Equipment health evaluation method, device, equipment, storage medium and program product

Abstract

The present invention provides a method, apparatus, device, storage medium and program product for evaluating the health of an equipment. The method for evaluating the health of an equipment includes: obtaining a plurality of real-time indicator data of the equipment; the indicator data includes information characterizing the operation stage of the equipment; determining first weight data corresponding to the operation stage of the equipment for each indicator data from the indicator weight corresponding data; the indicator weight corresponding data includes weight information corresponding to the indicator data of the equipment at different equipment operation stages; calculating the health data of the equipment based on each indicator data and the corresponding first weight data; and evaluating the health of the equipment based on the health data. The present invention is used to solve the defect in the prior art that it is impossible to realize real-time monitoring of the health of the equipment throughout its life cycle.

Description

Technical Field

[0001] The present invention relates to the field of electronic technology, and in particular to a device health evaluation method, apparatus, device, storage medium and program product. Background Art

[0002] Urban rail hardware equipment is developing towards large-scale, high-speed, automated, intelligent, and industrial interconnection. The Industrial Internet connects equipment, people, and information systems through data to achieve comprehensive perception of equipment status, dynamic transmission of industrial data, and real-time intelligent analysis. Mining fault feature information from hardware equipment status monitoring big data and efficiently and accurately identifying equipment health status, making maintenance decisions, and realizing equipment predictive maintenance have become challenges in the field of equipment dynamic monitoring, diagnosis, and maintenance. Extracting effective health indicators based on sensor monitoring data for early equipment fault detection, health evaluation, and operation prediction is one of the important contents of predictive maintenance research.

[0003] In the industrial Internet environment, the real-time perception data of equipment is relatively rich. The sensitive monitoring sensor data related to the performance degradation of equipment parts include vibration (displacement, acceleration), temperature, pressure or pressure difference, flow, lubricating oil composition (metal abrasive, acid value, kinematic viscosity), etc. It is relatively easy to obtain the fault sensitive feature monitoring data of equipment in normal state, but it is difficult to obtain the fault sensitive feature monitoring data of equipment in fault state, especially the acquisition of various types of fault sensitive feature monitoring data with different fault mechanisms requires prior knowledge. For example, the health index model is established by using Laplace characteristic Mahalanobis distance, convolutional recursive neural network, empirical mode decomposition and other methods, and the equipment health evaluation requires prior knowledge as support; if the health index model is established by using statistical analysis methods, it not only requires the monitoring data of the service life cycle of mechanical equipment "running to failure", but also needs to consider the differences in monitoring data of different equipment, different working conditions or different working conditions of the same equipment. Based on the above reasons, the existing methods cannot realize real-time monitoring of the health of the equipment throughout its life cycle. Summary of the invention

[0004] The present invention provides an equipment health evaluation method, device, equipment, storage medium and program product to solve the defect in the prior art that real-time monitoring of the health of equipment throughout its life cycle cannot be achieved.

[0005] The present invention provides a device health evaluation method, comprising:

[0006] Acquire multiple real-time indicator data of the device; the indicator data includes information characterizing the operation stage of the device;

[0007] Determine first weight data corresponding to each of the indicator data at the equipment operation stage from the indicator weight corresponding data; the indicator weight corresponding data includes weight information corresponding to the indicator data of the equipment at different equipment operation stages;

[0008] Calculate the health data of the device based on each of the indicator data and the corresponding first weight data;

[0009] The health of the device is evaluated based on the health data.

[0010] According to a device health evaluation method provided by the present invention, the health data of the device is calculated based on each of the indicator data and the corresponding first weight data, which is described by the following formula:

[0011] y=f(k1,x1,k2,x2,...,kn,xn);

[0012] Among them, y represents health data; x1 represents indicator data, k1 represents the first weight data determined by the indicator data x1 according to the indicator weight corresponding data; x2 represents indicator data, k2 represents the corresponding first weight data determined by the indicator data x2 according to the indicator weight corresponding data; xn represents indicator data, kn represents the corresponding first weight data determined by the indicator data xn according to the indicator weight corresponding data.

