Automatic inspection system and method

Abstract

The invention discloses an automatic inspection system and an automatic inspection method, which are used for solving the problem that the accuracy of an inspection result is difficult to ensure in related technologies. The system comprises inspection management equipment, a camera device and power and environment detection equipment, the inspection management equipment comprises an intelligent analysis module; and the intelligent analysis module is respectively connected with the camera device and the power and environment detection equipment. The method comprises the following steps: acquiring a first image of target to-be-tested equipment; determining whether the target to-be-tested equipment is abnormal or not according to the first image; when it is determined that the target to-be-tested equipment is abnormal, collecting first power and environment information corresponding to the abnormal type of the target to-be-tested equipment; the abnormal type comprises at least one of equipment change, equipment operation state and environment where the equipment is located; determining whether the target to-be-tested equipment is abnormal or not according to the first power and environment information; and when it is determined that the target to-be-tested device is abnormal, generating alarm information. According to the technical scheme, the accuracy of inspection results is improved.

Description

Technical Field

[0001] The present application relates to the field of automatic inspection technology, and in particular to an automatic inspection system and method. Background Art

[0002] With the rapid development of mobile communication technology, mobile communication networks have covered every corner of cities, counties, towns and rural areas, which has put forward higher operating requirements for mobile communication base stations. In order to ensure the stability and fluency of residents when using mobile networks, it is necessary to ensure that the working performance of mobile communication base stations is in a stable state. At present, the daily maintenance of mobile communication base stations is generally carried out through manual regular on-site inspections, relying on professionals to use senses, meter reading, records and some related supporting instruments to inspect the base station equipment to find hidden dangers in the operation of base station equipment, so as to deal with and rectify them, so as to ensure the safe and normal operation of base station equipment. However, on the one hand, the manual regular inspection method requires a lot of manpower and material resources, and because the inspection results can only be checked by spot checks, there are problems such as the inability to ensure the authenticity of the on-site inspection, the authenticity of the inspection, the handling of hidden dangers, and the quality of the inspection. On the other hand, there are problems such as high management costs, inability to supervise the work of inspection personnel, low degree of informatization of inspection data, and inability to analyze and process inspection data in a timely manner.

[0003] To this end, in the related technology, inspection tasks are carried out by intelligent devices such as robots and drones, and the base station equipment is photographed by the camera equipment they carry to realize the inspection of the base station equipment. However, with this method, on the one hand, due to the introduction of external intelligent devices, it is necessary to additionally maintain the external intelligent devices during the process of realizing automatic inspection, which increases the inspection cost. On the other hand, due to factors such as the camera shooting angle and image recognition accuracy, misjudgment is prone to occur, and the power and environmental conditions of the base station equipment cannot be remotely verified, so it is difficult to ensure the accuracy of the inspection results. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide an automatic inspection system and method to solve the problem in the related art that it is difficult to ensure the accuracy of the inspection results.

[0005] To solve the above technical problems, the embodiments of the present application are implemented as follows:

[0006] On the one hand, an embodiment of the present application provides an automatic inspection system, the system comprising an inspection management device, a camera device and a power and environment detection device; the inspection management device comprises an intelligent analysis module, and the intelligent analysis module is respectively connected to the camera device and the power and environment detection device; wherein,

[0007] The camera device is used to capture a first image of the target device under test under the control of the intelligent analysis module, and send the first image to the intelligent analysis module;

[0008] The intelligent analysis module is used to determine whether the target device to be tested has an abnormality based on the first image; if it is determined that the target device to be tested has an abnormality, determine the abnormality type of the target device to be tested; the abnormality type includes at least one of device change, device operating status, and the environment in which the device is located; control the power and environment detection equipment to collect first power and environment information corresponding to the abnormality type;

[0009] The power and environment detection device is used to collect the first power and environment information corresponding to the target device under test under the control of the intelligent analysis module, and send the first power and environment information to the intelligent analysis module;

[0010] The intelligent analysis module is further used to determine whether the target device to be tested has an abnormality based on the first power and environmental information; and generate alarm information when it is determined that the target device to be tested has an abnormality.

[0011] On the other hand, an embodiment of the present application provides an automatic inspection method, which is applied to the above-mentioned automatic inspection system; the method includes:

[0012] Acquire a first image of the target device under test;

[0013] Determining whether an abnormality occurs in the target device under test according to the first image;

[0014] When it is determined that the target device to be tested has an abnormality, first power and environment information corresponding to the abnormality type of the target device to be tested is collected; the abnormality type includes at least one of a device change, a device operating state, and an environment in which the device is located;

[0015] Determining whether the target device under test has an abnormality according to the first power and environment information;

[0016] When it is determined that the target device under test has an abnormality, an alarm message is generated.

[0017] On the other hand, an embodiment of the present application provides an electronic device, including a processor; and a memory arranged to store computer-executable instructions, wherein the computer-executable instructions are configured to be executed by the processor, and the computer-executable instructions are executed by the processor to implement the above-mentioned automatic inspection method.

[0018] On the other hand, an embodiment of the present application provides a storage medium for storing computer-executable instructions, which implement the above-mentioned automatic inspection method when executed by a processor.

