Fuzzy determination method and device for equipment fault, equipment and medium

Abstract

The invention discloses an equipment fault fuzzy determination method and device, equipment and a medium, and relates to the technical field of fault judgment of site equipment of overload control sites, and the method comprises the steps: obtaining site vehicle passing data corresponding to each overload control site and at least one fault judgment strategy corresponding to each overload control site; executing an analysis process on the station vehicle passing data of each overload control station; and determining the faulty site equipment and a target fault type corresponding to the faulty site equipment. The method and the device are used for solving the problem that station equipment faults cannot be found in time due to the fact that all equipment state data cannot be effectively obtained in the prior art, and the faults of the station equipment can be found in time through the station vehicle passing data of the overtaking station.

Description

Technical Field

[0001] The present application relates to the technical field of fault determination of site equipment at an overweight control site, and in particular to a fuzzy determination method, device, equipment and medium for equipment fault. Background Art

[0002] The current status of the equipment at the overload control sites is collected by each overload control site, but the collection methods and technologies of each overload control site are uneven. The equipment status data collected by each overload control site is based on its own development standards and data structure, and is obtained after integrating the SDK of each site equipment.

[0003] In the prior art, if you want to obtain the device status data of each site equipment in each overweight control site, you need to connect with each overweight control site and intuitively obtain the device status data through the SDK of each site equipment. However, in actual applications, due to the large number of overweight control sites, each overweight control site includes multiple site equipment, and the technologies used are uneven, resulting in the inability to effectively obtain some device status data. Since the device status data cannot be effectively obtained, the equipment failure cannot be discovered in time, which may cause some immeasurable impacts. Summary of the invention

[0004] In response to the above-mentioned problems and technical needs, the applicant has proposed a fuzzy determination method, device, equipment and medium for equipment failure, so as to solve the problem that the prior art cannot effectively obtain all equipment status data, resulting in the failure of site equipment to be discovered in time, and to realize the timely discovery of site equipment failure through the site vehicle passing data of the overload control site.

[0005] The present application provides a fuzzy determination method for equipment failure, the method comprising:

[0006] Obtaining the site vehicle passing data corresponding to each overweight control site and at least one first fault discrimination strategy corresponding to each overweight control site, wherein the first fault discrimination strategy is obtained based on the site health corresponding to each site equipment in the overweight control site, the site health corresponds to at least one fault type, each of the fault types corresponds to a first fault discrimination strategy, one overweight control site corresponds to at least one site equipment, and one site equipment corresponds to one site health;

[0007] The following analysis process is performed on the vehicle passing data of each overload control station:

[0008] Analyze the vehicle passing data of the station using the first fault identification strategy of the overload control station to obtain a first analysis result;

[0009] In the case where it is determined that the first analysis result includes a fault type, determining a site device where the fault occurs and a first target fault type corresponding to the faulty site device;

[0010] When it is determined that the first analysis result does not include the fault type, obtain a preset second fault identification strategy; analyze the site vehicle passing data based on the second fault identification strategy to obtain a second analysis result; when it is determined that the second analysis result includes the fault type, determine the site equipment where the fault occurs, and the second target fault type corresponding to the faulty site equipment.

[0011] According to a fuzzy determination method of equipment failure in one embodiment of the present application, the vehicle passing data of the overload control site is analyzed using the first fault discrimination strategy of the overload control site, or the vehicle passing data of the overload control site is analyzed based on the second fault discrimination strategy, including:

[0012] For each overload control site, perform one or more of the following fault determination processes:

[0013] In the case where the vehicle passing data corresponding to the overweight control site is not received within the first preset time period, it is determined that any one or more of the data collection equipment, the site network or the site power system of the overweight control site fails, wherein different overweight control sites correspond to different preset time periods;

[0014] When it is determined that the first field in the station vehicle passing data has continuous identical data, it is determined that the station equipment corresponding to the first field is faulty;

[0015] When it is determined that the data of the second field in the site vehicle passing data does not meet the preset data requirement, determining that the site equipment corresponding to the second field is faulty;

[0016] When it is determined that the time difference between the collection time and the upload time of the vehicle passing data at the site is greater than the preset time difference, it is determined that the site equipment has a timing failure;

[0017] When it is determined that the preset port data is not received within the second preset time period, and the site network and site power system of the overweight control site are normal, it is determined that the data acquisition device is faulty;

[0018] When it is determined that the actual number of video segments in the site vehicle passing data is continuously inconsistent with the preset number of video segments, and / or the actual number of pictures is continuously inconsistent with the preset number of pictures, it is determined that the acquisition camera of the site equipment is faulty.