[0013] According to a device health evaluation method provided by the present invention, after obtaining the index data of the device, the method further includes:

[0014] Get the device's attribute data;

[0015] Determine second weight data corresponding to the attribute data from attribute weight corresponding data; the attribute weight corresponding data includes weight information corresponding to the attribute data of the device;

[0016] The calculating the health data of the device based on each of the indicator data and the corresponding first weight data includes:

[0017] The health data of the device is calculated based on each of the indicator data and the corresponding first weight data, and each of the attribute data and the corresponding second weight data.

[0018] According to a device health evaluation method provided by the present invention, the health data of the device is calculated based on each of the indicator data and the corresponding first weight data, and each of the attribute data and the corresponding second weight data, and is implemented by the following formula:

[0019] y=(k1*x1+k2*x2+……+kn*xn)*(kn+1*xn+1)*(kn+2*xn+2)2 ;

[0020] Among them, y represents health data; x1 represents indicator data, k1 represents the first weight data determined by the indicator data x1 according to the indicator weight corresponding data; x2 represents indicator data, k2 represents the first weight data determined by the indicator data x2 according to the indicator weight corresponding data; xn represents indicator data, kn represents the first weight data determined by the indicator data xn according to the indicator weight corresponding data; xn+1 represents attribute data, kn+1 represents the second weight data determined by the attribute data xn+1 according to the attribute weight corresponding data; xn+2 represents attribute data, kn+2 represents the second weight data determined by the attribute data xn+2 according to the attribute weight corresponding data.

[0021] According to a device health evaluation method provided by the present invention, the health of the device is evaluated based on the health data, including:

[0022] When the health data is lower than a set threshold, it is determined that the device is in a healthy state; otherwise, it is determined that the device is in a state to be repaired.

[0023] According to a device health evaluation method provided by the present invention, before the step of obtaining the index data of the device, the method further includes:

[0024] The data corresponding to the indicator weights are formed.

[0025] The present invention also provides an equipment health evaluation device, comprising:

[0026] A first acquisition module is used to acquire multiple real-time indicator data of the device; the indicator data includes information representing the operation stage of the device;

[0027] A first determination module is used to determine first weight data corresponding to each indicator data of the equipment operation stage from indicator weight corresponding data; the indicator weight corresponding data includes weight information corresponding to the indicator data of the equipment at different equipment operation stages;

[0028] A calculation module, used for calculating the health data of the device based on each of the indicator data and the corresponding first weight data;

[0029] An evaluation module is used to evaluate the health of the device based on the health data.

[0030] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of any of the above-mentioned device health assessment methods are implemented.

[0031] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the above-mentioned equipment health assessment methods are implemented.

[0032] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the steps of any of the above-mentioned equipment health assessment methods are implemented.

[0033] The equipment health evaluation method, apparatus, device, storage medium and program product provided by the present invention obtain multiple real-time indicator data of the equipment; the indicator data contains information characterizing the equipment operation stage; and the first weight data corresponding to the equipment operation stage of each real-time indicator data is determined by the indicator weight corresponding data; the health data of the equipment is calculated based on each indicator data and the corresponding first weight data; and finally, the health of the equipment is evaluated based on the health data. Therefore, the present invention configures weight information for the indicator data of the equipment according to different equipment operation stages, and then according to the real-time multiple indicator data of each equipment operation stage and the corresponding first weight data, the health of each equipment operation stage can be calculated, thereby realizing real-time monitoring of the health of the equipment throughout its life cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 It is one of the flow charts of the equipment health evaluation method provided by the present invention;

[0036] Figure 2 This is the second flow chart of the equipment health evaluation method provided by the present invention;

[0037] Figure 3 This is the third flow chart of the equipment health evaluation method provided by the present invention;

[0038] Figure 4 This is the fourth flow chart of the equipment health evaluation method provided by the present invention;

[0039] Figure 5 This is the fifth flow chart of the equipment health evaluation method provided by the present invention;

[0040] Figure 6 It is a structural schematic diagram of the equipment health evaluation device provided by the present invention;