[0019] The automatic inspection system of the embodiment of the present application is adopted, by setting a camera device, a power and environment detection device and an inspection management device including an intelligent analysis module, and connecting the intelligent analysis module to the camera device and the power and environment detection device respectively, the automatic inspection can be completed by relying on the interaction between the devices inside the system, without relying on external intelligent devices (such as robots, drones, etc.) for shooting or monitoring, so there is no need to maintain the external intelligent devices for automatic inspection, saving the inspection cost. Among them, the camera device can capture a first image of the target device under the control of the intelligent analysis module, and send the first image to the intelligent analysis module, so that the intelligent analysis module can determine whether the target device is abnormal according to the first image, and determine the abnormal type of the target device (including at least one of the device change, the device operation state, and the environment in which the device is located) when determining that the target device is abnormal, and then control the power and environment detection device to collect the first power and environment information corresponding to the abnormal type, and determine whether the target device is abnormal according to the first power and environment information, and finally generate an alarm message when determining that the target device is abnormal. It can be seen that in the process of automatic inspection, the technical solution can first preliminarily determine whether the device under test has an abnormality based on the image of the device under test collected. In this way, for the device under test that has not had an abnormality, the automatic inspection process can be directly terminated, which is conducive to saving the computing resources of the system. For the device under test that has an abnormality, it can further obtain the corresponding power and environmental information based on the abnormal type of the abnormality that has occurred, so as to verify whether the device under test has an abnormality according to the real-time power state and environmental state of the device under test. Compared with the solution of shooting or monitoring by external intelligent devices to complete automatic inspection, the technical solution can effectively avoid the situation where the abnormality judgment of the device under test is inaccurate due to incomplete collected images or inaccurate image recognition, and improve the accuracy of the inspection results of the device under test. In addition, there is no need to collect all the power and environmental information of the device under test, which reduces the amount of data exchanged between devices, which is conducive to the system to quickly verify whether the device under test has an abnormality and improve the inspection efficiency. Finally, after double inspection, if it is found that the device under test does have an abnormality, an alarm message will be generated, which is conducive to reducing the probability of misjudgment and improving the accuracy of the inspection results.

[0020] The technical solution of the embodiment of the present application is adopted, by collecting the first image of the target device to be tested, and determining whether the target device to be tested has an abnormality based on the first image, so that when it is determined that the target device to be tested has an abnormality, the first power and environmental information corresponding to the abnormality type of the target device to be tested (including at least one of the device change, device operating status, and the environment in which the device is located) is collected, and then based on the first power and environmental information, it is determined whether the target device to be tested has an abnormality, and when it is determined that the target device to be tested has an abnormality, an alarm message is generated. It can be seen that during the automatic inspection process, this technical solution can first preliminarily determine whether the device to be tested has an abnormality based on the collected image of the device to be tested. In this way, for the device to be tested that has not an abnormality, the automatic inspection process can be directly ended, which is conducive to saving computing resources. For the equipment under test that has an abnormality, the corresponding power and environmental information can be further obtained in a targeted manner based on the abnormality type of the abnormality, so as to verify whether the equipment under test has an abnormality according to the real-time power status and environmental status of the equipment under test. Compared with the solution of shooting or monitoring by external intelligent devices to complete automatic inspections, this technical solution can effectively avoid the situation where the abnormality judgment of the equipment under test is inaccurate due to incomplete collected images or inaccurate image recognition, and improve the accuracy of the inspection results of the equipment under test. In addition, there is no need to collect all the power and environmental information of the equipment under test, which reduces the amount of data exchanged between devices, is conducive to quickly verifying whether the equipment under test has an abnormality and improves the inspection efficiency. Finally, after double inspection, if it is found that the equipment under test does have an abnormality, an alarm message will be generated, which is conducive to reducing the probability of misjudgment and improving the accuracy of the inspection results. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0022] Figure 1 is a schematic block diagram of an automatic inspection system according to an embodiment of the present application;

[0023] Figure 2 is a schematic block diagram of an automatic inspection system according to another embodiment of the present application;

[0024] Figure 3 is a schematic flow chart of an automatic inspection method according to an embodiment of the present application;

[0025] Figure 4is a schematic flow chart of an automatic inspection method according to another embodiment of the present application;

[0026] Figure 5 It is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] The embodiments of the present application provide an automatic inspection system and method to solve the problem in the related art that it is difficult to ensure the accuracy of the inspection results.

[0028] In order to enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0029] Figure 1 is a schematic block diagram of an automatic inspection system according to an embodiment of the present application, such as Figure 1 As shown, the system includes a patrol management device 10, a camera device 20 and a power and environment detection device 30. The patrol management device 10 includes an intelligent analysis module 110, which is connected to the camera device 20 and the power and environment detection device 30 respectively.

[0030] In practical applications, the automatic inspection system can automatically inspect multiple devices under test at the same time. Accordingly, the number of camera devices can be one or more, and each camera device can have one or more shooting points. One camera device can be used to shoot one device under test at different shooting points, or it can be used to shoot different devices under test at different shooting points. Figure 1 The connection relationship of a camera device in the automatic inspection system is only schematically shown.

[0031] In this embodiment, the camera device is used to capture a first image of the target device under the control of the intelligent analysis module, and send the first image to the intelligent analysis module. The intelligent analysis module is used to determine whether the target device under test is abnormal based on the first image, and then determine the abnormal type of the target device under test when it is determined that the target device under test is abnormal, and then control the power and environment detection device to collect the first power and environment information corresponding to the abnormal type.