[0019] According to a fuzzy determination method of equipment failure in one embodiment of the present application, the first fault discrimination strategy of the overload control site is used to analyze the vehicle passing data of the site, including:

[0020] Obtain the probability of occurrence of a fault corresponding to each fault type of each site equipment of the overload control site;

[0021] For each site device, based on the magnitude relationship of the fault occurrence probabilities, the fault types are sorted in descending order;

[0022] Based on the sorting result, the station vehicle passing data is analyzed using a first fault discrimination strategy corresponding to the fault type.

[0023] According to a fuzzy determination method for equipment failure in one embodiment of the present application, obtaining the probability of occurrence of a failure corresponding to each failure type of each site equipment of the overload control site includes:

[0024] The following query process is performed for each fault type of each site equipment of the overload control site:

[0025] Based on the site historical fault data query interface, obtain the historical fault occurrence ratio corresponding to the fault type, the first fault occurrence ratio corresponding to the first area, and the second fault occurrence ratio corresponding to the second area;

[0026] The product of the historical fault occurrence ratio and the first weight, the product of the first fault occurrence ratio and the second weight, and the product of the second fault occurrence ratio and the third weight are calculated, and the product results are summed to obtain the fault occurrence probability.

[0027] According to a fuzzy determination method of equipment failure in one embodiment of the present application, the site health is obtained based on the usage time of the site equipment, the number of historical failure occurrences, and the scoring result of the operating status of the site equipment.

[0028] According to a fuzzy determination method of equipment failure in one embodiment of the present application, the site types of the overload control site include: overload control type, non-stop monitoring point type and source site type;

[0029] After obtaining the vehicle passing data corresponding to each overload control station, it also includes:

[0030] Dividing the station vehicle passing data into non-motor vehicle data, passenger vehicle data and freight vehicle data based on vehicle passing types, wherein the vehicle passing types include: non-motor vehicle, passenger vehicle and freight vehicle;

[0031] Divide the non-motor vehicle data, the passenger transport data and the freight transport data into three data tables based on the station type, wherein the data tables include: an overload control data table, a non-stop monitoring point data table and a source data table;

[0032] Perform structural processing on the data in each data table to obtain the target data table;

[0033] The analysis process is performed on the vehicle passing data of each of the overload control stations, including:

[0034] Based on the target data table, an analysis process is performed on the vehicle passing data of each of the overload control sites.

[0035] According to a fuzzy determination method for equipment failure in one embodiment of the present application, after determining the faulty site equipment and the target fault type corresponding to the faulty site equipment, the method further includes:

[0036] Obtaining actual fault types and busyness of the overload control site reported by users;

[0037] The first fault identification strategy or the second fault identification strategy is optimized based on the actual fault type, the site traffic busyness, and the site health.

[0038] The embodiment of the present application also provides a fuzzy determination device for equipment failure, including:

[0039] An acquisition module is used to acquire the site vehicle passing data corresponding to each overweight control site and at least one first fault discrimination strategy corresponding to each overweight control site, wherein the first fault discrimination strategy is obtained based on the site health corresponding to each site equipment in the overweight control site, the site health corresponds to at least one fault type, each of the fault types corresponds to a first fault discrimination strategy, one overweight control site corresponds to at least one site equipment, and one site equipment corresponds to one site health;

[0040] The analysis module is used to perform the following analysis process on the vehicle passing data of each overload control station:

[0041] Analyze the vehicle passing data of the station using the first fault identification strategy of the overload control station to obtain a first analysis result;

[0042] A first determination module, configured to determine, when it is determined that the first analysis result includes a fault type, a site device where the fault occurs and a first target fault type corresponding to the faulty site device;

[0043] The second determination module is used to obtain a preset second fault discrimination strategy when it is determined that the first analysis result does not include a fault type; analyze the site vehicle passing data based on the second fault discrimination strategy to obtain a second analysis result; and determine the site equipment where the fault occurs and the second target fault type corresponding to the faulty site equipment when it is determined that the second analysis result includes a fault type.

[0044] An embodiment of the present application also provides an electronic device, including 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 fuzzy determination method of device failure as described in any one of the above items are implemented.

[0045] An embodiment of the present application further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the fuzzy determination method of equipment failure as described in any one of the above items.

