X_6(n)The seventh sensor output signal X_7(n)Output signal X by the eighth sensor_8(n)(ii) a The n is the serial number of the fault mode, the n is the serial number of the second data, and the n is a positive integer;

a running input/output sequence determining module for determining the second data G according to the first data G_(n)Identifying the second output data column F (n) and the second input matrix phi_(n)(ii) a The second output data sequence f (n) ═ X₁₍₁₎ X₁₍₂₎ … X_1(n))^TSaid second input matrix

The operation fault identification module is used for solving a second fault identification parameter omega of the faulty weighing sensor; the second fault identification parameter ω satisfies:wherein the ω is a column vector, the ω includes seven sub-terms; ω ═ b₍₁₎ b₍₂₎ b₍₃₎ b₍₄₎ b₍₅₎ b₍₆₎ b₍₇₎]^T；

A comparison module for comparing the second fault identification parameter omega and the first fault identification parameter eta_iComparing to obtain a comparison value D_(i)Taking the contrast value D_(i)And determining the faults of the vehicle-mounted truck scale for the number of roadblocks corresponding to the minimum value and the fault type.

In a specific embodiment, the alignment module further comprises:

a contrast value solving unit for solving the contrast value D_(i)(ii) a The contrast value D_(i)Satisfies the following conditions:m is the second fault identification parameter ω and the first fault identification parameter η_iThe number of the child entry;

a minimum value selection unit for selecting the minimum value according to the solved contrast value D_(i)Selecting D_min＝min(D_(i))；

A fault determination unit for determining a fault according to D_minDetermining the failure mode of the faulty load cell.

In one embodiment, the first data Q_(i,j)And outputting voltage or current for each path of weighing sensor.

In a specific embodiment, in the sample construction stage, the weighing sensors with faults are arranged on the corresponding paths for experiment.

The invention has the beneficial effects that: in the invention, a sample library establishing module is used for acquiring first data of various weighing sensor samples, and first fault identification parameters corresponding to the weighing sensor samples are identified and solved; and acquiring second data of the faulty weighing sensor through the operation data acquisition module, identifying and solving a second fault identification parameter of the faulty weighing sensor, and finally comparing the second fault identification parameter with the first fault identification parameter through the comparison module, thereby determining a fault mode of the vehicle-mounted truck scale fault. On one hand, the least square method is adopted to identify the system parameters, the physical significance of the system parameters is not required to be obtained, only solution is needed to be carried out and compared with the system parameters of various fault modes, and the fault mode of the vehicle-mounted truck scale is obtained; on the other hand, the detection system is simple, the vehicle-mounted truck scale fault detection system is optimized, the detection speed is improved, and the fault type can be visually detected; the method can be widely applied to the detection of the faults of the vehicle-mounted truck scale.

Drawings

Fig. 1 is a schematic structural diagram of a vehicle-mounted truck scale fault detection system according to an embodiment of the present invention.

Detailed Description

The invention is further illustrated by the following examples in conjunction with the accompanying drawings:

in a first example of the present invention, as shown in fig. 1, there is provided an on-board truck scale fault detection system, the system comprising:

a fault category establishing module 100, configured to determine that the number of the weighing sensors of the vehicle-mounted truck scale is eight, and determine that the fault category of the weighing sensor is: short-circuit faults, open-circuit faults, zero faults and sensitivity faults, and determining the total fault number as the product of the number of the circuits and the number of the fault categories;

a sample library establishing module 200, configured to experimentally control each weighing sensor to be in each fault category, and respectively acquire first data Q of the weighing sensor sample in the fault mode_(i,j)(ii) a The first data Q_(i,j)Comprises a first sensor output signal X_1(i,j)The second path of sensor output signal X_2(i,j)And the output signal X of the third sensor_3(i,j)And the fourth path of sensor output signal X_4(i,j)The fifth path of sensor output signal X_5(i,j)And the sixth path of sensor output signal X_6(i,j)The first stepSeven-channel sensor output signal X_7(i,j)Output signal X by the eighth sensor_8(i,j)(ii) a The i is the total failure number; j is the serial number of the first data, and j is a positive integer;

a sample input/output sequence determining module 300 for determining a sequence of samples based on the first data Q_(i,j)Confirming the first output data column F_i(j)And a first input matrix phi_(i,j)(ii) a The first output data column F_i(j)＝(X_1(i,1) X_1(i,2) … X_1(i,j))^TThe first input matrix

A sample failure identification module 400 for solving a first failure identification parameter η corresponding to the weighing sensor samples of each of the failure modes_i(ii) a The first fault identification parameter η_iSatisfies the following conditions:

wherein said eta_iIs a column vector of said η_iSeven sub-items are included; eta of_i＝[a_(i,1) a_(i,2) a_(i,3) a_(i,4) a_(i,5) a_(i,6)a_(i,7)]^T；

The operation data acquisition module 500 is used for acquiring the second data G of the faulty weighing sensor in real time in the actual detection process_(n)(ii) a The second data G_(n)Comprises a first sensor output signal X_1(n)The second path of sensor output signal X_2(n)And the output signal X of the third sensor_3(n)And the fourth path of sensor output signal X_4(n)The fifth path of sensor output signal X_5(n)The sixth path of sensor output signal X_6(n)The seventh sensor output signal X_7(n)Output signal X by the eighth sensor_8(n)(ii) a The n is the serial number of the fault mode, the n is the serial number of the second data, and the n is a positive integer;

run inputAn output sequence determination module 600 for determining the output sequence according to the second data G_(n)Identifying the second output data column F (n) and the second input matrix phi_(n)(ii) a The second output data sequence f (n) ═ X₁₍₁₎ X₁₍₂₎ … X_1(n))^TSaid second input matrix

The operation fault identification module 700 is used for solving a second fault identification parameter omega of the faulty weighing sensor; the second fault identification parameter ω satisfies:

wherein the ω is a column vector, the ω includes seven sub-terms; ω ═ b₍₁₎ b₍₂₎ b₍₃₎ b₍₄₎ b₍₅₎ b₍₆₎ b₍₇₎]^T；

A comparison module 800 for comparing the second fault identification parameter ω and the first fault identification parameter η_iComparing to obtain a comparison value D_(i)Taking the contrast value D_(i)And determining the faults of the vehicle-mounted truck scale for the number of roadblocks corresponding to the minimum value and the fault type.

In this embodiment, the comparing module 800 further includes:

a contrast value solving unit for solving the contrast value D_(i)(ii) a The contrast value D_(i)Satisfies the following conditions:

m is the second fault identification parameter ω and the first fault identification parameter η_iThe number of the child entry;

a minimum value selection unit for selecting the minimum value according to the solved contrast value D_(i)Selecting D_min＝min(D_(i))；

A fault determination unit for determining a fault according to D_minDetermining the failure mode of the faulty load cell.

In this embodiment, the first data Q_(i,j)And outputting voltage or current for each path of weighing sensor.

In this embodiment, in the sample construction stage, the load cells with faults are set to the corresponding paths for the experiment.

The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.