Method, device, equipment and medium for mobile metering calibration of mine repair pollutants

Abstract

The application discloses a mobile type measurement calibration method and device for mine repair pollutants, equipment and medium, relates to the technical field of measurement and detection, and the method comprises the following steps: according to the matching assembly target base and the pollutant measurement device of the mine repair working condition, and calling the standard substance to complete the initial calibration to establish the precision reference; in the mobile detection process, the original pollutant data and the working environment data are collected in real time, and the mobile operation distance and the detection frequency are continuously monitored, once the preset threshold is exceeded, the standard solution is automatically extracted for calibration comparison to obtain the real-time deviation value; the deviation value is corrected by multidimensional fitting combined with the environmental data, and the calibration correction parameter is generated, so that the original data is accurately compensated, and the target pollutant detection data and the calibration record data are output. The application effectively overcomes the sensor zero point and sensitivity drift caused by the dramatic change of the working condition on the mine site, and solves the problem of low accuracy of the monitoring data in the traditional discrete calibration mode.

Description

Technical Field

[0001] This application relates to the field of metrology and testing technology, and in particular to mobile metrology and calibration methods, devices, equipment and media for mine remediation pollutants. Background Technology

[0002] Mining activities generate a large number of characteristic pollutants, including heavy metal ions in the soil (such as lead, cadmium, zinc, mercury, etc.) and soluble heavy metals, sulfides, and COD in water bodies. Pollutant monitoring is conducted throughout the entire process of mine remediation, and the accuracy and real-time nature of the data directly determine the scientific validity of the remediation plan.

[0003] Currently, the detection of pollutants in mine remediation mainly relies on three traditional methods: fixed monitoring points, portable detection equipment, and manual sampling followed by laboratory analysis. However, existing practices have significant shortcomings under the complex conditions of mines: First, due to terrain limitations such as rugged topography and high slopes, manual detection or ordinary mobile platforms cannot achieve full coverage, easily creating detection blind spots. Second, the mine environment is characterized by high dust levels, strong vibrations, and extreme temperature differences; existing equipment lacks specific anti-interference designs, making it prone to drift in detection accuracy. Third, existing mobile detection equipment often focuses on a single scenario or a single pollutant, with separate metrology and calibration functions, and lacks specific adaptation designs for the harsh conditions of mines, failing to balance detection range, accuracy, and stability, and thus unable to support the actual needs of pollutant control throughout the entire mine remediation process. Finally, inconsistent metrological standards and the lack of collaborative calibration mechanisms for different scenarios and pollutants result in poor data traceability, making it difficult to meet the standardized requirements for environmental supervision and quantitative evaluation of remediation effectiveness. Therefore, in the process of mobile detection under complex mine conditions, the easy drift in metrological accuracy and the insufficient accuracy of detection data due to the separation of calibration and detection are urgent problems that need to be solved. Summary of the Invention

[0004] The purpose of this application is to provide a mobile metrological calibration method, device, equipment and medium for mine remediation pollutants, aiming to solve the technical problems of easy drift in metrological accuracy and insufficient accuracy of detection data caused by the separation of calibration and detection during mobile detection in complex mine working conditions.

[0005] To achieve the above objectives, this application proposes a mobile metrological calibration method for mine remediation pollutants, the method comprising: According to the mine restoration conditions, select the corresponding target base and pollutant metering device for assembly, and call the standard material storage chamber for initial calibration after assembly; Once the initial calibration is completed, mobile detection of characteristic pollutants in mine soil or water is performed to obtain raw pollutant detection data and corresponding work environment data. During the movement, calculate the current movement distance and the number of detections; When the mobile operation distance is greater than a preset distance threshold or the number of detections is greater than a preset number of detections threshold, a standard solution of a first preset concentration is extracted from the standard substance storage chamber for calibration and comparison to obtain a real-time deviation value reflecting the offset of the detection performance. Based on the operating environment data, the real-time deviation value is corrected by multi-dimensional error fitting to obtain calibration correction parameters; The original pollutant detection data is corrected according to the calibration correction parameters to obtain the target pollutant detection data and calibration record data.

[0006] In one embodiment, the step of performing multidimensional error fitting correction on the real-time deviation value based on the operating environment data to obtain calibration correction parameters includes: Extract real-time temperature and real-time vibration frequency from the operating environment data; Based on the real-time temperature value and the preset temperature drift correction function, a first correction weight for compensating for signal baseline drift is calculated. The preset temperature drift correction function is obtained by least squares fitting of the sensor's response output under different temperature gradients. Based on the real-time vibration frequency and the preset vibration interference model, the second correction weight is calculated. The preset vibration interference model is obtained by measuring the signal noise characteristics of the sensor at different vibration frequencies and amplitudes on a vibration test bench simulating mining conditions, and by using fast Fourier transform to extract the correlation between the interference main frequency and the signal fluctuation gain for fitting. The real-time deviation value, the first correction weight and the second correction weight are input into a preset multiple linear regression model for parameter fitting to obtain the fitting result between environmental factors and sensor performance deviation. The preset multiple linear regression model is obtained by statistical regression analysis of full-condition sample data of the pollutant metering device under various environmental temperatures, vibration intensities and standard substance comparison deviations. The error compensation coefficient under the current operating condition is determined based on the fitting results, and the error compensation coefficient is used as the calibration correction parameter.

[0007] In one embodiment, the step of performing mobile detection on characteristic pollutants in mine soil or water to obtain raw pollutant detection data and corresponding working environment data after the initial calibration is completed includes: Once the initial calibration is completed, the target base is driven to move along a preset path, and the pollutant metering device is activated. The pollutant metering device includes a soil pollutant metering device and a water pollutant metering device. The soil pollutant metering device includes a near-infrared spectroscopy metering unit and an electrochemical metering unit. The water pollutant metering device includes an ion-selective electrode metering unit, an ultraviolet spectrophotometer metering unit, and an electromagnetic flow metering unit. The soil in the mine is tested using the soil pollutant metering device to obtain first test data, and the water body in the mine is tested using the water pollutant metering device to obtain second test data. Monitor the real-time temperature of the working environment and the real-time vibration frequency of the target base during movement; By integrating the first detection data and the second detection data, the original pollutant detection data is obtained, and the real-time temperature value and the real-time vibration frequency are used as the corresponding working environment data.

[0008] In one embodiment, the steps of testing the mine soil using the soil pollutant metering device to obtain first test data, and testing the mine water using the water pollutant metering device to obtain second test data, include: The soil pollutant metering device is used to perform non-contact or contact scanning of the mine soil, the near-infrared spectral metering unit is used to collect spectral characteristic signals, and the electrochemical metering unit is used to collect heavy metal ion electrical signals. The water pollutant metering device is used to perform in-situ detection of mine water. The ion concentration signal is collected by the ion-selective electrode metering unit, the absorbance signal of organic pollutants is collected by the ultraviolet spectrophotometer metering unit, and the real-time flow signal of wastewater is collected by the electromagnetic flow metering unit. The spectral feature signal and the heavy metal ion electrical signal are converted into first detection data including total heavy metal concentration, soluble heavy metal concentration, sulfide concentration, pH and porosity. The ion concentration signal, the absorbance signal, and the real-time flow rate signal are converted into second detection data that includes total heavy metal concentration, sulfide concentration, chemical oxygen demand, and wastewater flow rate.

[0009] In one embodiment, the step of selecting the corresponding target base and pollutant metering device according to the mine restoration conditions, assembling them, and then calling the standard material storage chamber for initial calibration after assembly includes: Identify mine restoration conditions, including rugged reclamation areas, high-altitude slopes, or decentralized wastewater ponds; Match the corresponding target base according to the mine restoration conditions. The rugged reclamation area corresponds to the tracked base, the high drop slope corresponds to the handheld telescopic base, and the decentralized wastewater pond corresponds to the floating base. Assemble the target base with the pollutant metering device; The pollutant metering device is controlled to measure the standard substance of a second preset concentration in the standard substance storage chamber to obtain an initial measurement value; The initial calibration is completed based on the initial measurement value and the zero point of the second preset concentration calibration sensor.

[0010] In one embodiment, after the step of correcting the original pollutant detection data according to the calibration correction parameters to obtain the target pollutant detection data and calibration record data, the method further includes: The target pollutant detection data, the calibration record data, the detection location data, and the working environment data are fused together to obtain full-dimensional detection data. A traceability code is generated for the full-dimensional detection data, and the traceability code is associated and bound with full-link data including the detection device number, the calibration record data, the detection time, and the detection location data to obtain traceable detection data. The traceable detection data is compared with a preset pollutant concentration threshold to obtain the comparison result; Based on the comparison results, pollutant exceedance levels will be graded and warnings will be issued.

[0011] In one embodiment, the step of correcting the original pollutant detection data according to the calibration correction parameters to obtain target pollutant detection data and calibration record data includes: The original pollutant detection data is compensated point by point according to the calibration correction parameters to obtain the target pollutant detection data. Obtain the device number, standard substance batch, and calibration timestamp when the calibration action is performed; The device number, the standard substance batch, and the calibration timestamp are spatiotemporally aligned and encapsulated with the target pollutant detection data to obtain calibration record data.

