A coal mine gas safety intelligent inspection and linkage analysis system

Abstract

This invention relates to the field of coal mine safety technology, specifically to a coal mine gas safety intelligent inspection and linkage analysis system, comprising a sensor module, a manual inspection assistance module, a detection point module, and a processing module. The sensor module is used to collect some situational characteristic indicators required for gas safety status assessment. The manual inspection assistance module is used to monitor gas concentration within the monitoring area of ​​the detection point by inspection personnel. The detection point module is used to monitor the gas concentration information at the detection point. The processing module is used to classify the gas safety status level of the detection point based on a gas safety status level judgment strategy. This invention can improve the work standardization of inspectors during manual inspections when the manual inspection assistance module is activated, thereby improving the accuracy of manual assistance data. This facilitates continuous optimization of the entire intelligent inspection system after the linkage analysis of manual assistance data and intelligent inspection data, improving the accuracy of the overall system's analysis results.

Description

Technical Field

[0001] This invention relates to the field of coal mine safety technology, specifically to a coal mine gas safety intelligent inspection and linkage analysis system. Background Technology

[0002] Early coal mining relied primarily on manual labor, using simple tools for excavation. Due to limitations in technology and equipment, early coal mining carried high safety risks, low efficiency, and limited output. With the advancement of the Industrial Revolution and continuous technological development, coal mining gradually became mechanized, automated, and intelligent. Modern coal mining widely utilizes mechanical equipment such as fully mechanized mining machines, roadheaders, and hydraulic supports, greatly improving mining efficiency and significantly enhancing safety levels.

[0003] In the process of coal mine safety production, gas accidents have always been a major factor affecting the safety of underground personnel. To effectively prevent gas disasters, various gas prediction and early warning technologies have been gradually applied to coal mine safety management equipment. Accurate and effective gas prediction and early warning are of great significance to ensuring the safety of workers.

[0004] Some existing intelligent inspection technologies for coal mine gas safety employ a model that primarily uses intelligent inspection, supplemented by manual inspection, for coal mine gas safety detection. When intelligent equipment cannot achieve the expected inspection results, or when periodically checking the operational status of intelligent inspection equipment, manual inspection is activated. This allows for timely inspection of these devices or areas difficult to inspect intelligently, enabling appropriate measures to be taken, thereby improving the safety of coal mining. However, for manual inspection, the detection results are closely linked to the operator's adherence to operational standards. If the operator's operational standards are low (e.g., improper operation such as not conducting inspections at designated points), it will significantly affect the detection results, increasing the possibility of safety accidents due to excessive gas accumulation. Furthermore, for some equipment, it is impossible to compare data with manually detected data in a timely manner. This lack of timely data exchange also increases the risk. Moreover, if equipment malfunctions, they may not be detected promptly, further increasing the likelihood of accidents.

[0005] In summary, this invention proposes a coal mine gas safety intelligent inspection linkage analysis system. When manual inspection assists intelligent inspection, it improves the work standardization of inspectors during manual inspection and provides more accurate data. It facilitates the linkage analysis of manual inspection data and intelligent inspection data to continuously optimize the entire intelligent inspection system and improve the accuracy of the analysis results of the entire system. Summary of the Invention

[0006] To address the aforementioned issues, this invention provides a coal mine gas safety intelligent inspection and linkage analysis system. When manual inspections are used to assist intelligent inspections, this system improves the accuracy of inspectors' work procedures and provides more precise data. It also facilitates continuous optimization of the entire intelligent inspection system through the linkage analysis of manual and intelligent inspection data, thereby enhancing the accuracy of the overall system's analysis results.

