Data analysis method and system for coal mine safety monitoring

Abstract

The invention provides a data analysis method and system for coal mine safety monitoring, and belongs to the field of data processing. The method comprises the following steps: acquiring original acquisition data of a gas detector in a target area to obtain an acquired gas concentration; establishing an equipment attenuation characteristic curve of the gas detector, and obtaining an equipment attenuation coefficient; acquiring real-time environment data of the target area, and determining an environment influence coefficient of the gas detector under the equipment attenuation coefficient; and correcting the collected gas concentration to obtain the actual gas concentration of the target area. According to the method and the device, the technical problem of inaccurate detection of the gas detector caused by non-ideal environment correction effect due to the fact that an environment correction method based on a standard state is adopted to carry out environment factor influence correction on the gas detector in the prior art is solved; the technical effects that self-adaptive environment influence correction is achieved based on the equipment attenuation state of the gas detector, the environment correction effect is improved, and then the detection accuracy of the gas detector is improved are achieved.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and particularly to a data analysis method and system for coal mine safety monitoring. Background Art

[0002] Coal mine gas monitoring is an important link in coal mine safety production. As the core monitoring device, the accuracy of the detection data of the gas detector is directly related to the safety of coal mine workers and the safe operation of the mine.

[0003] However, when the gas detector works in the harsh underground environment, changes in environmental factors such as temperature, humidity, air pressure, and dust concentration will interfere with the detection results of the gas detector. In order to improve the detection accuracy of the gas detector, the prior art usually adopts an environmental correction method to eliminate the influence of environmental factors on the detection results, that is, by establishing a relationship model between environmental parameters and detection errors, obtaining corresponding environmental correction parameters to correct the detection data.

[0004] However, as the service time of the gas detector extends, its sensor elements will gradually decay in detection performance due to aging, pollution, etc. Gas detectors with different decay degrees have significant differences in response to the same environmental conditions. In actual applications, the existing environmental correction methods often have unsatisfactory correction effects, resulting in inaccurate detection of gas detectors and affecting the reliability of coal mine safety monitoring. Summary of the Invention

[0005] Aiming at the technical problem that the prior art uses an environmental correction method based on standard conditions to correct the influence of environmental factors on the gas detector, resulting in an unsatisfactory environmental correction effect and thus inaccurate detection of the gas detector, the present invention provides a data analysis method and system for coal mine safety monitoring to solve this problem.

[0006] The technical solutions of the present invention to solve the above technical problems are as follows: In a first aspect, the present invention provides a data analysis method for coal mine safety monitoring, including: obtaining the original acquisition data of a gas detector in a target area to obtain the collected gas concentration; collecting multiple groups of decay detection data of the gas detector, establishing an equipment decay characteristic curve of the gas detector based on the multiple groups of decay detection data, and obtaining an equipment decay coefficient of the gas detector according to the equipment decay characteristic curve; obtaining the real-time environmental data of the target area, and determining an environmental influence coefficient of the gas detector under the equipment decay coefficient based on the real-time environmental data; and correcting the collected gas concentration according to the environmental influence coefficient to obtain the actual gas concentration of the target area.

[0007] In a second aspect, the present invention provides a data analysis system for coal mine safety monitoring, including: a data acquisition module for acquiring the original acquisition data of a gas detector in a target area to obtain the acquired gas concentration; an attenuation influence analysis module for acquiring multiple groups of attenuation detection data of the gas detector, establishing an equipment attenuation characteristic curve of the gas detector based on the multiple groups of attenuation detection data, and obtaining an equipment attenuation coefficient of the gas detector according to the equipment attenuation characteristic curve; an environmental influence analysis module for acquiring real-time environmental data of the target area and determining an environmental influence coefficient of the gas detector under the equipment attenuation coefficient based on the real-time environmental data; and a data correction module for correcting the acquired gas concentration according to the environmental influence coefficient to obtain the actual gas concentration in the target area.

[0008] The beneficial effects of the present invention are as follows: Acquire the original acquisition data of the gas detector in the target area to obtain the acquired gas concentration, which serves as the basic data for subsequent correction processing; acquire multiple groups of attenuation detection data of the gas detector, establish an equipment attenuation characteristic curve of the gas detector based on the multiple groups of attenuation detection data, and obtain an equipment attenuation coefficient of the gas detector according to the equipment attenuation characteristic curve, providing equipment state parameters for environmental influence analysis; acquire real-time environmental data of the target area and determine an environmental influence coefficient of the gas detector under the equipment attenuation coefficient based on the real-time environmental data, realizing an adaptive environmental influence assessment based on the equipment attenuation state; correct the acquired gas concentration according to the environmental influence coefficient to obtain the actual gas concentration in the target area, realizing accurate correction of the original detection data, thereby obtaining true and accurate gas concentration data.