[0012] Furthermore, to achieve the above objectives, this application also proposes a mobile metering and calibration device for mine remediation pollutants, the device comprising: The initialization module is used to select the corresponding target base and pollutant metering device according to the mine restoration conditions, and to call the standard material storage bin for initial calibration after assembly. The mobile metering module is used to perform mobile detection of characteristic pollutants in mine soil or water after the initial calibration is completed, and to obtain raw pollutant detection data and corresponding working environment data. The status statistics module is used to calculate the current moving operation distance and the number of detections during the movement process; The dynamic comparison module is used to extract a standard solution of a first preset concentration from the standard substance storage chamber for calibration and comparison when the moving operation distance is greater than a preset distance threshold or the number of detections is greater than a preset number of detections threshold, so as to obtain a real-time deviation value that reflects the offset of the detection performance. The error correction module is used to perform multi-dimensional error fitting correction on the real-time deviation value based on the operating environment data to obtain calibration correction parameters. The data calibration module is used to correct the original pollutant detection data according to the calibration correction parameters to obtain target pollutant detection data and calibration record data.

[0013] Furthermore, to achieve the above objectives, this application also proposes a mobile metrological calibration device for mine remediation pollutants, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the mobile metrological calibration method for mine remediation pollutants as described above.

[0014] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of the mobile metrological calibration method for mine remediation pollutants as described above.

[0015] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the mobile metrological calibration method for mine remediation pollutants as described above.

[0016] One or more technical solutions proposed in this application have at least the following technical effects: First, the mobile metrology and calibration system identifies the mine restoration conditions and matches the corresponding target base and pollutant metering device. Before operation, it uses standard substances from the standard substance storage chamber to complete initial calibration, establishing an initial high-precision measurement benchmark for the equipment in specific terrains. Second, the system drives the target base along a preset path and uses the pollutant metering device to perform mobile detection on mine soil or water, acquiring raw pollutant detection data and operational environment data including temperature and vibration, achieving real-time synchronous perception of pollution indicators and physical background interference. Then, the system monitors the mobile operation distance and the number of detections in real time during the movement. Once a preset threshold is exceeded, it extracts a standard solution of a first preset concentration from the storage chamber for online calibration and comparison, thereby calculating the real-time deviation value reflecting the deviation in detection performance. This allows the equipment to proactively quantify the dynamic accuracy drift caused by long-distance operation or mechanical wear. Finally, the system uses operational environment data to perform multi-dimensional error fitting correction on the real-time deviation value to obtain calibration correction parameters, and performs calibration on the raw pollutant detection data accordingly, obtaining target pollutant detection data and calibration record data, ensuring the accuracy of the detection results under extreme interference and the traceability of the entire chain. This application effectively solves the technical problems of easy drift in metrological accuracy and insufficient accuracy of detection data caused by the separation of calibration and detection in the mobile detection process under complex working conditions in mines by deeply integrating dynamic trigger calibration and multi-dimensional environmental compensation into the mobile detection process. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating the first embodiment of the mobile metrological calibration method for mine remediation pollutants provided in this application; Figure 2 A flowchart illustrating Embodiment 2 of the mobile metrological calibration method for mine remediation pollutants provided in this application; Figure 3 This is a schematic diagram of the module structure of a mobile metering and calibration device for mine remediation pollutants according to an embodiment of this application; Figure 4 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the mobile metering and calibration method for mine remediation pollutants in the embodiments of this application.

[0020] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0022] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0023] It should be noted that the executing entity of this application embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or mobile metrology calibration system capable of performing the above functions. The following description uses a mobile metrology calibration system as an example to illustrate this embodiment and the subsequent embodiments.

[0024] 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 comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0025] Based on this, the embodiments of this application provide a mobile measurement and calibration method for mine remediation pollutants, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the mobile metrological calibration method for mine remediation pollutants in this application.

[0026] In this embodiment, the mobile metering and calibration method for mine remediation pollutants includes steps S10 to S60: Step S10: Select the corresponding target base and pollutant metering device according to the mine restoration conditions and assemble them. After the assembly is completed, call the standard material storage chamber for initial calibration. Step S20: After the initial calibration is completed, mobile detection is performed on characteristic pollutants in the mine soil or water to obtain raw pollutant detection data and corresponding working environment data. Step S30: During the movement, calculate the current movement distance and the number of detections; Step S40: When the moving operation distance is greater than a preset distance threshold or the number of detections is greater than a preset number of detections threshold, a standard solution of a first preset concentration is extracted from the standard substance storage chamber for calibration and comparison to obtain a real-time deviation value reflecting the offset of the detection performance. Step S50: Perform multidimensional error fitting correction on the real-time deviation value based on the operating environment data to obtain calibration correction parameters; Step S60: Correct the original pollutant detection data according to the calibration correction parameters to obtain target pollutant detection data and calibration record data.

[0027] It should be noted that "mine remediation conditions" refers to the specific operating environment type of the device, mainly including remediation scenarios with rugged terrain, extreme temperature differences, or high dust characteristics, such as mine reclamation areas, high-drop slopes, or dispersed wastewater ponds. The target base refers to the support platform selected according to the specific remediation conditions, such as a tracked base for rugged reclamation areas, a handheld telescopic base for high-drop slopes, and a floating base for wastewater ponds. The pollutant metering device refers to the core detection module integrated on the base for detecting pollutants, specifically including a soil detection device composed of high-frequency electromagnetic induction, near-infrared spectroscopy, and electrochemical units, and a water detection device composed of ion-selective electrodes, ultraviolet spectrophotometry, and electromagnetic flow units. The standard substance storage chamber refers to the sealed unit inside the device used to store standard samples, containing heavy metal standard solutions, sulfide standard solutions, and soil standard samples of different concentration gradients.

[0028] Characteristic pollutants refer to substances that require key monitoring during mine remediation, including heavy metals such as lead, cadmium, zinc, and mercury in the soil, and soluble heavy metals, sulfides, and chemical oxygen demand (COD) in the water. Raw pollutant detection data refers to pollutant information directly collected and preliminarily converted by the metering device without dynamic environmental compensation, including preliminary results such as total heavy metal concentration, soluble heavy metal concentration, sulfide concentration, and wastewater flow rate. Operating environment data refers to external physical interference parameters synchronously monitored by the sensor array, specifically real-time temperature values ​​(e.g., -20°C to 60°C) and real-time vibration frequencies generated during target base movement (e.g., 0 to 100 Hz). Operating distance refers to the actual displacement vector magnitude moved by the device relative to its initial or last calibrated position when performing detection tasks at the mine site. Number of detections refers to the cumulative number of times the pollutant metering device completes sampling and reads detection values ​​during the movement process. The preset distance threshold refers to the upper limit of the movement distance set to trigger the automatic calibration program (e.g., 500 meters), which is used to prevent accuracy drift caused by mechanical vibrations during long-distance movement.

[0029] The preset detection threshold refers to the maximum cumulative number of operations (e.g., 50 times) set to trigger the automatic calibration program, used to address the impact of high-frequency detection operations on sensor stability. The first preset concentration refers to a specific nominal concentration value (e.g., 1.0 mg / L) of the standard solution extracted from the storage chamber, serving as a comparison benchmark during mobile calibration. The standard solution is an aqueous solution of a chemical reagent with a known accurate concentration, typically containing specific heavy metals such as lead, cadmium, and zinc, used to verify the accuracy of the measuring device. Detection performance offset refers to the systematic error characteristic of the sensor, caused by factors such as environmental temperature differences, mechanical vibration, or component aging, resulting in the measured output value deviating from the true value.

[0030] Real-time deviation refers to the absolute difference between the measured standard value and the theoretical nominal value of the standard solution during the movement of the device. Calibration correction parameters are numerical corrections calculated by fitting the relationship between environmental factors and deviation using a multiple linear regression model. These corrections dynamically adjust the mapping relationship of the detection equation to compensate for measurement errors caused by current operating conditions. Target pollutant detection data refers to accurate detection results that truly reflect the pollution situation at the mine remediation site, obtained after the original pollutant detection data has been compensated by calibration correction parameters. Calibration record data refers to electronic evidence containing full-chain information such as calibration timestamp, standard substance batch, equipment number, real-time deviation value, and location coordinates, used to support the traceability of metrological data.

[0031] Understandably, firstly, the mobile metrology and calibration system identifies the terrain and media of the mine restoration work, assembles a suitable target base and pollutant metering device through a quick-release structure, and extracts standard substances from the standard substance storage bin for baseline measurement and zeroing before the operation begins to establish the initial accuracy of subsequent mobile detection. Secondly, during the movement of the target base, the mobile metrology and calibration system uses the pollutant metering device to continuously sample and analyze characteristic pollutants in the mine soil or water, while simultaneously monitoring ambient temperature and mechanical vibration frequency through a sensor array, thereby obtaining uncorrected raw pollutant detection data and operational environment data reflecting real-time interference effects.

