Method, device and equipment for fault diagnosis of roadside equipment

Abstract

The present application relates to the technical field of fault diagnosis and discloses a method for fault diagnosis of roadside equipment. The method comprises: obtaining abnormal status information corresponding to the roadside equipment through a first preset method, obtaining abnormal data information corresponding to the roadside equipment through a second preset method; obtaining first fault information based on the abnormal status information, obtaining second fault information based on the abnormal data information; and determining third fault information based on the first fault information and the second fault information. The first fault information is obtained through the abnormal status information corresponding to the roadside equipment, the second fault information is obtained through the abnormal data information corresponding to the roadside equipment, and the third fault information is obtained by performing a fusion calculation based on the first fault information and the second fault information. By taking into account multiple factors such as the abnormal status information or abnormal data information corresponding to the roadside equipment, the accuracy of fault diagnosis of the roadside equipment is improved. The present application also discloses a device and equipment for fault diagnosis of roadside equipment.

Description

Technical Field

[0001] The present application relates to the technical field of fault diagnosis, for example, to a method, apparatus and equipment for fault diagnosis of roadside equipment. Background Art

[0002] Intelligent traffic information systems (ITIS) are a typical IoT application, primarily composed of roadside sensing devices, network communication equipment, and intelligent application systems. These devices are numerous and scattered across various roads. Accurately detecting equipment failures is challenging due to various uncertainties and traffic control measures.

[0003] During the process of implementing the embodiments of the present disclosure, it was found that at least the following problems exist in the related art: the accuracy of the prior art in diagnosing roadside equipment faults by only considering a single factor is low. Summary of the Invention

[0004] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical elements or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0005] The embodiments of the present disclosure provide a method, apparatus, and device for roadside equipment fault diagnosis, so as to improve the accuracy of roadside equipment fault diagnosis.

[0006] In some embodiments, the method for fault diagnosis of roadside equipment includes:

[0007] Acquire abnormal status information corresponding to the roadside equipment through a first preset method, and acquire abnormal data information corresponding to the roadside equipment through a second preset method;

[0008] Acquire first fault information according to the abnormal state information, and acquire second fault information according to the abnormal data information;

[0009] Third fault information is determined according to the first fault information and the second fault information.

[0010] In some embodiments, the apparatus for fault diagnosis of roadside equipment includes: a processor and a memory storing program instructions, and the processor is configured to execute the above-mentioned method for fault diagnosis of roadside equipment when executing the program instructions.

[0011] In some embodiments, the device includes the above-mentioned apparatus for fault diagnosis of roadside equipment.

[0012] The method, apparatus, and device for diagnosing roadside equipment faults provided by the embodiments of the present disclosure can achieve the following technical effects: obtaining abnormal status information corresponding to the roadside equipment through a first preset method, and obtaining abnormal data information corresponding to the roadside equipment through a second preset method; obtaining first fault information based on the abnormal status information, and obtaining second fault information based on the abnormal data information; and determining third fault information based on the first fault information and the second fault information. The first fault information is obtained through the abnormal status information corresponding to the roadside equipment, the second fault information is obtained through the abnormal data information corresponding to the roadside equipment, and the third fault information is obtained through a multi-dimensional fusion calculation based on the first fault information and the second fault information. By taking into account multiple factors such as the abnormal status information or abnormal data information corresponding to the roadside equipment, the accuracy of roadside equipment fault diagnosis is improved.

[0013] The above general description and the following description are exemplary and explanatory only and are not intended to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] One or more embodiments are exemplarily described by corresponding drawings. These exemplary descriptions and drawings do not limit the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements. The drawings do not constitute a scale limitation. In addition,

[0015] Figure 1 is a schematic diagram of a method for fault diagnosis of roadside equipment provided by an embodiment of the present disclosure;

[0016] Figure 2 This is a schematic diagram of a device for fault diagnosis of roadside equipment provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0017] In order to be able to understand the features and technical content of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The accompanying drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the sake of convenience of explanation, a full understanding of the disclosed embodiments is provided through multiple details. However, one or more embodiments can still be implemented without these details. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.

[0018] In the description and claims of the embodiments of the present disclosure, as well as in the accompanying drawings, the terms "first," "second," and the like are used to distinguish similar items and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate to describe the embodiments of the present disclosure herein. In addition, the terms "including," "having," and any variations thereof are intended to cover non-exclusive inclusions.

[0019] Unless otherwise stated, the term "plurality" means two or more.

