Tunnel illumination fault detection method and system, terminal and storage medium

Abstract

The invention relates to the technical field of tunnel lighting fault detection, and particularly provides a tunnel lighting fault detection method and system, a terminal and a storage medium, and the method comprises the steps: obtaining street lamp illumination data uploaded by a sensor; finding street lamp illuminance abnormal data based on the street lamp illuminance data, finding position information of a target sensor based on the street lamp illuminance abnormal data, and obtaining n sensors adjacent to the target sensor according to a preset indexing method; judging whether the illumination data of the n sensors are abnormal or not, if not, determining that the target sensor has a fault, judging the fault type of the target sensor, and correcting or replacing the target sensor based on the fault type; if yes, the street lamp corresponding to the target sensor has a fault, information of the fault street lamp is uploaded, and maintenance is prompted. The method has the advantage of reducing in-tunnel light detection errors caused by sensor faults.

Description

Technical Field

[0001] The present invention belongs to the technical field of tunnel lighting fault detection, and in particular relates to a tunnel lighting fault detection method, system, terminal and storage medium. Background Art

[0002] With the rapid development of intelligent transportation systems, tunnel lighting fault detection has gradually become a key link in ensuring road traffic safety and efficient energy utilization. In order to improve the intelligence level of tunnel lighting systems, more and more lighting control systems have introduced sensor networks, which collect environmental data in real time through light sensors deployed in the tunnel and perform dynamic illumination adjustment.

[0003] However, in practical applications, sensors often face problems such as shielding, dirtiness, and sensor failure. These problems may cause the sensor to upload abnormal data, affecting the overall effect of tunnel lighting. For example, when the sensor is covered with stains or interfered with by the outside world, the illuminance value it measures may not match the actual situation, causing incorrect adjustment of street lights, which in turn affects the light distribution and traffic safety of the tunnel. In addition, the existing tunnel lighting fault detection system usually adopts a centralized computing mode, that is, all data is uploaded to the central server for analysis and processing. This approach has two main problems. First, the centralized system requires a large amount of computing resources and storage space to process the data of many sensors in the tunnel, which increases the system load and operating costs. For example, traditional neighboring sensor search usually performs traversal calculations based on the latitude and longitude information of the sensor, but due to the large number of sensors in the tunnel, this method is prone to calculation errors and system performance bottlenecks. Second, due to the delay in data processing, it is difficult for the system to respond quickly to sudden changes in light in the tunnel. Especially in the case of sensor abnormalities, it may cause untimely light adjustment in some areas of the tunnel, thus affecting driving safety. Summary of the invention

[0004] In view of the problems in the prior art that when the sensor is covered with stains or disturbed by external factors, the measured illuminance value does not match the actual situation, resulting in incorrect lighting adjustment in the tunnel, and the centralized system causes a large amount of calculation by traversing and calculating the data of many sensors, the present invention provides a tunnel lighting fault detection method, system, terminal and storage medium to solve the above technical problems.

[0005] In a first aspect, the present invention provides a tunnel lighting fault detection method, comprising: Get the street light illumination data uploaded by the sensor; Find the abnormal street light illumination data based on the street light illumination data, find the location information of the target sensor based on the abnormal street light illumination data, and obtain n sensors adjacent to the target sensor according to a preset indexing method; Determine whether the illumination data of n sensors are abnormal. If not, it is a target sensor fault. Determine the fault type of the target sensor and correct or replace the target sensor based on the fault type. If abnormal, it is a street lamp corresponding to the target sensor. Upload the information of the faulty street lamp and prompt for maintenance.

[0006] Furthermore, the location information of the target sensor is found based on the abnormal street light illumination data, and n sensors adjacent to the target sensor are obtained according to a preset indexing method, including: Based on the tunnel number, the street lights are numbered in order from the tunnel entrance to the tunnel exit, and a sensor with built-in longitude and latitude parameters is set for each street light and numbered. The tunnel number, street light number and sensor number corresponding to the street light are stored and bound to the gateway; The latitude and longitude parameters of the target sensor are found in the street lamp illumination anomaly data, and based on the latitude and longitude parameters of the target sensor, n sensors adjacent to the target street lamp are obtained.

