Intelligent inspection methods, devices, equipment and storage media for railway communication base stations

Abstract

This invention relates to an intelligent inspection method, apparatus, device, and storage medium for railway communication base stations. The intelligent inspection method for railway communication base stations includes: controlling an inspection device to acquire images of equipment to be inspected within the communication base station, obtaining at least one equipment image; performing status detection of the equipment to be inspected based on the at least one equipment image and / or the inspection device, obtaining detection data; determining an identification code pre-attached to the equipment to be inspected based on the at least one equipment image, and parsing a preset identifier contained in the identification code; the identification code is a batch-pre-generated standard code; storing the detection data or inspection data generated based on the detection data in a data table associated with the equipment identifier; a mapping relationship exists between the preset identifier and the equipment identifier, and the equipment identifier is an identity identifier assigned to the equipment to be inspected for use throughout its entire lifecycle. This method can quickly and accurately associate physical equipment with inspection data on-site, improving the overall efficiency of information management.

Description

Technical Field

[0001] This invention relates to the field of intelligent inspection technology, and in particular to an intelligent inspection method, apparatus, equipment and storage medium for railway communication base stations. Background Technology

[0002] With the rapid development of communication infrastructure, manual inspection methods are insufficient to meet the needs of large-scale facility operation and maintenance. Not only are labor costs high, but real-time performance is also poor, typically only allowing for weekly or monthly inspections, resulting in slow response times and an inability to promptly identify and resolve problems. Furthermore, the lack of standardized procedures and low inspection efficiency increases the difficulty of information management for communication equipment. Especially when dealing with a large number of devices or frequent information changes, methods based on QR codes for information management require generating and affixing pre-bound QR codes individually for each device, a cumbersome and inflexible process that negatively impacts inspection efficiency. Summary of the Invention

[0003] To address the aforementioned technical problems, this disclosure provides an intelligent inspection method, apparatus, equipment, and storage medium for railway communication base stations.

[0004] In a first aspect, embodiments of this disclosure provide an intelligent inspection method for railway communication base stations, including:

[0005] The control inspection device acquires images of the equipment to be inspected within the communication base station, obtaining an image of at least one device.

[0006] The status of the equipment to be inspected is detected based on at least one device image and / or inspection device to obtain inspection data.

[0007] The identification code to be pre-attached to the equipment to be inspected is determined based on at least one equipment image, and the preset identifier contained in the identification code is parsed; wherein, the identification code is a batch pre-generated standard code;

[0008] The detection data or the inspection data generated based on the detection data is stored in a data table associated with the equipment identifier; there is a mapping relationship between the preset identifier and the equipment identifier, and the equipment identifier is an identity identifier assigned to the equipment to be inspected for use throughout its entire life cycle.

[0009] Optionally, before parsing the preset identifier contained in the identifier code, the method further includes:

[0010] Determine whether the identification code has an associated image; where an associated image refers to a historical image of the equipment to be inspected that is associated with the identification code and contains the identification code.

[0011] If no associated image exists for the identification code, the current device image containing the identification code in at least one device image is used as the associated image; or, if an associated image exists for the identification code, the current device image is used as the associated image in response to a switching operation of the associated image.

[0012] Optionally, before storing the detection data or the inspection data generated based on the detection data in the data table associated with the equipment identifier, the method further includes:

[0013] Determine whether the equipment to be inspected is undergoing its first inspection or storing data for the first time;

[0014] If the device to be inspected is being inspected for the first time or storing data for the first time, a device identifier will be created or assigned to the device in the database. The database is used to store inspection data of multiple devices within the communication base station, and the device identifier is a unique identity assigned to the device to be inspected for use throughout its entire lifecycle.

[0015] Establish a mapping relationship between equipment identifiers and preset identifiers; the mapping relationship can be used throughout the entire life cycle of the equipment to be inspected.

[0016] Optionally, the identification code to be pre-attached to the equipment to be inspected is determined based on at least one equipment image, including:

[0017] Region labeling is performed on at least one device image to determine a first image region containing an identification code;

[0018] Identify the identification code pre-attached to the surface of the equipment to be inspected from the first image area.

[0019] Optionally, the inspection device adopts a gantry structure and is installed inside the housing of the equipment to be inspected. The gantry structure includes a longitudinal axis guide rail arranged along the length of the housing and a transverse axis guide rail arranged along the width of the housing. The longitudinal axis guide rail is fixedly installed on the two side walls of the housing, and the transverse axis guide rail is slidably installed on the longitudinal axis guide rail. A depth axis guide rail is installed on the slider of the transverse axis guide rail, and the inspection camera is installed on the slider of the depth axis guide rail. The inspection camera is used to acquire images of the equipment within its inspection area.

[0020] Optionally, the status of the equipment to be inspected is detected based on the inspection device to obtain inspection data, including:

[0021] The infrared thermal imaging component configured in the inspection camera detects the surface temperature of the equipment to be inspected, determines whether there are any temperature abnormalities in the equipment, and generates detection data; among which, status detection includes equipment temperature detection.

[0022] Optionally, the status of the equipment to be inspected is detected based on at least one device image to obtain detection data, including:

[0023] Region calibration is performed on at least one device image to determine the image region of at least one item to be inspected in the device to be inspected;

[0024] Obtain the current state value of at least one of the image regions representing the target item;

[0025] The current status value is compared with the preset status value or the target status value to determine whether the item to be inspected is in an abnormal state and to generate inspection data. The target status value is the default value when the equipment to be inspected is being inspected for the first time, and the historical status value when it is not being inspected for the first time.

[0026] Optionally, the status detection includes at least one of the following: device indicator status detection, circuit breaker status detection, and network port status detection. The image area of ​​at least one item to be detected includes at least one second image area of ​​the indicator light, at least one third image area of ​​the circuit breaker, and / or at least one fourth image area of ​​the network port. The item to be detected is the indicator light, the circuit breaker, and / or the network port.