[0041] Figure 7 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] In the industrial Internet environment, the real-time perception data of equipment is relatively rich. The sensitive monitoring sensor data related to the performance degradation of equipment parts include vibration (displacement, acceleration), temperature, pressure or pressure difference, flow, lubricating oil composition (metal abrasive, acid value, kinematic viscosity), etc. It is relatively easy to obtain the fault sensitive feature monitoring data of equipment in normal state, but it is difficult to obtain the fault sensitive feature monitoring data of equipment in fault state, especially the acquisition of various types of fault sensitive feature monitoring data with different fault mechanisms requires prior knowledge. For example, the health index model is established by using Laplace characteristic Mahalanobis distance, convolutional recursive neural network, empirical mode decomposition and other methods, and the equipment health evaluation requires prior knowledge as support; if the health index model is established by using statistical analysis methods, it not only requires the monitoring data of the service life cycle of mechanical equipment "running to failure", but also needs to consider the differences in monitoring data of different equipment, different working conditions or different working conditions of the same equipment. Based on the above reasons, the existing methods cannot realize real-time monitoring of the health of the equipment throughout its life cycle.

[0044] In view of this, the present invention proposes an equipment health evaluation method, apparatus, device, storage medium and program product to solve the defect in the prior art that it is impossible to realize real-time monitoring of the health of the equipment throughout its life cycle.

[0045] Combine the following Figure 1-Figure 5 For a description of the device health assessment method of the present invention, please refer to Figure 1 , equipment health assessment methods include:

[0046] Step 100: Acquire multiple real-time indicator data of the device; the indicator data includes information characterizing the operation stage of the device.

[0047] Multiple real-time indicator data of the device are obtained through the electronic device. The device may be a device that needs to be evaluated for health in various fields in actual production. For example, headphones in the field of consumer electronics, urban rail hardware equipment in the field of urban rail transit, etc. This embodiment is described by taking the urban rail hardware equipment in the field of urban rail transit as an example.

[0048] Specifically, the health evaluation can be performed by selecting indicator data according to the indicators that affect the health of the equipment. For example, when evaluating the health of the wear degree of the train wheel diameter, the last maintenance time and the running mileage from the last maintenance time to the present can be set as indicator data to evaluate the health of the train wheel diameter wear.

[0049] Step 200: Determine first weight data corresponding to each indicator data at the equipment operation stage from indicator weight corresponding data; the indicator weight corresponding data includes weight information corresponding to the indicator data of the equipment at different equipment operation stages.

[0050] The electronic device determines the first weight data of each indicator data corresponding to the device operation stage from the indicator weight corresponding data, wherein the indicator weight corresponding data includes the weight information corresponding to the indicator data of the device at different device operation stages.

[0051] For some equipment, such as the train wheel hub in the urban rail hardware equipment, the wheel diameter wear of the train wheel hub does not change linearly with time, that is, the wheel diameter wear rate of the train wheel hub does not remain constant. For example, at the beginning of the life cycle of the train wheel hub, the wheel diameter wear of the train wheel hub is faster, while in the middle stage of the life cycle of the train wheel hub, the wheel diameter wear of the train wheel hub slows down. Therefore, it is necessary to set different weight information for each operation stage of the wheel diameter wear of the train wheel hub to evaluate the health, so as to better provide early warning and predictive maintenance of the wheel diameter wear of the train wheel hub.

[0052] The following uses the train's last maintenance time to date running mileage to represent the equipment's operating stage, and uses the last wheel diameter maintenance time and the last maintenance time to date running mileage as indicator data, and illustrates the indicator weight corresponding data of the present invention through Table 1 and Table 2. As shown in Tables 1 and 2, Table 1 shows the weight information of each indicator data when the train's last maintenance time to date running mileage is 5,000-10,000 kilometers. Table 1 shows the weight information of each indicator data when the train's last maintenance time to date running mileage is 10,000-12,000 kilometers.

[0053]

[0054]

[0055] Table 1

[0056]

[0057]

[0058] Table 2

[0059] Specifically, when the indicator data obtained is that the last wheel diameter maintenance time is 10 days; the mileage from the last maintenance time to date is 11,000 kilometers, it can be seen from Table 2 that the weight information corresponding to the last wheel diameter maintenance time of 10 days is 0.2, and the weight information corresponding to the mileage from the last maintenance time to date is 11,000 kilometers is 0.006.

