Device deployment and long-term self-maintenance method and device, computer device, computer readable storage medium and computer program product

Abstract

The application relates to a device deployment and long-term self-maintenance method, device, computer equipment, computer readable storage medium and computer program product. The method comprises the following steps: obtaining a device running state, an installation relationship state, a calibration reference state and a reference archive state of a measuring device; determining an installation relationship parameter of the measuring device according to the installation relationship state, comparing the installation relationship parameter with a standard installation state of the measuring device, and obtaining a deployment health state of the measuring device; establishing a calibration reference archive of the measuring device according to the calibration reference state and the reference archive state; analyzing the device running state to obtain a component health state of the measuring device; performing device health self-maintenance or calibration maintenance on the measuring device according to the component health state, the deployment health state and the calibration reference archive, and outputting a maintenance action result. The application can improve the efficiency and accuracy of device maintenance.

Description

Technical Field

[0001] This application relates to the field of operation and maintenance technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for equipment deployment and long-term self-maintenance. Background Technology

[0002] With the rapid development of intelligent manufacturing, intelligent security, and automated inspection, sensing devices such as visual measurement equipment, depth cameras, and LiDAR are increasingly widely used in industrial production, logistics sorting, and security monitoring. These devices are typically fixedly installed on production lines, conveyor belts, supports, or walls for high-precision dimensional measurement, location positioning, or quality inspection of targets. However, the long-term operational stability and accuracy maintenance capabilities of these measuring devices have become key factors restricting their large-scale deployment.

[0003] In related technologies, measuring equipment enters a long-term continuous operation state after on-site installation and initial calibration. Maintenance strategies typically employ periodic manual inspections or time-based periodic maintenance. These methods suffer from low equipment maintenance efficiency and accuracy. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for equipment deployment and long-term self-maintenance that can improve the efficiency and accuracy of equipment maintenance, in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a method for equipment deployment and long-term self-maintenance, including:

[0006] Acquire the equipment operating status, installation relationship status, calibration reference status, and reference file status of the measuring equipment;

[0007] The installation relationship parameters of the measuring device are determined based on the installation relationship status, and the installation relationship parameters are compared with the standard installation status of the measuring device to obtain the deployment health status of the measuring device.

[0008] Based on the calibration reference status and the reference file status, a calibration reference file for the measuring equipment is established; the calibration reference file includes a feature template of the reference object of the measuring equipment and calibration baseline data corresponding to the standard observation data;

[0009] The operating status of the equipment is analyzed to obtain the health status of the components of the measuring equipment;

[0010] Based on the component health status, the deployment health status, and the calibration reference file, the measuring device performs device health self-maintenance or calibration maintenance, and outputs maintenance action results; wherein, the calibration maintenance includes at least one of generating calibration maintenance parameters based on the reference observation deviation, refreshing the calibration baseline data in the calibration reference file, or forming a calibration refresh status, and the device health self-maintenance includes at least one of isolating faulty components based on the component health status, limiting the function of the measuring device, or switching the operating mode of the measuring device.

[0011] Secondly, this application also provides a device for equipment deployment and long-term self-maintenance, the device comprising:

[0012] The status acquisition module is used to acquire the equipment operating status, installation relationship status, calibration reference status, and reference file status of the measuring equipment.

[0013] The installation relationship assessment module is used to determine the installation relationship parameters of the measuring device based on the installation relationship status, compare the installation relationship parameters with the standard installation status of the measuring device, and obtain the deployment health status of the measuring device.

[0014] The calibration reference file maintenance module is used to establish a calibration reference file for the measuring device based on the calibration reference status and the reference file status.

[0015] The analysis module is used to analyze the operating status of the equipment and obtain the health status of the components of the measuring equipment;

[0016] The maintenance action execution module is used to perform device health self-maintenance or calibration maintenance on the measuring device based on the component health status, the deployment health status, and the calibration reference file, and output the maintenance action results.

[0017] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps included in any of the foregoing method embodiments.

[0018] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps included in any of the foregoing method embodiments.

[0019] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps included in any of the foregoing method embodiments.

[0020] The aforementioned equipment deployment and long-term self-maintenance method, apparatus, computer equipment, computer-readable storage medium, and computer program product acquire the equipment operating status, installation relationship status, calibration reference status, and reference file status of the measuring equipment; determine the installation relationship parameters of the measuring equipment based on the installation relationship status, compare the installation relationship parameters with the standard installation status of the measuring equipment to obtain the deployment health status of the measuring equipment; establish a calibration reference file for the measuring equipment based on the calibration reference status and the reference file status; the calibration reference file includes feature templates of the reference objects of the measuring equipment and calibration baseline data corresponding to the standard observation data; analyze the equipment operating status to obtain the component health status of the measuring equipment; and based on the component health status, the deployment health status, and the calibration reference file, [the following steps are taken to determine the deployment health status of the measuring equipment]. The measuring equipment performs self-maintenance or calibration maintenance and outputs maintenance action results. The calibration maintenance includes at least one of generating calibration maintenance parameters based on the reference observation deviation, refreshing the calibration baseline data in the calibration reference file, or forming a calibration refresh status. The self-maintenance includes at least one of isolating faulty components based on the component health status, limiting the functions of the measuring equipment, or switching the operating mode of the measuring equipment. It can autonomously sense abnormalities, detect drift, and analyze health status during operation, and perform corresponding maintenance operations based on the analysis results. This solves the problems of response delay, high cost, and inconsistent standards caused by the passive maintenance mode that relies on periodic manual inspections or fault codes in related technologies. It achieves proactive prevention and early intervention of the equipment's "gray zone state," significantly improving the long-term operational reliability of the measuring equipment. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is an application environment diagram of the device deployment and long-term self-maintenance method in one embodiment;

[0023] Figure 2 This is a flowchart illustrating the device deployment and long-term self-maintenance method in one embodiment;

[0024] Figure 3 This is a structural block diagram of the equipment deployment and long-term self-maintenance device in one embodiment;

[0025] Figure 4This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0027] Before describing the embodiments of this application, the relevant technologies and their existing problems will be further explained:

[0028] In related technologies, equipment maintenance typically relies on maintenance personnel arriving at the installation site at fixed intervals (e.g., monthly or quarterly) to check the installation posture and measurement accuracy of the equipment using specialized testing tools (e.g., levels, laser rangefinders, and gauge blocks). If loose installation or measurement deviations are found, manual adjustments and recalibration are performed. Some equipment also employs self-diagnostic technology, capable of detecting internal component failures (e.g., sensor malfunctions, communication interruptions) and outputting fault codes to prompt maintenance personnel for repair or replacement.

[0029] The above-mentioned solutions have the following problems: First, the relevant technologies lack the ability to continuously sense the installation status of the equipment. During long-term operation, due to vibration, temperature changes, human contact, or foundation settlement, the installation height, installation distance, and equipment posture may experience slight but continuous shifts. Such changes in physical installation often cannot be detected by the equipment's own routine self-testing procedures, because routine self-testing usually only focuses on whether components have failed rather than whether installation parameters have shifted. This results in the equipment appearing to be operating normally, but in reality, the measured data is no longer accurate, i.e., it has fallen into a gray area state of "still operating but no longer reliable".

[0030] Second, the relevant technologies lack an active drift detection mechanism for the measurement accuracy of the equipment. When the lens focal length of the equipment expands and contracts due to temperature changes, or when the performance of the image sensor degrades due to long-term use, deviations will occur between the imaging parameters of the equipment and the actual physical state. Since there is no effective reference standard for comparison, these accuracy drifts are often only discovered after obvious anomalies appear in the measurement results, by which time a large amount of unreliable measurement data has already been generated.

[0031] Third, the related technologies disconnect between installation status monitoring and component health management. Existing solutions either focus only on hard component failures (such as whether a sensor has completely failed) or rely solely on manual inspections to assess installation status, lacking a unified maintenance framework that can simultaneously integrate installation status deviations, reference object measurement deviations, and component health status. Fourth, the triggering methods for equipment maintenance in these technologies are rather passive. Whether it's periodic manual inspections or fault code-based maintenance, they are reactive rather than proactive prevention. Manual inspections suffer from long cycles, high costs, and incomplete coverage, and different maintenance personnel have subjective differences in their inspection standards; while fault codes are only triggered when a component has already failed or is about to fail, making it impossible to intervene in the early stages when accuracy has just begun to drift.

[0032] Therefore, there is a need for a device maintenance method that can proactively sense changes in the device's installation status, automatically detect measurement accuracy drift, and make comprehensive decisions based on multi-dimensional information. This is to address the gray area problem in related technologies where the device is "still operational but no longer reliable," thereby improving the long-term operational reliability and measurement accuracy consistency of the measuring device.

[0033] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0034] The device deployment and long-term self-maintenance method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or located in the cloud or on other network servers. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, projection devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Head-mounted devices can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0035] In one exemplary embodiment, such as Figure 2 As shown, a method for equipment deployment and long-term self-maintenance is provided, which can be applied to... Figure 1 Taking terminal 102 or server 104 as an example, the following steps are included:

[0036] Step 202: Obtain the equipment operation status, installation relationship status, calibration reference status, and reference file status of the measuring equipment.

[0037] The measuring equipment can be intelligent visual measuring devices deployed in scenarios such as factories, warehouses, and shopping malls. Examples include 3D cameras for measuring package dimensions, industrial cameras for monitoring production lines, or intelligent cameras for security monitoring. During operation, the measuring equipment periodically or in response to triggered events (such as power-on, periodic self-tests, and maintenance instructions) collects its own installation status and equipment operating status.