[0007] Further, it is determined whether the illumination data of the n sensors are abnormal. If not, the target sensor is faulty. The fault type of the target sensor is determined, and the target sensor is corrected or replaced based on the fault type, including: Determine whether the illumination data of n sensors is abnormal: If it is normal, it is the target sensor fault. Determine whether the photoelectric characteristic curve of the target sensor's photoresistor is consistent with the normal photoresistor's photoelectric characteristic curve: If the curves are consistent, it is a measurement error caused by the target sensor being covered by stains. Use the compensation algorithm to perform mean calibration on the target sensor, and use the street light illumination data after mean calibration as the street light illumination data obtained by the target sensor. If the curves are inconsistent, it means that the target sensor hardware is faulty, and the street light illumination data of the street light corresponding to the target sensor is replaced by the weighted average of the street light illumination data of the n sensors adjacent to the target sensor; If it is abnormal, it means that the street light corresponding to the target sensor is faulty, and the faulty street light information will be reported and maintenance will be prompted.

[0008] Furthermore, a compensation algorithm is used to perform mean calibration on the target sensor, including: The compensation amount is obtained by removing the extreme value and averaging the actual current of the street lamps corresponding to the n sensors adjacent to the target sensor and subtracting the actual current of the current street lamp; Building an analog circuit of the target sensor based on the compensation amount, and using the analog circuit to replace the real circuit where the target sensor is located;

[0009]

[0010] in, is the compensation amount, n is the number of street lights, for Actual circuit current under light intensity, To simulate the circuit current.

[0011] In a second aspect, the present invention provides a tunnel lighting fault detection system, comprising: A data acquisition module is used to obtain street light illumination data uploaded by the sensor; A sensor positioning module is used to find abnormal street light illumination data based on the street light illumination data, find the location information of the target sensor based on the abnormal street light illumination data, and obtain n sensors adjacent to the target sensor according to a preset indexing method; The fault detection module is used to determine whether the illumination data of n sensors are abnormal. If not, it is a target sensor fault. The fault type of the target sensor is determined and the target sensor is corrected or replaced based on the fault type. If it is abnormal, it is a street lamp corresponding to the target sensor. The information of the faulty street lamp is uploaded and a maintenance prompt is given.

[0012] Furthermore, the sensor positioning module includes: A number setting unit is used to number the street lamps in order from the tunnel entrance to the tunnel exit based on the tunnel number, and to set a sensor with built-in longitude and latitude parameters for each street lamp and number it, and to store the tunnel number, street lamp number and sensor number corresponding to the street lamp and bind them to the gateway; The positioning unit is used to find the longitude and latitude parameters of the target sensor in the abnormal illumination data of the street lamp, and obtain n sensors adjacent to the target street lamp based on the longitude and latitude parameters of the target sensor.

[0013] Furthermore, the fault detection module includes: The fault detection module includes: The illumination data judgment unit is used to judge whether the illumination data of n sensors are abnormal: If there is no abnormality, the target sensor is faulty; The curve rule judgment unit is used to judge whether the curve rule of the photoelectric characteristic curve of the photoresistor of the target sensor is consistent with the curve rule of the photoelectric characteristic curve of the normal photoresistor: If the curves are consistent, it is a measurement error caused by the target sensor being covered by stains. Use the compensation algorithm to perform mean calibration on the target sensor, and use the street light illumination data after mean calibration as the street light illumination data obtained by the target sensor. If the curves are inconsistent, it means that the target sensor hardware is faulty, and the street light illumination data of the street light corresponding to the target sensor is replaced by the weighted average of the street light illumination data of the n sensors adjacent to the target sensor; The street lamp fault reporting unit is used to report the faulty street lamp information and prompt maintenance if there is an abnormality, that is, the street lamp corresponding to the target sensor is faulty.

[0014] Furthermore, the curve regularity determination unit includes: A compensation amount calculation unit, used to obtain a compensation amount by averaging the actual currents of the street lamps corresponding to the n sensors adjacent to the target sensor without removing the extreme value and subtracting the actual current of the current street lamp; An analog circuit construction unit, comprising: constructing an analog circuit of the target sensor based on the compensation amount, and using the analog circuit to replace the real circuit where the target sensor is located;

[0015]

[0016] in, is the compensation amount, n is the number of street lights, for Actual circuit current under light intensity, To simulate the circuit current.

[0017] In a third aspect, a terminal is provided, including: processor, memory, wherein: The memory is used to store computer programs. The processor is used to call and run the computer program from the memory, so that the terminal executes the above-mentioned terminal method.

[0018] According to a fourth aspect, a computer storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed on a computer, the computer executes the methods described in the above aspects.