[0032] Then, the mobile metrology calibration system accumulates the travel trajectory and sampling pulses. When the mobile operation distance or the number of tests exceeds a preset threshold, it controls the flow path switching and extracts a standard solution of a first preset concentration from the standard substance storage chamber for online comparison testing. By calculating the difference between the measured value and the nominal value, the real-time deviation value of the sensor caused by the complex working conditions of the mine is quantified. Finally, the mobile metrology calibration system combines the collected operating environment data and uses a preset mathematical model to perform multi-dimensional error fitting correction on the real-time deviation value. It analyzes the specific contribution of environmental interference to the measurement accuracy to generate accurate calibration correction parameters. The calibration correction parameters are then used to perform point-by-point compensation calculations on the aforementioned original pollutant detection data, thereby outputting the target pollutant detection data after offset elimination and encapsulating it to generate calibration record data containing calibration link information, ensuring the accuracy and traceability of the detection results.

[0033] As an example, the step of selecting the corresponding target base and assembling the pollutant metering device according to the mine restoration conditions, and then calling the standard material storage bin for initial calibration after assembly includes: identifying the mine restoration conditions, which include rugged reclamation areas, high-drop slopes, or decentralized wastewater ponds; matching the corresponding target base according to the mine restoration conditions, with rugged reclamation areas corresponding to tracked bases, high-drop slopes corresponding to handheld telescopic bases, and decentralized wastewater ponds corresponding to floating bases; assembling the target base and the pollutant metering device; controlling the pollutant metering device to measure the standard material at a second preset concentration in the standard material storage bin to obtain an initial measurement value; and calibrating the sensor zero point based on the initial measurement value and the second preset concentration to complete the initial calibration.

[0034] It should be noted that rugged reclamation areas refer to mining-related land areas with extremely uneven surfaces, covered with gravel, gullies, or loose soil layers due to mining activities, requiring large-scale, continuous soil pollutant monitoring during the remediation process. High-drop slopes refer to rock-soil interfaces with significant vertical height and steep slopes formed by mining operations, where personnel cannot directly access them due to the rugged terrain, necessitating remote or extended-range sampling of pollutants. Decentralized wastewater ponds refer to areas distributed around mining depressions, pits, or tailings ponds, accumulating large amounts of acidic mine wastewater or water with excessive heavy metal levels, and are relatively scattered with varying depths; these are static or semi-static water accumulation areas. Tracked platforms refer to mobile platforms driven by continuous metal or rubber tracks, with a large ground contact area and strong grip, capable of smoothly traversing complex terrain such as rugged reclamation areas, and providing a stable carrier for pollutant metering devices.

[0035] A handheld telescopic base refers to a support device with an adjustable-length rod structure, allowing operators to extend the pollutant metering device to high-drop slopes or dangerous in-situ detection from a safe distance. A floating base refers to a structural platform with sufficient buoyancy that can float stably on water, typically equipped with a propulsion system, used to carry the pollutant metering device for mobile water quality sampling and measurement in decentralized wastewater ponds. The second preset concentration refers to a specific standard substance concentration value (e.g., 0.5 mg / L) retrieved from the storage tank during the initial calibration phase to calibrate the sensor's baseline performance. The initial measurement value refers to the raw response value obtained by probing the standard substance at the second preset concentration before the pollutant metering device officially begins mobile detection, used to assess the sensor's initial accuracy. The sensor zero point refers to the corresponding output signal reference point or level value when the sensor comes into contact with a zero-concentration medium or reference standard substance; calibrating this point can eliminate inherent biases in the system.

[0036] Understandably, the mobile metrology calibration system first acquires on-site terrain features through built-in visual sensors or terrain scanning modules. It then analyzes the environmental undulations and hydrological characteristics using preset image recognition algorithms or laser point cloud data to identify whether the mine restoration work is located in an uneven, rugged reclamation area, a steep, high-drop slope, or a dispersed wastewater pond with accumulated water. This allows for establishing the feasibility of testing from a physical structural perspective. Secondly, based on the identification results, the mobile metrology calibration system matches the target base with the strongest dynamic characteristics: a tracked base for rugged reclamation areas with good mobility, a handheld telescopic base for high-drop slopes with easy extension, and a floating base for dispersed wastewater ponds that can operate on water. A standardized quick-release interface is used to assemble the target base and the pollutant metering device for physical and communication links, ensuring the testing equipment can smoothly enter the sampling point. Then, the mobile metrology calibration system drives the pollutant metering device to activate the sampling pump or probe, extracting or contacting a second preset concentration of standard substance from the standard substance storage chamber and recording the electrical signal feedback, thereby obtaining the initial measurement value reflecting the device's operating status. Finally, the mobile metrology calibration system calculates the absolute difference between the initial measured value and the second preset theoretical concentration value, and adjusts the sensor's output reference according to the difference to calibrate the sensor's zero point. This is done to eliminate inherent systematic errors caused by equipment transportation or environmental changes, and to ensure that the mobile metrology calibration system is on a uniform metrology accuracy reference line before it officially enters the mine operation.

[0037] As an example, the step of performing mobile detection of characteristic pollutants in mine soil or water to obtain raw pollutant detection data and corresponding working environment data after the initial calibration is completed includes: after the initial calibration is completed, driving the target base to move along a preset path and activating the pollutant metering device, which includes a soil pollutant metering device and a water pollutant metering device. The soil pollutant metering device includes a near-infrared spectroscopy metering unit and an electrochemical metering unit, and the water pollutant metering device includes an ion-selective electrode metering unit, an ultraviolet spectrophotometer metering unit, and an electromagnetic flow metering unit; detecting the mine soil through the soil pollutant metering device to obtain first detection data, and detecting the mine water through the water pollutant metering device to obtain second detection data; monitoring the real-time temperature value of the working environment and the real-time vibration frequency of the target base during movement; integrating the first detection data and the second detection data to obtain raw pollutant detection data, and using the real-time temperature value and the real-time vibration frequency as the corresponding working environment data.

[0038] It should be noted that the preset path refers to a pre-planned movement trajectory within the mine remediation area, which includes a set of coordinate points where pollutant sampling needs to be performed, guiding the target base to traverse the mine remediation site in an orderly manner. The soil pollutant metering device is an integrated module specifically designed to detect the chemical composition of terrestrial solid media. It uses multiple physical and chemical sensing methods to collaboratively analyze the metal and mineral content in mine soil. The water pollutant metering device is a module specifically designed to analyze the chemical content of mine wastewater, surface water, or tunnel sludge, capable of measuring the concentration of water components and the physical quantities of liquid flow. The near-infrared spectroscopy metering unit is an analytical module that uses light within a specific wavelength range to illuminate the sample and receives the reflected or transmitted spectra, identifying organic matter and mineral components in the soil by analyzing the characteristic absorption peaks of substances.

[0039] Electrochemical metrology units are sensing modules that operate based on the principle of electrode reactions. They achieve precise quantification of specific heavy metal ions in soil by measuring changes in current, potential, or resistance generated by chemical reactions. Ion-selective electrode metrology units are sensors that convert ion activity into potential using a sensitive membrane that selectively responds to specific ions. They are primarily used to measure the concentration of specific heavy metal ions or acid / base ions in water. Ultraviolet spectrophotometry units are modules that quantitatively analyze pollutants by utilizing their absorption characteristics in specific ultraviolet light bands. They are commonly used to monitor the concentration of organic pollutants and chemical oxygen demand (COD) in water. Electromagnetic flowmeters are devices that measure the volumetric flow rate of conductive liquids using Faraday's law of electromagnetic induction. They are used to simultaneously acquire wastewater discharge rates or flow velocity data during water body monitoring.

[0040] The first set of detection data refers to the set of raw electrical signals, including spectral absorption characteristics and electrochemical response values, generated by the soil pollutant metering device, along with their preliminary converted concentration indicators. The second set of detection data refers to the set of water quality parameters, including ion concentration signals, light absorption intensity, and liquid flow rate signals, generated by the water pollutant metering device. The real-time temperature value of the operating environment refers to the thermodynamic state value of the internal or external environment of the metering device, sensed in real-time by a temperature sensor during mobile detection; this value directly affects the sensor's sensitivity. The real-time vibration frequency refers to the mechanical wave characteristics generated when the target base moves across rough terrain, captured by a triaxial vibration sensor. It is usually measured by the number of vibrations per unit time and is an important basis for assessing signal noise interference.

[0041] Understandably, firstly, after confirming the initial calibration is complete, the mobile metrology calibration system controls the drive motor of the target base to perform displacement operations according to the planned coordinate points, guiding the device into the preset path of the mine remediation area, and simultaneously issuing a start command to the pollutant metering device, so that the internal soil pollutant metering device and water pollutant metering device simultaneously enter real-time monitoring status. Secondly, the mobile metrology calibration system uses the soil pollutant metering device to perform multi-physics field coupling scanning on the surface soil, and uses the water pollutant metering device to perform in-situ sampling and analysis of the accumulated water in the mining area. Through the internal metering units, it collects raw physical quantity signals such as spectral absorption, electrochemical potential, photometry, and flow velocity, respectively, and preliminarily converts them into first detection data reflecting the soil pollution status and second detection data reflecting the water pollution status.