[0038] The device operating status is used to characterize the current working status of each functional module within the measuring device. It is obtained by the measuring device through reading internal registers, calling diagnostic interfaces, or parsing system logs. The device operating status can include self-test results of each component, error logs, and cumulative runtime. Self-test results include the health status of the sensing unit, the light source brightness decay value, and the remaining capacity of the storage unit; error logs include records of recent errors such as connection timeouts and exposure anomalies.

[0039] The installation relationship status characterizes the deployment location and attitude information of the measuring equipment in physical space. The installation relationship status can include the actual installation height, actual installation distance, and actual equipment attitude relative to a reference plane (such as the ground or wall). The actual installation height is measured in meters or centimeters, the actual installation distance is the nominal distance between the measuring equipment and the measured area, and the actual equipment attitude includes pitch, yaw, and roll angles, measured in degrees. This information can be obtained through the equipment's built-in attitude sensors (such as a six-axis inertial measurement unit), ranging units (such as a laser ranging module), or visual calibration algorithms. For example, suppose a smart volumetric measuring camera is installed above a conveyor belt. Its built-in attitude sensor can detect the camera's pitch, yaw, and roll angles in real time, and the ranging unit can measure the vertical height of the camera lens from the conveyor belt surface.

[0040] The calibration reference status characterizes the current calibration-related status of the measuring equipment. It can include the difference between the most recent maintenance time and the current time, whether calibration cycle conditions are met, and consistency deviation status. The most recent maintenance time records the timestamp of the last calibration maintenance performed on the measuring equipment. The calibration cycle conditions are determined based on the difference between the most recent maintenance time and the current time, as well as a preset cycle threshold. The consistency deviation condition indicates whether the current installation attitude offset or the observed offset of the reference object exceeds a preset threshold.

[0041] Reference file status is used to characterize the status information of the calibration reference file itself for the measuring equipment. Reference file status can include the file version, validity status, storage location, and last update timestamp. Specifically, the file version identifies the iterative version of the calibration reference file, the validity status indicates whether the file is currently available (e.g., whether it is expired or damaged), and the storage location can be an address pointing to the measuring equipment's local storage or a remote maintenance server.

[0042] Component health status characterizes the operational reliability and availability of various functional components within a measuring device. Component health status can be obtained by parsing component self-test codes in the device's operating status, identifying components with abnormal self-test codes (i.e., returning error codes or warning codes) as abnormal components. Component health status can also be obtained from the device's error log, identifying components with repeated error records exceeding a preset number as abnormal components. For example, component health status may include one or more of the following: sensing component health level, light source component health level, attitude detection component health level, storage component health level, and communication component health level.

[0043] Step 204: Determine the installation relationship parameters of the measuring device based on the installation relationship status, and compare the installation relationship parameters with the standard installation status of the measuring device to obtain the deployment health status of the measuring device.

[0044] The installation relationship parameters are a set of parameters formed based on the actual installation height, actual installation distance, and actual equipment posture in the installation relationship state. These parameters may include at least one of the following: installation reference angle, installation reference distance, installation offset, and posture offset. Specifically, the height deviation is determined based on the difference between the actual installation height and the standard installation height; the distance deviation is determined based on the difference between the actual installation distance and the standard installation distance; and the posture offset is determined based on the difference between the actual equipment posture and the standard equipment posture.

[0045] Standard installation conditions are pre-recorded measurement equipment installation positions and attitude parameters that serve as a comparison benchmark. Standard installation conditions may include standard installation height, standard installation distance, and standard equipment attitude. The specific values ​​for standard installation conditions may come from factory installation parameters recorded when the measurement equipment leaves the factory, acceptance installation parameters confirmed and saved by engineers during installation and acceptance, or calibration refresh parameters saved after the most recent successful calibration and maintenance.

[0046] Deployment health results are assessments characterizing the degree of deviation between the current installation state and the standard installation state of a measuring device. Depending on the degree of deviation, deployment health results can include at least one of the following: normal deployment, slight deviation, requiring recalibration, requiring maintenance, or requiring degraded operation. For example, suppose a measuring device has a standard installation height of 3.00 meters and a standard device attitude of 0 degrees pitch. If the currently perceived actual installation height is 2.95 meters and the actual device attitude is 1 degree pitch, then the height deviation is -0.05 meters, and the attitude deviation is +1 degree. If the height deviation exceeds a preset height deviation threshold (e.g., 0.02 meters), the deployment health result is determined to be "recalibration required."

[0047] Step 206: Establish a calibration reference file for the measuring device based on the calibration reference status and the reference file status.

[0048] The calibration reference file is a collection of data used for equipment maintenance and calibration reference, stored in the local memory of the measuring equipment or a remote maintenance server. The calibration reference file contains feature templates of reference objects and calibration baseline data corresponding to standard observation data. A reference object is an external object independent of the measuring equipment, possessing stable and identifiable characteristics; examples include a checkerboard calibration board, a circular array calibration board, a reference object with target geometric features, a fixed positional object in the scene, or an active light source marker.

[0049] Specifically, the difference between the most recent maintenance time and the current time in the calibration reference status determines whether the calibration cycle condition is met. When the calibration cycle condition is met, or when the consistency deviation condition in the calibration reference status indicates that the current installation attitude offset or the reference object observation offset exceeds a preset threshold, the process of establishing or updating the calibration reference file is triggered.

[0050] The method for creating a calibration reference file can also be determined based on the file version and validity status in the reference file status. When the reference file status indicates that the calibration reference file does not exist or has expired, the initial creation method is used, that is, the characteristic data of the reference object is collected from scratch and the file is built. When the reference file status indicates that the calibration reference file exists and is valid but the version is lower than the latest version, the incremental update method is used, that is, only the changed data is updated.

[0051] When establishing or updating a calibration reference file, actual observation data of the reference object is acquired and compared with standard observation data of the reference object in its standard installation state to obtain the reference observation deviation. Actual observation data may include one or more of the following: actual imaging position, actual imaging size, actual imaging brightness, actual physical distance, or actual physical angle of the reference object. Standard observation data correspondingly includes the reference imaging position, reference imaging size, reference imaging brightness, reference physical distance, or reference physical angle.

[0052] Based on the reference observation deviation, a feature template for the reference object and calibration baseline data corresponding to the standard observation data are determined. The feature template is used to identify and locate the reference object during subsequent calibration maintenance, while the calibration baseline data serves as a comparison benchmark to determine whether the measurement system has drifted. After determination, the feature template and calibration baseline data are stored in the calibration reference archive according to the determined establishment method, and the archive's version information and last maintenance time are updated.

[0053] Step 208: Analyze the operating status of the equipment to obtain the health status of the components of the measuring equipment.

[0054] The system analyzes the component self-test codes in the equipment's operating status, identifying components with abnormal self-test codes as faulty components. For example, if the attitude sensor returns an error code instead of a normal code, the attitude sensor is identified as a faulty component. It can also analyze the error logs in the equipment's operating status, counting the frequency of error records for each component within a preset time window, identifying components with repeated error records exceeding a preset number as faulty components. For example, if the light source driver module has 15 "current instability" error records in the last 24 hours, the light source driver module is identified as a faulty component.

[0055] Based on the identified abnormal components, a health rating can be generated for each component. For example, the health rating can include three levels: Good, Warning, and Critical. Components with no recorded abnormalities are marked as Good; components with occasional error records that do not affect the main functions are marked as Warning; and components with persistent error records or that are completely faulty are marked as Critical.

[0056] Step 210: Based on the component health status, the deployment health status, and the calibration reference file, perform device health self-maintenance or calibration maintenance on the measuring device, and output the maintenance action results.

[0057] Equipment maintenance includes two branches: equipment health self-maintenance and calibration maintenance. Different maintenance branches can be triggered based on the health status of components, deployment health status, and information in the calibration reference file.

[0058] Calibration maintenance is triggered when the installation status deviation of the deployed health status indicator measurement equipment exceeds a preset installation deviation threshold, or when the consistency deviation condition in the calibration reference file indicates that the reference observation deviation exceeds a preset calibration deviation threshold, or when the calibration cycle condition in the calibration reference file indicates that the time since the last calibration maintenance exceeds a preset cycle threshold. During calibration maintenance, calibration maintenance parameters are generated based on the reference observation deviation. These parameters may include at least one of the following: a height compensation coefficient for compensating for installation height deviation, a distance compensation coefficient for compensating for installation distance deviation, and an attitude compensation matrix for compensating for attitude offset. The calibration baseline data in the calibration reference file is refreshed based on these calibration maintenance parameters, and the refreshed calibration baseline data, along with the updated version information, is stored in the calibration reference file to form a calibration refresh status.

[0059] When the component health status indicates a component malfunction in the measuring device, device health self-maintenance is triggered. Component malfunctions can include one or more of the following: sensing component malfunction, light source component malfunction, attitude detection component malfunction, storage component malfunction, or communication component malfunction. During device health self-maintenance, the malfunctioning component is marked as unavailable, causing the measuring device to skip calls to that component in subsequent operations. Simultaneously, measurement functions dependent on the malfunctioning component are disabled, the measuring device's operating mode is switched from normal mode to degraded operating mode, and a degraded status indicator is output in degraded operating mode.