[0019] The beneficial effect of the present invention is that the tunnel lighting fault detection method, system, terminal and storage medium provided by the present invention can quickly find the n sensors closest to the target sensor through a preset indexing method, reduce the complex geographical calculation process, save system resources, improve the response speed and accuracy of lighting control, reduce the calculation amount of the central server and reduce the delay of data transmission.

[0020] The tunnel lighting fault detection method, system, terminal and storage medium provided by the present invention can use the data of its adjacent sensors to replace the abnormal data of a certain sensor, so as to avoid the failure of local lighting control caused by the abnormality of a single sensor. This multi-source data fusion processing method greatly improves the fault tolerance of the system and ensures the continuity and stability of tunnel lighting.

[0021] In addition, the invention has a reliable design principle, a simple structure and a very broad application prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention 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, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0023] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention.

[0024] Figure 2 It is the photoelectric characteristic of the photoresistor of the sensor of one embodiment of the present invention under the influence of dust or polarizer.

[0025] Figure 3 is a schematic block diagram of a system according to an embodiment of the present invention.

[0026] Figure 4 A schematic diagram of the structure of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0029] The tunnel lighting fault detection method provided by the embodiment of the present invention is executed by a computer device, and accordingly, the tunnel lighting fault detection system runs in the computer device.

[0030] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention. Figure 1 The execution subject may be a tunnel lighting fault detection system. According to different requirements, the order of the steps in the flow chart may be changed, and some may be omitted.

[0031] In order to facilitate the understanding of the present invention, the tunnel lighting fault detection method provided by the present invention is further described below based on the principle of the tunnel lighting fault detection method of the present invention.

[0032] Specifically, Figure 1 As shown, the tunnel lighting fault detection method includes: S1. Acquire street lamp illumination data uploaded by a sensor, wherein the street lamp illumination data includes street lamp illumination abnormality data.

[0033] Specifically, light sensors deployed in the tunnel collect illumination data of each street lamp in real time. The collected data includes not only normal illumination values, but also possible abnormal data. Abnormal data usually refers to values ​​that exceed a preset illumination threshold or show unreasonable fluctuations.

[0034] S2. Find abnormal street light illumination data based on the street light illumination data, find the location information of the target sensor based on the abnormal street light illumination data, and obtain n sensors adjacent to the target sensor according to a preset indexing method.

[0035] Based on the tunnel number, the street lights are numbered in order from the tunnel entrance to the tunnel exit, and a sensor with built-in longitude and latitude parameters is set for each street light and numbered. The tunnel number, street light number and sensor number corresponding to the street light are stored and bound to the gateway. The longitude and latitude parameters of the target sensor are found in the street light illumination abnormality data, and based on the longitude and latitude parameters of the target sensor, n sensors adjacent to the target street light are obtained.

[0036] Specifically, each streetlight is equipped with a sensor with a unique number, and the location information of the sensor (such as longitude and latitude parameters) corresponds to the streetlight number and tunnel number and is stored in the system's database. Through this mapping relationship, each sensor and its corresponding streetlight can be quickly located.

[0037] When it is detected that the illuminance data uploaded by a sensor exceeds the preset threshold range or shows abnormal fluctuations, the data of the sensor will be marked as "abnormal data". At the same time, the target sensor of the abnormal data source will be quickly located by searching the sensor location information in the database.

[0038] Using a preset indexing method, that is, based on the tunnel number and the streetlight number, the streetlights are numbered in order from the tunnel entrance to the exit. Each streetlight sensor has a unique longitude and latitude parameter, which is stored one-to-one with the streetlight number. Through this structured data management, the location information related to the target streetlight can be efficiently retrieved. According to the longitude and latitude parameters of the target sensor, a calculation method will be used to find the n adjacent sensors closest to the target sensor. These sensors will be used as reference data sources for subsequent fault judgment and illumination adjustment.

[0039] S3. Determine whether the illumination data of n sensors are abnormal. If not, it is a target sensor fault. Determine the fault type of the target sensor and correct or replace the target sensor based on the fault type. If abnormal, it is a street lamp corresponding to the target sensor. Upload the information of the faulty street lamp and prompt for maintenance.

[0040] Determine whether the illumination data of n sensors is abnormal: If it is normal, it is the target sensor fault. Determine whether the photoelectric characteristic curve of the target sensor's photoresistor is consistent with the normal photoresistor's photoelectric characteristic curve: If the curves are consistent, it is a measurement error caused by the target sensor being covered by stains. Use a compensation algorithm to perform mean calibration on the target sensor, and use the street light illumination data after mean calibration as the street light illumination data obtained by the target sensor.