[0046] The fuzzy determination method, device, equipment and medium of equipment failure provided in the embodiments of the present application obtain the site vehicle passing data corresponding to each overweight control site and at least one first fault discrimination strategy corresponding to each overweight control site; use the first fault discrimination strategy of the overweight control site to analyze the site vehicle passing data to obtain a first analysis result; when it is determined that the first analysis result includes the fault type, determine the site equipment where the fault occurs and the first target fault type corresponding to the faulty site equipment; when it is determined that the first analysis result does not include the fault type, obtain a preset second fault discrimination strategy; analyze the site vehicle passing data based on the second fault discrimination strategy to obtain a second fault discrimination result; analysis results; when it is determined that the second analysis result includes a fault type, determine the site equipment where the fault occurs, and the second target fault type corresponding to the faulty site equipment. The present application analyzes the site vehicle passing data through the first fault discrimination strategy corresponding to the overload control site to determine the faulty site equipment in the overload control site, and uses the second fault discrimination device to further analyze the site vehicle passing data to prevent the problem that some faults that may occur in the first fault discrimination strategy cannot be identified. The site vehicle passing data can be analyzed in a timely and comprehensive manner, ensuring the reliability and stability of the analysis results, and achieving the purpose of timely discovering the fault of the site equipment through the site vehicle passing data of the overload control site. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 any creative work.

[0048] Figure 1 This is one of the flow charts of the fuzzy determination method of equipment failure provided in the embodiment of the present application;

[0049] Figure 2 This is the second flow field schematic diagram of the fuzzy determination method of equipment failure provided in the embodiment of the present application;

[0050] Figure 3 It is a structural schematic diagram of a fuzzy determination device for equipment failure provided in an embodiment of the present application;

[0051] Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] The embodiment of the present application provides a fuzzy determination method for equipment failure. The method can be applied to a smart terminal and a server. Some other descriptions in the embodiment of the present application are for illustrative purposes only and are not intended to limit the scope of protection of the present application, and will not be described one by one later.

[0054] Among them, the intelligent terminal includes the all-in-one equipment in the overload control site, and the logic of the fuzzy determination method of equipment failure is deployed in the all-in-one equipment. This method has strong timeliness and high data integrity in data collection.

[0055] The data of vehicles passing through the overload control equipment at each overload control station can also be summarized and uploaded to the server, which can then analyze the data. This method has low deployment and operation and maintenance costs and requires less development.

[0056] Users can deploy according to their actual needs. This application does not impose any restrictions. This application is explained using the application on the server as an example.

[0057] The specific implementation of this method is as follows Figure 1 As shown:

[0058] Step 101: Obtain vehicle passing data corresponding to each overload control station and at least one first fault identification strategy corresponding to each overload control station.

[0059] Among them, the first fault identification strategy is obtained based on the site health corresponding to each site equipment in the overweight control site. The site health corresponds to at least one fault type, each fault type corresponds to a first fault identification strategy, one overweight control site corresponds to at least one site equipment, and one site equipment corresponds to one site health.

[0060] Step 102, performing the following analysis process on the vehicle passing data of each overweight control station: using the first fault identification strategy of the overweight control station to analyze the vehicle passing data of the station, and obtaining a first analysis result.

[0061] Step 103: When it is determined that the first analysis result includes a fault type, determine a site device where the fault occurs and a first target fault type corresponding to the faulty site device.

[0062] Step 104, when it is determined that the first analysis result does not include the fault type, obtain a preset second fault identification strategy; analyze the site vehicle passing data based on the second fault identification strategy to obtain a second analysis result; when it is determined that the second analysis result includes the fault type, determine the site equipment where the fault occurs, and the second target fault type corresponding to the faulty site equipment.

[0063] The fuzzy determination method of equipment fault provided in the embodiment of the present application obtains the site vehicle passing data corresponding to each overweight control site and at least one first fault discrimination strategy corresponding to each overweight control site; uses the first fault discrimination strategy of the overweight control site to analyze the site vehicle passing data to obtain a first analysis result; when it is determined that the first analysis result includes the fault type, determines the site equipment where the fault occurs, and the first target fault type corresponding to the faulty site equipment; when it is determined that the first analysis result does not include the fault type, obtains a preset second fault discrimination strategy; analyzes the site vehicle passing data based on the second fault discrimination strategy to obtain a second analysis result; when it is determined that the second analysis result includes the fault type, determines the site equipment where the fault occurs, and the second target fault type corresponding to the faulty site equipment. The present application analyzes the site vehicle passing data through the first fault discrimination strategy corresponding to the overweight control site to determine the faulty site equipment in the overweight control site, and uses the second fault discrimination device to further analyze the site vehicle passing data to prevent the problem that some faults that may occur in the first fault discrimination strategy cannot be identified, and can timely and comprehensively analyze the site vehicle passing data, ensure the reliability and stability of the analysis results, and achieve the purpose of timely discovering the fault of the site equipment through the site vehicle passing data of the overweight control site.