[0007] To achieve the above objectives, the technical solution of the present invention is as follows: a coal mine gas safety intelligent inspection and linkage analysis system, comprising a sensor module, a manual inspection auxiliary module, a detection point module and a processing module;

[0008] The sensor module is used to collect some of the situational characteristic indicators required for gas safety status assessment;

[0009] The manual inspection auxiliary module is used to obtain manual monitoring auxiliary data for the detection point by having inspectors monitor the gas concentration within the monitoring area of ​​the detection point. According to the detection point number, the manual monitoring data is labeled accordingly, and the concentration and label information is transmitted to the detection point module of the monitoring point. It is also used to detect the working status of the intelligent inspection settings within the detection point.

[0010] The detection point module is used to monitor the gas concentration information at the detection point based on intelligent sensor technology and to collect image information within the detection point area;

[0011] The detection point module includes an intelligent inspection unit, which is used to conduct further all-round unmanned monitoring of underground coal mines through intelligent detection technology. The intelligent detection technology includes at least intelligent mechanical inspection technology and absorption spectroscopy detection technology.

[0012] The processing module is used to classify the gas safety status level of the detection point into A, B, C and D from high to low based on the gas safety status level judgment strategy; it is also used to determine whether the manual monitoring data of the detection point is usable based on whether there is an image of the inspector in the image of the detection point. When the image of the inspector exists, the manual monitoring data is usable and can be further analyzed and compared. When the image of the inspector does not exist or the completeness is less than a preset threshold, the manual monitoring data will not be further analyzed and compared, and an alarm signal will be generated and transmitted to the detection point module of the detection point.

[0013] Furthermore, the strategy for determining the gas safety status level includes:

[0014] Step 1: Quantitatively preprocess the collected situational characteristic index data samples to obtain the corresponding safety level; the situational characteristics include gas concentration, wind speed, gas pressure, coal seam permeability coefficient, gas emission, dust content, gas extraction rate, coal seam gas content, electrical equipment integrity, ambient temperature, upper corner gas concentration, return airway gas concentration, and intake air gas concentration;

[0015] Step 2: The weights of each quantitative indicator are determined by the analytic hierarchy process (AHP). The data of the indicator layer are evaluated by a first-level fuzzy comprehensive method to obtain the first state evaluation value of each event in the criterion layer. Then, the weights of each event in the criterion layer are obtained by the AHP method and evaluated by a second-level fuzzy method to obtain the second situation evaluation value.

[0016] Step 3: Determine the factor set and evaluation set. The factor set is determined based on the established safety situation characteristic index system, where the primary index U0 = {gas combustion and explosion}, the secondary indices U1 and U2 = {gas accumulation and ignition source}, and the tertiary indices U1m = {gas concentration, wind speed, gas pressure, coal seam permeability coefficient, gas emission rate, dust content, coal seam gas content, corner gas concentration, return airway gas concentration, and intake air gas concentration}, and U2n = {electrical equipment integrity, ambient temperature, and gas extraction rate}, where m belongs to {1, 2, 3, 4, 5, 6, 7, 8, 9, 10} and n belongs to {1, 2, 3}. The evaluation set is divided into four assessment level domains V = {A, B, C, D} according to the severity of the situation from low to high, combined with different numerical ranges.

[0017] Step four: The safety assessment level V = {A, B, C, D} data obtained in step three is sent to the detection point module. The detection point module visualizes the gas safety status level and transmits the gas safety status level data to the manual inspection auxiliary module in real time.

[0018] Furthermore, the detection point module also includes a gas detection unit, an image acquisition unit, a signal transmission unit, and a notification unit;

[0019] The gas detection unit is used to monitor the gas concentration at the detection point through a gas concentration sensor installed at the detection point, obtain non-manual monitoring data, label the data according to the detection point number, and transmit the concentration and label information to the signal transmission unit.

[0020] The image acquisition unit is used to acquire images within the detection point and label the images accordingly based on the detection point number.

[0021] The signal transmission unit is used to upload the image data generated by the image acquisition unit to the processing module; it is also used to transmit the image and its label information generated by the image acquisition unit to the processing module.

[0022] The indicator unit is used to display an indicator light of the corresponding color based on the gas safety factor level of the detection point; it is also used to display the working status of the detection point and whether it is normal.