[0009] Through the above technical solution, an adaptive environmental influence correction is realized based on the equipment attenuation state of the gas detector, which can dynamically adjust the environmental influence coefficient according to the current attenuation degree of the equipment, effectively improve the environmental correction effect, and further enhance the accuracy and reliability of gas concentration detection, solve the problem of unsatisfactory environmental correction effect in the prior art, and thus provide accurate data support for coal mine safety production. Description of the Drawings

[0010] Figure 1 It is a schematic flow chart of the data analysis method for coal mine safety monitoring provided by the present invention; Figure 2 It is a schematic structural diagram of the data analysis system for coal mine safety monitoring provided by the present invention.

[0011] In the drawings, the components represented by the respective reference numerals are as follows: Data acquisition module 11, attenuation influence analysis module 12, environmental influence analysis module 13, data correction module 14. Detailed Embodiments

[0012] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0013] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality of" means two or more, unless otherwise specifically defined.

[0014] In the description of the present invention, the term "for example" is used to mean "serving as an example, illustration, or explanation". Any embodiment described as "for example" in the present invention is not necessarily construed as being more preferred or having more advantages than other embodiments. In order for any person skilled in the art to implement and use the present invention, the following description is given. In the following description, details are set forth for purposes of explanation. It should be understood that those of ordinary skill in the art can recognize that the present invention can be implemented without the use of these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid unnecessary details from obscuring the description of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope that conforms to the principles and features disclosed in the present invention.

[0015] Embodiment 1, as Figure 1 shown, the embodiment of the present invention provides a data analysis method for coal mine safety monitoring. During the coal mining process, the accumulation of gas is one of the main safety hazards leading to coal mine accidents. Accurate monitoring of the gas concentration is crucial for preventing gas explosions and ensuring the safety of miners. In terms of gas monitoring in coal mine safety monitoring, it relies on gas detectors distributed in various underground areas for real-time monitoring, and judges whether the gas concentration exceeds the safety threshold through the monitoring data, and issues a warning signal in a timely manner. However, due to the complex and changeable environment in the coal mine, changes in environmental factors such as temperature, humidity, air pressure, and dust concentration will have a significant impact on the detection results of gas detectors. In order to improve the detection accuracy of gas detectors, the prior art usually adopts an environmental correction method to eliminate the influence of environmental factors on the detection results, that is, by establishing a relationship model between environmental parameters and detection errors, obtaining corresponding environmental correction parameters to correct the detection data.

[0016] However, when establishing the relationship model between environmental parameters and detection errors, existing environmental correction methods usually rely on the characteristic parameters of gas detectors under standard conditions and do not fully consider the impact of the self-decay state of gas detectors on environmental sensitivity. In fact, as the usage time of gas detectors increases, the detection performance of their sensor elements gradually decays due to reasons such as aging and pollution. Gas detectors with different decay degrees show significant differences in their responses to the same environmental conditions. The environmental correction model established based on standard conditions cannot accurately reflect the changes in the environmental sensitivity of gas detectors in different decay states, resulting in unsatisfactory environmental correction effects and inaccurate detection by gas detectors.

[0017] In this embodiment, by intelligently processing and correcting the original data collected by the gas detector and realizing adaptive environmental impact correction based on the equipment decay state of the gas detector, the environmental correction effect can be effectively improved, thereby enhancing the accuracy and reliability of gas concentration detection, solving the problem of unsatisfactory environmental correction effect in the prior art, and providing more accurate data support for coal mine safety production.

[0018] The data analysis method of this embodiment includes: S1. Obtain the original collected data of the gas detector in the target area to obtain the collected gas concentration.

[0019] Specifically, first, establish a data connection with the gas detector deployed in the target area through the communication interface to obtain the original detection data output by the gas detector in real time. The target area can be a specific roadway, working face, mining and excavation face in the coal mine or other areas where gas concentration monitoring is required.