[0060] When performing calibration maintenance, the maintenance action results may include calibration completion status and updated version information of the calibration reference file. When performing equipment health self-maintenance, the maintenance action results may include at least one of the following: abnormal component identification, degraded status identification, and maintenance prompt information. Maintenance action results can be output to the local maintenance management interface of the measuring equipment for on-site maintenance personnel to view, or they can be sent to a remote maintenance server for centralized monitoring and alarms.

[0061] Through this embodiment, the measuring device can autonomously sense the installation relationship status, calibration reference status, and component health status, establish and maintain calibration reference files, and make comprehensive decisions based on multi-dimensional information to execute targeted maintenance operations. This avoids the gray zone state of the device that is "still operational but no longer reliable" in traditional technologies, and realizes a unified technology chain of device installation status perception, calibration reference file maintenance, and device health self-maintenance, which significantly improves the long-term operational reliability and maintenance efficiency of the measuring device.

[0062] In some embodiments, the installation relationship state includes the actual installation height, actual installation distance, and actual device posture of the measuring device; the standard installation state includes the standard installation height, standard installation distance, and standard device posture; determining the installation relationship parameters of the measuring device based on the installation relationship state, and comparing the installation relationship parameters with the standard installation state of the measuring device to obtain the deployment health status of the measuring device includes:

[0063] The standard installation status is determined based on at least one of the following: the factory installation status recorded when the measuring device leaves the factory, the acceptance installation status recorded when the measuring device is installed and accepted, and the calibration refresh status recorded when the measuring device was last successfully calibrated.

[0064] Determine at least one of the following: the height deviation between the actual installation height and the standard installation height, the distance deviation between the actual installation distance and the standard installation distance, and the attitude offset between the actual equipment attitude and the standard equipment attitude;

[0065] The installation status deviation of the measuring device is determined based on at least one of the height deviation, distance deviation, and attitude offset, and the deployment health status is determined based on the installation status deviation.

[0066] Factory installation status refers to the installation parameters recorded by production equipment or quality control personnel after the measuring equipment has completed production and pre-shipment calibration at the manufacturing plant. Specifically, in the final inspection stage before shipment, the equipment is placed at a standard workstation, and its installation height, installation distance, and equipment attitude are recorded using automated measuring equipment (such as laser trackers or coordinate measuring machines) or manual readings. These parameters are written into the equipment's non-volatile memory (such as EEPROM or flash memory) as the factory installation status and accompany the equipment out of the factory. For example, when a smart volumetric measuring camera leaves the factory, its standard installation height is recorded as 3.00 meters, its standard installation distance as 2.50 meters, and its standard equipment attitude as pitch angle 0 degrees, yaw angle 0 degrees, and roll angle 0 degrees (i.e., the lens plane is parallel to the conveyor belt plane). These factory installation statuses serve as the initial benchmark for subsequent comparisons and judgments.

[0067] Acceptance installation status refers to the confirmation and entry of installation parameters into the system by the installation engineer or maintenance personnel during the acceptance process after the measuring equipment has been physically installed at the final use site. Specifically, after the equipment is deployed to the user site (such as a factory production line or warehouse sorting area) and mechanically fixed, the installation engineer uses professional tools such as a level, laser rangefinder, and inclinometer to measure the actual installation height, installation distance, and equipment orientation. The measurement results are then entered into the equipment via a maintenance terminal (such as a laptop or tablet) or uploaded to a remote management platform and saved as the acceptance installation status. For example, a logistics sorting center installed a volume measuring camera above a conveyor belt. After installation, the engineer used a laser rangefinder to measure the height of the camera lens from the conveyor belt surface as 3.02 meters and used an electronic inclinometer to measure the camera's pitch angle as 0.2 degrees. These measurements are entered into the system and saved as the acceptance installation status. Since on-site installation conditions may differ from the factory standard workstation (e.g., the conveyor belt height is not exactly equal to the nominal value), the acceptance installation status usually reflects the actual deployment of the equipment on site better than the factory installation status, and is therefore often used as the benchmark for subsequent maintenance.

[0068] Calibration refresh status refers to the process by which a measuring device saves its installation state at the time of a successful calibration maintenance, using it as a new comparison benchmark. Specifically, after the device completes a calibration maintenance process (e.g., automatic calibration based on a reference object) and the calibration results are verified, the currently acquired actual installation height, actual installation distance, and actual device attitude are written into memory as the calibration refresh status, overwriting or supplementing the original standard installation state. For example, after six months of operation, a measuring device's installation height may drop from 3.00 meters to 2.98 meters due to slight support loosening. After performing automatic calibration maintenance, the device successfully updates the imaging parameters and restores measurement accuracy. At this point, the device saves 2.98 meters as the new calibration refresh status. In subsequent operations, the device will use 2.98 meters, instead of the original 3.00 meters, as the standard installation height for deviation comparison. This design avoids frequent triggering of invalid calibration maintenance due to permanent installation offsets (such as foundation settlement), improving the system's adaptability.

[0069] Installation state deviation refers to the difference between the current installation state and the standard installation state as defined above. Installation state deviation is obtained by arithmetic subtraction of each component in the installation state with the corresponding component in the standard installation state. Height deviation is the difference between the current actual installation height and the standard installation height. The actual installation height is read from the installation state, and the standard installation height is read from the standard installation state. The difference between the actual installation height and the standard installation height is calculated to obtain the height deviation. The unit of height deviation is the same as the unit of installation height (e.g., meters or centimeters), and can be positive (indicating the actual installation position is higher than the standard height) or negative (indicating the actual installation position is lower than the standard height). For example, assuming the standard installation height of the equipment is 3.00 meters, and the currently perceived actual installation height is 2.95 meters, then the height deviation = 2.95 meters - 3.00 meters = -0.05 meters, indicating that the equipment has sunk 5 centimeters.

[0070] Distance deviation refers to the difference between the actual installation distance and the standard installation distance. The actual installation distance (e.g., the nominal distance between the measuring device's lens and the target) is read from the installation relationship status, and the standard installation distance is read from the standard installation status. The difference between the actual and standard installation distances is calculated to obtain the distance deviation. For example, assuming the standard installation distance is 2.50 meters and the currently perceived actual installation distance is 2.53 meters, then the distance deviation = 2.53 meters - 2.50 meters = +0.03 meters, indicating that the device is 3 centimeters further from the target than the standard position.

[0071] Attitude offset refers to the difference between the current actual equipment attitude and the standard equipment attitude. Equipment attitude is usually represented by Euler angles (pitch, yaw, and roll) or quaternions. The actual equipment attitude is read from the installation relationship state, and the standard equipment attitude is read from the standard installation state. The difference in rotation angles between the two is calculated to obtain the attitude offset. The attitude offset can be decomposed into three components: pitch offset, yaw offset, and roll offset, each measured in degrees. For example, suppose the standard equipment attitude is 0 degrees pitch, 0 degrees yaw, and 0 degrees roll (i.e., the lens plane is parallel to the ground, and the optical axis is perpendicular downwards). The currently perceived actual equipment attitude is 1 degree pitch, 0.5 degrees yaw, and 0 degrees roll. Then the attitude offset includes: pitch offset = +1 degree, yaw offset = +0.5 degrees, and roll offset = 0 degrees.

[0072] Installation status deviation can include at least one of the above-mentioned height deviation, distance deviation, and attitude offset. Specifically, in subsequent maintenance decisions, one or more of the above deviations can be selected as installation status deviations based on the sensitivity requirements of the application scenario. For example, for devices whose primary function is height measurement (such as volumetric cameras that measure the height of packages), the impact of height deviation is the most significant, and only height deviation can be considered as installation status deviation, triggering calibration measurements when the height deviation exceeds a threshold. For devices whose primary function is distance measurement (such as laser rangefinders), the impact of distance deviation is the most significant, and only distance deviation can be considered as installation status deviation. For devices requiring precise spatial positioning (such as robot vision guidance systems), installation height, installation distance, and attitude all have a significant impact on measurement accuracy, and all three can be included in the installation status deviation, triggering subsequent calibration procedures when any dimension exceeds a threshold.

[0073] Deployment health status is an assessment result characterizing the degree of deviation between the current installation state of a measuring device and its standard installation state. It is determined based on the magnitude of the installation state deviation and the severity of exceeding thresholds. Deployment health status can include at least one of the following: normal deployment, slight deviation, requiring recalibration, requiring maintenance, or requiring degraded operation. Specifically, when none of the deviations in the installation state exceed their corresponding preset thresholds, the deployment health status is determined to be normal, indicating that the current installation state of the measuring device is basically consistent with the standard installation state, requiring no maintenance. When any deviation exceeds the corresponding slight deviation threshold but not the recalibration threshold, the deployment health status is determined to be slight deviation, indicating that a noticeable but not yet serious change has occurred in the installation state of the measuring device; this status can be recorded and await subsequent periodic verification. When any deviation exceeds the corresponding recalibration threshold, the deployment health status is determined to be requiring recalibration, indicating that the installation deviation of the measuring device may have affected measurement accuracy, requiring calibration maintenance. When multiple deviations in the installation state significantly exceed thresholds or when there are abnormalities in the component health status indications, the deployment health status can be determined to be requiring maintenance or degraded operation. For example, suppose the preset height deviation threshold is 0.02 meters. If the standard installation height of a measuring device is 3.00 meters, and the current actual installation height is 2.95 meters, then the height deviation is -0.05 meters, exceeding the 0.02-meter threshold. Based on this height deviation, the deployment health status is determined to require recalibration, and a calibration maintenance process will be triggered. If the height deviation of another measuring device is only -0.01 meters, which does not exceed the threshold, then the deployment health status is determined to be normal, and no maintenance operation is required.