[0020] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0021] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0022] Combine Figure 1 As shown, an embodiment of the present disclosure provides a method for fault diagnosis of roadside equipment, comprising:

[0023] Step S101: Acquire abnormal status information corresponding to a roadside device through a first preset method, and acquire abnormal data information corresponding to the roadside device through a second preset method;

[0024] Step S102, obtaining first fault information according to the abnormal state information, and obtaining second fault information according to the abnormal data information;

[0025] Step S103: determining third fault information according to the first fault information and the second fault information.

[0026] The method for diagnosing roadside equipment faults provided in an embodiment of the present disclosure obtains abnormal status information corresponding to the roadside equipment through a first preset method, and obtains abnormal data information corresponding to the roadside equipment through a second preset method; obtains first fault information based on the abnormal status information, and obtains second fault information based on the abnormal data information; and determines third fault information based on the first fault information and the second fault information. The first fault information is obtained based on the abnormal status information corresponding to the roadside equipment, the second fault information is obtained based on the abnormal data information corresponding to the roadside equipment, and the third fault information is obtained by performing a multi-dimensional fusion calculation based on the first fault information and the second fault information. By taking into account multiple factors, such as the abnormal status information or abnormal data information corresponding to the roadside equipment, the accuracy of roadside equipment fault diagnosis is improved.

[0027] Optionally, obtaining abnormal status information corresponding to the roadside equipment in a first preset manner includes: obtaining operating status information of the roadside equipment within a preset time period; and extracting abnormal status information from the operating status information.

[0028] Optionally, the operating status information different from the set status information is determined as abnormal status information.

[0029] In some embodiments, abnormal status information includes: the roadside equipment is in a dead state, the operating temperature of the roadside equipment exceeds a set value, etc.

[0030] Optionally, obtaining the first fault information according to the abnormal state information includes: matching the first fault information corresponding to the abnormal state information from a preset first database; and storing a corresponding relationship between the abnormal state information and the first fault information in the first database.

[0031] Optionally, the first fault information includes a fault category, a fault code, a fault confidence level, etc. Optionally, the fault category includes a device fault, a non-device fault, etc.

[0032] Optionally, obtaining the first fault information based on the abnormal state information includes: if the first fault information corresponding to the abnormal state information is not found in a preset first database, obtaining alternative fault information corresponding to the abnormal state information; determining the alternative fault information as the first fault information; and storing the first fault information and the corresponding abnormal state information in the first database. Optionally, the alternative fault information is user-inputted.

[0033] Optionally, obtaining abnormal data information corresponding to the roadside equipment through a second preset method includes: obtaining business operation data of the roadside equipment within a preset time period; and determining abnormal data information from the business operation data.

[0034] Optionally, determining abnormal data information from the business operation data includes: comparing each business operation data within a preset time period with the corresponding historical business operation data mean to obtain a comparison deviation value; if the comparison deviation value is greater than or equal to a preset value, determining the business operation data corresponding to the comparison deviation value as abnormal data information. Optionally, the business operation data includes: traffic volume, vehicle passage records, traffic incident records, vehicle violation records, etc.

[0035] Optionally, obtaining the second fault information according to the abnormal data information includes: obtaining traffic control information within a preset time period; obtaining a fault correlation between the abnormal data information and the traffic control information; and obtaining the second fault information according to the fault correlation.

[0036] Optionally, the second fault information includes a fault category, a fault code, a fault confidence level, etc. Optionally, the fault category includes a device fault, a non-device fault, etc.

[0037] Optionally, traffic control information within a preset time period is obtained from a traffic control information database. The traffic control information database stores traffic control information and its corresponding traffic control information number.

[0038] Optionally, the traffic control information includes control time, controlled road sections, control measures and diversion routes, etc.

[0039] Optionally, obtaining the fault correlation between the abnormal data information and the traffic control information includes: obtaining the degree of influence of the traffic control information on the traffic volume; when the degree of influence meets the preset conditions, inputting the abnormal data information into the preset traffic control measure impact model to obtain the fault correlation between the abnormal data information and the traffic control information.

[0040] Optionally, historical abnormal data information and historical traffic control information are input into a preset neural network model for training to obtain a traffic control measure impact model.

[0041] Optionally, obtaining the degree of influence of traffic control information on traffic volume includes: calculating Obtain the degree of impact of traffic control information on traffic volume; where y is the degree of impact, x is the traffic volume, and z is the historical average of traffic volume.

[0042] Optionally, when the impact degree is greater than a first set threshold, the abnormal data information is input into a preset traffic control measure impact model to obtain a fault correlation degree. Optionally, the first set threshold is 0.7.