[0042] Then, the mobile metrology calibration system utilizes built-in temperature and triaxial vibration sensors to continuously capture real-time temperature values ​​inside the device and real-time mechanical vibration frequencies caused by terrain undulations during the movement of the target base, ensuring that each set of pollution data has a corresponding physical interference environmental background. Finally, the mobile metrology calibration system integrates the first and second detection data in a spatiotemporal dimension to form raw pollutant detection data characterizing the pollution level of the current work area. Based on the sampling timestamp, the real-time temperature values ​​and real-time vibration frequencies are aligned and encapsulated with the raw pollutant detection data, thereby obtaining complete work environment data covering pollution indicators and environmental parameters, providing data support for subsequent accuracy correction.

[0043] As an example, the steps of detecting mine soil using the soil pollutant metering device to obtain first detection data, and detecting mine water using the water pollutant metering device to obtain second detection data include: performing non-contact or contact scanning of the mine soil using the soil pollutant metering device, acquiring spectral characteristic signals using the near-infrared spectral metering unit, and acquiring heavy metal ion electrical signals using the electrochemical metering unit; performing in-situ detection of the mine water using the water pollutant metering device, acquiring ion concentration signals using the ion-selective electrode metering unit, acquiring organic pollutant absorbance signals using the ultraviolet spectrophotometer metering unit, and acquiring real-time wastewater flow signals using the electromagnetic flow metering unit; converting the spectral characteristic signals and heavy metal ion electrical signals into first detection data including total heavy metal concentration, soluble heavy metal concentration, sulfide concentration, pH, and porosity; and converting the ion concentration signals, absorbance signals, and real-time flow signals into second detection data including total heavy metal concentration, sulfide concentration, chemical oxygen demand, and wastewater flow rate.

[0044] It should be noted that the spectral characteristic signal refers to the specific wavelength light signal reflected or transmitted from the soil surface by the near-infrared spectroscopy metrology unit. Its intensity distribution curves at different wavelengths reflect the vibration and energy level transition information of specific molecular bonds in the soil. The heavy metal ion electrical signal refers to the current or potential difference signal captured by the electrochemical metrology unit through redox reactions under specific polarization voltages. The magnitude of this signal directly maps to the activity or content of heavy metal ions such as lead, cadmium, and zinc in the soil. The ion concentration signal refers to the potential signal output by the ion-selective electrode metrology unit after selectively responding to specific ions (such as mercury ions and sulfur ions) in the water. This signal follows the Nernst equation and is used to characterize the molar concentration of ions in the liquid. The organic pollutant absorbance signal refers to the intensity attenuation value of light after passing through the water sample, measured by the ultraviolet spectrophotometer. Based on the Beer-Lambert law, it determines the content of organic matter in the water by analyzing the degree of absorption in a specific ultraviolet band.

[0045] Real-time wastewater flow signal refers to the induced electromotive force signal generated by the electromagnetic flow metering unit using liquid cutting magnetic lines of force. Its amplitude is linearly related to the average flow velocity of conductive wastewater in the pipeline, and it is the basis for calculating instantaneous flow rate. Total heavy metal concentration refers to the sum of the masses of target heavy metal elements in all forms (solid particles, adsorbed state, and dissolved state) in soil or water, obtained after multi-source signal fusion calculation. Soluble heavy metal concentration refers to the concentration of heavy metal elements existing in soil pore water or water solution in ionic or complex form, determined by electrochemical or spectroscopic analysis. This indicator reflects the migration activity of pollutants. Porosity refers to the ratio of pore volume to total soil volume in soil, obtained through combined electromagnetic and near-infrared analysis. It is a key physical parameter for assessing the looseness of mine soil structure and the permeability characteristics of pollutants. Wastewater flow rate refers to the volume of wastewater flowing through the detection area per unit time (e.g., cubic meters per hour), obtained by time-domain integration of the real-time flow signal, used to assess the sewage load of the mine remediation area.

[0046] Understandably, the mobile metrology and calibration system first drives the soil pollutant metering device to be close to or near the ground surface during movement. Its internal near-infrared spectral metrology unit projects a specific wavelength light source and receives the reflected light intensity distribution to collect spectral characteristic signals. Simultaneously, an electrochemical metrology unit captures the charge drift generated by redox reactions under a specific polarization voltage to collect heavy metal ion electrical signals. Similarly, the mobile metrology and calibration system drives the water pollutant metering device to be immersed in the test liquid or extract a water sample. An ion-selective electrode metrology unit senses the potential difference across a sensitive membrane to collect ion concentration signals. An ultraviolet spectrophotometer metrology unit measures the light intensity attenuation ratio after passing through the water sample to collect organic pollutant absorbance signals. An electromagnetic flow metering unit is activated to generate an induced electromotive force by the conductive liquid cutting magnetic lines of force to collect real-time wastewater flow signals. Then, the mobile metrology and calibration system utilizes the signal processing circuits built into each metering unit to convert these signals into corresponding pollutant data, obtaining first and second detection data. This is done to convert the weak underlying physical electrical signals into specific indicator values ​​that meet environmental monitoring standards in real time, providing a standardized and calculable data benchmark for subsequent dynamic error correction based on environmental factors.

[0047] Specifically, the mobile metrology calibration system first utilizes the built-in signal processing circuits of each metrology unit to perform preliminary filtering and level conversion on the acquired spectral, potential, and electromagnetic analog signals, directly filtering out noise interference from the mine site. Subsequently, the system calls upon internally stored standard calibration curves to directly convert the spectral characteristic signals reflecting the soil and the heavy metal electrical signals into heavy metal concentration and pH indices, generating the first set of detection data. Simultaneously, it maps the ion potential difference, absorbance, and induced electromotive force signals of the water body to ion concentration, organic pollutant content, and wastewater flow rate according to a fixed ratio, generating the second set of detection data. Finally, the system structures and encapsulates these calculated values ​​according to timestamps.

[0048] As an example, the step of extracting a standard solution of a first preset concentration from the standard substance storage chamber for calibration and comparison when the moving operation distance is greater than a preset distance threshold or the number of detections is greater than a preset number of detections threshold, and obtaining a real-time deviation value reflecting the detection performance offset, includes: extracting a standard solution of a first preset concentration from the standard substance storage chamber when the moving operation distance is greater than a preset distance threshold or the number of detections is greater than a preset number of detections threshold; injecting the standard solution into the detection chamber of the pollutant metering device; controlling the pollutant metering device to measure the standard solution to obtain a measured concentration value; and using the absolute difference between the measured concentration value and the first preset concentration as the real-time deviation value reflecting the detection performance offset.

[0049] It should be noted that the detection chamber refers to a sealed or semi-open space located inside the pollutant metering device, used to contain the sample to be tested and provide a stable sensing environment. It integrates various precision sensor probes to ensure that the standard solution or environmental sample undergoes sufficient physical or chemical interaction with the metering unit under controlled conditions. The measured concentration value refers to the uncorrected instantaneous concentration value directly fed back and output by the pollutant metering device after detecting the extracted standard solution of the first preset concentration. It reflects the true response level of the sensor under the current operating conditions.

[0050] Understandably, this is done to accurately quantify the dynamic accuracy drift caused by mechanical vibration, changes in ambient temperature, or sensor fatigue during long-distance movement or high-frequency repetitive operations in complex mine terrain, thereby providing real-time quantitative basis for subsequent error fitting and correction.

[0051] As an example, the step of correcting the original pollutant detection data according to the calibration correction parameters to obtain target pollutant detection data and calibration record data includes: performing point-by-point compensation calculation on the original pollutant detection data according to the calibration correction parameters to obtain target pollutant detection data; obtaining the device number, standard substance batch, and calibration timestamp when the calibration action was performed; and spatiotemporally aligning and encapsulating the device number, the standard substance batch, and the calibration timestamp with the target pollutant detection data to obtain calibration record data.

[0052] It should be noted that a standard substance batch refers to the production batch number or unique identification code of the standard solution or standard sample stored in the standard substance storage warehouse. It is used to accurately trace the chemical properties, concentration determination results, and expiration date of the standard substance during the metrological traceability process.

[0053] Understandably, this is done to deeply link the test results with the calibration process, thereby ensuring that every piece of monitoring data has high precision and meets the strict regulatory requirements of environmental protection authorities for data authority and full-process traceability.

[0054] As an example, after the step of correcting the original pollutant detection data according to the calibration correction parameters to obtain target pollutant detection data and calibration record data, the method further includes: fusing the target pollutant detection data, the calibration record data, the detection location data, and the operating environment data to obtain full-dimensional detection data; generating a traceability code for the full-dimensional detection data, and associating and binding the traceability code with full-link data including the detection device number, the calibration record data, the detection time, and the detection location data to obtain traceable detection data; comparing the traceable detection data with a preset pollutant concentration threshold to obtain a comparison result; and issuing a graded early warning for pollutant exceedance based on the comparison result.