[0027] Optionally, determine whether the item to be detected is in an abnormal state and generate detection data, including:

[0028] Determine whether the indicator light color is normal, whether the circuit breaker is in the open or closed state, and / or whether the network port is connected, and generate detection data.

[0029] Secondly, embodiments of this disclosure provide an intelligent inspection device for railway communication base stations, comprising:

[0030] The acquisition unit is used to control the inspection device to acquire images of the equipment to be inspected in the communication base station and obtain at least one equipment image.

[0031] The detection unit is used to detect the status of the equipment to be inspected based on at least one equipment image and / or inspection device, and obtain detection data.

[0032] The identification unit is used to determine the identification code pre-attached to the device to be inspected based on at least one device image, and to parse the preset identifier contained in the identification code; wherein, the identification code is a batch-pre-generated standard code;

[0033] The storage unit is used to store the detection data or the inspection data generated based on the detection data into a data table associated with the device identifier; there is a mapping relationship between the preset identifier and the device identifier, and the device identifier is an identity identifier assigned to the device to be inspected for use throughout its entire life cycle.

[0034] Thirdly, embodiments of this disclosure provide an electronic device, including:

[0035] Memory;

[0036] Processor; and

[0037] Computer programs;

[0038] The computer program is stored in memory and configured to be executed by a processor to implement the first aspect of the method described above.

[0039] Fourthly, embodiments of this disclosure provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect above.

[0040] The intelligent inspection method for railway communication base stations disclosed herein includes: controlling an inspection device to acquire images of the equipment to be inspected within the communication base station, obtaining at least one equipment image; performing status detection of the equipment to be inspected based on the at least one equipment image and / or the inspection device, obtaining detection data; determining an identification code pre-attached to the equipment to be inspected based on the at least one equipment image, and parsing the preset identifier contained in the identification code; wherein the identification code is a batch-pre-generated standard code; storing the detection data or inspection data generated based on the detection data in a data table associated with the equipment identifier; wherein the preset identifier and the equipment identifier have a mapping relationship, and the equipment identifier is an identity identifier assigned to the equipment to be inspected for use throughout its entire life cycle. The method provided in this application can quickly and accurately associate physical equipment with digital information at the inspection site, and ensure that the detection data is accurately traced to the specific equipment, further improving the overall efficiency of information management. Attached Figure Description

[0041] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0042] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 A flowchart illustrating an intelligent inspection method for a railway communication base station provided in this embodiment of the present disclosure;

[0044] Figure 2 This is a schematic diagram of the structure of an inspection device provided in an embodiment of the present disclosure;

[0045] Figure 3 This is a schematic diagram of the structure of an intelligent inspection system provided in an embodiment of the present disclosure;

[0046] Figure 4 This is a schematic diagram of the structure of an intelligent inspection device for a railway communication base station provided in an embodiment of the present disclosure;

[0047] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0048] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0049] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0050] To address the aforementioned technical problems, this disclosure provides an intelligent inspection method for railway communication base stations, solving issues such as low identification efficiency, inaccurate association between physical devices and digital information, and complex deployment in traditional equipment inspections. Detailed explanations are provided through one or more of the following embodiments.

[0051] The intelligent inspection method for railway communication base stations provided in this disclosure is applicable to intelligent inspection scenarios for communication base stations. This method can be executed by an intelligent inspection device for railway communication base stations, which can be implemented in software and / or hardware and can be integrated into an electronic device. The electronic device can include, but is not limited to, mobile terminals such as smartphones, laptops, digital radio receivers, personal digital assistants (PDAs), tablet computers (Tablet PCs), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), wearable devices, etc., as well as fixed terminals such as digital televisions, desktop computers, smart home devices, etc.

[0052] Figure 1 This is a flowchart illustrating an intelligent inspection method for a railway communication base station provided in an embodiment of this disclosure, specifically including the following: Figure 1 The following steps are shown:

[0053] S101. The control inspection device acquires images of the equipment to be inspected within the communication base station, obtaining at least one equipment image.

[0054] Understandably, a communication base station comprises multiple physical devices, among which at least one device to be inspected (hereinafter referred to as "device") is identified. Subsequently, the device to be inspected is placed within the detection area of ​​the inspection device, or the inspection device is installed on the device to be inspected, enabling the inspection device to acquire images of the device's surface, thus obtaining at least one device image. The device image can be at least one of the following: a visible light image (e.g., device appearance, indicator light status, instrument readings, etc.), an infrared thermal imaging image (used to detect abnormal device temperature), a 3D point cloud image (used to identify device deformation, displacement, etc.), or an identification code / tag image (used to identify device identity). The inspection device can automatically acquire images of the device's surface in real-time or at regular intervals; that is, the user can set the inspection time and interval to address the issue of poor real-time performance during weekly or monthly device inspections.

[0055] Optionally, the inspection device adopts a gantry structure and is installed inside the housing of the equipment to be inspected. The gantry structure includes a longitudinal axis guide rail arranged along the length of the housing and a transverse axis guide rail arranged along the width of the housing. The longitudinal axis guide rail is fixedly installed on the two side walls of the housing, and the transverse axis guide rail is slidably installed on the longitudinal axis guide rail. A depth axis guide rail is installed on the slider of the transverse axis guide rail, and the inspection camera is installed on the slider of the depth axis guide rail. The inspection camera is used to acquire images of the equipment within its inspection area.