[0032] Optionally, the intelligent analysis module may use an image AI (Artificial Intelligence) algorithm to perform image AI recognition on the first image to determine whether an abnormality occurs in the target device under test, and when it is determined that an abnormality occurs in the target device under test, determine the abnormality type of the target device under test.

[0033] The abnormal type may include one or more of equipment changes, equipment operating status, and the environment in which the equipment is located. The environment in which the equipment is located may include fireworks, accumulated water, human activities, etc. Optionally, the intelligent analysis module may determine the first power and environment information corresponding to the abnormal type based on the third corresponding relationship between the abnormal type and the power and environment information, thereby controlling the power and environment detection device to collect the first power and environment information corresponding to the abnormal type.

[0034] In this embodiment, the power and environment detection device is used to collect the first power and environment information corresponding to the target device under test under the control of the intelligent analysis module, and send the first power and environment information to the intelligent analysis module. The intelligent analysis module can be used to determine whether the target device under test has an abnormality based on the first power and environment information, and generate an alarm message when it is determined that the target device under test has an abnormality.

[0035] Optionally, the imaging device may be a camera, and the power and environment detection equipment may include various types of equipment sensors.

[0036] The automatic inspection system of the embodiment of the present application is adopted, by setting a camera device, a power and environment detection device and an inspection management device including an intelligent analysis module, and connecting the intelligent analysis module to the camera device and the power and environment detection device respectively, the automatic inspection can be completed by relying on the interaction between the devices inside the system, without relying on external intelligent devices (such as robots, drones, etc.) for shooting or monitoring, so there is no need to maintain the external intelligent devices for automatic inspection, saving the inspection cost. Among them, the camera device can capture a first image of the target device under the control of the intelligent analysis module, and send the first image to the intelligent analysis module, so that the intelligent analysis module can determine whether the target device is abnormal according to the first image, and determine the abnormal type of the target device (including at least one of the device change, the device operation state, and the environment in which the device is located) when determining that the target device is abnormal, and then control the power and environment detection device to collect the first power and environment information corresponding to the abnormal type, and determine whether the target device is abnormal according to the first power and environment information, and finally generate an alarm message when determining that the target device is abnormal. It can be seen that in the process of automatic inspection, the technical solution can first preliminarily determine whether the device under test has an abnormality based on the image of the device under test collected. In this way, for the device under test that has not had an abnormality, the automatic inspection process can be directly terminated, which is conducive to saving the computing resources of the system. For the device under test that has an abnormality, it can further obtain the corresponding power and environmental information based on the abnormal type of the abnormality that has occurred, so as to verify whether the device under test has an abnormality according to the real-time power state and environmental state of the device under test. Compared with the solution of shooting or monitoring by external intelligent devices to complete automatic inspection, the technical solution can effectively avoid the situation where the abnormality judgment of the device under test is inaccurate due to incomplete collected images or inaccurate image recognition, and improve the accuracy of the inspection results of the device under test. In addition, there is no need to collect all the power and environmental information of the device under test, which reduces the amount of data exchanged between devices, which is conducive to the system to quickly verify whether the device under test has an abnormality and improve the inspection efficiency. Finally, after double inspection, if it is found that the device under test does have an abnormality, an alarm message will be generated, which is conducive to reducing the probability of misjudgment and improving the accuracy of the inspection results.

[0037] In one embodiment, the automatic inspection system may include an inspection platform. The inspection platform may be deployed on the network side or the terminal side. The inspection platform is used to provide the function of configuring the automatic inspection system and to provide the function of remotely monitoring the automatic inspection process. Figure 2 As shown, in addition to the intelligent analysis module 110, the inspection management device 10 may also include a wireless communication module 120. It should be noted that, Figure 2 is Figure 1The schematic block diagram of the automatic inspection system obtained by refining the inspection management device 10 based on Figure 2 Zhongyu Figure 1 For the functions and connections of components with the same reference numbers, please refer to Figure 1 , I will not go into details here.

[0038] In this embodiment, the inspection platform is used to send the inspection task to the intelligent analysis module through the wireless communication module. The inspection task may include the target device to be tested and the inspection cycle of the target device to be tested. The intelligent analysis module may be used to determine the target shooting point corresponding to the target device to be tested according to the first mapping relationship between the device to be tested and the shooting point, so as to control the camera device to shoot at the target shooting point according to the inspection cycle.

[0039] In this embodiment, the inspection task can be remotely configured by the technician on the inspection platform, and then sent to the intelligent analysis module through the wireless communication module, which is conducive to the flexible update of the inspection task. Optionally, the configuration of the inspection task can include the mapping configuration between the equipment to be tested and the shooting point of the camera device, the setting of the camera guard point, the mapping configuration between the image AI algorithm and the shooting point of the camera device, the configuration of the inspection cycle, the configuration of the inspection task effectiveness conditions (such as the inspection task effectiveness time), etc.

[0040] Among them, the mapping configuration between the device to be tested and the shooting point of the camera device is intended to establish a connection between the shooting point of the camera device and the device to be tested, so as to facilitate the rapid positioning of the device to be tested. The setting of the guard point of the camera device is intended to determine the default shooting point of the camera device, and ensure that the camera device returns to the key framing position to shoot related equipment and facilities after use. The mapping configuration between the image AI algorithm and the shooting point of the camera device is intended to determine the image AI algorithm that needs to be executed at the shooting point of the camera device, so as to improve the efficiency and accuracy of AI operations and quickly identify abnormalities in the captured images.