[0023] Furthermore, in the indicator unit, a green light illuminates when the gas safety status level is A, a yellow light illuminates when it is B, an orange light illuminates when it is C, and a red light illuminates when it is D.

[0024] Furthermore, the manual inspection auxiliary module is also used to receive reminder signals transmitted from the processing module to the signal transmission unit, reminding the inspection personnel to operate in accordance with regulations.

[0025] Furthermore, the processing module is also used to determine, based on the fault diagnosis strategy, whether the fault is caused by the manual inspection auxiliary module or the detection point module.

[0026] Furthermore, the fault judgment strategy includes: when the absolute value of the difference between the manual monitoring data and the intelligent inspection data of a detection point is greater than the allowable deviation value, the safety coefficients of the two detection data are compared with the preset fault safety coefficients to obtain two absolute differences, a first difference and a second difference. When the first difference is less than the second difference, the detection point module malfunctions and generates a first fault signal. When the first difference is greater than the second difference, the manual inspection auxiliary module malfunctions and generates a second fault signal.

[0027] Furthermore, the manual inspection auxiliary module is also used to receive the first fault signal and the second fault signal, and based on the two signals, to prompt the inspection personnel with two different patterns.

[0028] Furthermore, the processing module is also used to identify missing values ​​in gas monitoring data based on the isnull function, and to process the missing values ​​through interpolation.

[0029] Furthermore, the signal transmission unit is also used for real-time communication between the data information of the manual inspection auxiliary module and the data information of the processing module.

[0030] The above approach has the following beneficial effects:

[0031] 1. This solution utilizes intelligent sensor technology through a detection point module to conduct real-time monitoring of multiple locations underground in coal mines. Simultaneously, an intelligent inspection unit employs intelligent mechanical inspection technology and absorption spectroscopy detection technology to monitor the real-time gas safety status of underground coal mines. By operating these two methods in parallel, intelligent monitoring of coal mine gas safety status is achieved under normal circumstances, thereby improving inspection efficiency. Furthermore, a manual inspection auxiliary module assists the intelligent inspection (detection point module), conducting regular and fixed-point checks on the operational status of the intelligent detection equipment to ensure the entire intelligent detection system can operate normally for extended periods. By monitoring the inspection points on-site by inspectors, more comprehensive and accurate data can be obtained, providing reliable support for subsequent optimization of intelligent inspection data processing at these points. Furthermore, the system can determine the validity of manual monitoring data based on the inspectors' images, further improving data reliability and system intelligence. The system also features self-diagnostic capabilities, capable of determining whether the manual inspection auxiliary module or the inspection point module has malfunctioned and generating corresponding fault signals. This helps in timely detection and resolution of problems, ensuring stable system operation. Additionally, different graphic displays can prompt inspection personnel, making fault handling more convenient and efficient.

[0032] 2. This solution uses a signal transmission unit as a data relay station to enable real-time information exchange between the manual inspection auxiliary module, the detection point module, and the processing module. This allows the entire system to respond quickly to various changes, adjust monitoring strategies and countermeasures in a timely manner, and improve the system's flexibility and response speed.

[0033] 3. This solution collects images of the detection point area, determines the completeness of the inspector's image within the image, and immediately generates an alert signal when the completeness falls below a preset threshold. This timely warning mechanism can quickly attract the attention of relevant personnel, prompting them to take timely measures to rectify or strengthen monitoring, thereby effectively reducing potential safety hazards. Through the processing module's verification and alert functions for manually monitored data, it can encourage inspectors to perform their inspection tasks more systematically, reducing false alarms or omissions caused by human factors. Furthermore, it can provide inspectors with real-time safety assessment results and early warning information, helping them better understand the underground gas safety situation in coal mines, optimize inspection processes, improve work efficiency, reduce the workload of inspectors, and improve monitoring efficiency.