[0020] The gas detector can adopt detection principles such as catalytic combustion type, infrared absorption type or electrochemistry type. It detects the target area through the built-in sensor, converts the detected gas concentration signal into a corresponding electrical signal, and after amplification, filtering and analog-to-digital conversion processing by the signal conditioning circuit, outputs the digital gas concentration data as the original collected data of the gas detector, denoted as the collected gas concentration, providing basic data for subsequent data processing and correction.

[0021] S2. Collect multiple groups of decay detection data of the gas detector, establish the equipment decay characteristic curve of the gas detector based on the multiple groups of decay detection data, and obtain the equipment decay coefficient of the gas detector according to the equipment decay characteristic curve.

[0022] Specifically, first, collect multiple sets of attenuation detection data of the gas detector. Specifically, conduct regular gas concentration detection experiments on the gas detector. At different usage duration nodes, use a standard gas with a known concentration to detect the gas detector, and record the detected concentration value of the gas detector and the actual concentration value of the standard gas, obtaining multiple sets of attenuation detection data. Each set of attenuation detection data includes usage duration information, the detected concentration value of the gas detector, and the corresponding actual concentration value, thus forming a data sample set reflecting the performance change of the detector.

[0023] Secondly, establish the equipment attenuation characteristic curve of the gas detector based on multiple sets of attenuation detection data. Specifically, extract the historical attenuation characteristic records of the same model gas detector from the historical database according to multiple sets of attenuation detection data, and construct an attenuation characteristic data set containing the data of multiple complete usage cycles of the equipment. With the usage duration as the horizontal axis and the equipment attenuation coefficient as the vertical axis, use data fitting to establish the equipment attenuation characteristic curve, which can accurately describe the attenuation change law of the detection accuracy of the gas detector with the extension of usage time.

[0024] After that, obtain the actual usage duration of the current gas detector, and substitute this usage duration as an input parameter into the established equipment attenuation characteristic curve, then the equipment attenuation coefficient corresponding to the current usage state can be calculated. This equipment attenuation coefficient accurately reflects the attenuation degree of the current detection ability of the gas detector relative to the initial state, providing important equipment characteristic parameters for subsequent data correction.

[0025] S3. Obtain the real-time environmental data of the target area, and determine the environmental influence coefficient of the gas detector under the equipment attenuation coefficient based on the real-time environmental data.

[0026] Specifically, first, obtain the real-time environmental data of the target area. Through the environmental monitoring sensors deployed in the target area, collect multi-dimensional environmental parameters including temperature, humidity, air pressure, dust concentration, wind speed, gas components, etc. in real time. The real-time environmental data reflects the actual situation of the current working environment of the gas detector, and these environmental factors will have different degrees of influence on the sensor response characteristics, signal stability, and detection accuracy of the gas detector. The collection frequency of the environmental data is synchronized with the gas concentration detection frequency to ensure the timeliness and accuracy of environmental correction.

[0027] The degree of influence of environmental factors on the gas detector is not constant, but is closely related to the attenuation state of the gas detector. As the usage time of the gas detector prolongs and its performance attenuates, the sensitivity of the gas detector to environmental interference will change significantly. For example, after long-term use of the sensor element in the gas detector, its anti-interference ability to temperature fluctuations and humidity changes will decline, and the same environmental conditions will have different intensities of influence on gas detectors with different degrees of equipment attenuation. Therefore, based on real-time environmental data, determine the environmental influence coefficient of the gas detector under the equipment attenuation coefficient. Specifically, vectorize the real-time environmental data to convert multi-dimensional environmental parameters into a standardized real-time environmental vector. Then, retrieve the environmental impact analyzer corresponding to the gas detector model. This environmental impact analyzer is an intelligent analysis model trained based on a large amount of historical data. The environmental impact analyzer receives the real-time environmental vector and the current equipment attenuation coefficient as input parameters, and conducts comprehensive analysis through internal machine learning algorithms to output the environmental influence coefficient under the current environmental conditions and equipment attenuation state.

[0028] The obtained environmental influence coefficient accurately quantifies the comprehensive influence degree of complex environmental factors on the gas detector under the current equipment attenuation, thereby outputting a more accurate environmental influence coefficient. This coefficient takes into account the current attenuation state of the equipment, making the environmental correction more precise, and providing targeted environmental compensation parameters for subsequent gas concentration correction.

[0029] S4. Correct the collected gas concentration according to the environmental influence coefficient to obtain the actual gas concentration in the target area.

