Street lamp fault judgment method, system, terminal and medium based on single lamp image processing

Abstract

The application provides a street lamp fault judgment method, system, terminal and medium based on single lamp image processing, which can detect the working state and brightness color temperature of the street lamp in real time, effectively reduce the influence of brightness difference on fault judgment, improve the detection accuracy, eliminate the detection error, accurately judge the fault street lamp with different brightness and flicker in the road, facilitate the staff to accurately locate and timely handle the fault street lamp according to the fault information, efficiently guarantee the safety of vehicle night travel, and reduce the occurrence of road traffic problems.

Description

Technical Field

[0001] This invention relates to the field of lighting, and in particular to a method, system, terminal, and medium for diagnosing street light faults based on single-lamp image processing. Background Technology

[0002] To ensure the safety of residents on roads at night, it is necessary to ensure the safe and effective operation of streetlights. The existing streetlight system is not perfect and requires manual inspection at regular intervals to check for safety hazards and whether there are any streetlight malfunctions. However, due to the large number of vehicles on highways, maintenance is inconvenient, and it is impossible for people to directly identify problems such as uneven brightness and different color temperature ranges of streetlights with the naked eye. For vehicles traveling at high speeds, the alternation of light and dark caused by uneven brightness can cause visual illusions and visual fatigue to drivers, making them "dazzled" on long journeys and creating driving safety hazards. Summary of the Invention

[0003] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide a street light fault diagnosis method, system, terminal and medium based on single-lamp image processing to solve the problems of the prior art.

[0004] To achieve the above and other related objectives, this invention provides a street light fault judgment method based on single-lamp image processing. The method includes: obtaining single-lamp image information of each collected single lamp; wherein, the single-lamp image information includes: multiple frames of single-lamp image information; obtaining brightness detection results and color detection results corresponding to each frame of single-lamp image information of each single lamp based on the single-lamp image information of each single lamp; performing single-lamp fault judgment based on the brightness detection results and color detection results corresponding to each frame of single-lamp image information of each single lamp and single-lamp pre-stored information, and obtaining and uploading single-lamp fault judgment information for each single lamp; performing row lamp fault judgment based on the single-lamp fault judgment information of each row of lamps distributed in rows, and obtaining and uploading row lamp fault judgment information for each row of lamps; performing area lamp fault judgment based on the row lamp fault judgment information of each row of lamps in each area and the single-lamp fault judgment information of scattered lamps not distributed in rows, and obtaining and uploading area lamp fault judgment information for each area lamp.

[0005] In one embodiment of the present invention, obtaining the single-lamp image information of each collected lamp includes: acquiring a real-time collected street lamp video stream and dividing the street lamp video stream into a single-lamp real-time video stream for each lamp; and, based on a determined random time interval, randomly sampling and obtaining multiple frames of single-lamp image information for each lamp from the single-lamp real-time video stream of each lamp and outputting them.

[0006] In one embodiment of the present invention, obtaining the brightness detection result and color detection result corresponding to each frame of single-lamp image information based on the single-lamp image information includes: inputting each frame of single-lamp image information of each single-lamp to a feature extraction network to obtain a feature map of each frame of single-lamp image information; obtaining a ROI region detection box corresponding to each frame of single-lamp image information based on a detection box generation network according to the feature map of each frame of single-lamp image information; performing color detection on the image within the ROI region detection box corresponding to each frame of single-lamp image information based on a color detection network to obtain a color detection result corresponding to each frame of single-lamp image information of each single-lamp; and performing brightness detection on the image within the ROI region detection box corresponding to each frame of single-lamp image information based on a brightness detection network to obtain a brightness detection result corresponding to each frame of single-lamp image information of each single-lamp.

[0007] In one embodiment of the present invention, the pre-stored information for a single lamp includes: pre-stored single lamp working status information, pre-stored single lamp brightness information, pre-stored single lamp color temperature information, and single lamp address information.

[0008] In one embodiment of the present invention, the step of determining single-lamp faults based on the brightness detection results and color detection results corresponding to each frame of single-lamp image information of each single lamp, as well as the pre-stored information of the single lamp, and obtaining and uploading single-lamp fault judgment information for each single lamp includes: sequentially performing a single-lamp fault determination process on each single lamp based on the brightness detection results and color detection results corresponding to each frame of single-lamp image information of each single lamp, as well as the pre-stored information of the single lamp, and obtaining and uploading single-lamp fault judgment information for each single lamp respectively; wherein, the single-lamp fault determination process includes: determining the brightness detection results and color detection results corresponding to each frame of single-lamp image information of the current single lamp. If the two lights are not consistent, then generate and upload the corresponding single-lamp fault judgment information for abnormal working status, and send feedback information to prompt the next single lamp to execute the single-lamp fault judgment process; if they are consistent, then determine the single-lamp working status information of the single lamp, and determine whether the single-lamp working status information is consistent with the pre-stored single-lamp working status information in the corresponding single-lamp pre-stored information. If they are consistent, generate and upload the corresponding single-lamp fault judgment information for normal working status, and if they are inconsistent, generate and upload the corresponding single-lamp fault judgment information for abnormal working status, and send feedback information to prompt the next single lamp to execute the single-lamp fault judgment process.

[0009] In one embodiment of the present invention, the single-lamp fault judgment information includes one or more of the following: single-lamp working status information, single-lamp brightness information, single-lamp color temperature information, and single-lamp address information.

[0010] In one embodiment of the present invention, the step of determining the fault of each row of lights based on the fault judgment information of each individual light in a row, and obtaining and uploading the fault judgment information of each row of lights includes: performing a fault judgment process on each row of lights sequentially based on the fault judgment information of each individual light in each row of lights, and obtaining and uploading the fault judgment information of each row of lights; wherein, the fault judgment process includes: determining whether the fault judgment information of each individual light in the current row of lights is normal and consistent;

[0011] If all lights are normal and consistent, generate and upload fault judgment information for the corresponding row of lights that are in normal working condition. If they are not all normal and consistent, determine whether the fault judgment information for each individual light in the current row of lights is normal and inconsistent. If they are all normal and inconsistent, determine the case with the largest proportion of fault judgment information for individual lights and generate and upload the corresponding fault judgment information for the row of lights that are in abnormal working condition. If they are not all normal and inconsistent, execute the subsequent row of lights fault judgment process. The subsequent row of lights fault judgment process includes: determining whether there is an individual light in normal working condition based on the fault judgment information for each individual light in the current row of lights; if so, execute the partial normal judgment process to obtain the corresponding row of lights fault judgment information; if not, determine whether the fault judgment information for each individual light is abnormal and consistent. If they are all normal and consistent, determine and upload the corresponding fault judgment information for the row of lights that are in abnormal working condition. If they are not all abnormal and consistent, determine and upload the corresponding fault judgment information for the row of lights that are in abnormal working condition and whose individual light fault judgment information is abnormal.

[0012] In one embodiment of the present invention, the local normality determination process includes: determining whether the fault determination information of the single lamps in the current row of lights corresponding to the normal working state is consistent; if consistent, generating and uploading the row of lights fault determination information in which the brightness of the single lamps in the corresponding abnormal state and the normal working state are not different; if inconsistent, determining the case where the proportion of the single lamp fault determination information of the single lamps in the current row of lights corresponding to the normal working state is the largest, generating and uploading the row of lights fault determination information in which the brightness of the single lamps in the corresponding abnormal state and the normal working state are different.

[0013] In one embodiment of the present invention, the fault judgment information of the LED array includes one or more of the following: LED array working status information, LED array brightness information, LED array color temperature information, LED array address information, and faulty single lamp address information.