[0034] 4. This solution uses the isnull function to identify missing values ​​in gas monitoring data and processes them using interpolation, which ensures the integrity and continuity of the data and avoids deviations in evaluation results due to missing data.

[0035] 5. This solution, by integrating sensor modules, manual inspection assistance modules, and detection point modules, can comprehensively and in real-time monitor gas concentration and other relevant safety parameters in coal mines. This multi-level monitoring method significantly improves the accuracy and timeliness of gas safety monitoring, effectively preventing safety accidents such as gas combustion and explosion. Simultaneously, by employing a gas safety status level judgment strategy, and through methods such as quantitative preprocessing, hierarchical analysis, and fuzzy comprehensive evaluation, the collected situational characteristic data is intelligently analyzed to assess the gas safety status level. This not only improves the accuracy of the assessment but also reduces the interference of human factors, making the assessment results more objective and reliable.

[0036] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0037] Figure 1 This is a flowchart illustrating an embodiment of the intelligent inspection and linkage analysis system for coal mine gas safety of the present invention. Detailed Implementation

[0038] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0040] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0041] The following detailed description illustrates the specific implementation method:

[0042] Example 1:

[0043] As attached Figure 1 As shown: A coal mine gas safety intelligent inspection and linkage analysis system includes a sensor module, a manual inspection assistance module, a detection point module, and a processing module;

[0044] The sensor module is used to collect some of the situational characteristic indicators required for assessing the gas safety factor.

[0045] The manual inspection auxiliary module is used to obtain manual monitoring data for each monitoring point by inspectors within the monitoring area of ​​the detection point. Based on the detection point number, the module labels the manual monitoring data accordingly and transmits the concentration and label information to the monitoring point module. It also receives reminder signals from the processing module to the signal transmission unit, reminding inspectors to operate according to regulations. Furthermore, it monitors the operational status of the intelligent inspection settings within the detection point.

[0046] The detection point module is used to monitor the gas concentration information at the detection point based on intelligent sensor technology and to collect image information within the detection point area.

[0047] The detection point module includes an intelligent inspection unit, which is used to conduct further all-round unmanned monitoring of underground coal mines through intelligent detection technology. The intelligent detection technology includes at least intelligent mechanical inspection technology and absorption spectroscopy detection technology.

[0048] The detection point module also includes a gas detection unit, an image acquisition unit, a signal transmission unit, and a prompting unit.

[0049] The gas detection unit is used to monitor the gas concentration at the detection point through a gas concentration sensor installed at the detection point, obtain non-manual monitoring data, label the data according to the detection point number, and transmit the concentration and label information to the signal transmission unit.

[0050] The image acquisition unit is used to acquire images within the detection point and label the images accordingly based on the detection point number.

[0051] The signal transmission unit is used to upload the image data generated by the image acquisition unit to the processing module; it is also used to transmit the image and its label information generated by the image acquisition unit to the processing module.

[0052] The indicator unit is used to display indicator lights of corresponding colors based on the gas safety factor level of the detection point; it is also used to display the working status of the detection point, whether it is normal; when the gas safety status level is A, the light is green, when it is B, the light is yellow, when it is C, the light is orange, and when it is D, the light is red.