[0056] For example, Figure 2 This is a schematic diagram of an inspection device provided in an embodiment of this disclosure. The equipment to be inspected can be understood as a cabinet or enclosure, and the inspection device can be installed on the outer frame of the enclosure. Specifically, the inspection device refers to an equipment inspection camera device based on a gantry structure. Figure 2The inspection device shown can perform equipment inspections within a housing measuring 1.9m (length) × 1.0m (width) × 2.6m (height), creating an inspection area of ​​approximately 1.8m × 2.4m. The working distance of the inspection device can be set from 20cm to 40cm. The inspection device features an X / Y / Z three-axis linear guide structure and a dual-camera mounting module. The guide structure also incorporates a servo motor for synchronous belt drive. The dual-camera mounting module is arranged horizontally and fixed to the Z-axis slider, enabling simultaneous acquisition of depth, visual, and thermal imaging data. The gantry structure (also known as the X / Y / Z three-axis linear guide structure) includes a longitudinal axis guide rail (Y-axis guide rail, mounted on the 2.6m high outer frame of the housing) along the length of the housing and a transverse axis guide rail (X-axis, mounted on the 1.9m long outer frame of the housing) along the width of the housing. The longitudinal axis guide rail is fixedly mounted on the two side walls of the housing, while the transverse axis guide rail is slidably mounted on the longitudinal axis guide rail. Additionally, a depth axis guide rail (Z-axis) is mounted on the transverse axis guide rail slider, and a dual-camera mounting module is mounted on the depth axis guide rail slider (Z-axis slider). This structural design enables omnidirectional coverage of the required inspection area, ensuring no blind spots and meeting the needs of various complex inspection scenarios.

[0057] Understandably, the inspection device is controlled by servo motors. A longitudinal servo motor (denoted as the longitudinal axis motor) is mounted on the longitudinal guide rail to drive the transverse guide rail to slide along the longitudinal guide rail; a transverse servo motor (denoted as the transverse axis motor) is mounted on the transverse guide rail to drive the depth guide rail to slide along the transverse guide rail; and a depth adjustment motor (denoted as the depth axis motor) is used for camera depth control. The servo motors, connected to the guide rails through a high-precision transmission mechanism, can accurately move the camera to the designated position to complete image acquisition and status detection, ensuring the accuracy and consistency of the detection data.

[0058] Understandably, the dual-camera mounting module includes a main camera and an auxiliary camera. The main camera can be a high-definition industrial camera used for detailed imaging of equipment surfaces, and it also integrates infrared temperature measurement functionality, serving as the aforementioned inspection camera. This main camera also features QR code scanning capabilities for dynamic binding of on-site equipment with pre-generated QR codes; in other words, the main camera can also be used to identify identification codes on the equipment to be inspected. The auxiliary camera, combined with the main camera, shares the same physical coordinate system and is fixed to the Z-axis slider via a rigid bracket, enabling synchronous acquisition of multimodal data. Specifically, the auxiliary camera can be an auxiliary TOF (Time of Flight) camera. A TOF camera is a device that uses time-of-flight technology to measure distance and create depth maps, quickly and accurately capturing depth information in a scene, making it suitable for complex scenarios. Subsequent precise position and attitude control of the dual-camera mounting module along the X / Y / Z axes allows for the acquisition of multi-angle, omnidirectional, accurate, and clear images of the equipment. Specifically, the X / Y axes control horizontal movement, adjusting the camera's observation position on the plane to scan different areas of the equipment. The Z-axis controls vertical movement, adjusting the distance between the camera and the equipment to control image clarity and field of view. Furthermore, the dual-camera collaborative mechanism can acquire images from different perspectives and calculate the target's 3D information using a stereo matching algorithm, improving detection accuracy and data integrity. In other words, the dual-camera module can acquire at least one type of information, including 2D image information, 3D spatial data, equipment identification information, and equipment operating status. Further integration with technologies such as Time-of-Flight (TOF) and QR code recognition can achieve comprehensive functions such as automatic equipment identification, spatial positioning, and status detection. Intelligent inspection based on the inspection equipment significantly improves the automation and intelligence level of equipment inspection.

[0059] Understandably, the inspection device is also equipped with an intelligent lighting system, specifically adjustable color temperature LED supplementary lights that can be integrated on both sides of the three-axis platform. The brightness and color temperature are dynamically adjusted by real-time feedback data from the light sensor, and the light distortion suppression algorithm is used to eliminate uneven lighting interference.

[0060] S102. Based on at least one device image and / or inspection device, perform status detection of the device to be inspected to obtain detection data.

[0061] Understandably, based on the above S101, at least one equipment image collected by the inspection device, or the functions of the inspection device itself (such as ROI calibration and infrared detection), are used to perform status detection on the equipment to be inspected, thereby obtaining detection data reflecting the operating status or health status of the equipment. This achieves non-contact, automated detection of equipment status, improving inspection efficiency and accuracy. The detection data is obtained through image recognition, sensor acquisition, or algorithm analysis.

[0062] Optionally, the status of the equipment to be inspected can be detected using the inspection device to obtain inspection data. This can be achieved through the following steps:

[0063] The infrared thermal imaging component configured in the inspection camera detects the surface temperature of the equipment to be inspected, determines whether there are any temperature abnormalities in the equipment, and generates detection data; among which, status detection includes equipment temperature detection.

[0064] Understandably, status detection includes equipment temperature detection, which is used to detect the temperature of equipment within a designated area. Specifically, in one embodiment, a patrol camera / main camera / detection camera equipped with an infrared thermal imaging module detects and analyzes the surface temperature of the equipment to determine whether the equipment is operating normally, whether there are abnormalities such as overheating, poor contact, or aging, and generates detection data about the equipment temperature. The specific implementation of infrared thermal imaging detection is not detailed here. Another embodiment uses a contact temperature sensor to detect the equipment temperature, using a temperature probe, thermistor, etc., to directly contact the equipment surface to obtain accurate temperature values. Yet another embodiment uses a non-contact laser / infrared thermometer to detect the equipment temperature, allowing for remote measurement of the temperature of a specific point or area on the equipment. At least one equipment temperature detection method can be selected according to user needs; no limitation is made here. The equipment temperature monitoring data can include at least one of the following: current temperature value (e.g., 45.3℃), temperature distribution image (e.g., infrared thermal image), temperature change trend (historical temperature records), abnormal temperature rise markers (whether it is higher than normal), hot spot location information (e.g., abnormal temperature at a certain terminal), whether it exceeds a set threshold (e.g., whether it exceeds the safe operating temperature), and temperature gradient analysis results (whether the temperature difference between different areas is abnormal). Subsequent equipment temperature monitoring data can provide data support for equipment status assessment, fault early warning, and intelligent operation and maintenance.