[0014] In one embodiment of the present invention, the step of determining area light faults based on the fault judgment information of each row of lights in each area and the fault judgment information of scattered individual lights not distributed in rows, and obtaining and uploading the area light fault judgment information of each area light includes: performing an area light fault judgment process on each area based on the fault judgment information of each row of lights in each area and the fault judgment information of each scattered individual light, and obtaining and uploading the area light fault judgment information of each area light; wherein, the area light fault judgment process includes: determining whether the fault judgment information of each row of lights in the current area and the fault judgment information of each scattered individual light are all normal and consistent; if they are all normal and consistent, generating and uploading the area light fault judgment information corresponding to the normal working state; In cases where the fault assessment information for each row of lights is not uniformly normal but consistent, it is determined whether the fault assessment information for each individual light is uniformly normal but inconsistent. If the fault assessment information is uniformly normal but inconsistent, the case with the highest proportion of fault assessment information is identified, and corresponding area light fault assessment information for individual lights and / or rows of lights with abnormal working states and brightness differences is generated and uploaded. In cases where the fault assessment information is not uniformly normal but inconsistent, subsequent area light fault identification procedures are executed. The subsequent area light identification procedure includes: determining whether the fault assessment information for each row of lights and the individual light fault assessment information for each individual light in the current area is... If there are rows of lights and / or individual lights that are in normal working condition, execute the local normal judgment process for the area to obtain the corresponding area light fault judgment information; if not, determine whether the fault judgment information of each row of lights and the individual light fault judgment information of each dispersed light in the current area are all abnormal and consistent. If they are all abnormal and consistent, determine and upload the fault judgment information of the row of lights that are in abnormal working condition. If they are not all abnormal and consistent, determine and upload the fault judgment information of the row of lights that are in abnormal working condition and the fault judgment information of each dispersed light that is in abnormal working condition.

[0015] In one embodiment of the present invention, the regional local normality determination process includes: determining whether the fault judgment information of each row of lights and / or the fault judgment information of each individual light in the current region corresponding to normal working status is consistent; if consistent, generating and uploading regional light fault judgment information where the brightness of each row of lights and / or individual lights in the corresponding abnormal or normal working status is not different; if inconsistent, determining the case where the proportion of the fault judgment information of each row of lights and the fault judgment information of each individual light in the current region corresponding to normal working status is the largest, and generating regional light fault judgment information where the brightness of each row of lights and / or individual lights in the corresponding abnormal or normal working status is different.

[0016] In one embodiment of the present invention, the area light fault judgment information includes one or more of the following: area light working status information, area light brightness information, area light color temperature information, row light brightness information, single light brightness information, area light address information, row light address information, and single light address information.

[0017] To achieve the above and other related objectives, this invention provides a street light fault diagnosis system based on single-lamp image processing. The system includes: an information unit, a discrimination unit, and a processing unit. The information unit includes: a single-lamp image frame processing module for acquiring single-lamp image information of each collected single lamp; wherein the single-lamp image information includes: multiple frames of single-lamp image information; and a single-lamp control information storage module for storing pre-stored single-lamp information and single-lamp address information for each lamp. The discrimination unit includes: an image brightness and color detection module connected to the single-lamp image frame processing module for obtaining brightness and color detection results corresponding to each frame of single-lamp image information of each lamp based on the single-lamp image information; and a single-lamp fault diagnosis module connected to the image brightness and color detection module, the single-lamp control information storage module, and the single-lamp image frame processing module for determining single-lamp faults based on the brightness and color detection results corresponding to each frame of single-lamp image information of each lamp and the pre-stored single-lamp information. The system includes: a lamp fault identification module, which identifies, obtains, and uploads individual lamp fault identification information; a row lamp fault identification module, connected to the individual lamp fault identification module, which identifies row lamp faults based on the individual lamp fault identification information of each row of lamps, and obtains and uploads row lamp fault identification information for each row of lamps; and a zone lamp fault identification module, connected to the row lamp fault identification module and the individual lamp fault identification module, which identifies zone lamp faults based on the row lamp fault identification information of each row of lamps in each zone and the individual lamp fault identification information of scattered individual lamps not distributed in rows, and obtains and uploads zone lamp fault identification information for each zone lamp; the processing unit includes: an information upload module and a central processing module; wherein the information upload module is connected to the individual lamp fault identification module, the row lamp fault identification module, the zone lamp fault identification module, and the central processing module, and is used to upload the individual lamp fault identification information of each lamp, the row lamp fault identification information of each row of lamps, and the zone lamp fault identification information of each zone lamp to the central processing module.

[0018] To achieve the above and other related objectives, the present invention provides a street light fault diagnosis terminal based on single-lamp image processing, comprising: one or more memories and one or more processors; the one or more memories are used to store a computer program; the one or more processors are connected to the memories and are used to run the computer program to execute the street light fault diagnosis method based on single-lamp image processing.

[0019] To achieve the above and other related objectives, the present invention provides a computer-readable storage medium storing a computer program, which is executed by one or more processors to perform the street light fault judgment method based on single-lamp image processing.

[0020] As described above, this invention is a street light fault diagnosis method, system, terminal, and medium based on single-lamp image processing, which has the following beneficial effects: By processing single-lamp image frames and then performing multiple fault judgments on the street light through single-lamp fault judgment, row lamp fault judgment, and area lamp fault judgment, this invention can detect the working status, brightness, and color temperature of the street light in real time, effectively reducing the impact of brightness differences on fault judgment, improving detection accuracy, eliminating detection errors, and accurately identifying faulty street lights with uneven brightness and flickering on the road. This facilitates staff to accurately locate and promptly handle faulty street lights based on fault information, effectively ensuring the safety of vehicles traveling at night and reducing the occurrence of road traffic problems. Attached Figure Description

[0021] Figure 1 The diagram shown is a flowchart illustrating a street light fault diagnosis method based on single-lamp image processing according to an embodiment of the present invention.

[0022] Figure 2 The diagram shows a flowchart illustrating the process of obtaining individual lamp image information for each lamp in one embodiment of the present invention.

[0023] Figure 3 The diagram shows a flowchart illustrating the method for obtaining brightness and color detection results according to an embodiment of the present invention.

[0024] Figure 4 The diagram shown is a schematic diagram of a single-lamp fault detection process in one embodiment of the present invention.

[0025] Figure 5 The diagram shown is a schematic diagram of the lamp fault detection process in one embodiment of the present invention.

[0026] Figure 6 The diagram shown is a schematic of the area light status determination process in one embodiment of the present invention.

[0027] Figure 7 The diagram shown is a schematic representation of a street light fault diagnosis system based on single-lamp image processing according to an embodiment of the present invention.

[0028] Figure 8 The diagram shown is a schematic representation of a street light fault diagnosis terminal based on single-lamp image processing according to an embodiment of the present invention. Detailed Implementation

[0029] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0030] It should be noted that in the following description, reference is made to the accompanying drawings, which illustrate several embodiments of the invention. It should be understood that other embodiments may also be used, and changes in mechanical composition, structure, electrical system, and operation may be made without departing from the spirit and scope of the invention. The following detailed description should not be considered limiting, and the scope of the embodiments of the invention is defined only by the claims of the published patents. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. Spatially related terms, such as “upper,” “lower,” “left,” “right,” “below,” “below,” “lower part,” “above,” “upper part,” etc., may be used herein to illustrate the relationship between one element or feature shown in the figures and another element or feature.

[0031] Throughout this specification, when it is said that a part is "connected" to another part, this includes not only "direct connection" but also "indirect connection" by placing other elements in between. Furthermore, when it is said that a part "includes" a certain constituent element, unless otherwise stated otherwise, this does not exclude other constituent elements, but rather means that other constituent elements may also be included.

[0032] The terms "first," "second," and "third," etc., used herein are for the purpose of describing various parts, components, regions, layers, and / or segments, but are not limiting. These terms are used only to distinguish one part, component, region, layer, or segment from others. Therefore, the "first part," "component," "region," "layer," or "segment" described below may refer to a "second part," "component," "region," "layer," or "segment" without departing from the scope of this invention.

[0033] Furthermore, as used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context indicates otherwise. It should be further understood that the terms “comprising,” “including,” indicate the presence of the stated feature, operation, element, component, item, kind, and / or group, but do not preclude the presence, occurrence, or addition of one or more other features, operations, elements, components, items, kinds, and / or groups. The terms “or” and “and / or” as used herein are interpreted as inclusive, or mean any one or any combination thereof. Thus, “A, B, or C” or “A, B, and / or C” means “any one of: A; B; C; A and B; A and C; B and C; A, B, and C.” Exceptions to this definition arise only when combinations of elements, functions, or operations are inherently mutually exclusive in some manner.