[0053] By setting up several detection points underground and installing high-precision sensors at these points to monitor key parameters such as gas concentration and temperature in real time (including wind speed, gas pressure, coal seam permeability coefficient, and gas emission), real-time, fixed-point, unmanned detection can be achieved underground in coal mines, and this data can be fed back to the central control and monitoring platform on the ground. Although several detection points are set up for fixed-point monitoring, certain areas between each detection point are still difficult to detect accurately. Therefore, in addition to multi-point detection at the detection points, a robotic inspection method can be adopted. The inspection robot is equipped with a high-definition camera, an infrared thermal imager, and a multispectral imager. The high-definition camera is used to collect video and image information, while the infrared thermal imager can monitor the temperature of equipment, facilities, cables, and pipelines in real time. The multispectral imager, based on absorption spectroscopy detection technology, acquires information on the reflected or emitted light of objects in multiple spectral bands, providing richer and more detailed data than traditional imaging. It uses light of a specific wavelength to illuminate the object and captures the reflected or emitted light, thereby recording data from multiple spectral bands from visible light to near-infrared and even further wavelengths. Methane (usually a combustible gas such as methane) has a specific infrared absorption spectrum. These spectra are determined by the absorption characteristics of gas molecules at specific wavelengths. When light passes through a medium containing methane, the gas absorbs light of a specific wavelength that matches its absorption spectrum. This combination allows the inspection robot to comprehensively and meticulously observe the mine's internal environment, providing more accurate and comprehensive detection data to the central control platform on the ground. Simultaneously, an automatic inspection cycle can be set for the inspection robot based on different actual conditions, such as once a week or every two days, thereby ensuring the real-time nature and reliability of the monitoring data from the detection center while minimizing operating costs.

[0054] The processing module is used to classify the gas safety factor level of the detection point into A, B, C and D from high to low based on the gas safety status level judgment strategy; it is also used to determine whether the manual monitoring data of the detection point is usable based on whether there is an image of the inspector in the image of the detection point. When the image of the inspector exists, the manual monitoring data is usable and can be further analyzed and compared. When the image of the inspector does not exist or the completeness is less than a preset threshold, the manual monitoring data will not be further analyzed and compared, and an alarm signal will be generated and transmitted to the detection point module of the detection point.

[0055] For example, if the intelligent detection equipment at a certain detection point malfunctions and cannot collect and transmit real-time data from that point in a timely manner, the manual inspection auxiliary module is activated. This module collects coal mine safety status characteristic data from that detection point and simultaneously checks the intelligent inspection equipment at that point, such as image acquisition devices, recording and uploading fault information to the terminal for rapid processing. During regular manual inspections to ensure the normal operation of the intelligent inspection equipment, the manually collected auxiliary data is compared and analyzed with the intelligent inspection data measured at the corresponding detection point to determine the degree of similarity and thus assess whether the detection point module is operating normally.

[0056] The strategies for determining the gas safety status level include:

[0057] Step 1: Quantitatively preprocess the collected situational characteristic index data samples to obtain the corresponding safety level; the situational characteristics include gas concentration, wind speed, gas pressure, coal seam permeability coefficient, gas emission, dust content, gas extraction rate, coal seam gas content, electrical equipment integrity, ambient temperature, upper corner gas concentration, return airway gas concentration, and intake air gas concentration;

[0058] Step 2: The weights of each quantitative indicator are determined by the analytic hierarchy process (AHP). The data of the indicator layer are evaluated by a first-level fuzzy comprehensive method to obtain the first state evaluation value of each event in the criterion layer. Then, the weights of each event in the criterion layer are obtained by the AHP method and evaluated by a second-level fuzzy method to obtain the second situation evaluation value.

[0059] Step 3: Determine the factor set and evaluation set. The factor set is determined based on the established safety situation characteristic index system, where the primary index U0 = {gas combustion and explosion}, the secondary indices U1 and U2 = {gas accumulation and ignition source}, and the tertiary indices U1m = {gas concentration, wind speed, gas pressure, coal seam permeability coefficient, gas emission rate, dust content, coal seam gas content, corner gas concentration, return airway gas concentration, and intake air gas concentration}, and U2n = {electrical equipment integrity, ambient temperature, and gas extraction rate}, where m belongs to {1, 2, 3, 4, 5, 6, 7, 8, 9, 10} and n belongs to {1, 2, 3}. The evaluation set is divided into four assessment level domains V = {A, B, C, D} according to the severity of the situation from low to high, combined with different numerical ranges.

[0060] Step four: The safety assessment level V = {A, B, C, D} data obtained in step three is sent to the detection point module. The detection point module visualizes the gas safety status level and transmits the gas safety status level data to the manual inspection auxiliary module in real time.