[0030] Specifically, after determining the environmental influence coefficient, correct the collected gas concentration directly output by the gas detector according to the environmental influence coefficient to obtain the actual gas concentration in the target area.

[0031] The correction process is: actual gas concentration = collected gas concentration / environmental influence coefficient. Since the environmental influence coefficient reflects the degree of detection deviation caused by environmental factors under the equipment attenuation coefficient, this deviation influence can be eliminated through division operations. For example, when the collected gas concentration is 0.72% and the environmental influence coefficient is 0.92, the actual gas concentration is approximately 0.78% obtained by calculating 0.72% / 0.92, compensating for the influence caused by environmental factors; when the collected gas concentration is 1.31% and the environmental influence coefficient is 1.08, the actual gas concentration is approximately 1.21% obtained by calculating 1.31% / 1.08, eliminating the influence caused by environmental factors; when the collected gas concentration is 0.45% and the environmental influence coefficient is 0.90, the actual gas concentration is 0.50% obtained by calculating 0.45% / 0.90, accurately correcting the detection deviation caused by environmental interference.

[0032] Through the above calibration process, the actual gas concentration corrected for environmental impact is output. This value truly reflects the actual concentration level of the gas in the target area, effectively eliminates the combined effects of equipment aging and environmental interference, improves the accuracy and reliability of gas concentration detection, and provides reliable data support for coal mine safety monitoring.

[0033] Further, collect multiple groups of attenuation detection data of the gas detector, and establish an equipment attenuation characteristic curve of the gas detector based on the multiple groups of attenuation detection data, including: S21. According to a preset detection period, conduct gas concentration detection experiments on the gas detector at multiple usage duration nodes to obtain multiple groups of attenuation detection data. Each group of attenuation detection data includes a usage duration node, a detected concentration value, and an actual concentration value; S22. Obtain the equipment attenuation coefficient corresponding to each usage duration node according to the detected concentration value and the actual concentration value at each usage duration node; S23. Using each usage duration node and the corresponding equipment attenuation coefficient as retrieval conditions, extract the attenuation characteristic records of multiple gas detectors of the same model, and obtain an attenuation characteristic data set. The attenuation characteristic data set includes the corresponding relationship between the historical usage duration and the historical equipment attenuation coefficient of multiple gas detectors of the same model during the complete usage cycle; S24. Using the usage duration as the horizontal axis and the equipment attenuation coefficient as the vertical axis, establish the equipment attenuation characteristic curve of the gas detector based on the attenuation characteristic data set.

[0034] In a feasible implementation manner, first, according to a preset detection period, conduct gas concentration detection experiments on the gas detector at multiple usage duration nodes to obtain multiple groups of attenuation detection data. Among them, the preset detection period is determined according to the expected service life of the gas detector. For example, the detection is carried out once a week, once a month, or once a quarter. The multiple usage duration nodes refer to the detection time points of the gas detector under different cumulative working times. The gas concentration detection experiment is realized by introducing a standard gas with a known concentration into the gas detector. In each gas concentration detection experiment, record a group of attenuation detection data, including a usage duration node, a detected concentration value, and an actual concentration value. Among them, the usage duration node records the cumulative working time of the gas detector, the detected concentration value is the detection output of the gas detector for the standard gas, and the actual concentration value is the true concentration of the standard gas.

[0035] Then, based on the detected concentration values and the actual concentration values at each usage duration node, the device attenuation coefficients corresponding to each usage duration node are obtained. For example, according to the detected concentration values and the actual concentration values at each usage duration node, the detection accuracy at each usage duration node is obtained, and then the detection accuracies are compared with the reference detection accuracy in the initial state of the gas detector, so as to obtain the device attenuation coefficients corresponding to each usage duration node. The device attenuation coefficient reflects the degree of performance attenuation of the gas detector at the corresponding usage duration.