[0065] Optionally, the status of the equipment to be inspected can be detected based on at least one device image to obtain inspection data. This can be achieved through the following steps:

[0066] The system performs region calibration on at least one device image to determine the image region of at least one item to be inspected in the device to be inspected; obtains the current state value of at least one item to be inspected represented by the image region of at least one item to be inspected; compares the current state value with a preset state value or a target state value to determine whether the item to be inspected is in an abnormal state and generates detection data; wherein, the target state value is the default value when the device to be inspected is being inspected for the first time, and is the historical state value when it is not being inspected for the first time.

[0067] Understandably, the items to be detected in the device are identified, such as network ports, switches, and indicator lights. Then, the acquired device images are categorized into regions to determine the image regions of the items to be detected. An image region, or Region of Interest, refers to a specific area in an image or data that requires focused attention, analysis, or processing; this can be achieved using the ROI (Region of Interest) categorization method. Each item to be detected corresponds to at least one image region, and each image region includes at least one component. For example, an image region may include a row of network ports, and the component is the item to be detected; or an image region may include one network port. After completing the calibration of each detection item, the image regions of each item are detected using appropriate detection algorithms (such as vision-based, Time-of-Flight (ToF) based, or a combination of both). The current state value (denoted as CurrentValue) of the detection item is obtained, such as "not connected" for a network port and "closed" for a circuit breaker. Alternatively, different states of the detection item can be represented numerically; for example, a value of 1 indicates "not connected" and a value of 0 indicates "connected." Subsequently, the detected current status value is compared with the preset status value or the target status value to determine whether the detected item is abnormal (denoted as IsAnomaly), and a detection result is generated. The preset status value is set by the user and can be understood as a fixed / static status value. The target status value (denoted as ExpectedValue) is an editable and adaptively adjustable dynamic status value. For newly identified or first-time inspected devices, its ExpectedValue may be empty or a default value. After editing or calibration, the currently detected or user-confirmed CurrentValue (referring to historical status values) is set to or synchronized to ExpectedValue to serve as a benchmark for judging anomalies in subsequent inspections. For example, device A operates at a normal temperature of 50℃ during the day when the load is high and at 35℃ at night when the load is low. If a fixed threshold / status value (such as 45℃) is set to judge anomalies, there may be false alarms during the day and missed alarms at night. Setting a dynamic status value allows for dynamic setting of the "normal temperature range" according to different time periods or load conditions. This dynamic state value-based method of anomaly detection can adapt to operational differences under different environments, working conditions, and time periods, thus improving the accuracy and adaptability of anomaly detection.

[0068] Optionally, the status detection includes at least one of the following: device indicator status detection, circuit breaker status detection, and network port status detection. The image area of ​​at least one item to be detected includes at least one second image area of ​​the indicator light, at least one third image area of ​​the circuit breaker, and / or at least one fourth image area of ​​the network port. The item to be detected is the indicator light, the circuit breaker, and / or the network port.

[0069] Optionally, determine whether the item to be detected is in an abnormal state and generate detection data. This can be achieved through the following steps:

[0070] Determine whether the indicator light color is normal, whether the circuit breaker is in the open or closed state, and / or whether the network port is connected, and generate detection data.

[0071] Understandably, the inspection camera is mounted on a camera mounting bracket of the aforementioned gantry structure, utilizing a mobile platform (i.e., the gantry structure) to inspect and alarm on equipment within the entire inspection area. Status detection includes at least one of the following: equipment indicator light status detection, circuit breaker status detection, and network port status detection. Specifically, equipment indicator light status detection can identify the colors of various network port indicator lights and various ordinary indicator lights. Visual recognition algorithms can be used to process the second image area containing the indicator lights using the inspection camera or other processors to determine whether the indicator light colors are normal, thereby generating detection data reflecting the equipment's operating status. Circuit breaker status detection is used to detect the open / closed status of various circuit breakers. Visual recognition technology can be used to analyze the appearance of the circuit breakers to determine whether they are in an open or closed state. Network port status detection is used to detect whether the network port is working normally. A detection algorithm determines the physical connection status of the network port, such as whether the network cable is correctly inserted and free from damage or poor contact. Other methods based on image areas for detection are not limited.

[0072] Understandably, the inspection camera can also automatically send alarm signals to the control software based on the above inspection results or detection data. Simultaneously, the inspection device can collaborate with the local control platform to achieve visualized mobile monitoring of the inspection camera. Specifically, the local control platform can receive equipment images and detection data collected by the inspection camera in real time and intuitively display the camera's movement trajectory and detection area on the display interface, enabling operators to clearly understand the entire inspection process and the real-time status of the equipment.

[0073] S103. Determine the identification code pre-attached to the device to be inspected based on at least one device image, and parse the preset identifier contained in the identification code.

[0074] The identifier code is a standard code that is pre-generated in batches.

[0075] Understandably, based on the above S102, the identification code is a standard code pre-affixed to the device and pre-generated in batches. In other words, the identification code is a universal code. Specifically, it can be a series of QR codes pre-generated in batches, each containing different preset identifiers or preset identifiers (such as server addresses and path placeholders). The different identifiers can be of a universal format. The following embodiments use QR codes as an example for detailed explanation. When the QR code is printed, the identifier it contains (such as a URL, Uniform Resource Locator) points to a server endpoint to be bound or a universal server endpoint, such as "http: / / aa.com / id=XX" or "http: / / aa.com / device / YY", and the identification code itself is not strongly associated with any specific device when printed.