[0043] Optionally, obtaining second fault information based on the fault correlation includes: if the fault correlation reaches a second set threshold, determining the fault type as a non-equipment fault; determining the traffic control information number of the traffic control information corresponding to the maximum fault correlation as the fault code; and the fault confidence level is greater than or equal to a third set threshold. Optionally, the second set threshold is 0.7.

[0044] Optionally, when the fault correlation degree is greater than or equal to a second set threshold, traffic control information corresponding to the maximum fault correlation degree is sent to the user terminal.

[0045] In this way, when the fault correlation is greater than or equal to the second set threshold, it is determined that the abnormal data information is caused by traffic control measures, and the corresponding traffic control information is sent to the user terminal to remind the user of the traffic control information.

[0046] In some embodiments, when the fault correlation degree is less than a second set threshold, it is determined that the abnormal data information is not caused by traffic control measures.

[0047] Optionally, obtaining second fault information according to the fault correlation degree includes: when the fault correlation degree is less than a second set threshold, determining the fault category as an equipment fault; and determining a fault code and a fault confidence level according to the abnormal data information.

[0048] Optionally, determining the fault code and fault confidence based on the abnormal data information includes: matching the fault code and fault confidence corresponding to the abnormal data information from a preset second database, wherein the second database stores the correspondence between the abnormal data information and the fault code and fault confidence.

[0049] Optionally, determining the fault code and fault confidence based on the abnormal data information includes: obtaining an alternative fault code and an alternative fault confidence corresponding to the abnormal data information input by the user; and determining the alternative fault code as the fault code corresponding to the abnormal data information, and determining the alternative fault confidence as the fault confidence corresponding to the abnormal data information.

[0050] In this way, by obtaining the fault correlation between the traffic control information and the abnormal data information within a preset time period, and determining the second fault information based on the fault correlation; when the fault correlation reaches the second set threshold, it is determined that the abnormal data information is caused by traffic control measures; through the influence relationship between the abnormal data information and the traffic control information, various fault factors of the roadside equipment are taken into account, making the fault diagnosis of the roadside equipment more accurate.

[0051] Optionally, determining the third fault information according to the first fault information and the second fault information includes: determining the first fault information or the second fault information as the third fault information when the first fault information and the second fault information are the same.

[0052] In some embodiments, if the first fault information and the second fault information are the same, either the first fault information or the second fault information is selected as the third fault information. Optionally, the third fault information includes a fault type, a fault code, and a confidence level. Optionally, the confidence level is 99.99%.

[0053] Optionally, determining the third fault information based on the first fault information and the second fault information includes: when the first fault information and the second fault information are different, judging the first fault information and the second fault information according to a preset rule to obtain the third fault information.

[0054] Optionally, the preset rule is DS evidence theory fusion decision.

[0055] Optionally, determining an identification framework according to the first fault information and the second fault information;

[0056] Optionally, the subsets of the identification framework include: A1 = {first fault information}, A2 {second fault information}, and A3 {uncertain fault information}. The subsets in the identification framework are incompatible with each other.

[0057] Optionally, evidence information is established, that is, a probability distribution of each subset corresponding to the third fault information in the identification framework is established. Optionally, the distribution probability of each subset corresponding to the third fault information is determined by a basic trust distribution function.

[0058] Optionally, the basic trust allocation function satisfies the condition Where m is the basic trust assignment function, m(Φ) is the probability corresponding to the empty set, Θ is the identification framework, and m(A) is the probability that subset A is the third fault information under the evidence information.

[0059] In some embodiments, as shown in Table 1, the basic trust allocation function corresponding to the evidence information E1 is m1(*), and the basic trust allocation function corresponding to the evidence information E2 is m2(*);

[0060] <![CDATA[A1]]> <![CDATA[A2]]> <![CDATA[A3]]> <![CDATA[m1(*)]]> 0.4 0.1 0.5 <![CDATA[m2(*)]]> 0.6 0.3 0.1

[0061] Table 1

[0062] As shown in Table 1, under evidence information E1, the probability that subset A1 is the third fault information is 0.4, under evidence information E1, the probability that subset A2 is the third fault information is 0.1, and under evidence information E1, the probability that subset A3 is the third fault information is 0.5; under evidence information E2, the probability that subset A1 is the third fault information is 0.6, under evidence information E2, the probability that subset A2 is the third fault information is 0.3, and under evidence information E2, the probability that subset A3 is the third fault information is 0.6.