[0036] Subsequently, each obtained usage duration node and the corresponding device attenuation coefficient are used as retrieval conditions. These retrieval conditions are used to screen and match similar attenuation characteristic records in the historical database. For example, the device attenuation coefficients of the current gas detector at 3 months, 6 months, and 12 months of use are 0.98, 0.95, and 0.90 respectively. In the historical database, device records of other gas detectors of the same model with the same or similar attenuation coefficients at these corresponding usage duration nodes are retrieved. The retrieval process requires that the attenuation characteristics of multiple usage duration nodes can be matched, that is, the found gas detectors of the same model show similar attenuation laws at multiple duration nodes. Through this multi-node matching mechanism, a group of devices with similar attenuation characteristics can be screened out to ensure the consistency and reliability of subsequent data analysis. Then, for the gas detectors of the same model that successfully match the conditions of multiple usage duration nodes, all the attenuation data of these gas detectors of the same model within the complete usage cycle are extracted, including the corresponding relationship between the historical usage duration and the historical device attenuation coefficient from the initial use of the device to the scrapping and replacement throughout the entire life cycle, providing sufficient data sample support for establishing an accurate device attenuation characteristic curve in the future.

[0037] After that, with the usage duration as the horizontal axis and the device attenuation coefficient as the vertical axis, the device attenuation characteristic curve of the gas detector is established based on the attenuation characteristic data set. Specifically, all the data points in the obtained attenuation characteristic data set are plotted in a two-dimensional coordinate system. The horizontal axis represents the usage duration, and the unit can be time units such as weeks, months, or working hours; the vertical axis represents the device attenuation coefficient, and the numerical range is usually between 0 and 1. The closer the value is to 1, the closer the device performance is to the initial state, and the smaller the value, the more severe the attenuation. After the data plotting is completed, mathematical fitting is used to perform curve fitting on these discrete data points. The available fitting methods include the least squares method, polynomial fitting, exponential fitting, or spline interpolation, etc. The fitting process finds the optimal mathematical function to describe the variation law between the data points, so that the fitting curve can approximate the distribution trend of the actual data points to the greatest extent. By the fitting process, the device attenuation characteristic curve of the gas detector is established, which can continuously describe the variation law of the device attenuation coefficient with the usage duration during the process from the initial use to the end of the entire life cycle of the gas detector. Using this device attenuation characteristic curve, the corresponding device attenuation coefficient can be accurately predicted according to any usage duration of the gas detector, providing a reliable mathematical model support for subsequent data correction.

[0038] Further, according to the detected concentration values and the actual concentration values at each usage duration node, the device attenuation coefficients corresponding to each usage duration node are obtained, including: S221. Extract the first usage duration node from the multiple usage duration nodes, and obtain the detected concentration value and the actual concentration value corresponding to the first usage duration node as the first detected concentration value and the first actual concentration value; S222. According to the first detected concentration value and the first actual concentration value, obtain the device attenuation coefficient corresponding to the first usage duration node; S223. In the same way as obtaining the device attenuation coefficient corresponding to the first usage duration node, obtain the device attenuation coefficients of other usage duration nodes, and obtain the device attenuation coefficients corresponding to each usage duration node.

[0039] In a preferred embodiment, a traversal process is performed on multiple usage duration nodes. Each time, one usage duration node is extracted from the multiple usage duration nodes as the first usage duration node, and the first usage duration node can be any one of the multiple usage duration nodes. After selecting the first usage duration node, extract the detected concentration value (i.e., the actual detection output of the gas detector for the standard gas at this duration) and the actual concentration value (i.e., the known true concentration of the standard gas) from the attenuation detection data corresponding to the first usage duration node, and mark these two values as the first detected concentration value and the first actual concentration value respectively.

[0040] Then, the detection performance of the gas detector at this usage duration is evaluated by analyzing the relationship between the first detected concentration value and the first actual concentration value. Specifically, first, calculate the current detection accuracy of the gas detector at the first usage duration node. This detection accuracy can be quantitatively represented by the ratio of the detected concentration value to the actual concentration value (detection accuracy) or the absolute error between the two (detection deviation). Second, retrieve the reference detection accuracy of the gas detector. This reference detection accuracy refers to the detection performance index of the gas detector when it is in a brand-new state and initially put into use. Then, through comparative analysis of the current detection accuracy and the reference detection accuracy, calculate the deviation degree between the two, thereby obtaining the device attenuation coefficient corresponding to the first usage duration node, which reflects the attenuation degree of the gas detector's performance relative to the initial state. It is usually represented by a value between 0 and 1. The closer the value is to 1, the smaller the attenuation; the smaller the value, the more severe the performance attenuation.