[0060] Step 500: Calculate the health data of the device based on each of the indicator data and the corresponding first weight data.

[0061] The electronic device calculates the health data of the device based on each of the indicator data and the corresponding first weight data. Specifically, in some embodiments, the health data of the device is calculated based on each of the indicator data and the corresponding first weight data, which is described by the following formula:

[0062] y=f(k1,x1,k2,x2,...,kn,xn);

[0063] Among them, y represents health data; x1 represents indicator data, k1 represents the first weight data determined by the indicator data x1 according to the indicator weight corresponding data; x2 represents indicator data, k2 represents the corresponding first weight data determined by the indicator data x2 according to the indicator weight corresponding data; xn represents indicator data, kn represents the corresponding first weight data determined by the indicator data xn according to the indicator weight corresponding data.

[0064] Specifically, the health data of the device is calculated based on each of the indicator data and the corresponding first weight data, which is described by the following formula y=k1*x1+k2*x2+…+kn*xn; wherein y represents health data; x1 represents indicator data, k1 represents first weight data determined by indicator data x1 according to the indicator weight corresponding data; x2 represents indicator data, k2 represents first weight data determined by indicator data x2 according to the indicator weight corresponding data; xn represents indicator data, kn represents first weight data determined by indicator data xn according to the indicator weight corresponding data.

[0065] Taking the weight information corresponding to the last wheel diameter maintenance time of 10 days in step 200 as 0.2, and the weight information corresponding to the mileage of 11,000 kilometers since the last maintenance time as 0.006 as an example, the health data y=(k1*x1+k2*x2)=10*0.2+11000*0.006=68.

[0066] The above embodiment only lists the situation where the indicator data includes two indicators, namely, the last wheel diameter maintenance time and the running mileage from the last maintenance time to date. It can be understood that in some other embodiments, the indicator data may also include more than two indicators.

[0067] Step 600: Evaluate the health of the device based on the health data.

[0068] The electronic device evaluates the health of the device based on the health data. Specifically, a threshold value may be set for the health data. If the health data is lower than the set threshold value, the device is determined to be in a healthy state; otherwise, the device is determined to be in a state to be repaired.

[0069] For example, the threshold value of the health data is set to 100. When the calculated health data is lower than 100, it indicates that the wheel wear degree of the train is in a healthy state. For example, the health data of the wheel wear degree of the train obtained in step 300 is 68, which is less than the set threshold value of 100, indicating that the wheel wear degree of the train is in a healthy state and does not require maintenance. Otherwise, the health data is greater than or equal to the set threshold value of 100, and it is determined that the equipment is in a state to be repaired. It is necessary to notify the technicians in time for maintenance.

[0070] The equipment health evaluation method of the present invention obtains multiple real-time indicator data of the equipment; the indicator data contains information that characterizes the equipment operation stage; and determines the first weight data of the equipment operation stage corresponding to each real-time indicator data through the indicator weight corresponding data; and calculates the health data of the equipment based on each indicator data and the corresponding first weight data; and finally evaluates the health of the equipment based on the health data. Therefore, the present invention configures weight information for the indicator data of the equipment according to different equipment operation stages, and then according to the real-time multiple indicator data and corresponding weight information of each equipment operation stage, it can calculate the health of each equipment operation stage, thereby realizing real-time monitoring of the health of the equipment throughout its life cycle.

[0071] For other aspects of the present invention, please refer to Figure 2 After obtaining the indicator data of the device, the method further includes:

[0072] Step 300: Obtain attribute data of the device;

[0073] The attribute data of the device is obtained through the electronic device. Attribute data refers to attribute data representing the attribute information of the device itself. For example, the attribute data of the present invention also includes the vehicle model and the wheel set model. Since the change process of the wheel diameter wear degree of trains with different models of vehicles and different wheel set models will also be different. By increasing the attribute data of the device to evaluate the health, the present invention can evaluate the health of devices with different attributes or characteristics. Thereby, the health evaluation of the device is more refined and the application scope of the health evaluation of the device is expanded.