[0074] This embodiment provides a multi-layered reference system for measuring equipment by explicitly stating that the standard installation state can be derived from at least one of the following: factory installation record, acceptance record, or calibration refresh record. Specifically, the factory installation state provides the initial reference of the equipment under ideal conditions; the acceptance installation state reflects the actual reference of the equipment in the actual deployment site; and the calibration refresh state allows the equipment to adaptively adjust the reference after undergoing permanent changes. This multi-layered reference design enables the equipment to use the factory reference during initial deployment, switch to the acceptance reference after field installation, and automatically refresh the reference during long-term operation, thereby avoiding frequent false triggers or missed triggers caused by the reference not matching the actual situation.

[0075] In some embodiments, the calibration reference profile includes a feature template of a reference object of the measuring device and calibration baseline data corresponding to the standard observation data; establishing the calibration reference profile of the measuring device based on the calibration reference state and the reference profile state includes:

[0076] Based on the difference between the most recent maintenance time and the current time in the calibration reference state, determine whether the calibration cycle condition is met;

[0077] When the calibration cycle condition is met, or when the consistency deviation condition in the calibration reference state indicates that the current installation attitude offset or the reference object imaging offset exceeds a preset threshold, the process of establishing or updating the calibration reference file is triggered.

[0078] Based on the file version and validity status in the reference file status, the method for establishing the calibration reference file is determined; wherein, when the reference file status indicates that the calibration reference file does not exist or has expired, the initial establishment method is adopted; when the reference file status indicates that the calibration reference file exists and is valid but the version is lower than the latest version, the incremental update method is adopted.

[0079] Obtain the actual observation data of the reference object, and compare the actual observation data with the standard observation data of the reference object under standard installation conditions to obtain the reference observation deviation;

[0080] The feature template of the reference object and the calibration baseline data corresponding to the standard observation data are determined based on the reference observation deviation, and stored in the calibration reference archive according to the establishment method.

[0081] After creation or update, update the version information and last maintenance time of the calibration reference file. The calibration reference status is a set of information characterizing the current calibration-related status of the measuring equipment. The calibration reference status may include at least one of the following: last maintenance time, calibration cycle conditions, and consistency deviation conditions. The last maintenance time refers to the timestamp of the last calibration maintenance or calibration reference file update performed on the measuring equipment, recorded in absolute time form. Obtain the current system time and calculate the time difference between the current time and the last maintenance time; the unit of this difference can be days, hours, or minutes.

[0082] The calibration cycle condition is used to determine whether periodic calibration and maintenance are required. The calculated time difference is compared to a preset calibration cycle threshold. The calibration cycle threshold is a pre-set time length based on the accuracy retention capability of the measuring equipment and the usage environment; for example, it can be set to 30 days, 90 days, or a value dynamically adjusted according to the equipment's usage frequency. When the time difference is greater than or equal to the calibration cycle threshold, the calibration cycle condition is met, indicating that the measuring equipment has been running for a sufficient period and requires periodic calibration. When the time difference is less than the calibration cycle threshold, the calibration cycle condition is not met. For example, assuming the most recent maintenance record is May 1, 2026, the current time is June 1, 2026, and the preset calibration cycle threshold is 30 days, then the time difference is 31 days, which is greater than 30 days, and the calibration cycle condition is met.

[0083] A conformity deviation condition is a criterion used to determine whether there is a significant difference between the current state of a measuring device and the reference state in the calibration reference file. A conformity deviation condition may include at least one of an installation attitude conformity condition and a reference object imaging conformity condition.

[0084] The installation posture consistency condition is determined by comparing the current installation posture with the standard installation posture. The current installation posture of the measuring device is acquired, and its posture offset from the standard installation posture is calculated. This posture offset is then compared with a preset posture offset threshold. When the posture offset exceeds the posture offset threshold, the installation posture consistency condition is met, indicating that the measuring device may have been knocked askew or the support may have tilted.

[0085] The reference object imaging consistency condition is determined by comparing the currently acquired reference object imaging data with the standard observation data in the calibration reference file. Actual observation data of the reference object in its current state is acquired, including actual imaging position, actual imaging size, or actual imaging brightness. This actual observation data is compared with the standard observation data stored in the calibration reference file, and the corresponding observation deviation is calculated. When any of the observation deviations exceeds a preset observation deviation threshold, the reference object imaging consistency condition is met, indicating that the imaging system of the measuring equipment may have experienced a change in focal length or aging of the photosensitive element.

[0086] The calibration reference file creation or update process is triggered when either the calibration cycle condition or any of the aforementioned consistency deviation conditions is met. This dual-condition triggering mechanism ensures that the calibration reference file is proactively maintained within a predetermined time period and promptly updated when abnormal deviations are detected. The reference file status is a set of information characterizing the condition of the calibration reference file itself. The reference file status may include at least one of the following: file version, validity status, storage location, and most recent update timestamp.

[0087] The file version is an identifier used to identify iterative versions of the calibration reference file. For example, it can use a major version number followed by a minor version number, such as V1.0, V1.1, and V2.0. The version number increments each time the calibration reference file is updated. The validity status is a flag indicating whether the calibration reference file is currently available. The validity status can include several values ​​such as valid, invalid, or expired. When the calibration reference file exists, the data is complete, and it has not exceeded a preset validity period, the validity status is marked as valid. When the calibration reference file is damaged, the data is incomplete, or the version is too low, the validity status is marked as invalid.

[0088] The system reads the file version and validity status from the reference file status and determines the method for establishing the calibration reference file based on these two pieces of information. When the reference file status indicates that the calibration reference file does not exist (i.e., the device has never established a calibration reference file) or the validity status is invalid, the initial establishment method is used. The initial establishment method means collecting the characteristic data of the reference object from scratch and constructing a complete calibration reference file, including obtaining all characteristic templates and calibration baseline data of the reference object.

[0089] When the reference profile status indicates that the calibration reference profile exists and is valid, but the profile version is lower than the latest version (e.g., version V1.0 is stored on the device, while version V2.0 exists on a remote server), an incremental update method is used. Incremental updates only acquire the data that has changed since the last update; for example, only updating the offset calibration baseline data while retaining unchanged feature template data, thereby reducing data transfer volume and processing time. The reference object is an external object with stable, identifiable features, independent of the measurement device. Exemplarily, the reference object can be one or more of the following: a checkerboard calibration board, a circular array calibration board, a reference object with target geometry, a fixed positional object in the scene, or an active light source marker.

[0090] Actual observation data refers to the observation values ​​obtained by the measuring equipment in the current state when measuring the reference object. It may include one or more of the following: the actual imaging position of the reference object (represented by pixel coordinates), the actual imaging size (represented by pixel width and height), the actual imaging brightness (represented by grayscale value or lumen value), the actual physical distance (in meters), or the actual physical angle (in degrees).

[0091] Standard observation data are benchmark observations obtained by measuring the same reference object under standard installation conditions. They are either pre-stored in the measuring equipment's memory or acquired externally. Standard observation data correspondingly includes one or more of the following: reference imaging position, reference imaging size, reference imaging brightness, reference physical distance, or reference physical angle.

[0092] The reference observation bias is obtained by performing arithmetic subtraction or proportional calculation between each component in the actual observation data and the corresponding component in the standard observation data. The reference observation bias may include one or more of the following: positional bias (actual imaging position minus reference imaging position), size bias (actual imaging size minus reference imaging size), brightness bias (actual imaging brightness minus reference imaging brightness), distance bias (actual physical distance minus reference physical distance), or angle bias (actual physical angle minus reference physical angle).

[0093] For example, assuming the reference image size in the standard observation data is 200 pixels wide and 200 pixels high, and the actual image size in the actual observation data is 195 pixels wide and 195 pixels high, then the reference observation deviation includes -5 pixels in the width direction and -5 pixels in the height direction, which means that the image size is reduced by 2.5%.

[0094] Feature templates are descriptive data used to identify and locate reference objects during subsequent calibration and maintenance. Feature templates can include one or more of the following: a set of corner coordinates, an edge direction histogram, a set of contour points, or QR code encoding information of the reference object. The feature template is formed by extracting identifiable features of the reference object based on the reference observation bias, either by correcting the original observation data or by directly using the original observation data.

[0095] Calibration baseline data is a set of data used as a comparison benchmark to determine whether a measurement system has drifted. Calibration baseline data corresponds to standard observation data and may include one or more of the following: reference imaging position, reference imaging size, reference imaging brightness, reference physical distance, or reference physical angle. When initially established, calibration baseline data directly uses standard observation data. During incremental updates, calibration baseline data is refreshed based on reference observation deviations; for example, the original reference imaging size is updated to the current actual imaging size as the new baseline.

[0096] Depending on the setup method, the feature template and calibration baseline data are stored in the calibration reference archive. For the initial setup method, a new calibration reference archive record is created, and the feature template and calibration baseline data are written into it. For the incremental update method, only the changed data in the calibration reference archive is updated, such as only overwriting the calibration baseline data while retaining the original feature template.