[0061] Meanwhile, the signal transmission unit is also used for real-time communication between the data information of the manual inspection auxiliary module and the data information of the processing module, so as to quickly complete the information verification, improve work efficiency and ensure the timeliness of data.

[0062] The specific implementation process is as follows: Gas concentration sensors are installed at various key locations in the coal mine (such as roadways and working faces) to ensure real-time gas concentration data collection. Simultaneously, other necessary sensors (such as wind speed, temperature, and dust content) are configured to collect comprehensive situational characteristic indicators. A gas detection unit, image acquisition unit, signal transmission unit, and alert unit are installed at each detection point to ensure that each unit functions properly and communicates with other parts of the system. Inspection personnel are equipped with necessary monitoring equipment and communication tools to ensure they can accurately monitor gas concentration within the detection area and promptly receive and process alert signals issued by the system.

[0063] When inspection personnel arrive at a monitoring point, they use a manual inspection auxiliary module to detect the gas concentration in the area. Simultaneously, image analysis technology is used to check for the presence of the inspector's image in the picture, verifying the usability of the manual monitoring data. If the inspector's image is missing or its completeness is below a preset threshold, the manual monitoring data is ignored, and the inspector is alerted to whether the data is normal. If both manual and intelligent monitoring data are normal, the two types of data are preprocessed and then combined with the continuously collected data on gas concentration, wind speed, and dust content from the sensor module. Based on a gas safety factor judgment strategy, the corresponding gas safety status level (A, B, C, or D) is obtained. A green light illuminates for level A, a yellow light for level B, an orange light for level C, and a red light for level D, reminding the inspection personnel to operate according to regulations or take appropriate measures.

[0064] The system should be maintained and calibrated regularly to ensure the normal operation of each module and the accuracy of the data. The collected data should be analyzed regularly to generate safety status reports, providing a basis for safety management and decision-making in coal mines.

[0065] Example 2:

[0066] As attached Figure 1As shown, the difference from Embodiment 1 is that the processing module is further used to determine whether the manual inspection auxiliary module or the detection point module has failed, based on a fault judgment strategy. The fault judgment strategy includes: when the absolute value of the difference between the manual monitoring data and the intelligent inspection data of a detection point is greater than the allowable deviation value, the safety coefficients of the two detection data are compared with a preset fault safety coefficient to obtain two absolute differences, a first difference and a second difference. When the first difference is less than the second difference, the detection point module has failed and a first fault signal is generated; when the first difference is greater than the second difference, the manual inspection auxiliary module has failed and a second fault signal is generated.

[0067] The manual inspection auxiliary module is also used to receive the first fault signal and the second fault signal, and based on the two signals, to prompt the inspection personnel with two different patterns.

[0068] The specific implementation process is as follows: When the processing module compares the manual monitoring data and intelligent inspection data of the same detection point, calculates the difference and obtains the absolute value of the difference (|a|), the calculated |a| is compared with the preset allowable deviation value. If |a| is greater than the allowable deviation value, it indicates that there is a potential fault and further judgment is required; otherwise, the normal working process is carried out. When |a| is greater than the allowable deviation value, the safety factors (denoted as S_manual and S_intelligent) corresponding to the manual monitoring data and intelligent inspection data are calculated respectively. These two safety factors are compared with the preset fault safety factor (denoted as S_fault) to obtain two absolute differences: the first difference (|S_manual - S_fault|) and the second difference (|S_intelligent - S_fault|). If the first difference is less than the second difference (|S_manual - S_fault| < |S_intelligent - S_fault|), it is determined that the detection point module has failed, and a first fault signal is generated. If the first difference is greater than the second difference (|S_manual - S_fault| > |S_intelligent - S_fault|), it is determined that the manual inspection auxiliary module has failed, and a second fault signal is generated. After the processing module generates the fault signal (first fault signal or second fault signal), it will transmit it to the manual inspection auxiliary module, which will prompt the inspection personnel with two different patterns (such as different colors, shapes, or flashing patterns) according to the signal type. These patterns should be designed to be intuitive and easy to distinguish, so that inspection personnel can quickly identify them and take appropriate measures. Furthermore, the preset allowable deviation values ​​and fault safety factors are derived from big data analysis and formulated according to national standards, thereby ensuring that the preset allowable deviation values ​​and fault safety factors are reasonable and accurate, reducing the possibility of misjudgment or omission.