[0041] In one embodiment, the intelligent analysis module can be used to send the alarm information to the inspection platform through the wireless communication module. The inspection platform can be used to dispatch processing tasks for the target device under test according to the alarm information.

[0042] In this embodiment, alarm information is reported to the inspection platform by wireless communication, so that the inspection platform can issue a processing work order, thereby realizing a closed loop of automatic inspection, which is conducive to timely processing of abnormal equipment under test.

[0043] In one embodiment, after receiving the first image sent by the camera device, the intelligent analysis module can be used to determine the target guard point corresponding to the camera device according to the second mapping relationship between the camera device and the guard point, thereby controlling the camera device to move to the target guard point.

[0044] The target guard point may be a key shooting point corresponding to the device to be tested, or may be a shooting point corresponding to a key device that needs to be inspected. In this embodiment, the camera device is controlled to move to the target guard point after completing one image capture and upload based on the inspection task, so that the camera device can continuously shoot the corresponding device at the target guard point, thereby uploading the captured images to the intelligent analysis module, so as to continuously analyze and process the captured images and continuously detect whether the corresponding device has an abnormality.

[0045] In one embodiment, Figure 2 As shown, the power and environment detection device 30 may include a power detection module 310 and an environment detection module 320. The power detection module 310 and the environment detection module 320 are connected to the intelligent analysis module 110 respectively.

[0046] The power detection module is used to collect at least one of the following information: the device communication connection status information, the device load, the device fault signal quantity, and the device power supply status information of the target device under test. The environment detection module is used to collect at least one of the following information: the temperature, humidity, infrared information, smoke volume, and water level of the environment in which the target device under test is located.

[0047] Optionally, the intelligent analysis module can be used to control the power detection module to collect equipment communication connection status information and equipment load when the abnormality type is equipment change; to control the power detection module to collect equipment fault signal quantity and equipment power supply status information when the abnormality type is equipment operation status; to control the environment detection module to collect at least one of temperature, humidity, infrared information, smoke volume and water level information when the abnormality type is the environment in which the equipment is located, and to control the power detection module to collect at least one of equipment communication connection status information, equipment load, equipment fault signal quantity and equipment power supply status information.

[0048] Optionally, the power and environment detection equipment can be connected to the intelligent analysis module through an interface, and the interface types may include RJ (Registered Jack) 45, RS (Recommended Standard) 485, DI (Digital Input) / DO (Digital Output), USB (Universal Serial Bus), etc. The above interface can be adapted to intelligent devices such as cameras, power supplies, air conditioners, access control, temperature and humidity sensors, smoke sensors, infrared sensors, door magnets, etc., and can be connected to proximal debugging equipment. Proximal debugging equipment is a device deployed on the automatic inspection system side for debugging the automatic inspection system.

[0049] In addition, the automatic inspection system may include a power supply, which can provide power to components such as the intelligent analysis module and the wireless communication module. The wireless communication module can realize the baseband processing and radio frequency transceiver functions of the signal, and complete the data interaction between the terminal side and the platform side. The wireless communication module can adapt to the SIM card by connecting to the SIM (Subscriber Identity Module) card interface, and can complete the transceiver function of the radio frequency signal by connecting to the antenna module.

[0050] Figure 1 and Figure 2 The automatic inspection system shown can be widely used in remote intelligent inspection of equipment and facilities (such as equipment inside the computer room, towers, etc.) of unmanned base stations. An automatic inspection system is constructed by placing cameras, power detection modules, environmental detection modules, and inspection management equipment inside and outside the computer room. The camera monitors the indoor and outdoor conditions of the computer room in real time. The power detection module and the environmental detection module detect the operation and environmental conditions of the base station equipment. The inspection management equipment runs the inspection tasks, and uses the image AI algorithm to comprehensively analyze the operation of the base station, and transmits the inspection results back to the inspection platform through the wireless communication module. The original mode of periodic on-site inspection of all sites has been changed. The combination of remote inspection and on-site fault handling has been adopted. The inspection has changed from "normal planning" to "precise dispatching", realizing the transformation of resource allocation from fixed and standardized to on-demand and refined. In addition, the inspection process data and inspection results can be visualized throughout the process and can be left for reference, which effectively increases the inspection frequency. It is not limited to the inspection cycle of the station or the alarm of the base station fault to discover, handle and archive the hidden dangers of the base station. It has achieved early detection, early treatment and early closure of base station hidden dangers. At the same time, it has fully released manpower, improved production efficiency and benefits, promoted the digital transformation of the mobile communication base station operation and maintenance system, and promoted the dual improvement of the maintenance service capacity and quality of mobile communication base stations.

[0051] The above is an automatic inspection system provided in an embodiment of the present application. Based on the same idea, an automatic inspection method is also provided in an embodiment of the present application.

[0052] Figure 3 is a schematic flow chart of an automatic inspection method according to an embodiment of the present application. In this embodiment, the automatic inspection method is applied to Figure 1 and Figure 2 The automatic inspection system shown in Figure 1 is as follows. Figure 3 As shown, the method includes:

[0053] S302: Acquire a first image of the target device to be tested.