[0064] In a specific embodiment, the site health is obtained based on the usage time of the site equipment, the number of historical fault occurrences, and the scoring result of the operating status of the site equipment.

[0065] Specifically, each site equipment in each overload control site has a corresponding site health (vital health value), which is a dynamically changing value. The values ​​are refreshed based on the usage time of the site equipment, the number of historical faults, the type of each fault, and the score of the site equipment's operating status after the fault is repaired.

[0066] The scoring result of the operating status of the site equipment after the fault repair can be obtained through subjective evaluation of the user, and can also be obtained through analysis of the operating data.

[0067] The longer the usage time, the more faults occurred, and the lower the score after repair, the smaller the value. The site health represents the health of the site equipment, and the two are in direct proportion.

[0068] Specifically, the site health can be divided into three levels according to the size of the value, namely, the first level, the second level and the third level, the first level site health is greater than the second level site health, and the second level site health is greater than the third level site health. The user can set the first level, the second level and the third level division values ​​according to their actual needs, and this application does not limit it.

[0069] For example, at the first level, when the site health is high, the corresponding fault types are circled by fault types such as equipment network faults and data acquisition software faults. At the second level, when the site health is medium, the corresponding fault types are circled by fault types caused by weather, temperature, etc. At the third level, when the site health is low, the corresponding fault types are circled by fault types corresponding to the historical fault data of the site equipment.

[0070] After the fault type is identified, at least one fault type corresponding to the site health is obtained, and each fault type corresponds to a first fault identification strategy.

[0071] In a specific embodiment, the types of sites of the overload control site include: overload control type, non-stop monitoring point type and source site type; the types of vehicles passing through the overload control site include: non-motor vehicles, passenger vehicles and freight vehicles.

[0072] After obtaining the site vehicle passing data corresponding to each overweight control site in the overweight control system, the site vehicle passing data is divided into non-motor vehicle data, passenger data and freight data based on the vehicle passing type; the non-motor vehicle data, passenger data and freight data are divided into three data tables based on the site type, and the data in each data table is structured to obtain a target data table. Then, based on the obtained target data table, the operation steps of performing the analysis process on the site vehicle passing data of each of the overweight control sites are performed.

[0073] Among them, the data tables include: overload control data table, non-stop monitoring point data table and source data table.

[0074] Specifically, the full data of all overweight control sites in the overweight control system (full site vehicle passing data) is obtained and sent to the intermediate warehouse, and the fault of the site equipment is determined after cleaning in the intermediate warehouse.

[0075] The full amount of data is diverted based on the site type and the vehicle type, and the data is diverted into three data tables according to the site type. Since the weight data, unit precision, time format and field storage format of the attachments provided by different overload control sites are different, the data needs to be institutionalized, that is, to form a unified format. For example, weight (two decimal places), time (in the form of year, month, day, hour, minute, and second, for example, yyyymmddhhmiss), and field storage format of attachments (number of video segments, 0, 1, 2, ..., number of pictures, 0, 1, 2, 3, 4, ...).

[0076] In addition, the site passing data includes the site code, which is uniformly set according to user needs. The site code is the unique identifier of the overload control site. The fault overload control site is determined by the site code.

[0077] In a specific embodiment, the specific implementation of analyzing the vehicle passing data of the site using the first fault discrimination strategy of the overload control site, or analyzing the vehicle passing data of the site based on the second fault discrimination strategy includes:

[0078] For each overload control site, perform one or more of the following fault determination processes:

[0079] If the vehicle passing data corresponding to the overweight control site is not received within the first preset time period, it is determined that any one or more of the data collection equipment, site network or site power system of the overweight control site has failed. Different overweight control sites correspond to different preset time periods.

[0080] When it is determined that continuous identical data appear in the first field of the station vehicle passing data, it is determined that the station equipment corresponding to the first field is faulty.

[0081] When it is determined that the data of the second field in the site vehicle passing data does not meet the preset data requirement, it is determined that the site equipment corresponding to the second field is faulty.

[0082] When it is determined that the time difference between the collection time and the upload time of the site vehicle passing data is greater than the preset time difference, it is determined that there is a timing failure in the site equipment.

[0083] When it is determined that the preset port data is not received within the second preset time period and the site network and site power system of the overweight control site are normal, it is determined that the data acquisition equipment is faulty.

[0084] When the actual number of video segments in the vehicle passing data at the site is determined to be continuously inconsistent with the preset number of video segments, and / or the actual number of images is continuously inconsistent with the preset number of images, it is determined that the acquisition camera of the site equipment is faulty.