[0063] Optionally, the distribution probability of each subset under each piece of evidence information is used for calculation to obtain a first reference value corresponding to each subset; and the third fault information is obtained according to the first reference value corresponding to each subset.

[0064] Optionally, by calculating Obtain the first reference value corresponding to each subset; wherein, M(A j ) is the first reference value corresponding to the jth subset, m i (A j ) is the probability that the jth subset is the third fault information under the i-th evidence, n is the number of evidence information, K is the second reference value. Optionally, j=1, 2 or 3, i and n are positive integers.

[0065] Optionally, by calculating Get the second reference value; where K is the second reference value, m i (A j ) is the probability that the jth subset is the third fault information under the i-th evidence.

[0066] Optionally, obtaining the third fault information according to the first reference values corresponding to the subsets includes: determining the subset corresponding to the maximum value in the first reference values as the third fault information.

[0067] In some embodiments, a fusion calculation is performed based on the probability that each subset under the evidence information E1 and evidence information E2 shown in Table 1 corresponds to the third fault information, and the first reference value corresponding to subset A1 is 0.707, the first reference value corresponding to subset A2 is 0.232, and the first reference value corresponding to subset A3 is 0.061; among them, the first reference value corresponding to subset A1 is the largest, and subset A1 is determined to be the third fault information.

[0068] In this way, the first fault information is obtained through the abnormal status information corresponding to the roadside equipment, the second fault information is obtained through the abnormal data information corresponding to the roadside equipment, and the third fault information is obtained by performing multi-dimensional fusion calculation based on the first fault information and the second fault information. Since multiple factors such as the abnormal status information or abnormal data information corresponding to the roadside equipment are taken into consideration, the accuracy of roadside equipment fault diagnosis is improved.

[0069] Combine Figure 2 As shown, an embodiment of the present disclosure provides a device for fault diagnosis of roadside equipment, including a processor 100 and a memory 101 storing program instructions. Optionally, the device may also include a communication interface 102 and a bus 103. The processor 100, the communication interface 102, and the memory 101 can communicate with each other via the bus 103. The communication interface 102 can be used for information transmission. The processor 100 can call the program instructions in the memory 101 to execute the method for fault diagnosis of roadside equipment of the above embodiment.

[0070] In addition, the program instructions in the memory 101 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0071] Memory 101, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of the present disclosure. Processor 100 executes the program instructions / modules stored in memory 101 to perform functional applications and data processing, thereby implementing the method for fault diagnosis of roadside equipment in the above-mentioned embodiments.

[0072] The memory 101 may include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function; the data storage area may store data generated based on the use of the terminal device. Furthermore, the memory 101 may include high-speed random access memory and non-volatile memory.

[0073] The apparatus for diagnosing roadside equipment faults provided by the embodiments of the present disclosure obtains abnormal status information corresponding to the roadside equipment through a first preset method and abnormal data information corresponding to the roadside equipment through a second preset method; obtains first fault information based on the abnormal status information and obtains second fault information based on the abnormal data information; and determines third fault information based on the first and second fault information. The apparatus obtains the first fault information based on the abnormal status information corresponding to the roadside equipment, obtains the second fault information based on the abnormal data information corresponding to the roadside equipment, and performs a multi-dimensional fusion calculation based on the first and second fault information to obtain the third fault information. By taking into account multiple factors, such as the abnormal status information or abnormal data information corresponding to the roadside equipment, the accuracy of roadside equipment fault diagnosis is improved.

[0074] An embodiment of the present disclosure provides a device comprising the above-mentioned apparatus for diagnosing roadside equipment faults. The device obtains abnormal status information corresponding to the roadside equipment through a first preset method, and obtains abnormal data information corresponding to the roadside equipment through a second preset method; obtains first fault information based on the abnormal status information, and obtains second fault information based on the abnormal data information; and determines third fault information based on the first fault information and the second fault information. The first fault information is obtained through the abnormal status information corresponding to the roadside equipment, the second fault information is obtained through the abnormal data information corresponding to the roadside equipment, and the third fault information is obtained by performing a multi-dimensional fusion calculation based on the first fault information and the second fault information. Since multiple factors such as the abnormal status information or abnormal data information corresponding to the roadside equipment are taken into consideration, the accuracy of roadside equipment fault diagnosis is improved.

[0075] Optionally, the equipment includes: roadside equipment.

[0076] Optionally, the device includes: a computer, a server, etc.

[0077] Optionally, when the device is a computer or a server, the operation status information and business operation data sent by the roadside device are obtained.

[0078] An embodiment of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to execute the above-mentioned method for fault diagnosis of roadside equipment.