[0034] This invention discloses a street light fault diagnosis method based on single-lamp image processing. By processing single-lamp image frames and then performing multiple fault judgments on the street light through single-lamp fault judgment, row lamp fault judgment, and area lamp fault judgment, the method can detect the working status, brightness, and color temperature of the street light in real time. This effectively reduces the impact of brightness differences on fault judgment, improves detection accuracy, eliminates detection errors, and can accurately identify faulty street lights with uneven brightness and flickering on the road. This allows staff to accurately locate and promptly handle faulty street lights based on fault information, effectively ensuring the safety of vehicles traveling at night and reducing the occurrence of road traffic problems.

[0035] The present invention will now be described in detail with reference to the accompanying drawings, so that those skilled in the art can readily implement it. The present invention can be embodied in many different forms and is not limited to the embodiments described herein.

[0036] like Figure 1 This is a flowchart illustrating a street light fault diagnosis method based on single-lamp image processing according to an embodiment of the present invention.

[0037] The method includes:

[0038] Step S1: Obtain the image information of each individual lamp.

[0039] In detail, the single-lamp image information includes: multi-frame single-lamp image information.

[0040] In one embodiment, step S1 includes:

[0041] The system acquires real-time street light video streams and divides these streams into individual real-time video streams for each street light. The real-time video streams can be acquired using image and video acquisition devices, which can be any device with image and video acquisition capabilities, such as a camera.

[0042] Based on a defined random time interval, multiple frames of single-lamp image information for each lamp are randomly sampled from the real-time video stream of each lamp and output.

[0043] Specifically, such as Figure 2 As shown, the video stream acquired by the image and video acquisition device contains image information of multiple individual lights. First, the captured video stream is divided to obtain the independent video stream of each individual light. The total number of frames m of the real-time video stream of each individual light is obtained, and the number of image frames n to be processed is determined, where n≤m. A random time interval is determined within the total number of frames. Based on this random time interval, the corresponding image frames are randomly sampled from the real-time video stream of each individual light, and then multiple frames of individual light image information are output.

[0044] Step S2: Based on the image information of each individual lamp, obtain the brightness detection result and color detection result corresponding to the image information of each frame of each individual lamp.

[0045] In one embodiment, such as Figure 3 As shown, step S2 includes:

[0046] The image information of each single light in each frame is input into the feature extraction network to obtain the feature map of each frame of single light image information;

[0047] Based on the detection box generation network, the ROI region detection box corresponding to the single-lamp image information of each frame is obtained according to the feature map of the single-lamp image information of each frame.

[0048] Based on a color detection network, color detection is performed on the images within the ROI region detection box corresponding to each frame of single-lamp image information to obtain the color detection results of each frame of single-lamp image information corresponding to each single lamp; wherein, the color detection results include: consistent color temperature range, inconsistent color temperature range, color transformation, etc.

[0049] Based on a brightness detection network, brightness detection is performed on the images within the ROI region detection box corresponding to each frame of single-lamp image information to obtain the brightness detection results of each frame of single-lamp image information; wherein, the brightness detection results include bright, high brightness, medium brightness, low brightness and dark.

[0050] Step S3: Based on the brightness detection results and color detection results corresponding to each frame of single-lamp image information and the pre-stored information of each single lamp, perform single-lamp fault identification, obtain and upload the single-lamp fault identification information for each single lamp.

[0051] In one embodiment, the pre-stored information for a single lamp includes: pre-stored single lamp working status information, pre-stored single lamp brightness information, pre-stored single lamp color temperature information, and single lamp address information.

[0052] In one embodiment, step S3 includes:

[0053] Based on the brightness and color detection results corresponding to each frame of single-lamp image information and the pre-stored information of each single lamp, the single-lamp fault judgment process is executed sequentially for each single lamp, and the single-lamp fault judgment information of each single lamp is obtained and uploaded respectively.

[0054] The single-lamp fault detection process includes:

[0055] Determine whether the brightness detection results and color detection results corresponding to the single-lamp image information of each frame of the current single lamp are consistent;

[0056] If there is a discrepancy, generate and upload the corresponding single lamp fault judgment information for abnormal working status, and send feedback information to prompt the next single lamp to execute the single lamp fault judgment process;

[0057] If they match, the working status information of the single lamp is determined; and it is determined whether the working status information of the single lamp is consistent with the pre-stored working status information of the corresponding single lamp. If they match, a fault judgment information of the single lamp with normal working status is generated and uploaded. If they do not match, a fault judgment information of the single lamp with abnormal working status is generated and uploaded. Feedback information is sent to prompt the next single lamp to execute the single lamp fault judgment process.

[0058] In a preferred embodiment, the single-lamp fault judgment information includes one or more of the following: single-lamp working status information, single-lamp brightness information, single-lamp color temperature information, and single-lamp address information.

[0059] In one specific embodiment, such as Figure 4 As shown, the single-lamp fault diagnosis process includes:

[0060] Obtain the brightness and color detection results of single-lamp image information in each frame under the same address;

[0061] Determine whether the brightness detection results and color detection results of each frame are consistent;

[0062] If "No", meaning the brightness detection results and color detection results of each frame of single-lamp image information are inconsistent, then the working state of the single lamp is judged to be abnormal. After establishing the fault judgment information of this single lamp, it is uploaded, and a feedback information is sent to prompt the sending of the next multi-frame single-lamp image information for single lamp status judgment. In this case, the single lamp fault judgment information may be, for example: single lamp working state is abnormal, single lamp is flashing, single lamp address information, or single lamp working state is abnormal, single lamp is flashing, single lamp address information, etc.

[0063] If "yes", that is, the brightness detection results and color detection results of each frame are consistent, then the working state of this single lamp is established.

[0064] Next, determine whether the single lamp working status information is consistent with the pre-stored single lamp working status information in the corresponding single lamp pre-stored information;

[0065] If "No", meaning the single-lamp working status information is inconsistent with the single-lamp working status information in the pre-stored single-lamp information, the fault judgment information for the inconsistent working status information is established and uploaded, and feedback information is sent to prompt the sending of multi-frame single-lamp image information for the next single lamp to determine the single-lamp status. In this state, the single-lamp fault judgment information may include, for example, abnormal single-lamp working status, inconsistent color temperature range, single-lamp address information; or abnormal single-lamp working status, inconsistent brightness (bright when it should be dark or dark when it should be bright), single-lamp address information, etc.

[0066] If "yes", meaning the single-lamp working status information matches the single-lamp working status information in the pre-stored single-lamp information, the fault judgment information when the working status information matches is established and uploaded, and feedback information is sent to prompt the sending of multi-frame single-lamp image information of the next single lamp for single-lamp status judgment. In this state, the single-lamp fault judgment information may include, for example, the single lamp working status is normal, the brightness is consistent (i.e., dark when it should be dark), and the single lamp address information; or the single lamp working status is normal, the color temperature range is consistent, the brightness is consistent (i.e., bright when it should be bright), the single lamp brightness information (high brightness, medium brightness, low brightness), and the single lamp address information.

[0067] Step S4: Based on the individual lamp fault judgment information of each lamp distributed in a row, perform row lamp fault judgment, obtain and upload row lamp fault judgment information for each row of lamps.

[0068] In one embodiment, the fault judgment information of the LED array includes one or more of the following: LED array working status information, LED array brightness information, LED array color temperature information, LED array address information, and faulty single lamp address information.

[0069] In one embodiment, step S4 includes:

[0070] Based on the individual lamp fault judgment information of each lamp in each row of lights, the row of lights fault judgment process is executed sequentially for each row of lights to obtain and upload the row of lights fault judgment information of each row of lights.

[0071] The lamp fault detection process includes:

[0072] Determine whether the fault information of each lamp in the current light panel is normal and consistent. Specifically, the method to determine whether the fault information of a single lamp is normal is to judge by the working status information of the single lamp in the fault information. The working status information of a single lamp has two states: normal working status and abnormal working status. The method to determine whether the fault information of a single lamp is consistent is to judge whether the brightness information and color temperature information of the single lamp are consistent.