[0055] It should be noted that detection location data refers to the latitude and longitude coordinates and altitude information of sampling points acquired in real time through the built-in Global Positioning System (GPS) or BeiDou Navigation Satellite System (BDS), used to determine the geospatial distribution of pollutants. Full-dimensional detection data refers to a comprehensive dataset formed by deeply coupling the corrected pollutant concentration results, precise geographic coordinates, real-time environmental parameters, and corresponding calibration metadata in the same spatiotemporal dimension. The traceability code refers to a unique electronic identifier (e.g., a QR code or hexadecimal string) automatically generated by the system, serving as a digital index for accessing the entire lifecycle record of this batch of detection data. Traceable detection data refers to a legally valid and tamper-proof detection result package formed by logically associating the traceability code with full-link metadata containing hardware identity information, calibration records, timestamps, and location trajectories. The preset pollutant concentration threshold refers to the concentration limit value set according to the technical specifications for mine ecological restoration or national soil and water pollution prevention and control standards (e.g., 800 mg / kg lead content in soil). The comparison result refers to the logical judgment information generated after the target pollutant detection data is compared with the preset pollutant concentration threshold, which is about the multiple of exceeding the standard, the direction of deviation, or the standard status.

[0056] Understandably, the mobile metrology calibration system first performs multimodal fusion processing on corrected target pollutant detection data, calibration record data containing calibration process information, synchronously collected detection location data, and operational environment data reflecting the operational background. This eliminates time delays and spatial deviations between sensors, resulting in comprehensive detection data covering four dimensions: pollution, location, environment, and accuracy. Second, the system generates unique traceability codes for the comprehensive detection data using hash algorithms or unique coding algorithms. It then uses distributed ledger or database indexing technology to create a one-to-one association between this traceability code and the entire data chain, including the detection equipment number, calibration record data, detection time, and detection location data, encapsulating highly reliable traceable detection data. Finally, the system calls upon mine restoration standards stored locally or in the cloud, comparing the real-time concentration indicators in the traceable detection data with preset pollutant concentration thresholds item by item. This process analyzes the pollution level of the current sample point relative to the standard value and outputs the specific comparison results. Finally, the mobile metrology calibration system executes a preset pollutant exceedance classification and early warning logic based on the exceedance range and pollution nature of the comparison results. This is done to achieve accurate identification and classified control of pollution risks at the mine restoration site while ensuring data authenticity and traceability, providing a basis for decision-making in subsequent targeted governance.

[0057] This embodiment provides a mobile metrological calibration method for mine remediation pollutants. First, the mobile metrological calibration system identifies the mine remediation conditions and matches and assembles the corresponding target base and pollutant metering device. Before operation, it calls upon standard substances in the standard substance storage chamber to complete the initial calibration, which establishes the initial high-precision measurement benchmark for the equipment under specific terrain. Second, the target base is driven to move along a preset path and the pollutant metering device is used to perform mobile detection on the mine soil or water, acquiring original pollutant detection data and operating environment data including temperature and vibration, realizing real-time synchronous perception of pollution indicators and physical background interference. Then, the system monitors the mobile operation distance and the number of detections in real time during the movement. Once a preset threshold is exceeded, a standard solution of a first preset concentration is extracted from the storage chamber for online calibration and comparison, thereby calculating the real-time deviation value reflecting the deviation of detection performance. This allows the equipment to actively quantify the dynamic accuracy drift caused by long-distance operation or mechanical wear. Finally, the operating environment data is used to perform multi-dimensional error fitting correction on the real-time deviation value to obtain calibration correction parameters, and the original pollutant detection data is calibrated accordingly to obtain target pollutant detection data and calibration record data, ensuring the accuracy of the detection results under extreme interference and the traceability of the entire chain. This embodiment effectively solves the technical problems of easy drift in measurement accuracy and insufficient accuracy of detection data caused by the separation of calibration and detection during mobile detection in complex mining conditions by deeply integrating dynamic trigger calibration and multi-dimensional environmental compensation into the mobile detection process.

[0058] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 , Figure 2 This is a flowchart illustrating the second embodiment of the mobile metrological calibration method for mine remediation pollutants according to this application. Step S50 of the mobile metrological calibration method for mine remediation pollutants includes steps S51 to S55: Step S51: Extract real-time temperature value and real-time vibration frequency from the working environment data; Step S52: Calculate the first correction weight for compensating signal baseline drift based on the real-time temperature value and the preset temperature drift correction function. The preset temperature drift correction function is obtained by least squares fitting of the sensor's response output under different temperature gradients. Step S53: Calculate the second correction weight based on the real-time vibration frequency and the preset vibration interference model. The preset vibration interference model is obtained by measuring the signal noise characteristics of the sensor at different vibration frequencies and amplitudes on a vibration test bench simulating mining conditions, and using fast Fourier transform to extract the correlation between the interference main frequency and the signal fluctuation gain for fitting. Step S54: Input the real-time deviation value, the first correction weight and the second correction weight into a preset multiple linear regression model for parameter fitting to obtain the fitting result between environmental factors and sensor performance deviation. The preset multiple linear regression model is obtained by statistical regression analysis of full-condition sample data of the pollutant metering device under various environmental temperatures, vibration intensities and standard substance comparison deviations. Step S55: Determine the error compensation coefficient under the current operating condition based on the fitting result, and use the error compensation coefficient as the calibration correction parameter.

[0059] It should be noted that the preset temperature drift correction function is a mathematical mapping relationship describing the unexpected fluctuations in the sensor output signal caused by temperature changes. It is typically used to fit the measurement deviation at different temperature points using the least squares method to calculate the influence of temperature on the measurement reference. The preset temperature drift correction function is expressed as follows: ; in, This refers to the first adjusted weight. This refers to the real-time temperature value. This refers to the preset reference temperature (usually 25℃). It refers to the temperature correction factor, which reflects the physical characteristics of sensor materials and circuits as temperature changes.

[0060] The method for constructing the preset temperature drift correction function is as follows: Using a high and low temperature test chamber, the sensor is placed in an environment ranging from -20℃ to 60℃ under standard atmospheric pressure, with 5℃ increments. At each temperature equilibrium point, the sensor's output response at the standard substance concentration is recorded. The least squares method is used to perform polynomial fitting (usually n=3) on the temperature difference and signal offset to obtain the fitting coefficients. .

[0061] Signal baseline drift refers to the slow shift of a sensor's reference zero point or output reference over time due to factors such as temperature drift of electronic components or polarization of chemical electrodes, when the sensor is in a constant or zero input state. The first correction weight is a scaling factor calculated using a temperature correction function based on the difference between the real-time temperature and the reference temperature. It is used to quantitatively offset the numerical contribution of thermodynamic factors to the sensor signal.

[0062] A pre-defined vibration interference model is a physical model based on the signal-noise transfer function. It simulates and analyzes the interference characteristics of mechanical vibration on measurement accuracy by measuring the correlation between vibration parameters and signal fluctuations on a test bench. The pre-defined vibration interference model is represented as follows: ; in, This refers to the second adjusted weight; This refers to the dominant interference frequency, which is the most concentrated energy frequency identified from real-time vibrational frequencies using Fast Fourier Transform (FFT). One characteristic frequency point; This refers to the root mean square value of vibration acceleration, representing the vibration at a specific dominant frequency. Effective energy intensity of the vibration signal; It refers to the signal fluctuation gain, which is a linear regression coefficient measured by the test bench. It represents how much electrical signal offset (i.e., the slope k of the linear model) will be caused by the root mean square value of vibration acceleration per unit intensity to the sensor. It refers to the ambient noise floor constant, which represents the inherent weak electromagnetic or mechanical noise of the system even when it is at rest; This refers to the total number of extracted interference frequencies.

[0063] The method for constructing the pre-defined vibration interference model is as follows: First, the pollutant metering device is installed on a triaxial simulated vibration test bench simulating mining conditions, and the vibration frequency and amplitude are continuously changed within the range of 0-100Hz to simulate the physical impact of the target base operating on an uneven road surface. Second, the metering unit synchronously collects time-domain noise signals under various working conditions and performs a fast Fourier transform to identify the top n dominant interference frequencies that contribute the most to the sensor signal. Simultaneously, the root mean square (RMS) values ​​of vibration acceleration corresponding to these dominant frequency components are calculated. Then, the dynamic changes in the amplitude of the signal noise generated by the sensor with the RMS values ​​of vibration acceleration at each dominant frequency are recorded, and the experimental data are fitted using a linear regression algorithm. Finally, a linear correlation model between the RMS value of vibration acceleration and the amplitude of signal noise is established, and the signal fluctuation gain of each frequency band is extracted as the core parameter of the model. This is done to accurately identify the interference source in the frequency domain and quantify the physical impact of mechanical vibration on metering accuracy through time-domain energy indices, thereby achieving standardized linear correction for complex vibration noise.