[0085] Among them, the first fault discrimination strategy and the second fault discrimination strategy are relative, and the total number of fault discrimination strategies of the entire overload control system is fixed within a certain period. For each overload control site, the corresponding fault discrimination strategy is the first fault discrimination strategy, and the remaining fault discrimination strategy after removing the first fault discrimination strategy from the entire fault discrimination strategy is the second fault discrimination strategy.

[0086] Specifically, the busyness of each overweight control site is inconsistent, and the first preset duration corresponding to the busyness of the overweight control site is determined based on the busyness of the overweight control site. To determine that any one or more of the data acquisition equipment, site network or site power system of the overweight control site has failed, it is necessary to make a specific judgment based on the network and power conditions of the overweight control site.

[0087] Specifically, through network communication, the network status data of all network nodes in the overload control site is obtained, and the integrated machine, industrial computer, cabinet controller of the overload control site, and whether there are other site equipment failures in the overload control site are pinged to determine whether there are power problems and network stability in the overload control site. Then, network failures are screened out based on the network interface.

[0088] Specifically, when the overload detection equipment fails, normal detection data cannot be generated, and the overload control site will fill the first field with a default value. Therefore, when a certain field of the continuous business field (first field) of the integrated machine is the same, it is determined that the site equipment corresponding to the first field is faulty. For example, the license plate field is repeated once (distinguishing the front and rear license plates), which determines that the acquisition camera is faulty; for another example, if three consecutive data in the total weight field are the same, it is determined that the weighing scale is faulty.

[0089] Specifically, for existing technical specifications, there are clear requirements for the format and value range of some detection data. If the value corresponding to the business field (second field) is not compliant, the site equipment corresponding to the second field is determined to be faulty. For example, there are minimum and maximum limits for the weighbridge field. If the data is not within this range, the weighbridge is determined to be faulty. For example, the range of the weighbridge is 0 tons to 150 tons.

[0090] Specifically, after the data collection device collects data, it will upload it to the corresponding integrated machine. If the time difference between the same data collection time and the receiving time (upload time) displayed by the integrated machine is greater than the preset time difference, it is determined that there is a timing failure in the site equipment.

[0091] Specifically, the integrated machine collection port (for example, port 8890) is monitored, and the data collection service opens the port to collect data. If the duration of the failure to monitor port 8890 is greater than the second preset duration, and the site network and site power system of the overload control site are determined to be normal, the data collection device service failure is determined.

[0092] Specifically, each overload control site pre-sets collection rules, that is, preset video segments and preset image numbers, for example, three pictures (front, rear, license plate) + 1 video (passing video) are required. If there are missing pictures or videos, but the data has been collected, but when there are continuous missing pictures or videos within the third preset time, or the number of missing pictures or videos exceeds the preset number, it is determined that the collection camera of the site equipment is faulty.

[0093] Specifically, the thresholds in each fault discrimination strategy are flexibly configured, and users can set them according to their actual needs.

[0094] In a specific embodiment, the specific implementation of analyzing the vehicle passing data of the station by using the first fault discrimination strategy of the overload control station includes:

[0095] Obtain the fault probability corresponding to each fault type of each site equipment at the overload control site; for each site equipment, sort the fault types in descending order based on the size relationship of the fault probability; based on the sorting result, use the first fault discrimination strategy corresponding to the fault type to analyze the site vehicle passing data.

[0096] The above process is also used for calling the second fault identification strategy.

[0097] The present application schedules a fault identification strategy based on the magnitude relationship of the fault occurrence probability, and can quickly obtain the fault site equipment and the fault type.

[0098] In a specific embodiment, the specific implementation of obtaining the probability of occurrence of a fault corresponding to each fault type of each site equipment of the overload control site includes:

[0099] The following query process is performed for each fault type of each site equipment of the super control site: based on the site historical fault data query interface, the historical fault occurrence ratio corresponding to the fault type, the first fault occurrence ratio corresponding to the first area, and the second fault occurrence ratio corresponding to the second area are obtained.

[0100] The product of the historical fault occurrence ratio and the first weight, the product of the first fault occurrence ratio and the second weight, and the product of the second fault occurrence ratio and the third weight are calculated, and the product results are summed to obtain the fault occurrence probability.

[0101] Among them, the first failure occurrence ratio corresponding to the first area is, for example, the failure ratio of the equipment at the site in the city where the overload control site is located (for example, the first weight is 20%); the second failure occurrence ratio corresponding to the second area is, for example, the failure ratio of the equipment at the site in the province where the construction party of the overload control site is located (for example, the second weight is 40%). The third weight of the historical failure occurrence ratio of the equipment is 40%.