[0076] Understandably, during the initial installation or data entry phase, the final server data storage address (i.e., the address where the data table is located) of the device may not be fully determined or may require flexible allocation, increasing the complexity of associating physical devices with digital information systems. Therefore, to reduce the cumbersome process of generating and affixing pre-bound QR codes for each device, this embodiment pre-generates a series of universal QR codes. Once the universal QR code is initially bound to a specific device and its inspection data, it achieves a "one code, one device" effect. Subsequently, users can scan the QR code on the device to access that device's unique and continuously updated inspection data.

[0077] Optionally, the identification code to be pre-attached to the equipment to be inspected can be determined based on at least one equipment image, which can be achieved through the following steps:

[0078] At least one device image is tagged to identify a first image region containing an identification code; the identification code pre-attached to the surface of the device to be inspected is identified from the first image region.

[0079] Understandably, at least one device image is categorized into regions, specifically using ROI (Region of Interest) categorization methods. This involves determining a first image region containing the identifier code. This first image region can be understood as the image region corresponding to the device-level ROI, captured using an image region taken with a visible light camera synchronized with or calibrated with a ToF camera. Within this image region corresponding to the device-level ROI, a QR code detection and decoding algorithm is run to identify the preset identifier (denoted as QR_Temp_ID) contained in the general QR code. This device-level ROI generated based on ToF provides precise spatial constraints for QR code search, improving the accuracy of QR code recognition. Subsequently, if the QR_Temp_ID is successfully identified within the device-level ROI (corresponding to the local device identifier), a temporary association is established between the device-level ROI and the QR_Temp_ID on the local inspection client, realizing a local dynamic association between the device ROI and the temporary QR code identifier.

[0080] Optionally, before parsing the preset identifier contained in the identifier code, the method further includes:

[0081] Determine whether the identification code has an associated image; wherein, the associated image refers to a historical equipment image of the equipment to be inspected that is associated with the identification code and contains the identification code; if the identification code does not have an associated image, use at least one current equipment image containing the identification code as the associated image; or, if the identification code has an associated image, use the current equipment image as the associated image in response to the switching operation of the associated image.

[0082] Understandably, after identifying the QR code but before parsing it, a security verification step can be added to enhance system security and prevent risks from forged, tampered, or malicious QR codes. This security verification involves verifying the QR code itself or its source before formally parsing its content, ensuring its legality, integrity, and authenticity, and preventing unauthorized access, data tampering, or device impersonation. Specifically, it verifies whether the QR code determined from the device image or the first image area has a associated image. An associated image refers to a historical device image that is related to the QR code and contains it. In cases where the device is not undergoing its first inspection, the historical device image is an image collected during a previous inspection, which could be from the first inspection or a previous inspection. If the QR code does not have an associated image, it indicates that the device is undergoing its first inspection or that the associated image is missing, posing a security risk. In this case, the current device image containing the QR code is determined from the real-time captured device images, or the user can manually select the current device image from the real-time captured device images. A temporary or preliminary association is then established between the current device image and the QR code. If an associated image exists, it can be switched. Specifically, in response to the image switching operation, the current device image is used as the associated image. Alternatively, other images selected by the user can be used as the associated image for this device; that is, the source of the associated image for QR code security verification is not limited. After completing the image binding or switching, the preset identifier contained in the QR code is parsed. Specifically, a QR code detection and decoding algorithm can be run to identify the universal QR code pre-attached to the device surface, which contains a unique temporary identifier (i.e., QR_Temp_ID), and obtain the temporary identifier.

[0083] Understandably, dynamic binding of device images and QR codes can be achieved through local software. Specifically, in local inspection management or configuration software, users can identify and select physical devices (i.e., device frames) in device images through interface operations (such as camera scanning or image recognition). Users can also scan pre-generated QR codes affixed to devices through interface operations, identify the QR code image (i.e., QR code frame), and parse out the temporary ID or URL to be bound (i.e., preset identifier) ​​contained therein. The local software also provides a binding operation to establish a temporary or preliminary association between the user-selected "device frame" (representing the physical device or its initial identifier in the system) and the scanned "QR code frame" (and its contained temporary ID / URL) at the software level.

[0084] S104. Store the detection data or the inspection data generated based on the detection data into a data table associated with the equipment identifier.

[0085] Among them, there is a mapping relationship between the preset identifier and the device identifier. The device identifier is a unique identity identifier assigned to the device to be inspected throughout its entire life cycle.

[0086] Understandably, based on the above S103, after completing the equipment status detection, the collected detection data (such as temperature, images, instrument readings, etc.) or the inspection result data generated based on this data are stored in a data table in the database that is associated with the unique equipment identifier (such as equipment number, ID, etc.) of the equipment for subsequent querying, analysis, and management. There is a correlation between the preset identifier identified from the QR code and the unique identifier assigned to the equipment. Because the QR code is a universal QR code, and the identifiers it contains are all in the same format and are not unique, a long-term / permanent / lasting mapping relationship needs to be established between the preset identifier and the equipment identifier to ensure the stability and security of data management based on QR codes.

[0087] Optionally, before storing the detection data or the inspection data generated based on the detection data in the data table associated with the equipment identifier, the method further includes:

[0088] Determine whether the device to be inspected is undergoing its first inspection or storing data for the first time; if it is, create or assign a device identifier to the device in the database; the database is used to store inspection data of multiple devices within the communication base station; establish a mapping relationship between the device identifier and a preset identifier; the mapping relationship can be used throughout the entire lifecycle of the device to be inspected.