[0041] Specifically, Figure 2 As shown, Figure 2 It is the photoelectric characteristics of the photoresistor of the sensor under the influence of dust or polarizer.

[0042] The compensation amount is obtained by removing the extreme value and averaging the actual current of the street lamps corresponding to the n sensors adjacent to the target sensor and subtracting the actual current of the current street lamp; An analog circuit of the target sensor is constructed based on the compensation amount, and the analog circuit is used to replace the real circuit where the target sensor is located.

[0043]

[0044]

[0045] in, is the compensation amount, n is the number of street lights, for Actual circuit current under light intensity, To simulate the circuit current.

[0046] If the curve patterns are inconsistent, it indicates a hardware failure of the target sensor, and the street light illumination data of the street light corresponding to the target sensor is replaced by the weighted average of the street light illumination data of the n sensors adjacent to the target sensor.

[0047] If it is abnormal, it means that the street light corresponding to the target sensor is faulty, and the faulty street light information will be reported and maintenance will be prompted.

[0048] In some embodiments, the tunnel lighting fault detection system may include a plurality of functional modules composed of computer program segments. The computer programs of the various program segments in the tunnel lighting fault detection system may be stored in a memory of a computer device and executed by at least one processor to perform (see Figure 1 Description) Tunnel lighting fault detection function.

[0049] In this embodiment, the tunnel lighting fault detection system can be divided into multiple functional modules according to the functions it performs, such as Figure 2 As shown. The functional modules of the system 200 may include: a data acquisition module 210, a sensor positioning module 220 and a fault detection module 230. The module referred to in the present invention refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in a memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0050] A data acquisition module is used to obtain street light illumination data uploaded by the sensor; A sensor positioning module is used to find abnormal street light illumination data based on the street light illumination data, find the location information of the target sensor based on the abnormal street light illumination data, and obtain n sensors adjacent to the target sensor according to a preset indexing method; The fault detection module is used to determine whether the illumination data of n sensors are abnormal. If not, it is a target sensor fault. The fault type of the target sensor is determined and the target sensor is corrected or replaced based on the fault type. If it is abnormal, it is a street lamp corresponding to the target sensor. The information of the faulty street lamp is uploaded and a maintenance prompt is given.

[0051] Optionally, as an embodiment of the present invention, the sensor positioning module includes: A number setting unit is used to number the street lamps in order from the tunnel entrance to the tunnel exit based on the tunnel number, and to set a sensor with built-in longitude and latitude parameters for each street lamp and number it, and to store the tunnel number, street lamp number and sensor number corresponding to the street lamp and bind them to the gateway; The positioning unit is used to find the longitude and latitude parameters of the target sensor in the abnormal illumination data of the street lamp, and obtain n sensors adjacent to the target street lamp based on the longitude and latitude parameters of the target sensor.

[0052] Optionally, as an embodiment of the present invention, the fault detection module includes: The illumination data judgment unit is used to judge whether the illumination data of n sensors are abnormal: If there is no abnormality, the target sensor is faulty; The curve rule judgment unit is used to judge whether the curve rule of the photoelectric characteristic curve of the photoresistor of the target sensor is consistent with the curve rule of the photoelectric characteristic curve of the normal photoresistor: If the curves are consistent, it is a measurement error caused by the target sensor being covered by stains. Use the compensation algorithm to perform mean calibration on the target sensor, and use the street light illumination data after mean calibration as the street light illumination data obtained by the target sensor. If the curves are inconsistent, it means that the target sensor hardware is faulty, and the street light illumination data of the street light corresponding to the target sensor is replaced by the weighted average of the street light illumination data of the n sensors adjacent to the target sensor; The street lamp fault reporting unit is used to report the faulty street lamp information and prompt maintenance if there is an abnormality, that is, the street lamp corresponding to the target sensor is faulty.

[0053] The curve regularity judgment unit includes: A compensation amount calculation unit, used to obtain a compensation amount by averaging the actual currents of the street lamps corresponding to the n sensors adjacent to the target sensor without removing the extreme value and subtracting the actual current of the current street lamp; An analog circuit construction unit, comprising: constructing an analog circuit of the target sensor based on the compensation amount, and using the analog circuit to replace the real circuit where the target sensor is located;

[0054]

[0055] in, is the compensation amount, n is the number of street lights, for Actual circuit current under light intensity, To simulate the circuit current.