[0102] In a specific embodiment, after determining the faulty site equipment and the target fault type corresponding to the faulty site equipment, the actual fault type of the overload control site and the site traffic busyness reported by users are obtained; based on the actual fault type, site traffic busyness and site health, the first fault identification strategy or the second fault identification strategy is optimized.

[0103] The target fault type is the first target fault type or the second target fault type.

[0104] Specifically, the actual fault type will affect the parameters of the fault identification strategy, and the busyness of the station will also affect the parameters of the passing time.

[0105] In addition, the health of the site needs to be optimized. Except for the case where the site equipment is scrapped and cannot be used, each adjustment cannot exceed 15%. In addition, due to failures caused by extreme weather, electricity and network operations in the area where the overload control site is located, the parameter adjustment of the fault identification strategy cannot exceed 5%.

[0106] Next, through Figure 2 The following is a detailed description of this application:

[0107] Step 201, determining a first fault identification strategy corresponding to the current overload control site.

[0108] Step 202: Obtain the fault occurrence probability corresponding to each fault type of each site equipment of the overload control site, and determine the faulty site equipment and the fault type based on the fault occurrence probability.

[0109] Step 203: Acquire the actual fault site equipment and actual fault type of the overload control site fed back by the user.

[0110] Step 204: adjust the first fault identification strategy based on the actual fault site equipment and the actual fault type.

[0111] Specifically, the calling of the second fault discrimination strategy is the same as the above logic.

[0112] This application analyzes the data of vehicle passing through the site to achieve the control of the site equipment, solving the problem of incomplete and uneven site equipment status data in the prior art that the site equipment cannot be effectively controlled. In addition, during the execution process, the timeliness, accuracy and stability of the perception of the site equipment are guaranteed.

[0113] The embodiment of the present application also provides a fuzzy determination device for equipment failure. The specific implementation of the device can refer to the description of the fuzzy determination method for equipment failure, and the repeated parts will not be repeated. Figure 3 As shown, the device comprises:

[0114] The acquisition module 301 is used to obtain the site vehicle passing data corresponding to each overweight control site and at least one first fault discrimination strategy corresponding to each overweight control site, wherein the first fault discrimination strategy is obtained based on the site health corresponding to each site equipment in the overweight control site, the site health corresponds to at least one fault type, each fault type corresponds to a first fault discrimination strategy, one overweight control site corresponds to at least one site equipment, and one site equipment corresponds to one site health.

[0115] The analysis module 302 is used to perform the following analysis process on the vehicle passing data of each overweight control site: using the first fault discrimination strategy of the overweight control site to analyze the vehicle passing data of the site to obtain a first analysis result.

[0116] The first determination module 303 is used to determine the site device where the fault occurs and the first target fault type corresponding to the faulty site device when it is determined that the first analysis result includes the fault type.

[0117] The second determination module 304 is used to obtain a preset second fault discrimination strategy when it is determined that the first analysis result does not include the fault type; analyze the site vehicle passing data based on the second fault discrimination strategy to obtain a second analysis result; and determine the site equipment where the fault occurs and the second target fault type corresponding to the faulty site equipment when it is determined that the second analysis result includes the fault type.

[0118] In a specific embodiment, the analysis module 302 is used to perform any one or more of the following fault determination processes for each overweight control site: when it is determined that the site vehicle passing data corresponding to the overweight control site is not received within the first preset time period, it is determined that any one or more of the data acquisition equipment, site network or site power system of the overweight control site has failed, wherein different overweight control sites correspond to different preset time periods; when it is determined that the first field in the site vehicle passing data has continuous identical data, it is determined that the site equipment corresponding to the first field has failed; when it is determined that the data in the second field in the site vehicle passing data does not meet the preset data requirements, it is determined that the site equipment corresponding to the second field has failed; when it is determined that the time difference between the collection time and the upload time of the site vehicle passing data is greater than the preset time difference, it is determined that the site equipment has a timing failure; when it is determined that the preset port data is not received within the second preset time period, and the site network and site power system of the overweight control site are normal, it is determined that the data acquisition equipment has failed; when it is determined that the actual number of video segments in the site vehicle passing data is continuously inconsistent with the preset number of video segments, and / or the actual number of pictures is continuously inconsistent with the preset number of pictures, it is determined that the acquisition camera of the site equipment has failed.