[0089] Understandably, before storing the detection or inspection data into the data table, it is determined whether a device identifier with a mapping relationship to a preset identifier exists in the database, whether the device is undergoing its first inspection, and / or whether the device's data is being reported / stored for the first time. If no device identifier with a mapping relationship to a preset identifier exists in the database, or if the device is undergoing its first inspection and / or reporting data for the first time, the inspection or detection data, along with the preset identifier (in this case, the temporary ID / URL contained in the QR code), are sent to the server. After receiving the data, if the server receives the preset identifier for the first time, it will execute a formal binding logic, that is, create or assign a unique, persistent device record / ID (i.e., device identifier) ​​for the device (which can be determined based on the reported device identification information) in the database, and establish a permanent mapping relationship between the persistent device ID and the temporary ID / URL of the QR code. Subsequently, the inspection data is stored in the data table associated with the persistent device ID. Subsequently, the server can update the temporary ID / URL of the QR code to point to a more direct URL that includes a persistent device ID. That is, the server can set the temporary URL of the QR code attached to the device to point to the device's persistent URL, or the server can maintain the mapping relationship directly in the background.

[0090] Understandably, once the association between the preset identifier and the device identifier is established, or a device identifier with a mapping relationship to the preset identifier exists in the database, or the device is not undergoing its first inspection, or the device is not reporting data for the first time, i.e., when the same QR code is scanned again and the inspection data of the device is reported, the server directly stores the data into the corresponding persistent device data table through the established mapping relationship or the persistent URL pointed to by the temporary URL.

[0091] Understandably, the QR_Temp_ID, device-level ROI information, ROI information for all inspection items, and their inspection status (CurrentValue, ExpectedValue, IsAnomaly) can also be integrated into a data packet and uploaded to the server for storage. This establishes a permanent association between device information, ROI information, inspection item status (including network port status, circuit breaker status, etc.) and the device's ID. Subsequently, users can scan the QR code on the device to access the device's unique and continuously updated inspection data.

[0092] In one application scenario, the inspection device is also used for big data analysis and intelligent diagnosis. For example, when an abnormally high battery temperature is detected, it not only retrieves historical data such as the battery module's voltage, current, and charge / discharge cycle count, but also simultaneously reads the power fluctuations and interface connection status of the load end (such as inverters, RRUs (Remote Radio Units), and BBUs (Baseband Units)). Combined with environmental parameters such as temperature, humidity, and ventilation efficiency within the cabinet, it generates a multi-dimensional correlation graph in real time through the edge computing unit to accurately locate the cause of the excessive temperature, analyze whether it is due to battery aging, overload, or heat dissipation failure, and automatically pushes graded handling suggestions (such as prioritizing load reduction, remotely restarting the heat dissipation system, or arranging battery replacement).

[0093] Another application scenario for the inspection device is its applicability across multiple fields, including industrial equipment maintenance, power system inspection, data center management, and monitoring of rail transit infrastructure. For example, in industrial equipment maintenance, its two-axis moving platform and near-field visual inspection capabilities can be used for production line control cabinet inspection, identifying indicator lights, relays, knob positions, and terminal block status, and combining this with equipment operating parameters to determine anomalies. In power systems, it can detect the opening and closing status of circuit breakers and cable joint temperatures, enabling remote tripping of faulty circuits in conjunction with the power monitoring system. In data center scenarios, optimized image stitching algorithms can generate panoramic views of server racks, and U-position recognition technology can be used to calculate space utilization. In the rail transit sector, it can be used for relay status monitoring in subway signal rooms and rectifier temperature inspection in traction substations. Furthermore, based on the inspection device's mechanical structure compatibility, multimodal data acquisition capabilities, and remote control functions, low-cost reuse can be achieved simply by optimizing the algorithm model for the equipment characteristics of different scenarios. Miniaturization and integration into a single rack can also be considered to provide a smart rack device with inspection capabilities. Other possible application scenarios are not limited.

[0094] This disclosure provides an intelligent inspection method for railway communication base stations. By introducing Time-of-Flight (TOF) assisted recognition technology and visual detection algorithms, it can automatically identify the Region of Interest (ROI) of the equipment on-site and accurately locate and identify a universal QR code within this area. This enables dynamic binding of the equipment's physical characteristics and identity information, significantly improving the accuracy and automation level of equipment identity matching. Furthermore, by performing image recognition or sensor data acquisition on key detection items such as network port status, circuit breaker status, temperature, indicator lights, and instrument readings, and accurately associating the detection results with the equipment's identity information before uploading them to a server database, traceable, queryable, and visualized management of equipment status is achieved, further realizing comprehensive equipment information and status management functions. Users can then conveniently query the current status and historical inspection records of any equipment through a server-side webpage or client system, providing a solid data foundation and technical support for intelligent inspection, remote operation and maintenance, and predictive maintenance. The method provided in this application effectively improves the intelligence, standardization, and automation level of equipment inspection and is applicable to large-scale equipment management scenarios.

[0095] Based on the above embodiments, Figure 3This is a schematic diagram of the structure of an intelligent inspection system provided in an embodiment of this disclosure. The intelligent inspection system includes a main control PLC, a switch, and a dynamic environment system. The main control PLC is used to drive servo motors (i.e., longitudinal axis motor, transverse axis motor, and depth axis motor) along the XYZ axes. It is also used to control alarms, sensors, and light curtains. The sensors are mounted on the motion module and are used for zero-return calibration and limit protection during module operation. The light curtain is used for intrusion protection. When a foreign object enters the inspection area, the inspection device stops operating, similar to the function of an elevator light curtain. The main control PLC sends control commands to the servo drive (i.e., servo driver, hereinafter referred to as the driver), which then controls the motor operation. The real-time position information fed back by the motor is fed back to the driver through the encoder line to achieve closed-loop feedback of operation. The alarm is used for abnormal alarms of the inspection equipment. It can send alarm signals to the control software based on the real-time detected abnormal equipment status. The alarm signals can be implemented through devices such as indicator lights and audible and visual alarms. The main control PLC also connects to a switch, which can be understood as an interconnection device used for data communication with 5G modules, monitoring screens, dual-camera modules (such as vision cameras and TOF cameras), industrial computers, and the environmental monitoring system. The 5G module uploads inspection data to the cloud; the monitoring screen displays inspection data and can acquire data via network cable, or via the 5G module if no network cable connection is available on-site. The industrial computer interacts with the control panel to display operational behavior in real time. The environmental monitoring system also connects to surge protection units, high-voltage switching units, inverters, and multiple batteries. The environmental monitoring system, officially called the Power and Environment Monitoring System, uses sensors, intelligent devices, and software platforms to monitor, warn of, and remotely control the status of power equipment and environmental parameters in the communication room in real time. The environmental monitoring system is an independent system. Surge protection units, high-voltage switching units, inverters, and batteries are connected to the environmental monitoring system via communication (RS485 using the MODBUS protocol). It is understandable that the dynamic environmental system, lightning protection unit, high-voltage switching unit, inverter, and battery are not the inspection device itself, but rather the objects being inspected and components of the entire inspection system.