[0097] Version information identifies the iterative version of the calibration reference file and may include at least one of a major version number, minor version number, and revision number. After creation or update, the version number is incremented, for example, updating V1.0 to V1.1, or V1.9 to V2.0. The last maintenance time is updated to the current system time, recording the completion time of this calibration reference file creation or update. The updated last maintenance time will be used for condition determination in the next calibration cycle. After the update is completed, the measuring equipment uses the newly created or updated calibration reference file for calibration maintenance and conformance deviation detection in subsequent operation.

[0098] This embodiment implements a dual mechanism of periodic and event-triggered establishment of the calibration reference file by determining the calibration cycle condition based on the most recent maintenance time in the calibration reference status and determining whether an abnormal offset has occurred based on the consistency deviation condition. Specifically, periodic triggering ensures that the calibration reference file is actively maintained regularly, avoiding reference obsolescence caused by long-term lack of updates; event triggering ensures that the file is updated promptly when abnormal installation posture or imaging abnormalities are detected, avoiding misjudgments caused by reference failure. The two triggering mechanisms complement each other, ensuring that the calibration reference file remains valid and accurate at all times.

[0099] This embodiment also achieves differentiated management of file creation by determining the creation method based on the file version and validity status in the reference file status. Specifically, when the file does not exist or has expired, an initial creation method is used to build a complete file from scratch; when the file exists and is valid but the version is low, an incremental update method is used to update only the changed data. This design avoids unnecessary full data transmission and processing, improves the efficiency of creating calibration reference files, and is especially suitable for scenarios with limited network bandwidth or embedded resources.

[0100] In some embodiments, the calibration maintenance includes at least one of generating calibration maintenance parameters based on the reference observation deviation, refreshing the calibration baseline data in the calibration reference file, or forming a calibration refresh status; the device health self-maintenance includes at least one of isolating faulty components based on the component health status, limiting the function of the measuring device, or switching the operating mode of the measuring device; the step of performing device health self-maintenance or calibration maintenance on the measuring device based on the component health status, the deployment health status, and the calibration reference file, and outputting the maintenance action result, includes:

[0101] When the deployment health status indicates that the installation status deviation of the measuring device exceeds a preset installation deviation threshold, or the consistency deviation condition in the calibration reference file indicates that the reference observation deviation exceeds a preset calibration deviation threshold, or the calibration cycle condition in the calibration reference file indicates that the time since the last calibration maintenance exceeds a preset cycle threshold, the calibration maintenance of the measuring device is triggered.

[0102] The calibration baseline data in the calibration reference file is refreshed according to the calibration maintenance parameters, and the refreshed calibration baseline data, together with the updated version information, is stored in the calibration reference file to form a calibration refresh status.

[0103] The calibration and maintenance triggering conditions include three situations. As long as at least one of them is met, the calibration and maintenance of the measuring equipment will be triggered.

[0104] The first triggering scenario is when the deployment health status indicator's installation deviation exceeds a preset installation deviation threshold. Deployment health status is an evaluation result generated based on a comparison of installation relationship parameters with a standard installation state. When any of the installation deviations—height deviation, distance deviation, or attitude offset—exceeds the corresponding preset installation deviation threshold, the deployment health status is determined to require recalibration or maintenance, triggering calibration maintenance. For example, assuming the preset installation deviation threshold for height deviation is 0.02 meters, if the measurement equipment's height deviation reaches -0.05 meters, exceeding the 0.02-meter threshold, calibration maintenance is triggered.

[0105] The second triggering scenario is when the consistency deviation condition in the calibration reference file indicates that the reference observation deviation exceeds a preset calibration deviation threshold. The consistency deviation condition is determined by comparing the currently acquired reference object observation data with the standard observation data in the calibration reference file. When any of the positional deviation, dimensional deviation, brightness deviation, distance deviation, or angular deviation in the reference observation exceeds the corresponding preset calibration deviation threshold, the consistency deviation condition is met, triggering calibration maintenance. For example, assuming the preset calibration deviation threshold for dimensional deviation is ±3 pixels, if the dimensional deviation in the reference observation reaches -5 pixels, exceeding the 3-pixel threshold, calibration maintenance is triggered.

[0106] The third trigger scenario is when the calibration cycle condition in the calibration reference file indicates that the time since the last calibration maintenance exceeds a preset cycle threshold. The calibration cycle condition is determined based on the difference between the most recent maintenance time in the calibration reference file and the current time. When this difference is greater than or equal to the preset cycle threshold, the calibration cycle condition is met, triggering calibration maintenance. For example, assuming the preset cycle threshold is 30 days, if the most recent maintenance time is May 1, 2026, and the current time is June 2, 2026, the time difference is 32 days, exceeding the 30-day threshold, thus triggering calibration maintenance.

[0107] The three triggering conditions described above correspond to three different maintenance needs: abnormal installation status, measurement accuracy drift, and periodic maintenance. The abnormal installation status trigger is applicable to scenarios where the equipment is physically misaligned due to a bump or loose bracket. The measurement accuracy drift trigger is applicable to scenarios where changes in lens focal length or aging of the image sensor cause shifts in imaging parameters. The periodic maintenance trigger is applicable to scenarios where the equipment has been running for a long time and requires routine checks. These three triggering conditions are independent yet complementary, together forming a complete calibration and maintenance triggering mechanism.

[0108] Reference observation deviation is the difference obtained by comparing the actual observation data of a reference object with standard observation data. It can include one or more of the following: positional deviation, dimensional deviation, brightness deviation, distance deviation, or angular deviation. Calibration and maintenance parameters are a set of corrections calculated based on the reference observation deviation to correct various deviations of the measuring equipment.

[0109] When the reference observation bias includes positional bias, the positional bias reflects the offset of the imaged position of the reference object. This offset is typically due to a change in the relative position between the image sensor and the lens optical axis of the measuring device. The positional bias is used to generate the corresponding components in the attitude compensation matrix for compensating for installation attitude offsets. Specifically, the horizontal component of the positional bias is used to generate the yaw angle compensation coefficient, and the vertical component is used to generate the pitch angle compensation coefficient.

[0110] When reference observation deviation includes dimensional deviation, the dimensional deviation reflects the scaling of the image size of the reference object. This scaling is typically due to a change in the focal length of the measuring device's lens, or due to a discrepancy between the actual working distance between the measuring device and the reference object and the standard distance. A distance compensation coefficient is generated based on the dimensional deviation to compensate for installation distance deviation. Specifically, the distance compensation coefficient is calculated based on the ratio between the reference image size and the actual image size. For example, when the actual image size is smaller than the reference image size, the distance compensation coefficient is greater than 1, indicating that the measurement distance needs to be magnified to compensate for the effect of focal length shortening.

[0111] When reference observation bias includes distance bias, the distance bias reflects the difference between the physical distance measured by the measuring equipment and the reference physical distance. This difference is usually due to a drift in the reference of the ranging module. A height compensation coefficient is generated based on the distance bias to compensate for installation height bias. Specifically, the height compensation coefficient is calculated based on the ratio between the reference physical distance and the actual physical distance. For example, when the actual physical distance is less than the reference physical distance, the height compensation coefficient is less than 1, indicating that the measurement height needs to be reduced to compensate for the drift of the ranging module.

[0112] When the reference observation bias includes angular bias, the angular bias reflects the difference between the measured angle of the reference object relative to the optical axis of the measuring device and the reference angle. This difference is usually due to drift of the device's attitude sensor or a change in the device's installation attitude. An attitude compensation matrix is ​​generated based on the angular bias to compensate for the attitude offset. Specifically, the angular bias is converted into a corresponding rotation vector or quaternion, and a rotation matrix is ​​further constructed as the attitude compensation matrix to correct the attitude measurement results.

[0113] In practical applications, corresponding calibration and maintenance parameters can be selectively generated based on the type of deviation contained in the reference observation deviation. For example, when only dimensional deviations are detected, only distance compensation coefficients can be generated, without generating attitude compensation matrices or altitude compensation coefficients.

[0114] Calibration baseline data is a set of data stored in the calibration reference archive that serves as a comparison benchmark for determining whether a measurement system has drifted. Calibration baseline data may include one or more of the following: reference imaging position, reference imaging size, reference imaging brightness, reference physical distance, or reference physical angle.

[0115] Refreshing calibration baseline data refers to updating the existing calibration baseline data stored in the calibration reference archive based on the calibration maintenance parameters. Specifically, when a distance compensation coefficient is generated, the original reference imaging size is multiplied by the distance compensation coefficient to obtain the refreshed reference imaging size, which is then used as the new calibration baseline data. When an altitude compensation coefficient is generated, the original reference physical distance is multiplied by the altitude compensation coefficient, or the current actual physical distance is directly used as the new reference physical distance. When an attitude compensation matrix is ​​generated, the original reference imaging position is transformed according to the attitude compensation matrix to obtain the refreshed reference imaging position.

[0116] After refreshing the calibration baseline data, the refreshed data is written back to the calibration reference file, overwriting the original data items. Simultaneously, the version information of the calibration reference file is incremented, for example, the version number is updated from V1.0 to V1.1, and the last maintenance time is updated to the current system time. The calibration refresh status indicates that calibration maintenance is complete and the calibration reference file has been successfully updated. Once the calibration refresh status is established, the measurement equipment will use the refreshed calibration baseline data as a comparison benchmark in subsequent operation for judging consistency deviation conditions and triggering subsequent calibration maintenance. The calibration refresh status can also be output to the maintenance management interface or remote maintenance server to record the calibration maintenance history and notify maintenance personnel that calibration is complete.