[0073] Under normal and consistent conditions, generate and upload the corresponding fault judgment information for the LED array that is in normal working status. In this case, the fault judgment information for the LED array may be as follows: LED array working status is normal, brightness is consistent (dark when it should be dark), LED array address information; LED array working status is normal, brightness is consistent (bright when it should be bright), LED array brightness information (high brightness, medium brightness or low brightness), color temperature range is consistent, LED array address information.

[0074] In cases where the light distribution is not uniformly normal but consistent, determine whether the individual lamp fault judgment information of each lamp in the current light panel is both normal and inconsistent. If the distribution is uniformly normal but inconsistent, identify the case with the highest proportion of individual lamp fault judgment information and generate and upload the corresponding abnormal light panel fault judgment information. In this case, the light panel fault judgment information may include, for example: abnormal light panel working status, inconsistent brightness, light panel address information, and individual lamp address information with different brightness. In cases where the distribution is not uniformly normal but inconsistent, execute the subsequent light panel fault identification process.

[0075] Furthermore, the subsequent lamp fault detection process includes:

[0076] Determine whether there are any lamps that are functioning normally based on the individual lamp fault information of each lamp in the current lamp array;

[0077] If it exists, execute the local normal judgment process to obtain the corresponding lamp fault judgment information;

[0078] If not, determine whether the individual lamp fault judgment information of each lamp is abnormal and consistent. If all are abnormal and consistent, determine and upload the corresponding abnormal lamp panel fault judgment information. The lamp panel fault judgment information may be: abnormal lamp panel working status, inconsistent brightness, lamp panel address information; abnormal lamp panel working status, inconsistent color temperature range, lamp panel address information; abnormal lamp panel working status, flickering, lamp panel address information; abnormal lamp panel working status, color change, lamp panel address information; and if not all are abnormal and consistent, determine and upload the corresponding abnormal lamp panel fault judgment information where the individual lamp fault judgment information of each lamp is abnormal. The lamp panel fault judgment information may be: abnormal lamp panel working status, abnormal single lamp working status, lamp panel address information.

[0079] In a preferred embodiment, the local normality determination process includes:

[0080] Determine whether the fault diagnosis information of the single lamp that is working normally in the current light panel is consistent;

[0081] If they match, generate and upload the fault judgment information for the row of lights where the brightness of each individual light is not different for those in abnormal and normal working states.

[0082] If there is a discrepancy, the case where the proportion of fault judgment information for each lamp in the current light panel that is in normal working condition is determined, and the light panel fault judgment information for each lamp in the corresponding abnormal state and normal working condition that has different brightness is generated and uploaded.

[0083] In one specific embodiment, after generating single-lamp fault judgment information, the location of each street light can be obtained by inputting the single-lamp address information of each single lamp. If the single-lamp address information of street lights arranged in rows or columns is input, the fault judgment information of each street light in the row can be obtained, thereby performing row light status judgment, generating and uploading row light fault judgment information.

[0084] like Figure 5 As shown, the fault diagnosis process for LED strip lights includes:

[0085] Obtain individual lamp fault diagnosis information for each lamp in the current lamp array;

[0086] Determine whether the fault diagnosis information for each lamp in this row is normal and consistent;

[0087] If "yes", it means that the fault judgment information of each individual lamp in this row is normal and consistent, then the working status of the row of lamps is judged to be normal. After establishing the fault judgment information of the row of lamps, it is uploaded. In this case, the fault judgment information of the row of lamps can be, for example: The row of lamps is working normally, it is lit when it should be lit, the color temperature range is consistent, and it is high brightness, address of this row of lamps; The row of lamps is working normally, it is lit when it should be lit, the color temperature range is consistent, and it is medium brightness, address of this row of lamps; The row of lamps is working normally, it is lit when it should be lit, the color temperature range is consistent, and it is low brightness, address of this row of lamps; The row of lamps is working normally, it is dark when it should be dark, address of this row of lamps.

[0088] If "No", then determine whether the fault judgment information of each lamp in this row is normal but inconsistent;

[0089] If “yes”, determine the situation with the largest proportion in the fault judgment information of each individual lamp of this light panel, and upload the fault judgment information after establishing it. In this case, the working status of the light panel is abnormal and there are individual lamps with different brightness. The fault judgment information of the light panel may be: abnormal working status of the light panel, inconsistent brightness, light panel address information, address information of individual lamps with different brightness, etc.

[0090] If "no", then continue to determine whether there are any K lamps that are partially normal in the lamp fault judgment information of each lamp in this row;

[0091] If "No", determine whether the fault judgment information of each individual lamp in this row is abnormal but consistent, and establish and upload the fault judgment information of the row lights under different states. If the fault judgment information of each individual lamp is abnormal and consistent, the fault judgment information of the row lights may be as follows: The row lights are not working properly, they are sometimes bright and sometimes dim, and sometimes dim and sometimes bright, this row light address; The row lights are not working properly, they are flickering, this row light address; The row lights are not working properly, the color temperature range is inconsistent with the normal working state, this row light address; The row lights are not working properly, the color is changing, this row light address. If the fault judgment information of each individual lamp is abnormal and inconsistent, the fault judgment information of the row lights may be as follows: The row lights are not working properly, the working state of each individual lamp in this row is abnormal, this row light address.

[0092] If "yes", meaning there are K lamps that are partially normal in the fault judgment information of each lamp in this row, then continue to judge whether the fault judgment information of the K lamps that are partially normal in this row is consistent; and establish and upload the fault judgment information of the row lights under different states. If the fault judgment information of the K lamps that are partially normal in this row is consistent, then establish and upload the fault judgment information of the row lights at this time. For example, if the row lights are not working properly, but there are no lamps with brightness differences among the K lamps that are partially normal, then the address of this row light is determined. If the fault judgment information of the K lamps that are partially normal in this row is inconsistent, then determine the situation where the fault judgment information of the K lamps that are partially normal in this row has the largest proportion, establish and upload the fault judgment information of the row lights at this time. For example, if the row lights are not working properly, but there are lamps with brightness differences among the K lamps that are partially normal, then the address of this row light and the address of the lamp with the corresponding brightness difference are determined.

[0093] After the light panel status determination process is completed, the single-lamp fault determination information and the light panel fault determination information can be input together into the next process to determine the status of the area lights.

[0094] Step S5: Based on the fault judgment information of each row of lights in each area and the fault judgment information of individual lights that are not distributed in rows, perform area light fault judgment, obtain and upload the area light fault judgment information of each area light.

[0095] In one embodiment, the area light fault judgment information includes one or more of the following: area light working status information, area light brightness information, area light color temperature information, row light brightness information, single light brightness information, area light address information, row light address information, and single light address information.

[0096] In one embodiment, step S5 includes:

[0097] Based on the fault judgment information of each row of lights in each area and the fault judgment information of each individual light, the area light fault judgment process is executed for each area to obtain and upload the area light fault judgment information of each area light.

[0098] The fault detection process for the area lights includes:

[0099] The system determines whether the fault diagnosis information for each row of lights in the current area and the fault diagnosis information for each individual light are normal and consistent. Specifically, the system determines whether the fault diagnosis information is normal by checking the working status information of the row of lights and the individual lights in the fault diagnosis information. The working status information of the individual lights and the row of lights can be either normal or abnormal. The system determines whether the fault diagnosis information is consistent by checking whether the brightness and color temperature information are consistent.

[0100] Under normal and consistent conditions, generate and upload the corresponding fault judgment information for the area lights that are in normal working status. In this state, the fault judgment information for the area lights may be, for example: the area light is in normal working status, the brightness is consistent, the color temperature range is consistent, the brightness is high, and the area light address information; or the area light is in normal working status, the brightness is consistent, the color temperature range is consistent, the brightness is medium, and the area light address information, etc.