[0096] Based on the above embodiments, Figure 4 This is a schematic diagram of the structure of an intelligent inspection device for a railway communication base station provided in this embodiment of the disclosure. The intelligent inspection device for a railway communication base station provided in this embodiment can execute the processing flow provided in the intelligent inspection method embodiment for railway communication base stations, such as... Figure 4 As shown, the intelligent inspection device 400 for railway communication base stations includes:

[0097] The acquisition unit 401 is used to control the inspection device to acquire images of the equipment to be inspected in the communication base station and obtain at least one equipment image.

[0098] Detection unit 402 is used to detect the status of the equipment to be inspected based on at least one equipment image and / or inspection device, and obtain detection data;

[0099] The identification unit 403 is used to determine the identification code pre-attached to the device to be inspected based on at least one device image, and to parse the preset identification contained in the identification code; wherein, the identification code is a batch pre-generated standard code;

[0100] Storage unit 404 is used to store detection data or inspection data generated based on the detection data into a data table associated with the device identifier; wherein, there is a mapping relationship between the preset identifier and the device identifier, and the device identifier is a unique identity identifier assigned to the device to be inspected for use throughout its entire life cycle.

[0101] Optionally, the intelligent inspection device 400 for railway communication base stations is also used for:

[0102] Determine whether the identification code has an associated image; where an associated image refers to a historical image of the equipment to be inspected that is associated with the identification code and contains the identification code.

[0103] If no associated image exists for the identification code, the current device image containing the identification code in at least one device image is used as the associated image; or, if an associated image exists for the identification code, the current device image is used as the associated image in response to a switching operation of the associated image.

[0104] Optionally, the intelligent inspection device 400 for railway communication base stations is also used for:

[0105] Determine whether the equipment to be inspected is undergoing its first inspection or storing data for the first time;

[0106] If the device to be inspected is being inspected for the first time or storing data for the first time, a device identifier will be created or assigned to the device in the database; the database is used to store inspection data for multiple devices within the communication base station.

[0107] Establish a mapping relationship between equipment identifiers and preset identifiers; the mapping relationship can be used throughout the entire life cycle of the equipment to be inspected.

[0108] Optionally, the identification unit 403 is used for:

[0109] Region labeling is performed on at least one device image to determine a first image region containing an identification code;

[0110] Identify the identification code pre-attached to the surface of the equipment to be inspected from the first image area.

[0111] The inspection device adopts a gantry structure and is installed inside the housing of the equipment to be inspected. The gantry structure includes a longitudinal axis guide rail arranged along the length of the housing and a transverse axis guide rail arranged along the width of the housing. The longitudinal axis guide rail is fixedly installed on the two side walls of the housing, and the transverse axis guide rail is slidably installed on the longitudinal axis guide rail. A depth axis guide rail is installed on the slider of the transverse axis guide rail, and the inspection camera is installed on the slider of the depth axis guide rail. The inspection camera is used to acquire images of the equipment within its inspection area.

[0112] Optionally, the detection unit 402 is used for:

[0113] The infrared thermal imaging component configured in the inspection camera detects the surface temperature of the equipment to be inspected, determines whether there are any temperature abnormalities in the equipment, and generates detection data; among which, status detection includes equipment temperature detection.

[0114] Optionally, the detection unit 402 is used for:

[0115] Region calibration is performed on at least one device image to determine the image region of at least one item to be inspected in the device to be inspected;

[0116] Obtain the current state value of at least one of the image regions representing the target item;

[0117] The current status value is compared with the preset status value or the target status value to determine whether the item to be inspected is in an abnormal state and to generate inspection data. The target status value is the default value when the equipment to be inspected is being inspected for the first time, and the historical status value when it is not being inspected for the first time.

[0118] The status detection includes at least one of the following: device indicator status detection, circuit breaker status detection, and network port status detection. The image area of ​​at least one item to be detected includes at least one second image area of ​​the indicator light, at least one third image area of ​​the circuit breaker, and / or at least one fourth image area of ​​the network port. The item to be detected is the indicator light, the circuit breaker, and / or the network port.

[0119] Optionally, the detection unit 402 is used for:

[0120] Determine whether the indicator light color is normal, whether the circuit breaker is in the open or closed state, and / or whether the network port is connected, and generate detection data.

[0121] Figure 4 The intelligent inspection device for railway communication base stations in the illustrated embodiment can be used to execute the technical solutions of the above method embodiments. Its implementation principle and technical effects are similar, and will not be repeated here.

[0122] Figure 5This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. See below for details. Figure 5 The diagram illustrates a structural schematic suitable for implementing the electronic device 500 in the embodiments of this disclosure. The electronic device 500 in the embodiments of this disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), wearable electronic devices, etc., as well as fixed terminals such as digital TVs, desktop computers, smart home devices, etc. Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0123] like Figure 5 As shown, the electronic device 500 may include a processing unit 501 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503 to implement the intelligent inspection method for railway communication base stations as described in the embodiments of this disclosure. The RAM 503 also stores various programs and data required for the operation of the electronic device 500. The processing unit 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0124] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 508 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows electronic device 500 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 An electronic device 500 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0125] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts, thereby implementing the intelligent inspection method for railway communication base stations as described above. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, it performs the functions defined in the methods of embodiments of this disclosure.