[0117] For example, suppose the lens focal length of the measuring device changes due to temperature variations, and the size deviation in the reference observation bias is -5 pixels. Based on this size deviation, a distance compensation factor of 1.025 is calculated. Then, the original reference image size (width 200 pixels, height 200 pixels) in the calibration reference file is multiplied by the distance compensation factor 1.025 to obtain the refreshed reference image size (width 205 pixels, height 205 pixels), and this refreshed image size is stored in the calibration reference file. Simultaneously, the version information is updated from V1.0 to V1.1, and the last maintenance time is updated to the current time. At this point, the calibration refresh status is established, and subsequent measurements using the device will use the new calibration baseline data for consistency assessment.

[0118] This embodiment establishes three independent calibration and maintenance trigger conditions to comprehensively cover abnormal installation status of measuring equipment, measurement accuracy drift, and periodic maintenance needs. Specifically, it deploys a physiological installation offset scenario triggered by a healthy state, an accuracy drift scenario triggered by a consistency deviation condition, and a travel maintenance scenario triggered by a calibration cycle condition. These three trigger conditions together constitute a comprehensive calibration and maintenance trigger network, ensuring that any type of deviation in the equipment can be detected in a timely manner and trigger the corresponding calibration and maintenance, avoiding missed triggers caused by an imperfect single trigger mechanism.

[0119] This embodiment also achieves targeted correction of various deviations of the measuring equipment by generating corresponding calibration and maintenance parameters according to the type of reference observation deviation. Specifically, position deviation guides the update of the attitude compensation matrix, size deviation guides the update of the distance compensation coefficient, distance deviation guides the update of the height compensation coefficient, and angle deviation guides the update of the attitude compensation matrix. This classification compensation mechanism ensures that each type of accuracy drift has a targeted correction method, avoiding inaccurate compensation or the introduction of new systematic errors that may result from using a general correction model.

[0120] In some embodiments, performing device health self-maintenance or calibration maintenance on the measuring device based on the component health status, the deployment health status, and the calibration reference file, and outputting maintenance action results, includes: triggering device health self-maintenance on the measuring device when the component health status indicates that the measuring device has a component abnormality; the component abnormality includes at least one of sensing component abnormality, light source component abnormality, attitude detection component abnormality, storage component abnormality, or communication component abnormality; the device health self-maintenance includes: marking the abnormal component as unavailable, causing the measuring device to skip calling the abnormal component in subsequent operation; and disabling measurement functions that depend on the abnormal component, switching the operating mode of the measuring device from normal mode to degraded operating mode, and outputting a degraded status identifier in the degraded operating mode.

[0121] Component health status is a set of information characterizing the operational reliability and availability of various functional components within a measurement device. Component health status is obtained by parsing component self-test codes and error logs during device operation. Component health status can include one or more of the following: sensing component health level, light source component health level, attitude detection component health level, storage component health level, and communication component health level.

[0122] Component malfunction refers to a state in which a functional component in a measuring device fails or its performance is severely degraded, rendering it unable to continue performing its designed functions normally. The system analyzes the component self-test codes in the device's operating status, identifying components with abnormal self-test codes (i.e., returning error codes or warning codes instead of the preset normal codes) as malfunctioning components. It can also analyze the error logs in the device's operating status, statistically analyze the frequency of error records for each component within a preset time window, and identify components with repeated error records exceeding a preset threshold as malfunctioning components.

[0123] Component malfunctions can include at least one of the following: sensing component malfunction, light source component malfunction, attitude detection component malfunction, storage component malfunction, or communication component malfunction. Sensing component malfunction refers to a failure in sensing elements such as image sensors, depth sensors, or ranging sensors, for example, excessive sensor output noise, too many dead pixels, or signal interruption. Light source component malfunction refers to a failure in the active light source module, for example, laser diode brightness decay, unstable LED drive current, or complete light source failure. Attitude detection component malfunction refers to a failure in attitude sensors such as inertial measurement units, electronic compasses, or inclinometers, for example, severe output data drift, unstable sampling frequency, or communication timeout. Storage component malfunction refers to a failure in storage media such as memory or flash memory, for example, read / write errors, too many bad blocks, or insufficient remaining capacity. Communication component malfunction refers to a failure in communication modules such as network interfaces, Bluetooth modules, or serial ports, for example, frequent connection drops, excessively high packet loss rate, or insufficient signal strength.

[0124] For example, suppose when parsing the self-test codes of components in the device's operating status, it is found that the attitude detection component returns error code 0x01 instead of the normal code 0x00, then it is determined that the attitude detection component is abnormal. Assuming that when parsing the error log, it is found that the light source driver module has 15 "current instability" error records in the last 24 hours, while the preset threshold is 10 times, then it is determined that the light source component is abnormal.

[0125] Equipment health self-maintenance is a type of maintenance operation distinct from calibration maintenance. Its core objective is to ensure the operational availability of the measuring equipment rather than to restore measurement accuracy. The equipment health self-maintenance process is triggered when the component health status indicates any of the aforementioned component anomalies. Unlike calibration maintenance, equipment health self-maintenance does not rely on reference objects or calibration reference files; instead, it directly operates on the abnormal components.

[0126] Marking an abnormal component as unavailable involves setting a flag in the measurement device's system configuration to indicate that the component is currently unavailable. The identifier of the abnormal component is added to a list of unavailable components, which is checked during system runtime. This list can be stored in the measurement device's volatile memory or persisted to non-volatile memory so that the marking remains after a device restart.

[0127] Specific methods to enable measuring equipment to skip calls to faulty components during subsequent operation include: adding a conditional statement before calling the component; when the component is detected as unavailable, directly returning a preset default value or error code without executing the actual component call instruction. This method avoids serious problems such as program hangs, long wait times, or system crashes caused by calling faulty components.

[0128] For example, suppose the attitude detection component is identified as an abnormal component and marked as unavailable. When the measurement equipment needs to acquire attitude data, it first checks the availability flag of the attitude detection component. If it finds that the component is marked as unavailable, it skips the reading operation of the attitude detection component and directly returns the preset default attitude values, such as pitch angle 0 degrees, yaw angle 0 degrees, roll angle 0 degrees, or returns an error code indicating that the attitude data is unavailable.

[0129] Measurement functions that depend on faulty components refer to those functions that require input data from the faulty component to function correctly during operation. Based on a pre-defined component and function dependency table, identify which measurement functions depend on faulty components marked as unavailable, and disable these functions. Dependency functions can be disabled by setting their enable flag to false or by removing their execution entry point from the function scheduler list.

[0130] For example, if the light source component is identified as an abnormal component, then the structured light depth measurement function that depends on the light source component is determined to be disabled. If the attitude detection component is identified as an abnormal component, then the image correction function that depends on the attitude data is determined to be disabled. If the sensing component is identified as an abnormal component, then all measurement functions that depend on that sensing component are determined to be disabled.

[0131] Operating mode refers to the overall state setting of a measuring device during operation. Normal mode refers to the standard operating state where all functions of the measuring device are available, all components are engaged, and the measurement output is of the highest quality. Degraded operating mode refers to a special operating state where the measuring device continues to operate even when some components are unavailable or some functions are disabled. In degraded operating mode, the measuring accuracy, measurement range, or measurement frequency of the measuring device may be reduced, but the device can still perform the most basic measurement tasks without completely shutting down due to component malfunction.

[0132] The measurement device's operating mode is switched from normal mode to degraded operation mode. Degraded operation mode can include several different levels. For example, the first level of degraded operation mode can disable only specific measurement functions that depend on the faulty component, while other measurement functions that do not depend on the component continue to operate normally. The second level of degraded operation mode can reduce the sampling rate of the measurement device from a first sampling rate in normal operation mode to a second sampling rate, thereby reducing the frequency of calls to the faulty component or reducing the overall load on the system. The third level of degraded operation mode can switch the measurement device to a maintenance mode that only outputs basic status information and does not output measurement results.

[0133] A degraded status identifier is a flag indicating that a measuring device is currently in degraded operation mode. It is generated upon switching to degraded operation mode. The degraded status identifier can include the reason for the degrade (e.g., which specific component is malfunctioning), the level of degrade (e.g., level one or level two degrade), and a list of affected measuring functions. The degraded status identifier can be output to the measuring device's local maintenance management interface for on-site maintenance personnel to view, or it can be sent to a remote maintenance server for centralized monitoring and alarm functions.

[0134] For example, suppose both the attitude detection component and the light source component are identified as abnormal. Mark both components as unavailable, and disable image correction (which relies on attitude data) and structured light depth measurement (which relies on the light source component). Then, switch the measurement device's operating mode from normal mode to the second-level degraded operating mode. In this mode, the device reduces the sampling rate from 30 frames per second to 10 frames per second and outputs only passive light measurement results (i.e., grayscale images relying solely on ambient light, without outputting depth information). Simultaneously, generate degraded status indicators including "Attitude Sensor Abnormal" and "Light Source Module Abnormal," and send them to the remote maintenance server via the network. At the same time, display a status indicator light on the local panel to alert on-site personnel.