[0101] In cases where the fault assessment information for each row of lights is not uniformly normal but consistent, it is determined whether the fault assessment information for each individual light is uniformly normal but inconsistent. If the fault assessment information is uniformly normal but inconsistent, the case with the highest proportion of fault assessment information is identified, and corresponding area light fault assessment information for individual lights and / or rows of lights with abnormal operating states and brightness differences is generated and uploaded. In this case, the area light fault assessment information may include, for example: abnormal area light operating state, inconsistent row light brightness, area light address information, address information for rows of lights with brightness differences, etc.; abnormal area light operating state, inconsistent individual light brightness, area light address information, address information for individual lights with brightness differences, etc.; abnormal area light operating state, inconsistent row and individual light brightness, area light address information, address information for rows of lights with brightness differences, etc., address information for individual lights with brightness differences; and in cases where the fault assessment information is not uniformly normal but inconsistent, the subsequent area light fault identification process is executed.

[0102] Furthermore, the subsequent area light determination process includes:

[0103] Based on the fault judgment information of each row of lights in the current area and the fault judgment information of each individual light, determine whether there are rows of lights and / or individual lights that are in normal working condition.

[0104] If it exists, the local normal judgment process for the area is executed to obtain the corresponding area light fault judgment information;

[0105] If not, determine whether the fault judgment information of each row of lights and the fault judgment information of each individual light in the current area are all abnormal and consistent. If they are all abnormal and consistent, identify and upload the fault judgment information of the corresponding row of lights with abnormal working status. For example, the fault judgment information of the area lights may be: abnormal working status of the area light, inconsistent brightness, area light address information; abnormal working status of the area light, flickering, area light address information; abnormal working status of the area light, inconsistent color temperature range, area light address information; abnormal working status of the area light, color change, area light address information. If they are not all abnormal and consistent, identify and upload the fault judgment information of the row of lights and the individual light fault judgment information of each individual light with abnormal working status. For example, the fault judgment information of the area lights may be: abnormal working status of the area lights, abnormal working status of the row of lights, abnormal working status of individual lights, area light address information.

[0106] In a preferred embodiment, the regional local normality determination process includes:

[0107] Based on the fault judgment information of each row of lights and / or the fault judgment information of each individual light in the current area, determine whether the working status of each row of lights and / or each individual light in the current area is consistent.

[0108] If consistent, generate and upload the corresponding fault judgment information for the area lights where the brightness of each row of lights and / or individual lights is not different, whether the working status is abnormal or normal. The fault judgment information for the area lights may be, for example, the address information of the X row of lights or Y individual lights where the brightness is inconsistent and the working status of the area lights is abnormal or partially normal.

[0109] If there is a discrepancy, the system determines the scenario with the highest proportion of fault judgment information for each row of lights in the current area that is in normal working condition, as well as for each individual light in the current area. This generates area light fault judgment information for the corresponding area where the brightness of each row of lights and / or individual lights differs, indicating either abnormal or normal working conditions. Examples of area light fault judgment information include: X rows of lights with inconsistent brightness (where the area light is in an abnormal working condition but partially normal), area light address information, and address information for the lights with inconsistent brightness; Y individual lights with inconsistent brightness (where the area light is in an abnormal working condition but partially normal), area light address information, and address information for the individual lights with inconsistent brightness; X rows of lights with inconsistent brightness (where the area light is in an abnormal working condition but partially normal), Y individual lights with inconsistent brightness, area light address information, address information for the row of lights with inconsistent brightness, and address information for the individual lights with inconsistent brightness, etc.

[0110] In one specific embodiment, after generating single-lamp fault judgment information and row-lamp fault judgment information, the single-lamp fault judgment information and row-lamp fault judgment information are input to determine the fault status of one or more rows or columns of streetlights in a certain area or road section.

[0111] like Figure 6 As shown, the area light status determination process determines faults based on row light fault determination information and individual light fault determination information. The area light fault determination process includes:

[0112] Obtain fault diagnosis information for each row of lights and individual lights within the area;

[0113] Determine whether the fault diagnosis information for each row of lights and each individual light in this area is normal and consistent.

[0114] If "Yes", then the fault judgment information of the light in that area is established and uploaded. In this state, the fault judgment information of the light in that area can be, for example: The light in that area is working normally, it is on when it should be on, the color temperature range is consistent, and it is high brightness, address of this light in that area; The light in that area is working normally, it is on when it should be on, the color temperature range is consistent, and it is medium brightness, address of this light in that area; The light in that area is working normally, it is on when it should be on, the color temperature range is consistent, and it is low brightness, address of this light in that area; The light in that area is working normally, it is off when it should be off, address of this light in that area.

[0115] If "No", then determine whether the fault diagnosis information of each row of lights and individual lights in this area is normal but inconsistent;

[0116] If "Yes", determine the situation with the highest proportion of fault judgment information for each row of lights and individual lights in this area, establish the area light fault judgment information, and upload it. In this case, the area light fault judgment information may be as follows: The area light is not working properly, there are rows of lights with different brightness, the address of this area light, and the address of the row of lights with different brightness (inconsistency only exists in each row of lights); The area light is not working properly, there are individual lights with different brightness, the address of this area light, and the address of the individual light with different brightness (inconsistency only exists in the individual lights); The area light is not working properly, there are rows of lights and individual lights with different brightness, the address of this area light, the address of the row of lights with different brightness, and the address of the individual lights (inconsistency exists in both each row of lights and the individual lights).

[0117] If "no", then continue to check whether there are any partially normal X row lights or Y scattered individual lights in the fault judgment information of each row of lights and each scattered individual light in this area.

[0118] If "No", determine whether the fault judgment information of each row of lights and each individual light in this area is abnormal and consistent, and establish and upload the fault judgment information of the area lights under different states. When the fault judgment information of each row of lights and each individual light in the area is abnormal and consistent, the fault judgment information of the area lights may be as follows: The area light is not working properly, it is dark when it should be on / bright when it should be dark, address of this area light; The area light is not working properly, it is flickering, address of this area light; The area light is not working properly, the color temperature range is inconsistent with the normal working state, address of this area light; The area light is not working properly, the color is changing, address of this area light. When the fault judgment information of each row of lights and each individual light in the area is abnormal and inconsistent, the fault judgment information of the area lights may be as follows: The area light is not working properly, the working state of each row of lights in this area is abnormal (each row of lights has one of the eight abnormal states of the row of lights), and the working state of all individual lights is also abnormal (all individual lights have one of the four abnormal states of the individual lights), address of this area light.

[0119] If "yes", determine whether the fault judgment information of the X-row lights or Y individual lights in this row that are partially normal is consistent, and whether they correspond consistently when both exist; establish and upload the fault judgment information of the area lights under each condition. If the fault judgment information of the X-row lights or Y individual lights in this row that are partially normal is consistent and corresponds consistently, the area light fault judgment information could be, for example: the area light is not working properly, but there are no lights with brightness differences among the X-row lights or individual lights in the Y-row that are partially normal, and the address of this area light; if the fault judgment information of the X-row lights or Y individual lights in this row is inconsistent and does not correspond consistently, determine the case with the largest proportion of fault judgment information for the rows of lights and individual lights in this area, and establish the fault judgment information for this area light. In this case, the area light fault judgment information could be, for example: the area light is not working properly, there are lights with brightness differences in the X-row that are partially normal, the address of this area light, and the address of the light with brightness differences (inconsistency only exists in the X-row lights that are partially normal). The area lights are malfunctioning. Among the Y individual lights that are partially normal, there are individual lights with brightness differences. The address of the area light corresponds to the address of the individual light with brightness differences (the inconsistency only exists in the Y individual lights that are partially normal). The area lights are malfunctioning. Among the X rows of lights that are partially normal, there are rows of lights with brightness differences. At the same time, among the Y individual lights, there are individual lights with brightness differences. The address of the area light corresponds to the address of the row of lights with brightness differences and the address of the individual light with brightness differences (the inconsistency exists in both the X rows of lights and the Y individual lights that are partially normal).

[0120] Similar to the above embodiments, the present invention provides a street light fault diagnosis system based on single-lamp image processing.

[0121] The following specific embodiments are provided in conjunction with the accompanying drawings:

[0122] like Figure 7 This invention presents a schematic diagram of a street light fault diagnosis system based on single-lamp image processing, according to an embodiment of the present invention.