[0056] Figure 3 This is a schematic diagram of the structure of a terminal 300 provided in an embodiment of the present invention. The terminal 300 can be used to execute the tunnel lighting fault detection method provided in an embodiment of the present invention.

[0057] The terminal 300 may include: a processor 310, a memory 320 and a communication unit 330. These components communicate via one or more buses. Those skilled in the art will appreciate that the server structure shown in the figure does not limit the present invention, and it may be a bus structure or a star structure, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0058] The memory 320 can be used to store the execution instructions of the processor 310, and the memory 320 can be implemented by any type of volatile or non-volatile storage terminal or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. When the execution instructions in the memory 320 are executed by the processor 310, the terminal 300 can perform some or all of the steps in the following method embodiments.

[0059] The processor 310 is the control center of the storage terminal, and uses various interfaces and lines to connect various parts of the entire electronic terminal. It runs or executes software programs and / or modules stored in the memory 320, and calls data stored in the memory to perform various functions of the electronic terminal and / or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of multiple packaged ICs with the same or different functions. For example, the processor 310 can only include a central processing unit (CPU). In the embodiment of the present invention, the CPU can be a single computing core or multiple computing cores.

[0060] The communication unit 330 is used to establish a communication channel so that the storage terminal can communicate with other terminals, receive user data sent by other terminals or send user data to other terminals.

[0061] The present invention also provides a computer storage medium, wherein the computer storage medium may store a program, and when the program is executed, the program may include some or all of the steps in each embodiment provided by the present invention. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0062] Therefore, the present invention can quickly find the sensor closest to the target street lamp through a preset indexing method, reduce the complex geographical calculation process, save system resources, improve the response speed and accuracy of lighting control, reduce the calculation amount of the central server and reduce the delay of data transmission.

[0063] The tunnel lighting fault detection method, system, terminal and storage medium provided by the present invention can use the data of its adjacent sensors to replace and compensate the data when the data of a certain sensor is abnormal, so as to avoid the failure of local lighting control caused by the abnormality of a single sensor. This multi-source data fusion processing method greatly improves the fault tolerance of the system and ensures the continuity and stability of tunnel lighting. The technical effects that can be achieved by this embodiment can be found in the description above and will not be repeated here.

[0064] Those skilled in the art can clearly understand that the technology in the embodiments of the present invention can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution in the embodiments of the present invention, in essence or in other words, the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media that can store program codes, including several instructions for enabling a computer terminal (which can be a personal computer, a server, or a second terminal, a network terminal, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention.

[0065] In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.

[0066] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or modules, which can be electrical, mechanical or other forms.

[0067] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0068] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0069] Although the present invention has been described in detail by referring to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, and all of these shall be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A tunnel lighting fault detection method, characterized in that: include: Get the street light illumination data uploaded by the sensor; Find the abnormal street light illumination data based on the street light illumination data, find the location information of the target sensor based on the abnormal street light illumination data, and obtain n sensors adjacent to the target sensor according to a preset indexing method; Determine whether the illumination data of n sensors are abnormal. If not, it is a target sensor failure. Determine the failure type of the target sensor and correct or replace the target sensor based on the failure type. If it is abnormal, it means that the street light corresponding to the target sensor is faulty, and the information of the faulty street light is uploaded and a maintenance prompt is given.

2. The method according to claim 1, characterized in that The location information of the target sensor is found based on the abnormal street light illumination data, and n sensors adjacent to the target sensor are obtained according to the preset indexing method, including: Based on the tunnel number, the street lights are numbered in order from the tunnel entrance to the tunnel exit, and a sensor with built-in longitude and latitude parameters is set for each street light and numbered. The tunnel number, street light number and sensor number corresponding to the street light are stored and bound to the gateway; The latitude and longitude parameters of the target sensor are found in the street lamp illumination anomaly data, and based on the latitude and longitude parameters of the target sensor, n sensors adjacent to the target street lamp are obtained.