[0074] Step 400: Determine second weight data corresponding to the attribute data from attribute weight corresponding data; the attribute weight corresponding data includes weight information corresponding to different attribute data of the device;

[0075] The electronic device determines second weight data corresponding to the attribute data from attribute weight corresponding data, wherein the attribute weight corresponding data includes weight information corresponding to different attribute data of the device.

[0076] It can be understood that the present invention can combine attribute data with index data to evaluate the health of the equipment. For example, please refer to Table 3, which shows that the attribute data and corresponding weight information of the vehicle model and wheelset model are added on the basis of the last wheel diameter maintenance time and the running mileage since the last maintenance time as the index data, and are used as the indicators for evaluating the health of the equipment.

[0077]

[0078]

[0079] Table 3

[0080] Specifically, when the index data obtained is that the last wheel diameter maintenance time is 10 days; the running mileage from the last maintenance time to date is 11,000 kilometers, the vehicle model is type A, and the wheel set model is type B. From Table 3, it can be seen that the weight information corresponding to the last wheel diameter maintenance time of 10 days is 0.2, the weight information corresponding to the running mileage from the last maintenance time to date is 11,000 kilometers is 0.006, the weight corresponding to the vehicle model type A is 0.3, and the weight corresponding to the wheel set model type B is 0.5.

[0081] It is understandable that when the vehicle model changes, the weight corresponding to the vehicle model will also change accordingly. When the wheel set model changes, the weight corresponding to the wheel set model will also change accordingly.

[0082] Step 500, calculating the health data of the device based on each of the indicator data and the corresponding first weight data, includes:

[0083] Step 510: Calculate the health data of the device based on each of the indicator data and the corresponding first weight data, and each of the attribute data and the corresponding second weight data.

[0084] The electronic device calculates the health data of the device based on each of the indicator data and the corresponding first weight data, and each of the attribute data and the corresponding second weight data. Specifically, in some embodiments, step 510 can be implemented by the following formula:

[0085] y=(k1*x1+k2*x2+……+kn*xn)*(kn+1*xn+1)*(kn+2*xn+2) 2 ;

[0086] Among them, y represents health data; x1 represents indicator data, k1 represents the first weight data determined by the indicator data x1 according to the indicator weight corresponding data; x2 represents indicator data, k2 represents the first weight data determined by the indicator data x2 according to the indicator weight corresponding data; xn represents indicator data, kn represents the first weight data determined by the indicator data xn according to the indicator weight corresponding data; xn+1 represents attribute data, kn+1 represents the second weight data determined by the attribute data xn+1 according to the attribute weight corresponding data; xn+2 represents attribute data, kn+2 represents the second weight data determined by the attribute data xn+2 according to the attribute weight corresponding data.

[0087] For example, when the weight information corresponding to the last wheel diameter maintenance time of 10 days is 0.2, the weight information corresponding to the mileage of 11,000 kilometers since the last maintenance time is 0.006, the weight corresponding to the vehicle model A is 0.3, and the weight corresponding to the wheel model B is 0.5, then the health data y=(10*0.2+11000*0.006)*0.3*1*(0.5*2) 2 = 20.4. At this time, the health data is less than the set threshold of 100, indicating that the wheel wear of the train is in a healthy state and does not require maintenance.

[0088] For other aspects of this application, please refer to Figure 3 , before the step of obtaining the index data of the device, it also includes:

[0089] Step 001: Form data corresponding to the indicator weights.

[0090] Specifically, the electronic device may receive in advance the weight information of each indicator data of each equipment operation stage obtained through expert scoring and actual experience, and form the indicator weight corresponding data. For details, please refer to Tables 1, 2 and 3 above.

[0091] By forming the indicator weight corresponding data, a basis is provided for the subsequent step of determining the first weight data corresponding to the equipment operation stage of each indicator data from the indicator weight corresponding data.

[0092] For other aspects of this application, please refer to Figure 4 , before the step of obtaining the index data of the device, it also includes:

[0093] Step 002: Generate data corresponding to the attribute weights.