[0069] Example 3:

[0070] As attached Figure 1As shown, the difference from Embodiment 2 is that the processing module is also used to identify missing values ​​in the gas monitoring data based on the isnull function, and to process the missing values ​​by interpolation.

[0071] The specific implementation process is as follows: After identifying missing values ​​in the gas monitoring data using the isnull function, the missing values ​​are processed using interpolation methods, including nearest neighbor interpolation and mean interpolation. Here, Lagrange interpolation is preferred for handling missing values. Explanation: The basic principle of Lagrange interpolation is that for n known points on a plane, an (n-1)th degree polynomial can be found:

[0072] y = a0 + a1x + a2x 2 +...+a n-1 x n-1

[0073] Given the coordinates of n points (x1, y1), (x2, y2), ..., (x...), ..., (x...). n ,y n Substituting into the polynomial function, we get:

[0074]

[0075] The Lagrange interpolation polynomial is obtained as follows:

[0076]

[0077] The missing values ​​in the gas monitoring data sequence were processed using the Lagrange interpolation method, and the first 7 data points before the missing value were used for modeling.

[0078] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A coal mine gas safety intelligent inspection and linkage analysis system, characterized in that, It includes a sensor module, a manual inspection assistance module, a detection point module, and a processing module; The sensor module is used to collect some of the situational characteristic indicators required for gas safety status assessment; The manual inspection auxiliary module is used to obtain manual monitoring auxiliary data for a detection point by having an inspector monitor the gas concentration within the monitoring area of ​​the detection point. The module then labels the manual monitoring auxiliary data according to the detection point number and transmits the concentration and label information to the detection point module of the monitored detection point. It is also used to detect the working status of the intelligent inspection settings within the detection point. The detection point module is used to monitor the gas concentration information at the detection point based on intelligent sensor technology and to collect image information within the detection point area; The detection point module includes an intelligent inspection unit, which is used to conduct further all-round unmanned monitoring of underground coal mines through intelligent detection technology. The intelligent mechanical detection technology includes at least intelligent mechanical inspection technology and absorption spectroscopy detection technology. The processing module is used to classify the gas safety status level of the detection point into A, B, C and D from high to low based on the gas safety status level judgment strategy; it is also used to determine whether the manual monitoring data of the detection point is usable based on whether there is an image of the inspector in the image of the detection point. When the image of the inspector exists, the manual monitoring data is usable and can be further analyzed and compared. When the image of the inspector does not exist or the completeness is less than a preset threshold, the manual monitoring data will not be further analyzed and compared, and an alarm signal will be generated and transmitted to the detection point module of the detection point. The gas safety status level determination strategy includes: Step 1: Quantitatively preprocess the collected situational characteristic index data samples to obtain the corresponding safety level; the situational characteristics include gas concentration, wind speed, gas pressure, coal seam permeability coefficient, gas emission, dust content, gas extraction rate, coal seam gas content, electrical equipment integrity, ambient temperature, upper corner gas concentration, return airway gas concentration, and intake air gas concentration; Step 2: The weights of each quantitative indicator are determined by the analytic hierarchy process (AHP). The data of the indicator layer are evaluated by a first-level fuzzy comprehensive method to obtain the first state evaluation value of each event in the criterion layer. Then, the weights of each event in the criterion layer are obtained by the AHP method and evaluated by a second-level fuzzy method to obtain the second situation evaluation value. Step 3: Determine the factor set and evaluation set. The factor set is determined based on the established safety situation characteristic index system, where the primary index U0 = {gas combustion and explosion}, the secondary indices U1 and U2 = {gas accumulation and ignition source}, and the tertiary indices U1m = {gas concentration, wind speed, gas pressure, coal seam permeability coefficient, gas emission rate, dust content, coal seam gas content, corner gas concentration, return airway gas concentration, and intake air gas concentration}, and U2n = {electrical equipment integrity, ambient temperature, and gas extraction rate}, where m belongs to {1, 2, 3, 4, 5, 6, 7, 8, 9, 10} and n belongs to {1, 2, 3}. The evaluation set is divided into four assessment level domains V = {A, B, C, D} according to the severity of the situation from low to high, combined with different numerical ranges. Step four: The safety assessment level V = {A, B, C, D} data obtained in step three is sent to the detection point module. The detection point module visualizes the gas safety status level and transmits the gas safety status level data to the manual inspection auxiliary module in real time.