[0079] An embodiment of the present disclosure provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the above-mentioned method for fault diagnosis of roadside equipment.

[0080] The aforementioned computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0081] The technical solution of the embodiments of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the embodiments of the present disclosure. The aforementioned storage medium may be a non-transitory storage medium, including: 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, and other media that can store program code, or a transient storage medium.

[0082] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible variations. Unless explicitly required, individual components and functions are optional, and the order of operations may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to also include plural forms. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of one or more associated listings. In addition, when used in this application, the term "comprise" and its variations "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups of these. In the absence of further restrictions, an element defined by the sentence "comprising a..." does not exclude the presence of other identical elements in the process, method or device that includes the element. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the various embodiments can be referenced to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can be found in the description of the method part.

[0083] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present disclosure. The technicians will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0084] In the embodiments disclosed herein, the disclosed methods and products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units can be merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, and can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components shown 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 units may be selected to implement this embodiment according to actual needs. In addition, the functional units in the embodiments of the present disclosure may be integrated into a processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0085] The flowcharts and block diagrams in the accompanying drawings show the possible implementation architectures, functions and operations of the systems, methods and computer program products according to the embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of the code, and the module, program segment or part of the code contains one or more executable instructions for implementing the specified logical functions. In some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, which can depend on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in an order different from that disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified function or action, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A method for fault diagnosis of roadside equipment, characterized in that: include: Acquire abnormal status information corresponding to the roadside equipment through a first preset method, and acquire abnormal data information corresponding to the roadside equipment through a second preset method; Acquire first fault information according to the abnormal state information, and acquire second fault information according to the abnormal data information; When the first fault information and the second fault information are different, an identification framework is determined based on the first fault information and the second fault information; subsets of the identification framework include: A1 {first fault information}, A2 {second fault information}, and A3 {uncertain fault information}; each subset in the identification framework is incompatible with each other; The probability of each subset corresponding to the third fault information is determined by the basic trust allocation function; wherein the basic trust allocation function satisfies the condition m is the basic trust allocation function, m(Φ) is the probability corresponding to the empty set, Θ is the identification framework, and m(A) is the probability that subset A is the third fault information under the evidence information; By calculation Obtain the first reference value corresponding to each subset; wherein, M(A j ) is the first reference value corresponding to the jth subset, m i (A j ) is the probability that the jth subset is the third fault information under the i-th evidence, n is the number of evidence information, and K is the second reference value; where j = 1, 2 or 3, i and n are positive integers; The subset corresponding to the maximum value of the first reference values is determined as third fault information.

2. The method according to claim 1, characterized in that The obtaining of abnormal status information corresponding to the roadside equipment in a first preset manner includes: Obtain operating status information of roadside equipment within a preset time period; Abnormal state information is determined from the operating state information.

3. The method according to claim 1, characterized in that Acquiring first fault information according to the abnormal state information includes: First fault information corresponding to the abnormal state information is matched from a preset first database; the first database stores a corresponding relationship between the abnormal state information and the first fault information.

4. The method according to claim 1, wherein Acquiring first fault information according to the abnormal state information includes: If there is no first fault information corresponding to the abnormal state information in the preset first database, obtaining alternative fault information corresponding to the abnormal state information; The candidate fault information is determined as the first fault information.

5. The method according to claim 1, wherein The obtaining of abnormal data information corresponding to the roadside equipment by a second preset method includes: Obtain business operation data of roadside equipment within a preset time period; Abnormal data information is determined from the business operation data.

6. The method according to claim 1, characterized in that Acquiring second fault information according to the abnormal data information includes: Obtain traffic control information within a preset time period; Acquiring a fault correlation between the abnormal data information and the traffic control information; Second fault information is acquired according to the fault correlation degree.

7. The method according to any one of claims 1 to 6, characterized in that Also includes: If the first fault information and the second fault information are the same, the first fault information or the second fault information is determined as third fault information.

8. The method according to any one of claims 1 to 6, characterized in that The first fault information includes a fault category, a fault code, and a fault confidence level; the second fault information includes a fault category, a fault code, and a fault confidence level; wherein the fault category includes equipment fault and non-equipment fault.

9. A device for fault diagnosis of roadside equipment, comprising a processor and a memory storing program instructions, characterized in that: The processor is configured to perform the method for fault diagnosis of roadside equipment according to any one of claims 1 to 8 when executing the program instructions.

10. A device, characterized in that The method comprises the apparatus for fault diagnosis of roadside equipment as claimed in claim 9.

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