[0094] Specifically, the electronic device may receive in advance the weight information corresponding to each attribute data obtained through expert scoring and actual experience, and form attribute weight corresponding data. For details, please refer to Table 3 above.

[0095] By forming the attribute weight corresponding data, a basis is provided for the subsequent step of determining the second weight data corresponding to the attribute data from the attribute weight corresponding data.

[0096] For other aspects of this application, please refer to Figure 5 , the equipment health evaluation method of the present invention further includes:

[0097] Step 700: Update the weight information of the data corresponding to the indicator weight according to the operation data of the equipment.

[0098] Specifically, after evaluating the health of the train wheel wear degree through the above-mentioned equipment health evaluation method, it may happen that the train wheel wear degree is evaluated as healthy using the above-mentioned equipment health evaluation method, but in fact the train wheel wear degree is too large. At this time, it is necessary to analyze and summarize the operating data of the equipment (such as the train wheel wear degree of the train hub at different train mileages) to obtain the updated weight information corresponding to each indicator data. For example, the weight of the mileage from the last maintenance time to the present of 10,000 to 12,000 kilometers in Table 3 above is modified to 0.007.

[0099] By updating the weight information of the indicator weight corresponding to the data according to the equipment's operating data, the accuracy of the equipment health evaluation can be further improved.

[0100] The equipment health evaluation device provided by the present invention is described below. The equipment health evaluation device described below and the equipment health evaluation method described above can be referenced to each other.

[0101] Please refer to Figure 6 The present invention also proposes a device for evaluating equipment health, comprising:

[0102] The first acquisition module 201 is used to acquire multiple real-time indicator data of the device; the indicator data includes information representing the operation stage of the device;

[0103] A first determination module 202 is used to determine first weight data corresponding to each indicator data of the equipment operation stage from indicator weight corresponding data; the indicator weight corresponding data includes weight information corresponding to the indicator data of the equipment at different equipment operation stages;

[0104] A calculation module 203, configured to calculate the health data of the device based on each of the indicator data and the corresponding first weight data;

[0105] The evaluation module 204 is used to evaluate the health of the device based on the health data.

[0106] The equipment health evaluation device of the present invention obtains multiple real-time indicator data of the equipment; the indicator data contains information that characterizes the equipment operation stage; and determines the first weight data of the equipment operation stage corresponding to each real-time indicator data through the indicator weight corresponding data; and calculates the health data of the equipment based on each indicator data and the corresponding first weight data; and finally evaluates the health of the equipment based on the health data. Therefore, the present invention configures weight information for the indicator data of the equipment according to different equipment operation stages, and then according to the real-time multiple indicator data and corresponding weight information of each equipment operation stage, it can calculate the health of each equipment operation stage, thereby realizing real-time monitoring of the health of the equipment throughout its life cycle.

[0107] Based on the above embodiments, as an optional embodiment, the calculation module is implemented by the following formula:

[0108] y=f(k1,x1,k2,x2,...,kn,xn);

[0109] Among them, y represents health data; x1 represents indicator data, k1 represents the first weight data determined by the indicator data x1 according to the indicator weight corresponding data; x2 represents indicator data, k2 represents the corresponding first weight data determined by the indicator data x2 according to the indicator weight corresponding data; xn represents indicator data, kn represents the corresponding first weight data determined by the indicator data xn according to the indicator weight corresponding data.

[0110] Based on the above embodiments, as an optional embodiment, the device health evaluation apparatus further includes:

[0111] A second acquisition module is used to acquire attribute data of a device;

[0112] A second determination module, configured to determine second weight data corresponding to the attribute data from attribute weight corresponding data; the attribute weight corresponding data includes weight information corresponding to the attribute data of the device;

[0113] The calculation module is also used to calculate the health data of the device based on each of the indicator data and the corresponding first weight data, and each of the attribute data and the corresponding second weight data.