[0119] In a specific embodiment, the analysis module 302 is used to obtain the fault occurrence probability corresponding to each fault type of each site equipment at the overload control site; for each site equipment, the fault types are sorted in descending order based on the size relationship of the fault occurrence probability; based on the sorting result, the site vehicle passing data is analyzed using the first fault judgment strategy corresponding to the fault type.

[0120] In a specific embodiment, the analysis module 302 is used to perform the following query process for each fault type of each site equipment of the super site: based on the site historical fault data query interface, obtain the historical fault occurrence ratio corresponding to the fault type, the first fault occurrence ratio corresponding to the first area, and the second fault occurrence ratio corresponding to the second area; calculate the product of the historical fault occurrence ratio and the first weight, the product of the first fault occurrence ratio and the second weight, and the product of the second fault occurrence ratio and the third weight, and sum the product results to obtain the fault occurrence probability.

[0121] In a specific embodiment, the site health is obtained based on the usage time of the site equipment, the number of historical fault occurrences, and the scoring result of the operating status of the site equipment.

[0122] In a specific embodiment, the site types of the overload control site include: overload control type, non-stop monitoring point type and source site type; the acquisition module 301 is also used to divide the site passing vehicle data into non-motor vehicle data, passenger data and freight data based on the passing vehicle type, wherein the passing vehicle types include: non-motor vehicle, passenger vehicle and freight vehicle; based on the site type, the non-motor vehicle data, passenger data and freight data are diverted into three data tables, wherein the data tables include: overload control data table, non-stop monitoring point data table and source data table; the data in each data table is structured to obtain a target data table; the analysis module 302 is used to perform an analysis process on the site passing vehicle data of each overload control site based on the target data table.

[0123] In a specific embodiment, the device also includes an optimization module for obtaining the actual fault type and site traffic busyness of the overload control site fed back by users; and optimizing the first fault identification strategy or the second fault identification strategy based on the actual fault type, site traffic busyness and site health.

[0124] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4As shown, the electronic device may include: a processor 401, a communications interface 402, a memory 403 and a communication bus 404, wherein the processor 401, the communications interface 402 and the memory 403 communicate with each other via the communication bus 404. The processor 401 may call the logic instructions in the memory 403 to execute the fuzzy determination method of the device failure.

[0125] In addition, the logic instructions in the above-mentioned memory 403 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 can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several 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: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0126] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the fuzzy determination method of equipment failure provided by the above-mentioned methods.

[0127] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to execute the fuzzy determination method of device failure provided in the above embodiments.

[0128] 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.

[0129] 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.

[0130] Finally, it should be noted that the above is only the preferred implementation of the present application, and the present application is not limited to the above embodiments. It is understood that other improvements and changes directly derived or associated by those skilled in the art without departing from the spirit and concept of the present application should be considered to be included in the scope of protection of the present application.

Claims

1. A fuzzy determination method for equipment failure, characterized in that: The method comprises: Obtaining the site vehicle passing data corresponding to each overweight control site and at least one first fault discrimination strategy corresponding to each overweight control site, wherein the first fault discrimination strategy is obtained based on the site health corresponding to each site equipment in the overweight control site, the site health corresponds to at least one fault type, each of the fault types corresponds to a first fault discrimination strategy, one overweight control site corresponds to at least one site equipment, and one site equipment corresponds to one site health; The following analysis process is performed on the vehicle passing data of each overload control station: Analyze the vehicle passing data of the station using the first fault identification strategy of the overload control station to obtain a first analysis result; In the case where it is determined that the first analysis result includes a fault type, determining a site device where the fault occurs and a first target fault type corresponding to the faulty site device; When it is determined that the first analysis result does not include the fault type, obtain a preset second fault identification strategy; analyze the site vehicle passing data based on the second fault identification strategy to obtain a second analysis result; when it is determined that the second analysis result includes the fault type, determine the site equipment where the fault occurs, and the second target fault type corresponding to the faulty site equipment.

2. The fuzzy determination method of equipment failure according to claim 1, characterized in that: Analyzing the vehicle passing data of the site using the first fault discrimination strategy of the overload control site, or analyzing the vehicle passing data of the site based on the second fault discrimination strategy, including: For each overload control site, perform one or more of the following fault determination processes: In the case where the vehicle passing data corresponding to the overweight control site is not received within the first preset time period, it is determined that any one or more of the data collection equipment, the site network or the site power system of the overweight control site fails, wherein different overweight control sites correspond to different preset time periods; When it is determined that the first field in the station vehicle passing data has continuous identical data, it is determined that the station equipment corresponding to the first field is faulty; When it is determined that the data of the second field in the site vehicle passing data does not meet the preset data requirement, determining that the site equipment corresponding to the second field is faulty; When it is determined that the time difference between the collection time and the upload time of the vehicle passing data at the site is greater than the preset time difference, it is determined that the site equipment has a timing failure; When it is determined that the preset port data is not received within the second preset time period, and the site network and site power system of the overweight control site are normal, it is determined that the data acquisition device is faulty; When it is determined that the actual number of video segments in the site vehicle passing data is continuously inconsistent with the preset number of video segments, and / or the actual number of pictures is continuously inconsistent with the preset number of pictures, it is determined that the acquisition camera of the site equipment is faulty.