[0054] S304: Determine whether an abnormality occurs in the target device under test according to the first image.

[0055] In one embodiment, when it is determined that no abnormality occurs in the target device under test, the current automatic inspection process may be terminated.

[0056] S306: When it is determined that the target device under test has an abnormality, first power and environment information corresponding to the abnormality type of the target device under test is collected.

[0057] Among them, the abnormal type may include one or more of equipment change, equipment operation status, and equipment environment. The power and environment information may include at least one of equipment communication connection status information, equipment load, equipment fault signal, equipment power supply status information, and the temperature, humidity, infrared information, smoke volume, and water level information of the equipment environment. Optionally, the first power and environment information corresponding to the abnormal type can be determined according to the third corresponding relationship between the abnormal type and the power and environment information. Exemplarily, in the case where the abnormal type is equipment change, the first power and environment information may include equipment communication connection status information and equipment load; in the case where the abnormal type is equipment operation status, the first power and environment information may include equipment fault signal and equipment power supply status information; in the case where the abnormal type is the equipment environment, the first power and environment information may include at least one of temperature, humidity, infrared information, smoke volume, water level information, equipment communication connection status information, equipment load, equipment fault signal, and equipment power supply status information.

[0058] S308: Determine whether the target device under test has an abnormality according to the first power and environment information.

[0059] S310: When it is determined that the target device under test has an abnormality, an alarm message is generated.

[0060] In one embodiment, a processing task for the target device under test may be dispatched according to the alarm information to complete the closed loop of automatic inspection, so that the fault of the target device under test can be processed in time.

[0061] The technical solution of the embodiment of the present application is adopted, by collecting the first image of the target device to be tested, and determining whether the target device to be tested has an abnormality based on the first image, so that when it is determined that the target device to be tested has an abnormality, the first power and environmental information corresponding to the abnormality type of the target device to be tested (including at least one of the device change, device operating status, and the environment in which the device is located) is collected, and then based on the first power and environmental information, it is determined whether the target device to be tested has an abnormality, and when it is determined that the target device to be tested has an abnormality, an alarm message is generated. It can be seen that during the automatic inspection process, this technical solution can first preliminarily determine whether the device to be tested has an abnormality based on the collected image of the device to be tested. In this way, for the device to be tested that has not an abnormality, the automatic inspection process can be directly ended, which is conducive to saving computing resources. For the equipment under test that has an abnormality, the corresponding power and environmental information can be further obtained in a targeted manner based on the abnormality type of the abnormality, so as to verify whether the equipment under test has an abnormality according to the real-time power status and environmental status of the equipment under test. Compared with the solution of shooting or monitoring by external intelligent devices to complete automatic inspections, this technical solution can effectively avoid the situation where the abnormality judgment of the equipment under test is inaccurate due to incomplete collected images or inaccurate image recognition, and improve the accuracy of the inspection results of the equipment under test. In addition, there is no need to collect all the power and environmental information of the equipment under test, which reduces the amount of data exchanged between devices, is conducive to quickly verifying whether the equipment under test has an abnormality and improves the inspection efficiency. Finally, after double inspection, if it is found that the equipment under test does have an abnormality, an alarm message will be generated, which is conducive to reducing the probability of misjudgment and improving the accuracy of the inspection results.

[0062] In one embodiment, acquiring the first image of the target device under test (ie, S302) may be performed as follows: Steps A1 to A3:

[0063] Step A1: Get the inspection task.

[0064] The inspection task may include a target device to be tested and an inspection cycle of the target device to be tested.

[0065] Step A2: determining a target shooting point corresponding to the target device under test according to a first mapping relationship between the device under test and the shooting point.

[0066] The first mapping relationship between the device to be tested and the shooting points may be pre-configured in the automatic inspection system.

[0067] Step A3: collecting a first image of the target device to be tested at a target shooting point according to the inspection cycle.

[0068] In this embodiment, based on the pre-configured first mapping relationship, the shooting point corresponding to the target device to be inspected as indicated by the inspection task can be quickly and accurately determined, so that the image of the target device to be tested is captured at the shooting point according to the inspection cycle, which not only improves the efficiency of automatic inspection, but also provides more accurate data for analyzing equipment abnormalities, which is conducive to improving the accuracy of the inspection results.

[0069] In one embodiment, determining whether an abnormality occurs in the target device under test (ie, S304) according to the first image may be performed as follows: Steps B1 to B3:

[0070] Step B1, determining a target image recognition algorithm corresponding to a target shooting point according to a first corresponding relationship between the shooting point and the image recognition algorithm.

[0071] The image recognition algorithm may be the image AI algorithm described in the above embodiment. The image recognition algorithm may include a device recognition algorithm, a device change recognition algorithm, a device operation status recognition algorithm, a smoke and fire recognition algorithm, a water accumulation recognition algorithm, a combustible material recognition algorithm, a human figure recognition algorithm, a behavior recognition algorithm, etc.

[0072] Step B2: Perform image recognition on the first image using a target image recognition algorithm to obtain an image recognition result.

[0073] Among them, image recognition includes at least one of equipment change recognition, equipment operation status recognition, and equipment environment recognition.

[0074] Step B3: Determine whether an abnormality occurs in the target device under test according to the image recognition result.

[0075] In this embodiment, by configuring a corresponding image recognition algorithm for each shooting point, image recognition is made more detailed and targeted, which is beneficial to improving the accuracy of the recognition result, thereby helping to improve the accuracy of the inspection result.