[0114] Based on the above embodiments, as an optional embodiment, the calculation module is also implemented by the following formula:

[0115] y=(k1*x1+k2*x2+……+kn*xn)*(kn+1*xn+1)*(kn+2*xn+2) 2 ;

[0116] Among them, y represents health data; x1 represents indicator data, k1 represents the first weight data determined by the indicator data x1 according to the indicator weight corresponding data; x2 represents indicator data, k2 represents the first weight data determined by the indicator data x2 according to the indicator weight corresponding data; xn represents indicator data, kn represents the first weight data determined by the indicator data xn according to the indicator weight corresponding data; xn+1 represents attribute data, kn+1 represents the second weight data determined by the attribute data xn+1 according to the attribute weight corresponding data; xn+2 represents attribute data, kn+2 represents the second weight data determined by the attribute data xn+2 according to the attribute weight corresponding data.

[0117] Based on the above embodiments, as an optional embodiment, the evaluation module is specifically used to: when the health data is lower than a set threshold, determine that the device is in a healthy state; otherwise, determine that the device is in a state to be repaired.

[0118] Based on the above embodiments, as an optional embodiment, the device health evaluation apparatus further includes:

[0119] The indicator weight corresponding data forming module is used to form the indicator weight corresponding data.

[0120] Figure 7 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 7 As shown, the electronic device may include: a processor 710, a communication interface 720, a memory 730 and a communication bus 740, wherein the processor 710, the communication interface 720 and the memory 730 communicate with each other through the communication bus 740. The processor 710 may call the logic instructions in the memory 730 to execute the device health evaluation method, which includes: obtaining multiple real-time indicator data of the device; the indicator data includes information characterizing the operation stage of the device; determining the first weight data corresponding to the operation stage of the device for each indicator data from the indicator weight corresponding data; the indicator weight corresponding data includes the weight information corresponding to the indicator data of the device at different device operation stages; calculating the health data of the device based on each indicator data and the corresponding first weight data; and evaluating the health of the device based on the health data.

[0121] In addition, the logic instructions in the above-mentioned memory 730 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0122] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the equipment health evaluation method provided by the above methods, which method includes: obtaining multiple real-time indicator data of the equipment; the indicator data contains information characterizing the operation stage of the equipment; determining the first weight data corresponding to the operation stage of the equipment for each indicator data from the indicator weight corresponding data; the indicator weight corresponding data includes the weight information corresponding to the indicator data of the equipment in different equipment operation stages; calculating the health data of the equipment based on each indicator data and the corresponding first weight data; and evaluating the health of the equipment based on the health data.

[0123] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the above-mentioned methods to perform a device health evaluation method, the method comprising: obtaining multiple real-time indicator data of the device; the indicator data contains information characterizing the operation stage of the device; determining first weight data corresponding to the operation stage of the device for each indicator data from indicator weight corresponding data; the indicator weight corresponding data includes weight information corresponding to the indicator data of the device at different device operation stages; calculating the health data of the device based on each indicator data and the corresponding first weight data; and evaluating the health of the device based on the health data.

[0124] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0125] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0126] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A device health evaluation method, characterized in that: include: Acquire multiple real-time indicator data of the equipment; the indicator data includes information characterizing the operation stage of the equipment; the equipment includes urban rail hardware equipment; The multiple indicator data include the most recent maintenance time and the running mileage from the most recent maintenance time to date; Determine first weight data corresponding to each of the indicator data at the equipment operation stage from the indicator weight corresponding data; the indicator weight corresponding data includes weight information corresponding to the indicator data of the equipment at different equipment operation stages; Calculate the health data of the device based on each of the indicator data and the corresponding first weight data; evaluating the health of the device based on the health data; After obtaining the indicator data of the device, the method further includes: Acquire attribute data of the device; the attribute data includes vehicle model and wheel set model; Determine second weight data corresponding to the attribute data from attribute weight corresponding data; the attribute weight corresponding data includes weight information corresponding to the attribute data of the device; The calculating the health data of the device based on each of the indicator data and the corresponding first weight data includes: Calculating the health data of the device based on each of the indicator data and the corresponding first weight data, and each of the attribute data and the corresponding second weight data; The health data of the device is calculated based on each of the indicator data and the corresponding first weight data, and is described by the following formula: y=f(k1,x1,k2,x2,...,kn,xn); Wherein, y represents health data; x1 represents indicator data, k1 represents first weight data determined by indicator data x1 according to the indicator weight corresponding data; x2 represents indicator data, k2 represents first weight data corresponding to indicator data x2 determined according to the indicator weight corresponding data; xn represents indicator data, kn represents first weight data corresponding to indicator data xn determined according to the indicator weight corresponding data; The calculation of the health data of the device based on each of the indicator data and the corresponding first weight data, and each of the attribute data and the corresponding second weight data is implemented by the following formula: y=(k1*x1+k2*x2+……+kn*xn)*(kn+1*xn+1)*(kn+2*xn+2) 2 ; Among them, y represents health data; x1 represents indicator data, k1 represents the first weight data determined by the indicator data x1 according to the indicator weight corresponding data; x2 represents indicator data, k2 represents the first weight data determined by the indicator data x2 according to the indicator weight corresponding data; xn represents indicator data, kn represents the first weight data determined by the indicator data xn according to the indicator weight corresponding data; xn+1 represents attribute data, kn+1 represents the second weight data determined by the attribute data xn+1 according to the attribute weight corresponding data; xn+2 represents attribute data, kn+2 represents the second weight data determined by the attribute data xn+2 according to the attribute weight corresponding data.