[0123] The system includes: an information unit 10, a discrimination unit 20, and a processing unit 30;

[0124] The information unit 10 includes: a single-lamp image frame processing module 11, used to obtain single-lamp image information of each collected single lamp; wherein the single-lamp image information includes: multi-frame single-lamp image information; and a single-lamp control information storage module 12, used to store single-lamp pre-stored information and single-lamp address information of each single lamp.

[0125] The discrimination unit 20 includes: an image brightness and color detection module 21, connected to the single-lamp image frame processing module 11, which obtains the brightness detection result and color detection result corresponding to each frame of single-lamp image information for each single lamp based on the single-lamp image information; and a single-lamp fault discrimination module 22, connected to the single-lamp image frame processing module 11, the single-lamp control information storage module 12, and the image brightness and color detection module 21, which is used to perform single-lamp fault discrimination based on the brightness detection result and color detection result corresponding to each frame of single-lamp image information for each single lamp and the single-lamp pre-stored information, and to obtain and upload the information for each single lamp. The system includes: a single-lamp fault judgment module 23, connected to the single-lamp fault judgment module 22, used to perform row-light fault judgment based on the single-lamp fault judgment information of each row of lamps, and to obtain and upload the row-light fault judgment information of each row of lamps; and a zone-light fault judgment module 24, connected to the row-light fault judgment module 23 and the single-lamp fault judgment module 22, used to perform zone-light fault judgment based on the row-light fault judgment information of each row of lamps in each zone and the single-lamp fault judgment information of scattered lamps not distributed in rows, and to obtain and upload the zone-light fault judgment information of each zone-light.

[0126] The processing unit 30 includes an information uploading module 31 and a central processing module 32; wherein the information uploading module 31 is connected to the single lamp fault judgment module, the row lamp fault judgment module, the area lamp fault judgment module and the central processing module, and is used to upload the single lamp fault judgment information of each single lamp, the row lamp fault judgment information of each row lamp and the area lamp fault judgment information of each area lamp to the central processing module for subsequent processing.

[0127] It should be noted that, as should be understood Figure 7The division of modules in the system embodiment is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, these modules can be implemented entirely in software through processing element calls; they can be implemented entirely in hardware; or some modules can be implemented through processing element calls in software, while others are implemented in hardware.

[0128] For example, each module can be one or more integrated circuits configured to implement the above methods, such as one or more Application Specific Integrated Circuits (ASICs), one or more digital signal processors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs). As another example, when a module is implemented using processing element scheduler code, the processing element can be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. Furthermore, these modules can be integrated together to form a system-on-a-chip (SOC).

[0129] Since the implementation principle of the street light fault judgment system based on single-lamp image processing has been described in the foregoing embodiments, it will not be repeated here.

[0130] In one embodiment, the single-lamp image frame processing module 11 is used to acquire the real-time street lamp video stream and divide the street lamp video stream into single-lamp real-time video streams for each single lamp; based on a determined random time interval, it randomly samples from the single-lamp real-time video streams of each single lamp to obtain and output multiple frames of single-lamp image information for each single lamp.

[0131] In one embodiment, the image brightness and color detection module 21 is used to input the image information of each frame of each single lamp into a feature extraction network to obtain feature maps of each frame of single lamp image information; based on the detection box generation network, to obtain ROI region detection boxes corresponding to each frame of single lamp image information according to the feature maps of each frame of single lamp image information; based on the color detection network, to perform color detection on the images within the ROI region detection boxes corresponding to each frame of single lamp image information to obtain color detection results for each frame of single lamp image information corresponding to each single lamp; and based on the brightness detection network, to perform brightness detection on the images within the ROI region detection boxes corresponding to each frame of single lamp image information to obtain brightness detection results for each frame of single lamp image information corresponding to each single lamp.

[0132] In one embodiment, the single-lamp fault identification module 22 is used to sequentially perform a single-lamp fault identification process on each single lamp based on the brightness detection results and color detection results corresponding to each frame of single-lamp image information of each single lamp and the single-lamp pre-stored information, thereby obtaining and uploading single-lamp fault identification information for each single lamp; wherein, the single-lamp fault identification process includes: determining whether the brightness detection results and color detection results corresponding to each frame of single-lamp image information of the current single lamp are consistent; if they are inconsistent, generating and uploading single-lamp fault identification information corresponding to the abnormal working state, and sending feedback information to prompt the next single lamp to perform the single-lamp fault identification process; if they are consistent, determining the single-lamp working state information of the single lamp, and determining whether the single-lamp working state information is consistent with the pre-stored single-lamp working state information in the corresponding single-lamp pre-stored information, generating and uploading single-lamp fault identification information corresponding to the normal working state if they are consistent, and generating and uploading single-lamp fault identification information corresponding to the abnormal working state if they are inconsistent, and sending feedback information to prompt the next single lamp to perform the single-lamp fault identification process.

[0133] In one embodiment, the single-lamp fault judgment information includes one or more of the following: single-lamp working status information, single-lamp brightness information, single-lamp color temperature information, and single-lamp address information.

[0134] In one embodiment, the row light fault identification module 23 is used to sequentially execute a row light fault identification process for each row of lights based on the individual lamp fault identification information of each lamp in each row, to obtain and upload the row light fault identification information of each row of lights; wherein, the row light fault identification process includes: determining whether the individual lamp fault identification information of each lamp in the current row of lights is normal and consistent; if they are all normal and consistent, generating and uploading the row light fault identification information corresponding to the normal working state; if they are not all normal and consistent, determining whether the individual lamp fault identification information of each lamp in the current row of lights is normal and inconsistent, and if they are all normal and inconsistent, determining the case with the largest proportion of individual lamp fault identification information and generating the row light fault identification information corresponding to the abnormal working state. The system diagnoses and uploads lamp fault information, and executes subsequent lamp fault identification procedures when the faults are not uniformly normal and inconsistent. The subsequent lamp fault identification procedures include: determining whether any lamps in the current lamp array are functioning normally based on their individual lamp fault information; if so, executing a partial normality identification procedure to obtain the corresponding lamp array fault information; if not, determining whether the individual lamp fault information is uniformly abnormal and consistent, and, if uniformly normal and consistent, determining and uploading the corresponding lamp array fault information that is not functioning normally, and, if uniformly abnormal and consistent, determining and uploading the corresponding lamp array fault information that is not functioning normally and where the individual lamp fault information is not uniformly normal.

[0135] In one embodiment, the local normality determination process includes: determining whether the working status of the individual lamps in the current row of lights is consistent based on the individual lamp fault determination information of each lamp in the current row of lights that is in a normal working status; if consistent, generating and uploading row of lights fault determination information in which the brightness of the individual lamps in the corresponding abnormal status and normal working status are not different; if inconsistent, determining the case where the proportion of individual lamp fault determination information of each lamp in the current row of lights that is in a normal working status is the largest, generating and uploading row of lights fault determination information in which the brightness of the individual lamps in the corresponding abnormal status and normal working status are different.

[0136] In one embodiment, the fault judgment information of the LED array includes one or more of the following: LED array working status information, LED array brightness information, LED array color temperature information, LED array address information, and faulty single lamp address information.

[0137] In one embodiment, the area light fault identification module 24 is used to perform an area light fault identification process for each area based on the fault identification information of each row of lights and the fault identification information of each individual light in each area, to obtain and upload the area light fault identification information of each area light; wherein, the area light fault identification process includes: determining whether the fault identification information of each row of lights and the fault identification information of each individual light in the current area are all normal and consistent; if they are all normal and consistent, generating and uploading the area light fault identification information corresponding to the normal working state; if they are not all normal and consistent, determining whether the fault identification information of each row of lights and the fault identification information of each individual light are all normal but inconsistent, and in the case of being all normal but inconsistent, determining the case with the largest proportion of fault identification information and generating and uploading the area light fault identification information of the individual light and / or row of lights with abnormal working state and brightness differences; and in the case of being not all normal but inconsistent, executing the subsequent area light fault identification process; Furthermore, the subsequent area light judgment process includes: determining whether there are rows of lights and / or individual lights in normal working condition based on the row light fault judgment information and the individual light fault judgment information of each row of lights in the current area; if so, executing the area local normal judgment process to obtain the corresponding area light fault judgment information; if not, determining whether the row light fault judgment information and the individual light fault judgment information of each row of lights in the current area are all abnormal and consistent, and determining and uploading the corresponding row light fault judgment information with abnormal working condition when they are all abnormal and consistent, and determining and uploading the row light fault judgment information with abnormal working condition and where the row light fault judgment information and the individual light fault judgment information of each row of lights are all abnormal when they are not all abnormal and consistent.