[0064] The second correction weight refers to the correction coefficient calculated by extracting the main interference frequency after performing spectral analysis on the vibration frequency. It is specifically used to filter out or reduce mechanical noise caused by the movement of the base at the algorithm level.

[0065] A pre-defined multiple linear regression model is a mathematical model that uses statistical analysis to determine the linear relationship between multiple independent variables (such as temperature drift weight, vibration weight, and initial deviation) and a dependent variable (actual performance deviation). It is used to find the optimal deviation prediction pattern under full-condition sample data. The pre-defined multiple linear regression model is expressed as follows: ; in, This represents the calibration correction parameters after fitting; This refers to the original performance offset (i.e., real-time deviation value) obtained during the calibration process. , , These refer to the regression coefficients, which represent the contribution weights of real-time deviation, temperature, and vibration to the final measurement result, respectively. This refers to the constant term (intercept), which represents the inherent bias of the system. This represents the random error term or residual, which indicates the portion of the sensor's performance deviation that cannot be explained by known environmental factors such as real-time temperature (first correction weight) and real-time vibration frequency (second correction weight). In the algorithm, The distribution characteristics are used to evaluate the reliability of the model; ideally, It should follow a normal distribution with a mean of 0.

[0066] The pre-defined method for constructing a multiple linear regression model involves collecting a large number of experimental samples during the mobile operation, including real-time deviation values, temperature correction weights (i.e., the first correction weight), vibration correction weights (i.e., the second correction weight), and the true values ​​of known standard materials. Regression coefficients are calculated using regression analysis to minimize the sum of squared residuals between the model's predicted values ​​and the actual drift values.

[0067] Environmental factors refer to various external physical variables that have non-target effects on sensor measurement accuracy during mine restoration operations; in this scheme, they specifically refer to real-time temperature and real-time vibration frequency. Sensor performance offset refers to the degree to which the output characteristics of the pollutant metering device deviate from its standard calibration state during actual operation, typically manifested as changes in sensitivity or zero drift. The error compensation coefficient is an adjustment parameter obtained by inverting the comprehensive deviation value predicted by the model; adding it to the original data achieves physical cancellation of measurement deviations.

[0068] Understandably, firstly, the mobile metrology and calibration system extracts real-time temperature and vibration frequencies from the acquired operating environment data, providing underlying parameter support for the quantification of environmental interference. Secondly, the system substitutes the real-time temperature values ​​into a preset temperature drift correction function, and uses the response characteristics fitted by the least squares method to calculate the first correction weight used to offset thermodynamic fluctuations, thereby suppressing signal baseline drift. Then, it uses a fast Fourier transform to analyze the interference dominant frequency in the real-time vibration frequency, and combines it with a preset vibration interference model to calculate the second correction weight used to eliminate mechanical noise.

[0069] Subsequently, the mobile metrology calibration system inputs the aforementioned real-time deviation value, the first correction weight, and the second correction weight into a preset multiple linear regression model for parameter fitting. By analyzing the statistical regression relationship between these variables and the sensor output characteristics, the system outputs a fitting result characterizing the correlation between current environmental factors and sensor performance deviation, aiming to determine the error distribution pattern under the current multi-factor coupling. Finally, the system calculates the comprehensive predicted deviation value of the sensor due to environmental interference under the current operating conditions based on the fitting result, and inverts this comprehensive predicted deviation value (i.e., converts it to its opposite) as the error compensation coefficient, which is determined as the calibration correction parameter. This is done to separate the system deviation predicted by the model from the original detection data through mathematical inverse compensation, thereby ensuring that the detection values ​​can still maintain high accuracy and stability in the variable dynamic environment of mobile mining operations.

[0070] This embodiment first extracts real-time temperature and vibration frequency from the operating environment data, providing basic environmental parameter inputs for subsequent multi-dimensional compensation. Second, the real-time temperature value is substituted into a preset temperature drift correction function obtained through least squares fitting to calculate the first correction weight used to offset thermodynamic fluctuations, effectively suppressing the signal baseline drift caused by environmental temperature differences. Simultaneously, the real-time vibration frequency is analyzed using fast Fourier transform, and a second correction weight for eliminating mechanical noise is calculated using a preset vibration interference model, solving the high-frequency vibration interference caused by the mobile base traveling on the rugged surface of the mine. Then, the aforementioned measured real-time deviation value and the two correction weights are input into a preset multiple linear regression model obtained through statistical regression of full-condition sample data for parameter fitting. By analyzing the coupling relationship between environmental factors and sensor performance deviation, accurate identification of error distribution patterns under complex operating conditions is achieved. Finally, the comprehensive predicted deviation value caused by sensor interference is calculated based on the fitting results and inverted to determine the error compensation coefficient. This coefficient is used as a calibration correction parameter to perform real-time correction of the original data, thereby ensuring the measurement accuracy and data stability of the mobile mine detection system under dynamic changing environments.

[0071] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the mobile measurement and calibration method for mine remediation pollutants in this application. Any simple modifications based on this technical concept are within the scope of protection of this application.

[0072] The mobile metrology calibration system of this application adopts a modular quick-release structure, mainly including a main support section, a pollutant-specific metrology section, a dynamic metrology calibration section, a data processing and transmission section, and an auxiliary adapter section. Each part can be quickly assembled and disassembled and work together through a universal interface, taking into account both portability and mobile operation requirements. The system exterior adopts an IP67 fully sealed protection design, with the shell made of high-strength aluminum alloy and coated with an anti-corrosion and anti-static coating. The sensor interface uses a dustproof and sealed connector, and the junction box is filled with dustproof and moisture-proof adhesive, which can effectively resist the corrosion of the high dust and humid environment of the mine. The main support section is equipped with a shock-absorbing and buffering structure, which can absorb more than 70% of vibration energy, ensuring stable metrological accuracy during mobile operations.

[0073] (1) The main support part is the core load-bearing structure of the system. It adopts a four-wheel drive off-road vehicle chassis or a towable container structure, and is equipped with hydraulic leveling outriggers to adapt to unpaved sites with a slope of ≤15°.

[0074] (2) The pollutant-specific metering section is the core detection unit of the device. It is designed for characteristic pollutants in mines (heavy metals, sulfides), and integrates multi-principle metering technology to achieve simultaneous and accurate detection of multiple parameters of pollutants in soil and water. Specifically, it includes a soil pollutant metering device and a water pollutant metering device, which can be switched according to the needs of the scenario: ① Soil pollutant metering device: integrates near-infrared spectroscopy metering unit and electrochemical metering unit to simultaneously detect total heavy metals (lead, cadmium, zinc, mercury), soluble heavy metals, sulfides and auxiliary parameters (pH value, porosity) in soil.

[0075] ② Water pollutant metering device: integrates ion-selective electrode metering unit, ultraviolet spectrophotometer metering unit and electromagnetic flow metering unit, and simultaneously detects total heavy metals, soluble heavy metals, sulfides, COD and wastewater flow in water.

[0076] The ion-selective electrode metering unit features a dedicated electrode designed for heavy metal ions in mine water, specifically identifying ions such as lead, cadmium, and zinc, unaffected by turbidity or impurities. The ultraviolet spectrophotometer metering unit detects sulfide and COD concentrations using ultraviolet absorption, and includes a built-in turbidity compensation module to eliminate interference from mine wastewater turbidity. The electromagnetic flowmeter unit collects wastewater flow data in real time and calculates total pollutant emissions based on pollutant concentrations. The metering device is equipped with a waterproof detection probe made of titanium alloy, which is corrosion-resistant and wear-resistant, suitable for detecting acidic mine wastewater and wastewater containing heavy metals.

[0077] Both metering devices have a built-in multi-parameter adaptation database, which automatically matches metering parameters for different types of soil (imported soil, virgin soil, reclaimed soil) and different water qualities (acidic wastewater, subsidence water, leached water) in the mine, avoiding manual adjustment and improving detection efficiency.

[0078] (3) The dynamic metrology calibration section is the core unit to ensure metrological accuracy. It constructs a closed-loop mechanism of "automatic calibration-error correction-data association" to realize real-time calibration during mobile operations and correct accuracy drift caused by vibration and temperature changes.

[0079] (4) The data processing and transmission section realizes the fusion processing, real-time transmission and hierarchical early warning of detection data, calibration data and location data, including a data fusion unit, a wireless transmission unit, an early warning unit and a data tracing unit: ① Data Fusion Unit: Built-in edge computing chip with a processing speed of ≥1GHz, it can fuse pollutant detection data, calibration correction parameters, Beidou positioning data, and environmental parameters (temperature, vibration) in real time, and automatically generate detection reports. The reports include pollutant type, concentration value, detection location, calibration information, error range, etc. It also supports real-time data analysis and generates a heat map of the spatial distribution of pollutant concentration, which intuitively presents the pollutant diffusion range and concentration gradient.

[0080] ② Wireless transmission unit: integrates 4G / 5G and WiFi dual-mode transmission modules, adapting to the complex signal environment of mines. It prioritizes 5G transmission (transmission rate ≥100Mbps), and automatically switches to 4G or WiFi transmission in areas without 5G signal. Data transmission adopts an encrypted protocol to prevent data leakage and tampering, ensuring that the detection data is transmitted back to the ground terminal (computer, tablet, mobile phone) in real time with a delay of ≤1 second, and supports multiple people to view simultaneously.