[0076] In one embodiment, determining whether the target device under test has an abnormality (ie, S308) based on the first power and environment information may be performed as follows: Steps C1 to C4:

[0077] Step C1, determining a first data verification rule corresponding to the first power and environment information according to a second corresponding relationship between the power and environment information and the data verification rule.

[0078] Among them, the data verification rules provide the data range for the corresponding power and environmental information, as well as under what circumstances the verification is passed and under what circumstances the verification is failed. For example, in the case where the power and environmental information is temperature, the temperature range can be agreed upon in the data verification rules, and it can be agreed that if the collected temperature is not within the temperature range, the verification result is a verification failure; if the collected temperature is within the temperature range, the verification result is a verification pass. In actual applications, corresponding data verification rules can be configured for power and environmental information, and this embodiment of the application does not limit this.

[0079] Optionally, the data verification rule may adopt a verification algorithm. The verification algorithm may include a device communication connection status verification algorithm, a device load verification algorithm, a device fault signal verification algorithm, a device power supply status verification algorithm, a device environment temperature verification algorithm, a humidity verification algorithm, an infrared verification algorithm, a smoke verification algorithm, a water level verification algorithm, etc.

[0080] Step C2, using the first data verification rule to verify the first power and environment information to obtain a verification result.

[0081] Step C3: when the verification result is verification failure, it is determined that the target device under test has an abnormality.

[0082] Step C4: when the verification result is that the verification is passed, it is determined that there is no abnormality in the target device under test.

[0083] Among them, if there is no abnormality in the target device under test, it means that there is an error in the image-based recognition result. At this time, the image recognition result can be recorded as a sample for optimizing the image AI algorithm.

[0084] Optionally, if the results of the two tests are inconsistent, that is, based on the first image, it is identified that an abnormality has occurred in the target device to be tested, but by verifying the power and environmental information of the target device to be tested, it is found that there is no abnormality in the target device to be tested, then the relevant data and the inconsistency of this result can be uploaded to the inspection platform through the wireless communication module for manual remote review. The technician can manually identify the image remotely or call the camera device to shoot again for analysis and judgment. If the result of the manual remote review is that there is an abnormality in the target device to be tested, an alarm message is generated; if the result of the manual remote review is that there is no abnormality in the target device to be tested, the image recognition result this time can be recorded as a sample for optimizing the image AI algorithm.

[0085] In this embodiment, corresponding data verification rules are used to verify different power and environmental information, so that the verification is more targeted and the accuracy of the verification result can be improved, which is conducive to improving the accuracy of the inspection result.

[0086] Figure 4 is a schematic flow chart of an automatic inspection method according to another embodiment of the present application. In this embodiment, the automatic inspection method is applied to Figure 1 and Figure 2 The automatic inspection system shown in Figure 1 is as follows. Figure 4 As shown, the method includes:

[0087] S401 , according to an inspection cycle, capturing a first image of the target device under test at a target shooting point corresponding to the target device under test.

[0088] S402: Determine a target image recognition algorithm corresponding to the target shooting point according to a first corresponding relationship between the shooting point and the image recognition algorithm.

[0089] S403: Perform image recognition on the first image using a target image recognition algorithm to obtain an image recognition result.

[0090] Among them, image recognition includes at least one of equipment change recognition, equipment operation status recognition, and equipment environment recognition.

[0091] S404, determining whether an abnormality occurs in the target device under test according to the image recognition result; if so, executing S405; if not, executing S411.

[0092] S405: Collect first power and environment information corresponding to the abnormal type of the target device under test.

[0093] The abnormality type includes at least one of equipment change, equipment operation status, and equipment environment.

[0094] S406: Determine a first data verification rule corresponding to the first power and environment information according to a second corresponding relationship between the power and environment information and the data verification rule.

[0095] S407, using the first data verification rule to verify the first power and environment information to obtain a verification result; if the verification result is verification failure, execute S408; if the verification result is verification success, execute S410.

[0096] S408: Determine whether the target device under test has an abnormality.

[0097] S409: Generate warning information.

[0098] S410, determining that there is no abnormality in the target device under test.

[0099] S411, end the current automatic inspection.

[0100] The specific implementation of the above S401-S411 has been described in detail in the above embodiments and will not be repeated here.

[0101] The technical solution of the embodiment of the present application is adopted, by collecting the first image of the target device to be tested, and determining whether the target device to be tested has an abnormality based on the first image, so that when it is determined that the target device to be tested has an abnormality, the first power and environmental information corresponding to the abnormality type of the target device to be tested (including at least one of the device change, device operating status, and the environment in which the device is located) is collected, and then based on the first power and environmental information, it is determined whether the target device to be tested has an abnormality, and when it is determined that the target device to be tested has an abnormality, an alarm message is generated. It can be seen that during the automatic inspection process, this technical solution can first preliminarily determine whether the device to be tested has an abnormality based on the collected image of the device to be tested. In this way, for the device to be tested that has not an abnormality, the automatic inspection process can be directly ended, which is conducive to saving computing resources. For the equipment under test that has an abnormality, the corresponding power and environmental information can be further obtained in a targeted manner based on the abnormality type of the abnormality, so as to verify whether the equipment under test has an abnormality according to the real-time power status and environmental status of the equipment under test. Compared with the solution of shooting or monitoring by external intelligent devices to complete automatic inspections, this technical solution can effectively avoid the situation where the abnormality judgment of the equipment under test is inaccurate due to incomplete collected images or inaccurate image recognition, and improve the accuracy of the inspection results of the equipment under test. In addition, there is no need to collect all the power and environmental information of the equipment under test, which reduces the amount of data exchanged between devices, is conducive to quickly verifying whether the equipment under test has an abnormality and improves the inspection efficiency. Finally, after double inspection, if it is found that the equipment under test does have an abnormality, an alarm message will be generated, which is conducive to reducing the probability of misjudgment and improving the accuracy of the inspection results.