[0138] In one embodiment, the regional local normality determination process includes: determining whether the fault judgment information of each row of lights and / or the fault judgment information of each individual light in the current region corresponding to normal working status is consistent; if consistent, generating and uploading regional light fault judgment information where the brightness of each row of lights and / or individual lights in the corresponding abnormal or normal working status is not different; if inconsistent, determining the case where the proportion of the fault judgment information of each row of lights and the fault judgment information of each individual light in the current region corresponding to normal working status is the largest, and generating regional light fault judgment information where the brightness of each row of lights and / or individual lights in the corresponding abnormal or normal working status is different.

[0139] In one embodiment, the area light fault judgment information includes one or more of the following: area light working status information, area light brightness information, area light color temperature information, row light brightness information, single light brightness information, area light address information, row light address information, and single light address information.

[0140] like Figure 8 This invention presents a schematic diagram of the structure of a street light fault diagnosis terminal 80 based on single-lamp image processing in an embodiment of the present invention.

[0141] The street light fault diagnosis terminal 80 based on single-lamp image processing includes a memory 81 and a processor 82. The memory 81 stores a computer program; the processor 82 runs the computer program to implement, for example... Figure 1 The street light fault diagnosis method based on single-lamp image processing.

[0142] Optionally, the number of memories 81 can be one or more, and the number of processors 82 can be one or more. Figure 8 Each example is taken as an instance.

[0143] Optionally, the processor 82 in the street light fault judgment terminal 80 based on single-lamp image processing will perform the following... Figure 1 The steps described involve loading one or more instructions corresponding to the process of an application into memory 81, and then having the processor 82 run the application stored in the first memory 81, thereby achieving the following: Figure 1 The various functions in the street light fault diagnosis method based on single-lamp image processing.

[0144] Optionally, the memory 81 may include, but is not limited to, high-speed random access memory and non-volatile memory. For example, one or more disk storage devices, flash memory devices, or other non-volatile solid-state storage devices; the processor 82 may include, but is not limited to, a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0145] Optionally, the processor 82 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0146] The present invention also provides a computer-readable storage medium storing a computer program, wherein the computer program, when executed, implements as follows: Figure 1 The illustrated method for determining street light faults based on single-lamp image processing. The computer-readable storage medium may include, but is not limited to, floppy disks, optical disks, CD-ROMs (Read-Only Optical Disk Memory), magneto-optical disks, ROMs (Read-Only Memory), RAMs (Random Access Memory), EPROMs (Erasable Programmable Read-Only Memory), EEPROMs (Electrically Erasable Programmable Read-Only Memory), magnetic cards or optical cards, flash memory, or other types of media / machine-readable media suitable for storing machine-executable instructions. The computer-readable storage medium may be a product not connected to a computer device or a component used with a computer device.

[0147] In summary, the street light fault diagnosis method, system, terminal, and medium based on single-lamp image processing of the present invention, by processing single-lamp image frames and then performing multiple fault judgments on the street light through single-lamp fault judgment, row lamp fault judgment, and area lamp fault judgment, can detect the working status, brightness, and color temperature of street lights in real time. This effectively reduces the impact of brightness differences on fault judgment, improves detection accuracy, eliminates detection errors, and can accurately identify faulty street lights with uneven brightness and flickering on the road. This allows staff to accurately locate and promptly handle faulty street lights based on fault information, effectively ensuring the safety of vehicles traveling at night and reducing the occurrence of road traffic problems. Therefore, the present invention effectively overcomes the various shortcomings of the prior art and has high industrial application value.

[0148] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for determining street light faults based on single-lamp image processing, characterized in that, The method includes: Obtain the single-lamp image information of each captured single lamp; wherein, the single-lamp image information includes: multi-frame single-lamp image information; Based on the image information of each individual lamp, obtain the brightness detection results and color detection results corresponding to the image information of each frame of each individual lamp; Based on the brightness and color detection results corresponding to each frame of single-lamp image information and the pre-stored information of single lamp, single-lamp fault judgment is performed, and single-lamp fault judgment information for each single lamp is obtained and uploaded; the pre-stored information of single lamp includes: pre-stored single-lamp working status information, pre-stored single-lamp brightness information, pre-stored single-lamp color temperature information, and single-lamp address information. Based on the fault judgment information of each individual lamp distributed in a row, the fault judgment of the row lamp is performed, and the fault judgment information of each row lamp is obtained and uploaded. Based on the fault judgment information of each row of lights in each area and the fault judgment information of individual lights that are not distributed in rows, area light faults are judged, and area light fault judgment information of each area light is obtained and uploaded; the area light fault judgment process includes: Determine whether the fault information of each row of lights in the current area and the fault information of each individual light are normal and consistent. Under the condition that all are normal and consistent, generate and upload the fault judgment information of the corresponding area lights that are in normal working status; In cases where the fault judgment information of each row of lights is not uniform but consistent, determine whether the fault judgment information of each row of lights and the fault judgment information of each individual light are both normal but inconsistent. If the fault judgment information is the most common, generate the corresponding fault judgment information of individual lights and / or rows of lights with abnormal working status and brightness differences, and upload it. If the fault judgment information is not uniform but inconsistent, execute the subsequent fault judgment process of the area lights. Furthermore, the subsequent area light determination process includes: Based on the fault judgment information of each row of lights in the current area and the fault judgment information of each individual light, determine whether there are rows of lights and / or individual lights that are in normal working condition. If present, the local normality determination process is executed to obtain the corresponding area light fault determination information. The local normality determination process includes: determining whether the fault determination information of each row of lights in the current area corresponding to normal working status and / or the fault determination information of each individual light is consistent; if consistent, generating and uploading the area light fault determination information where the brightness of each row of lights and / or individual lights in the corresponding abnormal working status and normal working status is not different; if inconsistent, determining the case where the proportion of the fault determination information of each row of lights in the current area corresponding to normal working status and the fault determination information of each individual light is the largest, and generating the area light fault determination information where the brightness of each row of lights and / or individual lights in the corresponding abnormal working status and normal working status is different. If not, determine whether the fault judgment information of each row of lights and the fault judgment information of each individual light in the current area are all abnormal and consistent. If they are all abnormal and consistent, determine and upload the fault judgment information of the row of lights with abnormal working status. If they are not all abnormal and consistent, determine and upload the fault judgment information of the row of lights with abnormal working status and the fault judgment information of each row of lights and the fault judgment information of each individual light.

2. The street light fault diagnosis method based on single-lamp image processing according to claim 1, characterized in that, The acquired single-lamp image information for each lamp includes: Acquire real-time street light video streams and divide the street light video streams into individual real-time video streams for each street light; Based on a defined random time interval, multiple frames of single-lamp image information for each lamp are randomly sampled from the real-time video stream of each lamp and output.

3. The street light fault diagnosis method based on single-lamp image processing according to claim 2, characterized in that, The process of obtaining the brightness detection results and color detection results corresponding to each frame of single-lamp image information based on the image information of each single lamp includes: The image information of each single light in each frame is input into the feature extraction network to obtain the feature map of each frame of single light image information; Based on the detection box generation network, the ROI region detection box corresponding to the single-lamp image information of each frame is obtained according to the feature map of the single-lamp image information of each frame. Based on the color detection network, color detection is performed on the images within the ROI region detection box corresponding to each frame of single-lamp image information to obtain the color detection results of each frame of single-lamp image information corresponding to each single lamp. Based on a brightness detection network, brightness detection is performed on the images within the ROI region detection box corresponding to each frame of single-lamp image information to obtain the brightness detection results of each frame of single-lamp image information corresponding to each single lamp.