[0081] ③ Early Warning Unit: Supports users to preset the concentration thresholds of various pollutants (refer to the "Technical Specifications for Ecological Restoration of Mines" and "Surface Water Environmental Quality Standards"). When the concentration of pollutants is detected to exceed the threshold, a graded early warning will be automatically triggered: Level 1 warning (minor exceedance) will be reminded through a pop-up window on the terminal; Level 2 warning (moderate exceedance) will be reminded through an audible and visual alarm (alarm volume ≥ 80dB) + push notification on the terminal; Level 3 warning (severe exceedance) will be triggered simultaneously with on-site emergency equipment (such as wastewater treatment valves and warning lights) and the location of the exceedance will be marked to support emergency response.

[0082] ④ Data Traceability Unit: Generates a unique traceability code for each piece of test data. The traceability code is associated with the entire data chain, including the testing equipment number, calibration record, testing personnel, testing time, and location information. The complete data chain can be queried by scanning the code at the terminal, meeting the requirements of environmental metrology supervision for data traceability. It also supports exporting data to standardized formats (PDF, Excel) for direct use in remediation effect assessment reports and environmental verification.

[0083] (5) The auxiliary adapter section provides auxiliary support for the stable operation of the device, including the attitude adjustment unit, the lighting unit, and the fault diagnosis unit: ① Lighting unit: It adopts LED high-brightness light source with a brightness of ≥500lm and an illumination range of ≥5m. It supports two levels of adjustment: strong light and weak light, which is suitable for underground mines, tunnels and nighttime operation scenarios to ensure clear detection operation and data reading.

[0084] ② Fault diagnosis unit: Real-time monitoring of the operating status of each module (battery power, sensor performance, transmission signal, calibration function). When problems such as sensor failure, calibration failure, insufficient power, or signal interruption occur, it automatically issues a fault reminder and displays the fault location, facilitating on-site troubleshooting and maintenance and reducing equipment downtime.

[0085] This system can quickly adapt to core mine remediation scenarios such as soil reclamation areas, high slopes, and wastewater ponds, overcoming the limitations of existing equipment in adapting to a single scenario and enabling full-area detection without replacing multiple devices.

[0086] This system features a specialized metering device designed for characteristic pollutants such as heavy metals and sulfides in mines. It integrates multiple metering technologies, including high-frequency electromagnetic induction, near-infrared spectroscopy, and ion-selective electrodes, along with error compensation and anti-interference design, to improve the detection accuracy of heavy metals and sulfides. Simultaneously, a dynamic calibration unit enables real-time calibration during mobile operations, correcting accuracy drift and ensuring the stability of detection data under high dust and strong vibration conditions. This significantly improves data reliability and allows for the accurate capture of pollutant concentration gradients and dynamic migration patterns.

[0087] This system is the first to construct a closed-loop mechanism of "real-time measurement - automatic calibration - data association" in a mobile mining detection scenario, breaking through the bottleneck of the separation of measurement and calibration in existing technologies and ensuring that every piece of detection data has corresponding calibration support. At the same time, by linking the entire chain of data through a unique traceability code, it realizes the traceability of information such as detection, calibration, location, and personnel, which fully meets the requirements of environmental metrology supervision for data authority and verifiability, eliminating the need for additional calibration certificates and significantly reducing environmental verification costs.

[0088] This system integrates functions such as mobile inspection, precise metering, real-time calibration, data transmission, and exceedance warning, enabling real-time data transmission, automatic analysis, and tiered warnings, avoiding secondary manual processing. The exceedance warning function can quickly locate pollution peak areas, providing precise basis for targeted addition of amendments and adjustment of wastewater treatment parameters during the remediation process, reducing material waste. The generated standardized test reports and concentration heat maps can be directly used for remediation effect evaluation, supporting scheme optimization and promoting the transformation of mine remediation from experience-based to precision-based.

[0089] This system adopts a modular quick-release design and high-strength lightweight materials to control the total weight of the equipment. Its portability is significantly better than existing heavy mobile inspection equipment. At the same time, through special shock absorption and sealing protection design, it ensures that the equipment can operate stably in the harsh working conditions of the mine with a battery life of ≥8 hours, which can meet the needs of all-day field operations. Compared with existing equipment, the operational flexibility and battery life are improved by more than 40%.

[0090] This system is not only applicable to various mine restoration scenarios, including metal and non-metal mines, but also adaptable to pollutant detection needs in similar scenarios such as wetland remediation and soil pollution control. By adjusting standard substances and metrological parameters, it can be extended to the detection of other characteristic pollutants, demonstrating broad applicability. The device has a mature structural design, core modules can be mass-produced, and costs are controllable. Compared to existing imported equipment, its price is reduced by more than 50%, indicating promising prospects for industrialization and promotion. It is of great significance for promoting the refined and standardized development of mine ecological restoration technology in my country.

[0091] This application also provides a mobile metering and calibration device for mine remediation pollutants; please refer to [reference needed]. Figure 3 The mobile metering and calibration device for mine remediation pollutants includes: Initialization module 10 is used to select the corresponding target base and pollutant metering device according to the mine restoration conditions, and to call the standard material storage bin for initial calibration after assembly. The mobile metering module 20 is used to perform mobile detection of characteristic pollutants in mine soil or water after the initial calibration is completed, and to obtain the original pollutant detection data and the corresponding working environment data. The status statistics module 30 is used to calculate the current moving operation distance and the number of detections during the movement process; The dynamic comparison module 40 is used to extract a standard solution of a first preset concentration from the standard substance storage chamber for calibration and comparison when the moving operation distance is greater than a preset distance threshold or the number of detections is greater than a preset number of detections threshold, so as to obtain a real-time deviation value that reflects the offset of the detection performance. Error correction module 50 is used to perform multi-dimensional error fitting correction on the real-time deviation value based on the working environment data to obtain calibration correction parameters; The data calibration module 60 is used to correct the original pollutant detection data according to the calibration correction parameters to obtain target pollutant detection data and calibration record data.

[0092] The mobile metrological calibration device for mine remediation pollutants provided in this application, employing the mobile metrological calibration method for mine remediation pollutants in the above embodiments, can solve the technical problems of easy drift in metrological accuracy and insufficient accuracy of detection data caused by the separation of calibration and detection during mobile detection in complex mine working conditions. Compared with the prior art, the beneficial effects of the mobile metrological calibration device for mine remediation pollutants provided in this application are the same as the beneficial effects of the mobile metrological calibration method for mine remediation pollutants provided in the above embodiments, and other technical features in the mobile metrological calibration device for mine remediation pollutants are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0093] This application provides a mobile metrological calibration device for mine remediation pollutants. The mobile metrological calibration device for mine remediation pollutants includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the mobile metrological calibration method for mine remediation pollutants in the above embodiment 1.

[0094] The following is for reference. Figure 4 The diagram illustrates a structural schematic of a mobile metrological calibration device suitable for implementing embodiments of the present application for mine remediation pollutants. The mobile metrological calibration device for mine remediation pollutants in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), vehicle terminals (e.g., vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 4 The mobile metering and calibration device for mine remediation pollutants shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments in this application.

[0095] like Figure 4As shown, the mobile metrology and calibration device for mine remediation pollutants may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in ROM (Read Only Memory) 1002 or a program loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the mobile metrology and calibration device for mine remediation pollutants. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. Input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, LCDs (Liquid Crystal Displays), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the mobile metrology and calibration equipment for mine remediation contaminants to exchange data wirelessly or via wired communication with other devices. Although the figure shows a mobile metrology and calibration equipment for mine remediation contaminants with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems may be implemented alternatively.

[0096] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0097] The mobile metrological calibration device for mine remediation pollutants provided in this application, employing the mobile metrological calibration method for mine remediation pollutants in the above embodiments, can solve the technical problems of easy drift in metrological accuracy and insufficient accuracy of detection data caused by the separation of calibration and detection during mobile detection in complex mine working conditions. Compared with the prior art, the beneficial effects of the mobile metrological calibration device for mine remediation pollutants provided in this application are the same as the beneficial effects of the mobile metrological calibration method for mine remediation pollutants provided in the above embodiments, and other technical features in this mobile metrological calibration device for mine remediation pollutants are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0098] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0099] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0100] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the mobile metering and calibration method for mine remediation pollutants in the above embodiments.

[0101] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable Read Only Memory or Flash Memory), optical fibers, CD-ROM (CD-Read Only Memory), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0102] The aforementioned computer-readable storage medium may be included in a mobile metrology and calibration device for mine remediation pollutants; or it may exist independently and not be assembled into a mobile metrology and calibration device for mine remediation pollutants.