3. The fuzzy determination method of equipment failure according to claim 1, characterized in that: Analyzing the vehicle passing data of the station by using the first fault identification strategy of the overload control station includes: Obtain the probability of occurrence of a fault corresponding to each fault type of each site equipment of the overload control site; For each site device, based on the magnitude relationship of the fault occurrence probabilities, the fault types are sorted in descending order; Based on the sorting result, the station vehicle passing data is analyzed using a first fault discrimination strategy corresponding to the fault type.

4. The fuzzy determination method of equipment failure according to claim 3 is characterized in that: Obtaining the probability of occurrence of each fault type corresponding to each site equipment of the overload control site, including: The following query process is performed for each fault type of each site equipment of the overload control site: Based on the site historical fault data query interface, obtain the historical fault occurrence ratio corresponding to the fault type, the first fault occurrence ratio corresponding to the first area, and the second fault occurrence ratio corresponding to the second area; The product of the historical fault occurrence ratio and the first weight, the product of the first fault occurrence ratio and the second weight, and the product of the second fault occurrence ratio and the third weight are calculated, and the product results are summed to obtain the fault occurrence probability.

5. The fuzzy determination method of equipment failure according to any one of claims 1 to 4, characterized in that: The site health is obtained based on the usage time of the site equipment, the number of historical fault occurrences, and the scoring result of the operating status of the site equipment.

6. The fuzzy determination method of equipment failure according to any one of claims 1 to 4, characterized in that: The types of the overload control sites include: overload control type, non-stop monitoring point type and source site type; After obtaining the vehicle passing data corresponding to each overload control station, it also includes: Dividing the station vehicle passing data into non-motor vehicle data, passenger vehicle data and freight vehicle data based on vehicle passing types, wherein the vehicle passing types include: non-motor vehicle, passenger vehicle and freight vehicle; Divide the non-motor vehicle data, the passenger transport data and the freight transport data into three data tables based on the station type, wherein the data tables include: an overload control data table, a non-stop monitoring point data table and a source data table; Perform structural processing on the data in each data table to obtain the target data table; The analysis process is performed on the vehicle passing data of each of the overload control stations, including: Based on the target data table, an analysis process is performed on the vehicle passing data of each of the overload control sites.

7. The fuzzy determination method for equipment failure according to any one of claims 1 to 4, characterized in that: After determining the faulty site device and the target fault type corresponding to the faulty site device, the following steps are also included: Obtaining actual fault types and busyness of the overload control site reported by users; The first fault identification strategy or the second fault identification strategy is optimized based on the actual fault type, the site traffic busyness, and the site health.

8. A fuzzy determination device for equipment failure, characterized in that: The device comprises: An acquisition module is used to acquire the site vehicle passing data corresponding to each overweight control site and at least one first fault discrimination strategy corresponding to each overweight control site, wherein the first fault discrimination strategy is obtained based on the site health corresponding to each site equipment in the overweight control site, the site health corresponds to at least one fault type, each of the fault types corresponds to a first fault discrimination strategy, one overweight control site corresponds to at least one site equipment, and one site equipment corresponds to one site health; The analysis module is used to perform the following analysis process on the vehicle passing data of each overload control station: Analyze the vehicle passing data of the station using the first fault identification strategy of the overload control station to obtain a first analysis result; A first determination module is used to determine the site device where the fault occurs and a first target fault type corresponding to the faulty site device when it is determined that the first analysis result includes the fault type; The second determination module is used to obtain a preset second fault discrimination strategy when it is determined that the first analysis result does not include a fault type; analyze the site vehicle passing data based on the second fault discrimination strategy to obtain a second analysis result; and determine the site equipment where the fault occurs and the second target fault type corresponding to the faulty site equipment when it is determined that the second analysis result includes a fault type.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the fuzzy determination method for equipment failure as described in any one of the above items are implemented.

10. 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 fuzzy determination method of equipment failure as described in any one of the above items are implemented.

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