[0102] In summary, specific embodiments of the present subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recorded in the claims can be performed in a different order and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing can be advantageous.

[0103] Based on the same idea, the embodiment of the present application also provides an electronic device, such as Figure 5As shown. The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors 501 and memory 502, and one or more applications or data may be stored in the memory 502. Among them, the memory 502 may be a temporary storage or a permanent storage. The application stored in the memory 502 may include one or more modules (not shown in the figure), and each module may include a series of computer executable instructions in the electronic device. Furthermore, the processor 501 can be configured to communicate with the memory 502 to execute a series of computer executable instructions in the memory 502 on the electronic device. The electronic device may also include one or more power supplies 503, one or more wired or wireless network interfaces 504, one or more input and output interfaces 505, and one or more keyboards 506.

[0104] Specifically in this embodiment, the electronic device includes a memory and one or more applications, wherein the one or more applications are stored in the memory, and the one or more applications may include one or more modules, and each module may include a series of computer executable instructions for the electronic device, and the one or more applications are configured to be executed by one or more processors, including computer executable instructions for performing the following:

[0105] Acquire a first image of the target device under test;

[0106] Determine whether an abnormality occurs in the target device under test according to the first image;

[0107] When it is determined that the target device to be tested has an abnormality, first power and environment information corresponding to the abnormality type of the target device to be tested is collected; the abnormality type includes at least one of a device change, a device operating state, and an environment in which the device is located;

[0108] Determine whether the target device under test has an abnormality according to the first power and environment information;

[0109] When it is determined that the target device under test has an abnormality, an alarm message is generated.

[0110] Optionally, when the computer executable instructions are executed, the processor may also:

[0111] Obtain inspection tasks; the inspection tasks include the target device to be tested and the inspection cycle of the target device to be tested;

[0112] Determine a target shooting point corresponding to the target device under test according to a first mapping relationship between the device under test and the shooting point;

[0113] According to the inspection cycle, a first image of the target device to be tested is collected at a target shooting point.

[0114] Optionally, when the computer executable instructions are executed, the processor may also:

[0115] Determine the target image recognition algorithm corresponding to the target shooting point according to the first corresponding relationship between the shooting point and the image recognition algorithm;

[0116] Performing image recognition on the first image using a target image recognition algorithm to obtain an image recognition result; wherein the image recognition includes at least one of equipment change recognition, equipment operation status recognition, and equipment environment recognition;

[0117] Based on the image recognition results, determine whether the target device under test has an abnormality.

[0118] Optionally, when the computer executable instructions are executed, the processor may also:

[0119] Determining a first data verification rule corresponding to the first power and environment information according to a second corresponding relationship between the power and environment information and the data verification rule;

[0120] Using the first data verification rule to verify the first power and environment information, and obtain a verification result;

[0121] When the verification result is that the verification fails, it is determined that the target device under test has an abnormality;

[0122] When the verification result is that the verification is passed, it is determined that there is no abnormality in the target device under test.

[0123] The technical solution of the embodiment of the present application is adopted, by collecting the first image of the target device to be tested, and determining whether the target device to be tested has an abnormality based on the first image, so that when it is determined that the target device to be tested has an abnormality, the first power and environmental information corresponding to the abnormality type of the target device to be tested (including at least one of the device change, device operating status, and the environment in which the device is located) is collected, and then based on the first power and environmental information, it is determined whether the target device to be tested has an abnormality, and when it is determined that the target device to be tested has an abnormality, an alarm message is generated. It can be seen that during the automatic inspection process, this technical solution can first preliminarily determine whether the device to be tested has an abnormality based on the collected image of the device to be tested. In this way, for the device to be tested that has not an abnormality, the automatic inspection process can be directly ended, which is conducive to saving computing resources. For the equipment under test that has an abnormality, the corresponding power and environmental information can be further obtained in a targeted manner based on the abnormality type of the abnormality, so as to verify whether the equipment under test has an abnormality according to the real-time power status and environmental status of the equipment under test. Compared with the solution of shooting or monitoring by external intelligent devices to complete automatic inspections, this technical solution can effectively avoid the situation where the abnormality judgment of the equipment under test is inaccurate due to incomplete collected images or inaccurate image recognition, and improve the accuracy of the inspection results of the equipment under test. In addition, there is no need to collect all the power and environmental information of the equipment under test, which reduces the amount of data exchanged between devices, is conducive to quickly verifying whether the equipment under test has an abnormality and improves the inspection efficiency. Finally, after double inspection, if it is found that the equipment under test does have an abnormality, an alarm message will be generated, which is conducive to reducing the probability of misjudgment and improving the accuracy of the inspection results.