4. The street light fault diagnosis method based on single-lamp image processing according to claim 1, characterized in that, The process of determining single-lamp faults based on the brightness and color detection results corresponding to each frame of single-lamp image information and the pre-stored information of each single lamp, and obtaining and uploading single-lamp fault determination information for each single lamp, includes: Based on the brightness and color detection results corresponding to each frame of single-lamp image information and the pre-stored information of each single lamp, the single-lamp fault judgment process is executed sequentially for each single lamp, and the single-lamp fault judgment information of each single lamp is obtained and uploaded respectively. The single-lamp fault detection process includes: Determine whether the brightness detection results and color detection results corresponding to the single-lamp image information of each frame of the current single lamp are consistent; If there is a discrepancy, generate and upload the corresponding single lamp fault judgment information for abnormal working status, and send feedback information to prompt the next single lamp to execute the single lamp fault judgment process; If they match, the single lamp working status information is determined, and it is determined whether the single lamp working status information is consistent with the pre-stored single lamp working status information in the corresponding single lamp pre-stored information. If they match, a single lamp fault judgment information corresponding to a normal working status is generated and uploaded. If they do not match, a single lamp fault judgment information corresponding to an abnormal working status is generated and uploaded, and feedback information is sent to prompt the next single lamp to execute the single lamp fault judgment process.

5. The street light fault diagnosis method based on single-lamp image processing according to claim 1, characterized in that, The single-lamp fault judgment information includes one or more of the following: single-lamp working status information, single-lamp brightness information, single-lamp color temperature information, and single-lamp address information.

6. The street light fault diagnosis method based on single-lamp image processing according to claim 4, characterized in that, The process of determining row lamp faults based on individual lamp fault judgment information distributed in rows, and obtaining and uploading row lamp fault judgment information for each row of lamps, includes: Based on the individual lamp fault judgment information of each lamp in each row of lights, the row of lights fault judgment process is executed sequentially for each row of lights to obtain and upload the row of lights fault judgment information of each row of lights. The fault detection process for the LED light array includes: Determine whether the fault information of each lamp in the current light panel is normal and consistent; Under the condition that all are normal and consistent, generate and upload the corresponding fault judgment information of the row lights that are in normal working status; In the case of non-uniform normal and consistent, determine whether the individual lamp fault judgment information of each lamp in the current lamp row is normal and inconsistent. If they are all normal and inconsistent, determine the case with the largest proportion of individual lamp fault judgment information and generate the corresponding lamp row fault judgment information with abnormal working status and upload it. In the case of non-uniform normal and inconsistent, execute the subsequent lamp row fault judgment process. Furthermore, the subsequent lamp fault detection process includes: Determine whether there are any lamps that are functioning normally based on the individual lamp fault information of each lamp in the current lamp array; If present, a local normality determination process is executed to obtain the corresponding lamp fault determination information. The local normality determination process includes: determining whether the fault determination information of the single lamps in the current lamp row corresponding to normal working status is consistent; if consistent, generating and uploading lamp row fault determination information where the brightness of the single lamps in the corresponding abnormal status and normal working status is not different; if inconsistent, determining the case where the proportion of single lamp fault determination information of the single lamps in the current lamp row corresponding to normal working status is the largest, generating and uploading lamp row fault determination information where the brightness of the single lamps in the corresponding abnormal status and normal working status is different. If not, determine whether the individual lamp fault judgment information of each lamp is abnormal and consistent. If they are all normal and consistent, determine and upload the corresponding lamp fault judgment information that is not in normal working condition. If they are not all abnormal and consistent, determine and upload the corresponding lamp fault judgment information that is not in normal condition and where the individual lamp fault judgment information of each lamp is abnormal.

7. The street light fault diagnosis method based on single-lamp image processing according to claim 5, characterized in that, The fault diagnosis information for the LED array includes one or more of the following: LED array working status information, LED array brightness information, LED array color temperature information, LED array address information, and faulty single LED address information.

8. The street light fault diagnosis method based on single-lamp image processing according to claim 1, characterized in that, The fault diagnosis information for the area lights includes one or more of the following: area light working status information, area light brightness information, area light color temperature information, row light brightness information, individual light brightness information, area light address information, row light address information, and individual light address information.

9. A street light fault diagnosis system based on single-lamp image processing, characterized in that, The system includes: an information unit, a discrimination unit, and a processing unit; The information unit includes: A single-lamp image frame processing module is used to obtain single-lamp image information for each acquired single lamp; wherein, the single-lamp image information includes: multi-frame single-lamp image information; The single-lamp control information storage module is used to store the pre-stored information of each single lamp and the address information of each single lamp; the pre-stored information of each single lamp includes: pre-stored single lamp working status information, pre-stored single lamp brightness information, pre-stored single lamp color temperature information and single lamp address information. The discrimination unit includes: The image brightness and color detection module is connected to the single-lamp image frame processing module, and obtains the brightness detection result and color detection result corresponding to each frame of single-lamp image information based on the single-lamp image information of each single lamp. The single-lamp fault detection module is connected to the image brightness and color detection module, the single-lamp control information storage module, and the single-lamp image frame processing module. It is used to perform single-lamp fault detection based on the brightness detection results and color detection results corresponding to each frame of single-lamp image information of each single lamp and the pre-stored information of the single lamp, and to obtain and upload the single-lamp fault judgment information of each single lamp. The row light fault detection module is connected to the single light fault detection module. It is used to detect row light faults based on the single light fault detection information of each single light distributed in a row, and to obtain and upload the row light fault detection information of each row light. A zone light fault detection module, connected to the row light fault detection module and the single light fault detection module, is used to perform zone light fault detection based on the row light fault detection information of each row of lights in each zone and the single light fault detection information of scattered single lights not distributed in rows, to obtain and upload the zone light fault detection information of each zone light; the zone light fault detection process includes: Determine whether the fault information of each row of lights in the current area and the fault information of each individual light are normal and consistent. Under the condition that all are normal and consistent, generate and upload the fault judgment information of the corresponding area lights that are in normal working status; In cases where the fault judgment information of each row of lights is not uniform but consistent, determine whether the fault judgment information of each row of lights and the fault judgment information of each individual light are both normal but inconsistent. If the fault judgment information is the most common, generate the corresponding fault judgment information of individual lights and / or rows of lights with abnormal working status and brightness differences, and upload it. If the fault judgment information is not uniform but inconsistent, execute the subsequent fault judgment process of the area lights. Furthermore, the subsequent area light determination process includes: Based on the fault judgment information of each row of lights in the current area and the fault judgment information of each individual light, determine whether there are rows of lights and / or individual lights that are in normal working condition. If present, the local normality determination process is executed to obtain the corresponding area light fault determination information. The local normality determination process includes: determining whether the fault determination information of each row of lights in the current area corresponding to normal working status and / or the fault determination information of each individual light is consistent; if consistent, generating and uploading the area light fault determination information where the brightness of each row of lights and / or individual lights in the corresponding abnormal working status and normal working status is not different; if inconsistent, determining the case where the proportion of the fault determination information of each row of lights in the current area corresponding to normal working status and the fault determination information of each individual light is the largest, and generating the area light fault determination information where the brightness of each row of lights and / or individual lights in the corresponding abnormal working status and normal working status is different. If not, it determines whether the fault judgment information of each row of lights and the fault judgment information of each individual light in the current area are all abnormal and consistent. If they are all abnormal and consistent, it identifies and uploads the fault judgment information of the corresponding row of lights with abnormal working status. If they are not all abnormal and consistent, it identifies and uploads the fault judgment information of the row of lights with abnormal working status and where both the fault judgment information of each row of lights and the fault judgment information of each individual light are abnormal. The processing unit includes: an information uploading module and a central processing module; and wherein, The information upload module is connected to the single lamp fault detection module, the row lamp fault detection module, the area lamp fault detection module, and the central processing module. It is used to upload the single lamp fault detection information of each single lamp, the row lamp fault detection information of each row lamp, and the area lamp fault detection information of each area lamp to the central processing module.

10. A street light fault diagnosis terminal based on single-lamp image processing, characterized in that, include: One or more memories and one or more processors; The one or more memories are used to store computer programs; The one or more processors are connected to the memory and are used to run the computer program to perform the method as described in any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, The device contains a computer program that, when executed by one or more processors, performs the method as described in any one of claims 1 to 8.

Images