[0135] This embodiment achieves rapid response and automated handling of hardware faults in measurement equipment by triggering device health self-maintenance based on component health status. Specifically, when any of the sensing components, light source components, attitude detection components, storage components, or communication components malfunctions, the device health self-maintenance process is automatically triggered without manual intervention. This automated response mechanism avoids the delays required for on-site troubleshooting by maintenance personnel after component malfunctions in traditional solutions, significantly shortening fault response time. Furthermore, by disabling measurement functions dependent on malfunctioning components and switching the equipment to a degraded operation mode, the measurement equipment can maintain a certain level of measurement capability even when some components malfunction. Specifically, by disabling specific functions dependent on malfunctioning components, unreliable measurement results are prevented when critical components are missing; by reducing the sampling rate or switching to a degraded operation mode, measurement services are extended as much as possible while ensuring safe equipment operation. This design avoids the extreme handling method of "component malfunction equals system shutdown" in traditional solutions, significantly improving the fault tolerance and service availability of the measurement equipment. Meanwhile, the timely output of the degradation status indicator ensures that abnormal components can be detected and handled by maintenance personnel in a timely manner, avoiding secondary damage or continuous deterioration of measurement data quality that may result from prolonged operation of equipment in abnormal conditions.

[0136] In some embodiments, performing device health self-maintenance or calibration maintenance on the measuring device based on the component health status, the deployment health status, and the calibration reference file, and outputting the maintenance action result, includes:

[0137] After performing the calibration maintenance or the device health self-maintenance, the corresponding maintenance action result is output;

[0138] The maintenance action results include at least one of the following: when performing the calibration maintenance, outputting the calibration completion status and the updated version information of the calibration reference file; when performing the device health self-maintenance, outputting at least one of the following: abnormal component identifier, degraded status identifier, and maintenance prompt information;

[0139] The maintenance action results are output to the local maintenance management interface or remote maintenance server of the measuring device.

[0140] Maintenance action results are a collection of information characterizing the type, status, and outcome of maintenance operations performed on the measuring equipment. Depending on the type of maintenance performed, the maintenance action results contain different information.

[0141] When calibration maintenance is performed, it is the process of refreshing and updating the calibration reference file of the measuring equipment. After calibration maintenance is completed, a maintenance action result is generated. This result includes at least one of the following: calibration completion status and updated version information of the calibration reference file.

[0142] The calibration completion status is a status indicator used to indicate whether calibration maintenance has been successfully completed. The calibration completion status can include several values, such as calibration successful, calibration failed, or partial calibration successful. When all steps in the calibration maintenance process are executed normally and the calibration baseline data is successfully updated, the calibration completion status is determined to be calibration successful. When the calibration maintenance process is interrupted for any reason or the calibration result verification fails, the calibration completion status is determined to be calibration failed. When some calibration baseline data is successfully updated but other data cannot be updated due to an anomaly, the calibration completion status is determined to be calibration partially successful.

[0143] The updated version information of the calibration reference file is data used to identify the version of the calibration reference file after calibration maintenance. The updated version information may include at least one of the major version number, minor version number, and revision number, and may also include the version update time and version change description. After each calibration maintenance, the version number of the calibration reference file is incremented, for example, updating V1.0 to V1.1, or V1.9 to V2.0. The updated version information corresponds to the latest status of the calibration reference file and is used for subsequent version comparisons and incremental update determination.

[0144] For example, suppose the measuring device performs a successful calibration maintenance, and the calibration reference file version is updated from V1.0 to V1.1. The generated maintenance action result will include a calibration completion status of "calibration successful" and an updated version information of "V1.1".

[0145] When performing equipment health self-maintenance, this process involves isolating and limiting the functionality of abnormal components in the measuring equipment. After the equipment health self-maintenance is completed, a maintenance action result corresponding to the self-maintenance is generated. This result may include at least one of the following: abnormal component identifier, degraded status identifier, and maintenance prompt information.

[0146] An abnormal component identifier is information used to uniquely identify components marked as unavailable. The abnormal component identifier can include at least one of the following: component name, component number, component type, or component address in the system. For example, the abnormal component identifier can be a readable string such as "attitude sensor," "light source module," "sensing unit," or "communication module," or it can be a predefined component error code such as 0x81, 0x82, etc. Using the abnormal component identifier, maintenance personnel can quickly locate the specific faulty component without needing to perform a comprehensive inspection of the entire device.

[0147] A degraded status identifier is a flag indicating that the measuring device is currently in a degraded operating mode, as described in detail in Embodiment 5 above. The degraded status identifier may include information such as the reason for the degrade, the level of degrade, and a list of affected measurement functions. For example, the degraded status identifier may be "Level 1 Degrade: Attitude sensor malfunction, image correction function disabled," or "Level 2 Degrade: Light source module malfunction, structured light depth measurement disabled, sampling rate reduced to 10fps."

[0148] Maintenance prompts are advisory messages used to guide maintenance personnel in troubleshooting and repair operations. These prompts may include a detailed description of the malfunctioning component, suggested repair procedures, information on required tools or spare parts, and the urgency level of the fault. For example, when an attitude detection component malfunctions, the maintenance prompt might be, "Attitude sensor self-test failed; please check the sensor connection cable or replace the attitude sensor module." When a light source component malfunctions, the prompt might be, "Light source drive current is unstable; 15 consecutive errors have occurred; it is recommended to check the drive circuit or replace the light source module." Maintenance prompts may also include urgency levels, such as "Urgent," "High," "Medium," and "Low," to help maintenance personnel prioritize repairs.

[0149] For example, suppose the device's health self-maintenance is triggered by an malfunction in the attitude detection component, marking the attitude detection component as unavailable and switching the device to degraded operation mode. The generated maintenance action results would include the malfunctioning component identified as "Attitude Detection Component", the degraded status identified as "Degraded Operation Mode: Attitude Compensation Function is Disabled", and the maintenance prompt message as "The attitude sensor is continuously outputting abnormal data. Please check if the sensor is securely installed. If the problem persists, please replace the sensor module."

[0150] A local maintenance and management interface refers to a human-machine interface provided on the measuring equipment itself, which may include one or more of the following: a display screen, indicator lights, a buzzer, or a touch screen. The local maintenance and management interface is typically located on the measuring equipment itself or on a maintenance terminal directly connected to the equipment, for direct viewing by on-site maintenance personnel.

[0151] The specific methods for outputting maintenance action results to the local maintenance management interface can include the following: Displaying text information about the maintenance action results on the screen, such as "Calibration complete, version updated to V1.1" after calibration, or "Attitude sensor abnormal, device switched to degraded mode" after device health self-maintenance. Indicating maintenance action results through the color or flashing pattern of status indicator lights, such as solid green for normal, flashing yellow for requiring attention, and solid red for a serious fault. Using different numbers of beeps or different tones of the buzzer to indicate different types of maintenance results, such as a short beep for successful calibration and three long beeps for component abnormalities. For devices with touchscreens, a maintenance prompt dialog box can also pop up on the screen for maintenance personnel to confirm and view detailed information.

[0152] A remote maintenance server is a server system that connects to measurement equipment via a network and is used for centralized management and monitoring of multiple measurement devices. Remote maintenance servers can be deployed in a user's computer room or in the cloud. They receive maintenance results from multiple measurement devices, centrally store, display, and analyze them, facilitating remote monitoring of equipment operating status and maintenance history by operations and maintenance personnel.

[0153] The specific methods for outputting maintenance action results to the remote maintenance server include: encapsulating the maintenance action results into data packets and sending them to a designated interface of the remote maintenance server via a network protocol. For example, the maintenance action results can be sent to the remote maintenance server's API interface in JSON format using the HTTP POST protocol, or the maintenance action results can be published to a designated topic using the MQTT protocol, which the remote maintenance server can then subscribe to and receive.

[0154] The data sent can include the unique identifier of the measuring device (such as the device serial number or device ID), the type of maintenance action result (calibration maintenance or device health self-maintenance), the specific content of the maintenance action result (calibration completion status, update information, abnormal component identification, degradation status identification, maintenance prompt information, etc.), and the timestamp of the result generation. After receiving the data, the remote maintenance server stores it in the database and displays it in real time on the operation and maintenance management interface. Operation and maintenance personnel can view the maintenance status of all online devices through a web page or mobile application, and can promptly arrange on-site repairs when abnormal component identification or maintenance prompt information is received.

[0155] For example, suppose a measuring device performs calibration maintenance and generates a maintenance action result. This result is encapsulated as a JSON message with the device ID "CAM001", maintenance type "calibration maintenance", calibration completion status "successful", update version information "V1.1", and timestamp "2026-06-05 14:30:00". This message is sent to the remote maintenance server's API interface via an HTTP POST request. Maintenance personnel see the device's calibration record on the remote maintenance management interface, confirming that the device has completed calibration. Now suppose another measuring device performs device health self-maintenance, sending a maintenance action result with the device ID "CAM002", maintenance type "device health self-maintenance", abnormal component identifier "attitude sensor", degraded status identifier "Level 1 degraded", maintenance prompt message "Please check attitude sensor connection cable", and timestamp "2026-06-05 15:00:00". Upon receiving this message, maintenance personnel promptly arrange for on-site repair personnel to check the attitude sensor.

[0156] This embodiment achieves transparency and traceability of equipment maintenance status by outputting corresponding maintenance action results after performing calibration maintenance or equipment health self-maintenance. Specifically, the calibration completion status and updated version information output after calibration maintenance allow maintenance personnel to confirm whether the calibration was successful and the current version of the calibration reference file. The abnormal component identifier and degraded status identifier output after equipment health self-maintenance allow maintenance personnel to quickly locate faulty components and understand the current operating mode of the equipment. This transparent maintenance result feedback mechanism avoids the problem of unclear equipment status after maintenance in traditional solutions, improving the verifiability and manageability of maintenance work.