2. The intelligent inspection and linkage analysis system for coal mine gas safety according to claim 1, characterized in that, The detection point module also includes a gas detection unit, an image acquisition unit, a signal transmission unit, and a prompting unit; The gas detection unit is used to monitor the gas concentration at the detection point through a gas concentration sensor installed at the detection point, obtain non-manual monitoring data, label the data according to the detection point number, and transmit the concentration and label information to the signal transmission unit. The image acquisition unit is used to acquire images within the detection point and label the images accordingly based on the detection point number. The signal transmission unit is used to upload the image data generated by the image acquisition unit to the processing module; It is also used to transmit the images generated by the image acquisition unit and their labeling information to the processing module; The indicator unit is used to display an indicator light of the corresponding color based on the gas safety factor level of the detection point; it is also used to display the working status of the detection point and whether it is normal.

3. The intelligent inspection and linkage analysis system for coal mine gas safety according to claim 2, characterized in that, In the indicator unit, a green light illuminates when the gas safety status level is A, a yellow light illuminates when it is B, an orange light illuminates when it is C, and a red light illuminates when it is D.

4. The intelligent inspection and linkage analysis system for coal mine gas safety according to claim 1, characterized in that, The manual inspection auxiliary module is also used to receive reminder signals transmitted from the processing module to the signal transmission unit, reminding the inspection personnel to operate in accordance with regulations.

5. The intelligent inspection and linkage analysis system for coal mine gas safety according to claim 1, characterized in that, The processing module is also used to determine, based on the fault diagnosis strategy, whether the fault is caused by the manual inspection auxiliary module or the detection point module.

6. The intelligent inspection and linkage analysis system for coal mine gas safety according to claim 5, characterized in that, The fault judgment strategy includes: when the absolute value of the difference between the manual monitoring data and the intelligent inspection data of a detection point is greater than the allowable deviation value, the safety coefficients of the two detection data are compared with the preset fault safety coefficients to obtain two absolute differences, the first difference and the second difference. When the first difference is less than the second difference, the detection point module malfunctions and generates a first fault signal. When the first difference is greater than the second difference, the manual inspection auxiliary module malfunctions and generates a second fault signal.

7. The intelligent inspection and linkage analysis system for coal mine gas safety according to claim 1, characterized in that, The manual inspection auxiliary module is also used to receive the first fault signal and the second fault signal, and based on the two signals, to prompt the inspection personnel with two different patterns.

8. The intelligent inspection and linkage analysis system for coal mine gas safety according to claim 1, characterized in that, The processing module is also used to identify missing values ​​in gas monitoring data based on the isnull function and to process the missing values ​​using interpolation.

9. The intelligent inspection and linkage analysis system for coal mine gas safety according to claim 1, characterized in that, The signal transmission unit is also used for real-time communication between the data information of the manual inspection auxiliary module and the data information of the processing module.

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