3. The method according to claim 1, characterized in that Determine whether the illumination data of n sensors are abnormal. If not, the target sensor is faulty. Determine the fault type of the target sensor and correct or replace the target sensor based on the fault type, including: Determine whether the illumination data of n sensors is abnormal: If it is normal, it is the target sensor fault. Determine whether the photoelectric characteristic curve of the target sensor's photoresistor is consistent with the normal photoresistor's photoelectric characteristic curve: If the curves are consistent, it is a measurement error caused by the target sensor being covered by stains. Use the compensation algorithm to perform mean calibration on the target sensor, and use the street light illumination data after mean calibration as the street light illumination data obtained by the target sensor. If the curves are inconsistent, it means that the target sensor hardware is faulty, and the street light illumination data of the street light corresponding to the target sensor is replaced by the weighted average of the street light illumination data of the n sensors adjacent to the target sensor; If it is abnormal, it means that the street light corresponding to the target sensor is faulty, and the faulty street light information will be reported and maintenance will be prompted.

4. The method according to claim 3, characterized in that Use the compensation algorithm to perform mean calibration on the target sensor, including: The compensation amount is obtained by removing the extreme value and averaging the actual current of the street lamps corresponding to the n sensors adjacent to the target sensor and subtracting the actual current of the current street lamp; Building an analog circuit of the target sensor based on the compensation amount, and using the analog circuit to replace the real circuit where the target sensor is located; in, is the compensation amount, n is the number of street lamps, for Actual circuit current under light intensity, To simulate the circuit current.

5. A tunnel lighting fault detection system, characterized in that: include: A data acquisition module is used to obtain street light illumination data uploaded by the sensor; A sensor positioning module is used to find abnormal street light illumination data based on the street light illumination data, find the location information of the target sensor based on the abnormal street light illumination data, and obtain n sensors adjacent to the target sensor according to a preset indexing method; A fault detection module is used to determine whether the illumination data of n sensors are abnormal. If not, it is a target sensor fault. The fault type of the target sensor is determined and the target sensor is corrected or replaced based on the fault type. If it is abnormal, it means that the street light corresponding to the target sensor is faulty, and the information of the faulty street light is uploaded and a maintenance prompt is given.

6. The system according to claim 5, characterized in that The sensor positioning module includes: A number setting unit is used to number the street lamps in order from the tunnel entrance to the tunnel exit based on the tunnel number, and to set a sensor with built-in longitude and latitude parameters for each street lamp and number it, and to store the tunnel number, street lamp number and sensor number corresponding to the street lamp and bind them to the gateway; The positioning unit is used to find the longitude and latitude parameters of the target sensor in the abnormal illumination data of the street lamp, and obtain n sensors adjacent to the target street lamp based on the longitude and latitude parameters of the target sensor.

7. The system according to claim 5, characterized in that The fault detection module includes: The illumination data judgment unit is used to judge whether the illumination data of n sensors are abnormal: If there is no abnormality, the target sensor is faulty; The curve rule judgment unit is used to judge whether the curve rule of the photoelectric characteristic curve of the photoresistor of the target sensor is consistent with the curve rule of the photoelectric characteristic curve of the normal photoresistor: If the curves are consistent, it is a measurement error caused by the target sensor being covered by stains. Use the compensation algorithm to perform mean calibration on the target sensor, and use the street light illumination data after mean calibration as the street light illumination data obtained by the target sensor. If the curves are inconsistent, it means that the target sensor hardware is faulty, and the street light illumination data of the street light corresponding to the target sensor is replaced by the weighted average of the street light illumination data of the n sensors adjacent to the target sensor; The street lamp fault reporting unit is used to report the faulty street lamp information and prompt maintenance if there is an abnormality, that is, the street lamp corresponding to the target sensor is faulty.

8. The system according to claim 5, characterized in that The curve regularity judgment unit includes: A compensation amount calculation unit, used to obtain a compensation amount by averaging the actual currents of the street lamps corresponding to the n sensors adjacent to the target sensor without removing the extreme value and subtracting the actual current of the current street lamp; An analog circuit construction unit, comprising: constructing an analog circuit of the target sensor based on the compensation amount, and using the analog circuit to replace the real circuit where the target sensor is located; in, is the compensation amount, n is the number of street lamps, for Actual circuit current under light intensity, To simulate the circuit current.

9. A terminal, characterized in that: include: A memory, used for storing a tunnel lighting fault detection program; A processor is used to implement the steps of the tunnel lighting fault detection method according to any one of claims 1 to 4 when executing the tunnel lighting fault detection program.

10. A computer-readable storage medium storing a computer program, characterized in that: The readable storage medium stores a tunnel lighting fault detection program, and when the tunnel lighting fault detection program is executed by the processor, the steps of the tunnel lighting fault detection method according to any one of claims 1 to 4 are implemented.

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