[0157] This embodiment also achieves dual coverage of on-site operation and maintenance and remote monitoring by simultaneously outputting maintenance action results to both the local maintenance management interface and the remote maintenance server. Specifically, the local maintenance management interface allows on-site personnel to directly obtain the maintenance status of the equipment without the need for additional query tools; the remote maintenance server enables the operation and maintenance team to centrally monitor multiple measuring devices distributed in different locations, promptly detect anomalies, and perform remote dispatching. This dual-output design takes into account both the need for rapid on-site response and the efficiency requirements of centralized management, and is particularly suitable for large-scale deployments of measuring equipment.

[0158] This embodiment also provides maintenance personnel with specific troubleshooting and repair guidance through maintenance prompts. The maintenance prompts not only indicate which component is malfunctioning, but also describe the specific manifestations of the malfunction (e.g., "15 consecutive errors") and suggested repair actions (e.g., "Check connection cables" or "Replace module"). This detailed maintenance guidance lowers the technical barrier to troubleshooting, enabling even novice maintenance personnel to perform preliminary diagnoses by following the prompts. This reduces ineffective repairs and repeated site visits due to inaccurate fault location, significantly improving maintenance efficiency.

[0159] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0160] Based on the same inventive concept, this application also provides an apparatus for implementing the aforementioned equipment deployment and long-term self-maintenance method. The solution provided by this apparatus is similar to the solution described in the above method; therefore, the specific limitations in one or more embodiments of the equipment deployment and long-term self-maintenance apparatus provided below can be found in the limitations of the equipment deployment and long-term self-maintenance method described above, and will not be repeated here.

[0161] In one exemplary embodiment, such as Figure 3 As shown, a device for equipment deployment and long-term self-maintenance is provided, the device comprising:

[0162] The status acquisition module is used to acquire the equipment operating status, installation relationship status, calibration reference status, and reference file status of the measuring equipment.

[0163] The installation relationship assessment module is used to determine the installation relationship parameters of the measuring device based on the installation relationship status, compare the installation relationship parameters with the standard installation status of the measuring device, and obtain the deployment health status of the measuring device.

[0164] The calibration reference file maintenance module is used to establish a calibration reference file for the measuring device based on the calibration reference status and the reference file status.

[0165] The status analysis module is used to analyze the operating status of the equipment and obtain the health status of the components of the measuring equipment;

[0166] The maintenance action execution module is used to perform device health self-maintenance or calibration maintenance on the measuring device based on the component health status, the deployment health status, and the calibration reference file, and output the maintenance action results.

[0167] The modules in the aforementioned equipment deployment and long-term self-maintenance device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0168] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 3As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a device deployment and long-term self-maintenance method. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0169] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0170] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps included in any of the foregoing method embodiments.

[0171] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps included in any of the foregoing method embodiments.

[0172] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps included in any of the foregoing method embodiments.

[0173] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0174] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0175] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0176] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for equipment deployment and long-term self-maintenance, characterized in that, The method includes: Acquire the equipment operating status, installation relationship status, calibration reference status, and reference file status of the measuring equipment; The installation relationship parameters of the measuring device are determined based on the installation relationship status, and the installation relationship parameters are compared with the standard installation status of the measuring device to obtain the deployment health status of the measuring device. Based on the calibration reference status and the reference file status, a calibration reference file for the measuring device is established; The operating status of the equipment is analyzed to obtain the health status of the components of the measuring equipment; Based on the health status of the components, the health status of the deployment, and the calibration reference file, the measuring device performs self-maintenance or calibration maintenance and outputs the maintenance action results.

2. The method according to claim 1, characterized in that, The installation relationship status includes the actual installation height, actual installation distance, and actual device posture of the measuring equipment; the standard installation status includes the standard installation height, standard installation distance, and standard device posture; determining the installation relationship parameters of the measuring equipment based on the installation relationship status, and comparing the installation relationship parameters with the standard installation status of the measuring equipment to obtain the deployment health status of the measuring equipment includes: The standard installation status is determined based on at least one of the following: the factory installation status recorded when the measuring device leaves the factory, the acceptance installation status recorded when the measuring device is installed and accepted, and the calibration refresh status recorded when the measuring device was last successfully calibrated. Determine at least one of the following: the height deviation between the actual installation height and the standard installation height, the distance deviation between the actual installation distance and the standard installation distance, and the attitude offset between the actual equipment attitude and the standard equipment attitude; The installation status deviation of the measuring device is determined based on at least one of the height deviation, distance deviation, and attitude offset, and the deployment health status is determined based on the installation status deviation.

3. The method according to claim 1, characterized in that, The calibration reference file includes a feature template of the reference object of the measuring equipment and calibration baseline data corresponding to the standard observation data; the step of establishing the calibration reference file of the measuring equipment based on the calibration reference state and the reference file state includes: Based on the difference between the most recent maintenance time and the current time in the calibration reference state, determine whether the calibration cycle condition is met; When the calibration cycle condition is met, or when the consistency deviation condition in the calibration reference state indicates that the current installation attitude offset or the reference object imaging offset exceeds a preset threshold, the process of establishing or updating the calibration reference file is triggered. Based on the file version and validity status in the reference file status, the method for establishing the calibration reference file is determined; wherein, when the reference file status indicates that the calibration reference file does not exist or has expired, the initial establishment method is adopted; when the reference file status indicates that the calibration reference file exists and is valid but the version is lower than the latest version, the incremental update method is adopted. Obtain the actual observation data of the reference object, and compare the actual observation data with the standard observation data of the reference object under standard installation conditions to obtain the reference observation deviation; The feature template of the reference object and the calibration baseline data corresponding to the standard observation data are determined based on the reference observation deviation, and stored in the calibration reference archive according to the establishment method. After the creation or update is completed, update the version information and last maintenance time of the calibration reference file.

4. The method according to claim 1, characterized in that, The calibration maintenance includes at least one of generating calibration maintenance parameters based on reference observation deviation, refreshing calibration baseline data in the calibration reference file, or forming a calibration refresh status. The device health self-maintenance includes at least one of isolating faulty components based on the component health status, limiting the function of the measuring device, or switching the operating mode of the measuring device. The step of performing device health self-maintenance or calibration maintenance on the measuring device based on the component health status, the deployment health status, and the calibration reference file, and outputting the maintenance action results, includes: When the deployment health status indicates that the installation status deviation of the measuring device exceeds a preset installation deviation threshold, or the consistency deviation condition in the calibration reference file indicates that the reference observation deviation exceeds a preset calibration deviation threshold, or the calibration cycle condition in the calibration reference file indicates that the time since the last calibration maintenance exceeds a preset cycle threshold, calibration maintenance of the measuring device is triggered; the calibration maintenance includes: generating calibration maintenance parameters based on the reference observation deviation; The calibration baseline data in the calibration reference file is refreshed according to the calibration maintenance parameters, and the refreshed calibration baseline data, together with the updated version information, is stored in the calibration reference file to form a calibration refresh status.

5. The method according to claim 1, characterized in that, The step of performing device health self-maintenance or calibration maintenance on the measuring device based on the component health status, the deployment health status, and the calibration reference file, and outputting the maintenance action results, includes: When the component health status indicates that the measuring device has a component malfunction, the device health self-maintenance of the measuring device is triggered; the component malfunction includes at least one of the following: sensing component malfunction, light source component malfunction, attitude detection component malfunction, storage component malfunction, or communication component malfunction. The device health self-maintenance includes: marking abnormal components as unavailable, so that the measuring device skips calling the abnormal components in subsequent operation; and disabling measurement functions that depend on the abnormal components, switching the operating mode of the measuring device from normal mode to degraded operating mode, and outputting a degraded status indicator in the degraded operating mode.

6. The method according to claim 1, characterized in that, The step of performing device health self-maintenance or calibration maintenance on the measuring device based on the component health status, the deployment health status, and the calibration reference file, and outputting the maintenance action results, includes: After performing the calibration maintenance or the device health self-maintenance, the corresponding maintenance action result is output; The maintenance action results include at least one of the following: when performing the calibration maintenance, outputting the calibration completion status and the updated version information of the calibration reference file; when performing the device health self-maintenance, outputting at least one of the following: abnormal component identifier, degraded status identifier, and maintenance prompt information; The maintenance action results are output to the local maintenance management interface or remote maintenance server of the measuring device.

7. A device for equipment deployment and long-term self-maintenance, characterized in that, The device includes: The status acquisition module is used to acquire the equipment operating status, installation relationship status, calibration reference status, and reference file status of the measuring equipment. The installation relationship assessment module is used to determine the installation relationship parameters of the measuring device based on the installation relationship status, compare the installation relationship parameters with the standard installation status of the measuring device, and obtain the deployment health status of the measuring device. The calibration reference file maintenance module is used to establish a calibration reference file for the measuring device based on the calibration reference status and the reference file status. The status analysis module is used to analyze the operating status of the equipment and obtain the health status of the components of the measuring equipment; The maintenance action execution module is used to perform device health self-maintenance or calibration maintenance on the measuring device based on the component health status, the deployment health status, and the calibration reference file, and output the maintenance action results.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to 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 a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

Images