[0124] An embodiment of the present application also proposes a storage medium, which stores one or more computer programs, and the one or more computer programs include computer executable instructions. When the computer executable instructions are executed by an electronic device including multiple application programs, the electronic device can perform the various processes of the above-mentioned automatic inspection method embodiment and achieve the same technical effect. To avoid repetition, they are not repeated here.

[0125] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0126] For the convenience of description, the above device is described in terms of functions and is described separately in various units. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0127] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0128] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0129] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0130] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0131] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0132] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0133] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0134] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0135] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0136] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0137] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. An automatic inspection system, characterized in that: The system includes inspection management equipment, a camera device and power and environment detection equipment; the inspection management equipment includes an intelligent analysis module, and the intelligent analysis module is connected to the camera device and the power and environment detection equipment respectively; wherein, The camera device is used to capture a first image of the target device under test under the control of the intelligent analysis module, and send the first image to the intelligent analysis module; The intelligent analysis module is used to determine whether the target device to be tested has an abnormality based on the first image; if it is determined that the target device to be tested has an abnormality, determine the abnormality type of the target device to be tested; the abnormality type includes at least one of device change, device operating status, and the environment in which the device is located; control the power and environment detection device to collect first power and environment information corresponding to the abnormality type; The power and environment detection device is used to collect the first power and environment information corresponding to the target device under test under the control of the intelligent analysis module, and send the first power and environment information to the intelligent analysis module; The intelligent analysis module is further used to determine whether the target device to be tested has an abnormality based on the first power and environmental information; and generate alarm information when it is determined that the target device to be tested has an abnormality.

2. The system according to claim 1, characterized in that The system also includes an inspection platform; the inspection management device also includes a wireless communication module; The inspection platform is used to send an inspection task to the intelligent analysis module through the wireless communication module; the inspection task includes the target device to be tested and the inspection cycle of the target device to be tested; The intelligent analysis module is further used to determine the target shooting point corresponding to the target device under test according to the first mapping relationship between the device under test and the shooting point; and control the camera device to shoot at the target shooting point according to the inspection cycle.

3. The system according to claim 2, characterized in that The intelligent analysis module is further used to send the alarm information to the inspection platform through the wireless communication module; The inspection platform is further used to dispatch a processing task for the target device under test according to the alarm information.

4. The system according to claim 2, characterized in that The intelligent analysis module is also used to determine the target guard point corresponding to the camera device according to the second mapping relationship between the camera device and the guard point after receiving the first image sent by the camera device; and control the camera device to move to the target guard point.

5. The system according to claim 1, characterized in that The power and environment detection equipment includes a power detection module and an environment detection module; the power detection module and the environment detection module are respectively connected to the intelligent analysis module; The power detection module is used to collect at least one of the device communication connection status information, device load, device fault signal quantity, and device power supply status information of the target device to be tested; The environment detection module is used to collect at least one of the temperature, humidity, infrared information, smoke volume, and water level information of the environment in which the target device to be tested is located.

6. An automatic inspection method, characterized in that: Applicable to the automatic inspection system according to any one of claims 1 to 5; the method comprises: Acquire a first image of the target device under test; Determining whether an abnormality occurs in the target device under test according to the first image; When it is determined that the target device to be tested has an abnormality, first power and environment information corresponding to the abnormality type of the target device to be tested is collected; the abnormality type includes at least one of a device change, a device operating state, and an environment in which the device is located; Determining whether the target device under test has an abnormality according to the first power and environment information; When it is determined that the target device under test has an abnormality, an alarm message is generated.

7. The method according to claim 6, characterized in that The step of acquiring a first image of the target device under test includes: Obtaining an inspection task; the inspection task includes the target device to be tested and the inspection cycle of the target device to be tested; Determine the target shooting point corresponding to the target device under test according to the first mapping relationship between the device under test and the shooting point; According to the inspection cycle, the first image of the target device to be tested is collected at the target shooting point.

8. The method according to claim 7, characterized in that The step of determining whether an abnormality occurs in the target device under test according to the first image includes: Determining a target image recognition algorithm corresponding to the target shooting point according to a first corresponding relationship between the shooting point and the image recognition algorithm; Performing image recognition on the first image using the target image recognition algorithm to obtain an image recognition result; wherein the image recognition includes at least one of equipment change recognition, equipment operation status recognition, and equipment environment recognition; According to the image recognition result, it is determined whether an abnormality occurs in the target device under test.

9. The method according to claim 6, characterized in that The determining, according to the first power and environment information, whether the target device under test has an abnormality includes: Determining a first data verification rule corresponding to the first power and environment information according to a second corresponding relationship between the power and environment information and the data verification rule; Using the first data verification rule to verify the first power and environment information, and obtain a verification result; If the verification result is a verification failure, determining that an abnormality exists in the target device under test; When the verification result is that the verification is passed, it is determined that there is no abnormality in the target device under test.

10. An electronic device, characterized in that: include: processor; as well as A memory arranged to store computer executable instructions, wherein the computer executable instructions are configured to be executed by the processor, and the computer executable instructions are executed by the processor to implement the automatic inspection method according to any one of claims 6 to 9.

11. A storage medium, characterized in that: The storage medium is used to store computer executable instructions, and when the computer executable instructions are executed by the processor, the automatic inspection method according to any one of claims 6 to 9 is implemented.

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