[0126] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0127] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0128] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0129] Optionally, when one or more of the above-described procedures are executed by the electronic device, the electronic device may also perform other steps described in the above embodiments.

[0130] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0131] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0132] The units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0133] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0134] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0135] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or gateway that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or gateway. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or gateway that includes said element.

[0136] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for intelligent inspection of railway communication base stations, characterized in that, include: The control inspection device acquires images of the equipment to be inspected within the communication base station, obtaining an image of at least one device. Based on the image of at least one device and / or the inspection device, the status of the device to be inspected is detected to obtain inspection data; Based on the image of at least one device, determine the identification code to be pre-attached to the device to be inspected, and parse the preset identifier contained in the identification code; wherein, the identification code is a batch-pre-generated standard code; The detection data or the inspection data generated based on the detection data is stored in a data table associated with the device identifier; wherein, the preset identifier and the device identifier have a mapping relationship, and the device identifier is an identity identifier assigned to the device to be inspected for use throughout its entire life cycle; Before parsing the preset identifier contained in the identifier code, the method further includes: Determine whether the identification code has an associated image; wherein, the associated image refers to a historical equipment image of the equipment to be inspected that is associated with the identification code and contains the identification code; If no associated image exists for the identification code, the current device image containing the identification code in the at least one device image is used as the associated image; or, if an associated image exists for the identification code, the current device image is used as the associated image in response to a switching operation of the associated image.

2. The method according to claim 1, characterized in that, Before storing the detection data or the inspection data generated based on the detection data into the data table associated with the device identifier, the method further includes: Determine whether the device to be inspected is undergoing its first inspection or storing data for the first time; If the device to be inspected is being inspected for the first time or storing data for the first time, then a device identifier is created or assigned to the device in the database; wherein, the database is used to store inspection data of multiple devices within the communication base station; Establish a mapping relationship between the device identifier and the preset identifier; wherein the mapping relationship can be used throughout the entire life cycle of the device to be inspected.

3. The method according to claim 1, characterized in that, The step of determining the identification code to be pre-attached to the equipment to be inspected based on the image of the at least one equipment includes: The image of the at least one device is region-labeled to determine a first image region containing the identification code; Identify the identification code pre-attached to the surface of the equipment to be inspected from the first image area.

4. The method according to claim 1, characterized in that, The inspection device adopts a gantry structure and is installed inside the housing of the equipment to be inspected. The gantry structure includes a longitudinal axis guide rail arranged along the length of the housing and a transverse axis guide rail arranged along the width of the housing. The longitudinal axis guide rail is fixedly installed on the two side walls of the housing, and the transverse axis guide rail is slidably installed on the longitudinal axis guide rail. A depth axis guide rail is installed on the transverse axis guide rail slider, and an inspection camera is installed on the depth axis guide rail slider. The inspection camera is used to acquire images of the equipment within its inspection area. Based on the inspection device, the status of the equipment to be inspected is detected to obtain detection data, including: The surface temperature of the equipment to be inspected is detected by the infrared thermal imaging component configured in the inspection camera to determine whether there is an abnormal temperature in the equipment and to generate detection data; wherein, the status detection includes equipment temperature detection.

5. The method according to claim 1, characterized in that, Based on the image of at least one device, the status of the device to be inspected is detected to obtain detection data, including: Region calibration is performed on the image of the at least one device to determine the image region of at least one item to be inspected in the device to be inspected; Obtain the current state value of the at least one detectable item as a representation of the image region of the at least one detectable item; The current state value is compared with the preset state value or the target state value to determine whether the item to be inspected is in an abnormal state and to generate detection data; wherein, the target state value is the default value when the device to be inspected is being inspected for the first time, and is the historical state value when it is not being inspected for the first time.

6. The method according to claim 5, characterized in that, The status detection includes at least one of device indicator light status detection, circuit breaker status detection, and network port status detection. The image area of ​​the at least one item to be detected includes at least one second image area of ​​the indicator light, at least one third image area of ​​the circuit breaker, and / or at least one fourth image area of ​​the network port. The item to be detected is the indicator light, the circuit breaker, and / or the network port. The step of determining whether the item to be detected is in an abnormal state and generating detection data includes: Determine whether the indicator light color is normal, whether the air switch is in the open or closed state, and / or whether the network port is in the connected state, and generate detection data.

7. An intelligent inspection device for railway communication base stations, characterized in that, include: The acquisition unit is used to control the inspection device to acquire images of the equipment to be inspected in the communication base station and obtain at least one equipment image. The detection unit is used to detect the status of the equipment to be inspected based on the image of at least one device and / or the inspection device, and obtain detection data. The identification unit is configured to determine the identification code pre-attached to the device to be inspected based on the at least one device image, and to parse the preset identifier contained in the identification code; wherein the identification code is a batch-pre-generated standard code; A storage unit is used to store the detection data or the inspection data generated based on the detection data into a data table associated with the device identifier; wherein, the preset identifier and the device identifier have a mapping relationship, and the device identifier is an identity identifier assigned to the device to be inspected for use throughout its entire life cycle; Among them, the intelligent inspection device is also used for: Determine whether the identification code has an associated image; wherein, the associated image refers to a historical device image of the device to be inspected that is associated with the identification code and contains the identification code; if the identification code does not have an associated image, use the current device image containing the identification code in the at least one device image as the associated image; or, if the identification code has an associated image, use the current device image as the associated image in response to the switching operation of the associated image.

8. An electronic device, characterized in that, include: Memory; processor; as well as Computer programs; The computer program is stored in the memory and configured to be executed by the processor to implement the intelligent inspection method for railway communication base stations as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent inspection method for railway communication base stations as described in any one of claims 1 to 6.

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