2. The device health evaluation method according to claim 1, characterized in that: The evaluating the health of the device based on the health data includes: When the health data is lower than a set threshold, it is determined that the device is in a healthy state; otherwise, it is determined that the device is in a state to be repaired.

3. The device health evaluation method according to claim 1, characterized in that: Before the step of obtaining the index data of the device, the method further includes: The data corresponding to the indicator weights are formed.

4. A device for evaluating equipment health, characterized in that: include: The first acquisition module is used to acquire multiple real-time indicator data of the equipment; the indicator data includes information representing the operation stage of the equipment; the equipment includes urban rail hardware equipment; the multiple indicator data includes the last maintenance time and the running mileage from the last maintenance time to the present; A first determination module, used to determine first weight data corresponding to the equipment operation stage of each indicator data from indicator weight corresponding data; The indicator weight corresponding data includes weight information corresponding to the indicator data of the equipment at different equipment operation stages; A calculation module, used for calculating the health data of the device based on each of the indicator data and the corresponding first weight data; An evaluation module, configured to evaluate the health of the device based on the health data; A second acquisition module is used to acquire attribute data of the device; the attribute data includes a vehicle model and a wheelset model; A second determination module, configured to determine second weight data corresponding to the attribute data from attribute weight corresponding data; the attribute weight corresponding data includes weight information corresponding to the attribute data of the device; The calculation module is further used to: calculate the health data of the device based on each of the indicator data and the corresponding first weight data, and each of the attribute data and the corresponding second weight data; The calculation module is implemented by the following formula: y=f(k1,x1,k2,x2,...,kn,xn); Wherein, y represents health data; x1 represents indicator data, k1 represents first weight data determined by indicator data x1 according to the indicator weight corresponding data; x2 represents indicator data, k2 represents first weight data corresponding to indicator data x2 determined according to the indicator weight corresponding data; xn represents indicator data, kn represents first weight data corresponding to indicator data xn determined according to the indicator weight corresponding data; The calculation module is also implemented by the following formula: y=(k1*x1+k2*x2+……+kn*xn)*(kn+1*xn+1)*(kn+2*xn+2)2; Among them, y represents health data; x1 represents indicator data, k1 represents the first weight data determined by the indicator data x1 according to the indicator weight corresponding data; x2 represents indicator data, k2 represents the first weight data determined by the indicator data x2 according to the indicator weight corresponding data; xn represents indicator data, kn represents the first weight data determined by the indicator data xn according to the indicator weight corresponding data; xn+1 represents attribute data, kn+1 represents the second weight data determined by the attribute data xn+1 according to the attribute weight corresponding data; xn+2 represents attribute data, kn+2 represents the second weight data determined by the attribute data xn+2 according to the attribute weight corresponding data.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the device health evaluation method according to any one of claims 1 to 3 are implemented.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the device health assessment method according to any one of claims 1 to 3 are implemented.

7. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the device health assessment method according to any one of claims 1 to 3 are implemented.

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