[0103] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the mobile metering and calibration equipment for mine remediation pollutants, the mobile metering and calibration equipment for mine remediation pollutants performs the following actions: It selects a corresponding target base and assembles it with the pollutant metering device according to the mine remediation conditions; after assembly, it calls the standard material storage chamber for initial calibration; after the initial calibration is completed, it performs mobile detection of characteristic pollutants in the mine soil or water to obtain original pollutant detection data and corresponding operating environment data; during the movement, it calculates the current mobile operating distance and the number of detections; when the mobile operating distance is greater than a preset distance threshold or the number of detections is greater than a preset number of detections threshold, it extracts a standard solution of a first preset concentration from the standard material storage chamber for calibration comparison to obtain a real-time deviation value reflecting the deviation in detection performance; it performs multi-dimensional error fitting correction on the real-time deviation value based on the operating environment data to obtain calibration correction parameters; and it corrects the original pollutant detection data based on the calibration correction parameters to obtain target pollutant detection data and calibration record data.

[0104] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including LAN (Local Area Network) or WAN (Wide Area Network)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0105] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0106] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0107] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned mobile metrological calibration method for mine remediation pollutants. This solves the technical problem of insufficient accuracy of detection data due to easy drift in metrological accuracy and separation of calibration and detection during mobile detection in complex mine conditions. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the mobile metrological calibration method for mine remediation pollutants provided in the above embodiments, and will not be repeated here.

[0108] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the mobile metrological calibration method for mine remediation pollutants as described above.

[0109] The computer program product provided in this application can solve the technical problems of insufficient accuracy of detection data due to easy drift in measurement accuracy and separation of calibration and detection during mobile detection in complex mining conditions. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the mobile measurement and calibration method for mine remediation pollutants provided in the above embodiments, and will not be repeated here.

[0110] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A mobile metrological calibration method for mine remediation pollutants, characterized in that, The method includes: According to the mine restoration conditions, select the corresponding target base and pollutant metering device for assembly, and call the standard material storage chamber for initial calibration after assembly; Once the initial calibration is completed, mobile detection of characteristic pollutants in mine soil or water is performed to obtain raw pollutant detection data and corresponding work environment data. During the movement, calculate the current movement distance and the number of detections; When the mobile operation distance is greater than a preset distance threshold or the number of detections is greater than a preset number of detections threshold, a standard solution of a first preset concentration is extracted from the standard substance storage chamber for calibration and comparison to obtain a real-time deviation value reflecting the offset of the detection performance. Based on the operating environment data, the real-time deviation value is corrected by multi-dimensional error fitting to obtain calibration correction parameters; The original pollutant detection data is corrected according to the calibration correction parameters to obtain the target pollutant detection data and calibration record data.

2. The method as described in claim 1, characterized in that, The step of performing multidimensional error fitting correction on the real-time deviation value based on the working environment data to obtain calibration correction parameters includes: Extract real-time temperature and real-time vibration frequency from the operating environment data; Based on the real-time temperature value and the preset temperature drift correction function, a first correction weight for compensating for signal baseline drift is calculated. The preset temperature drift correction function is obtained by least squares fitting of the sensor's response output under different temperature gradients. Based on the real-time vibration frequency and the preset vibration interference model, the second correction weight is calculated. The preset vibration interference model is obtained by measuring the signal noise characteristics of the sensor at different vibration frequencies and amplitudes on a vibration test bench simulating mining conditions, and by using fast Fourier transform to extract the correlation between the interference main frequency and the signal fluctuation gain for fitting. The real-time deviation value, the first correction weight and the second correction weight are input into a preset multiple linear regression model for parameter fitting to obtain the fitting result between environmental factors and sensor performance deviation. The preset multiple linear regression model is obtained by statistical regression analysis of full-condition sample data of the pollutant metering device under various environmental temperatures, vibration intensities and standard substance comparison deviations. The error compensation coefficient under the current operating condition is determined based on the fitting result, and the error compensation coefficient is used as the calibration correction parameter.

3. The method as described in claim 1, characterized in that, The step of performing mobile detection of characteristic pollutants in mine soil or water to obtain raw pollutant detection data and corresponding working environment data after the initial calibration is completed includes: Once the initial calibration is completed, the target base is driven to move along a preset path, and the pollutant metering device is activated. The pollutant metering device includes a soil pollutant metering device and a water pollutant metering device. The soil pollutant metering device includes a near-infrared spectroscopy metering unit and an electrochemical metering unit. The water pollutant metering device includes an ion-selective electrode metering unit, an ultraviolet spectrophotometer metering unit, and an electromagnetic flow metering unit. The soil in the mine is tested using the soil pollutant metering device to obtain first test data, and the water body in the mine is tested using the water pollutant metering device to obtain second test data. Monitor the real-time temperature of the working environment and the real-time vibration frequency of the target base during movement; By integrating the first detection data and the second detection data, the original pollutant detection data is obtained, and the real-time temperature value and the real-time vibration frequency are used as the corresponding working environment data.

4. The method as described in claim 3, characterized in that, The steps of testing the mine soil using the soil pollutant metering device to obtain first test data, and testing the mine water using the water pollutant metering device to obtain second test data, include: The soil pollutant metering device is used to perform non-contact or contact scanning of the mine soil, the near-infrared spectral metering unit is used to collect spectral characteristic signals, and the electrochemical metering unit is used to collect heavy metal ion electrical signals. The water pollutant metering device is used to perform in-situ detection of mine water. The ion concentration signal is collected by the ion-selective electrode metering unit, the absorbance signal of organic pollutants is collected by the ultraviolet spectrophotometer metering unit, and the real-time flow signal of wastewater is collected by the electromagnetic flow metering unit. The spectral feature signal and the heavy metal ion electrical signal are converted into first detection data including total heavy metal concentration, soluble heavy metal concentration, sulfide concentration, pH and porosity. The ion concentration signal, the absorbance signal, and the real-time flow rate signal are converted into second detection data that includes total heavy metal concentration, sulfide concentration, chemical oxygen demand, and wastewater flow rate.

5. The method as described in claim 1, characterized in that, The steps of selecting the appropriate target base and pollutant metering device according to the mine restoration conditions, assembling them, and then calling the standard material storage bin for initial calibration after assembly include: Identify mine restoration conditions, including rugged reclamation areas, high-altitude slopes, or decentralized wastewater ponds; Match the corresponding target base according to the mine restoration conditions. The rugged reclamation area corresponds to the tracked base, the high drop slope corresponds to the handheld telescopic base, and the decentralized wastewater pond corresponds to the floating base. Assemble the target base with the pollutant metering device; The pollutant metering device is controlled to measure the standard substance of a second preset concentration in the standard substance storage chamber to obtain an initial measurement value; The initial calibration is completed based on the initial measurement value and the zero point of the second preset concentration calibration sensor.

6. The method as described in claim 1, characterized in that, After the step of correcting the original pollutant detection data according to the calibration correction parameters to obtain the target pollutant detection data and calibration record data, the method further includes: The target pollutant detection data, the calibration record data, the detection location data, and the working environment data are fused together to obtain full-dimensional detection data. A traceability code is generated for the full-dimensional detection data, and the traceability code is associated and bound with full-link data including the detection device number, the calibration record data, the detection time, and the detection location data to obtain traceable detection data. The traceable detection data is compared with a preset pollutant concentration threshold to obtain the comparison result; Based on the comparison results, pollutant exceedance levels will be graded and warnings will be issued.

7. The method according to any one of claims 1 to 6, characterized in that, The step of correcting the original pollutant detection data according to the calibration correction parameters to obtain the target pollutant detection data and calibration record data includes: The original pollutant detection data is compensated point by point according to the calibration correction parameters to obtain the target pollutant detection data. Obtain the device number, standard substance batch, and calibration timestamp when the calibration action is performed; The device number, the standard substance batch, and the calibration timestamp are spatiotemporally aligned and encapsulated with the target pollutant detection data to obtain calibration record data.

8. A mobile metering and calibration device for mine remediation pollutants, characterized in that, The device includes: The initialization module is used to select the corresponding target base and pollutant metering device according to the mine restoration conditions, and to call the standard material storage bin for initial calibration after assembly. The mobile metering module is used to perform mobile detection of characteristic pollutants in mine soil or water after the initial calibration is completed, and to obtain raw pollutant detection data and corresponding working environment data. The status statistics module is used to calculate the current moving operation distance and the number of detections during the movement process; The dynamic comparison module is used to extract a standard solution of a first preset concentration from the standard substance storage chamber for calibration and comparison when the moving operation distance is greater than a preset distance threshold or the number of detections is greater than a preset number of detections threshold, so as to obtain a real-time deviation value that reflects the offset of the detection performance. The error correction module is used to perform multi-dimensional error fitting correction on the real-time deviation value based on the operating environment data to obtain calibration correction parameters. The data calibration module is used to correct the original pollutant detection data according to the calibration correction parameters to obtain target pollutant detection data and calibration record data.

9. A mobile metering and calibration device for mine remediation pollutants, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the mobile metrological calibration method for mine remediation pollutants as claimed in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the mobile metering and calibration method for mine remediation pollutants as described in any one of claims 1 to 7.

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