[0041] Subsequently, continue to perform the traversal operation and process all the remaining usage duration nodes in sequence. For each subsequent usage duration node, process it according to the calculation method and algorithm flow established in step S222. That is: extract the detected concentration value and the actual concentration value corresponding to this usage duration node, calculate the current detection accuracy at this usage duration node, compare it with the reference detection accuracy, and finally obtain the device attenuation coefficient corresponding to this usage duration node. This process realizes the standardization and consistency of the calculation method, ensuring that the device attenuation coefficients of all usage duration nodes adopt the same calculation standard and evaluation criteria. By traversing all usage duration nodes, generate the device attenuation coefficients corresponding to each usage duration node, recording the performance attenuation trajectory of the gas detector from the initial use to the current state, providing a data support basis for establishing the device attenuation characteristic curve in the future.

[0042] Further, obtaining the device attenuation coefficient corresponding to the first usage duration node according to the first detected concentration value and the first actual concentration value includes: S2221. Obtain the current detection accuracy of the gas detector at the first usage duration node according to the first detected concentration value and the first actual concentration value; S2222. Obtain the reference detection accuracy of the gas detector, and the reference detection accuracy is the detection accuracy of the gas detector in the initial use state; S2223. Obtain the device attenuation coefficient corresponding to the first usage duration node according to the current detection accuracy and the reference detection accuracy.

[0043] In a preferred embodiment, first, based on the first detected concentration value and the first actual concentration value, the current detection accuracy of the gas detector at the first usage duration node is obtained. Specifically, the current detection accuracy is an index for evaluating the detection performance of the gas detector at a specific usage duration. For example, the current detection accuracy is calculated by performing a mathematical operation on the first detected concentration value and the first actual concentration value. The calculation method can adopt the accuracy ratio method, that is, the current detection accuracy = the first detected concentration value / the first actual concentration value, and this ratio reflects the closeness of the detection result of the gas detector to the true value. Or the error analysis method can be used, and the detection accuracy is quantified by calculating the relative error or absolute error between the first detected concentration value and the first actual concentration value. The value of the current detection accuracy directly reflects the actual detection ability level of the gas detector at the first usage duration node.

[0044] Then, the reference detection accuracy of the gas detector is obtained. The reference detection accuracy is the reference standard for the performance evaluation of the gas detector. This reference detection accuracy represents the best detection performance of the gas detector in a brand-new state. The reference detection accuracy can be obtained from the technical specification of the gas detector, or retrieved from the equipment file record, or determined by conducting a standard gas detection experiment on a brand-new detector of the same model. The reference detection accuracy serves as the baseline reference for the performance decay evaluation and provides a standardized comparison basis for the subsequent calculation of the decay degree.

[0045] Subsequently, based on the current detection accuracy and the reference detection accuracy, the equipment decay coefficient corresponding to the first usage duration node is obtained. Specifically, the equipment decay coefficient is calculated by comparing the current detection accuracy and the reference detection accuracy. The calculation formula is: equipment decay coefficient = current detection accuracy / reference detection accuracy. This ratio directly reflects the degree of maintenance of the performance of the gas detector relative to the initial state. When the equipment decay coefficient is close to 1, it indicates that the performance of the gas detector is well maintained and the decay degree is small; when the equipment decay coefficient is significantly less than 1, it indicates that the performance of the gas detector has a significant decay. Through the above calculation method, the performance decay degree of the gas detector at the first usage duration node can be accurately quantified, providing reliable data support for subsequent data correction and equipment maintenance decisions.

[0046] Furthermore, obtaining the equipment decay coefficient of the gas detector according to the equipment decay characteristic curve includes: S25. Obtain the current usage duration of the gas detector; S26. Substitute the current usage duration as an input parameter into the equipment decay characteristic curve to obtain the equipment decay coefficient corresponding to the current usage duration.

[0047] In a feasible implementation manner, the current usage duration refers to the cumulative working time of the gas detector from the initial commissioning to the current moment. By querying the equipment file record of the gas detector, the initial activation time of the equipment is obtained, and then the time difference from the initial activation time to the current moment is calculated to obtain the current usage duration. The current usage duration can be expressed in different time units, such as hours, days, months, or years, etc., and needs to be consistent with the horizontal axis time unit of the equipment attenuation characteristic curve. This current usage duration reflects the actual usage condition of the gas detector and is the input parameter for querying the corresponding equipment attenuation coefficient through the equipment attenuation characteristic curve subsequently.

[0048] Then, the obtained current usage duration is used as the abscissa input value and substituted into the established equipment attenuation characteristic curve for query calculation. The substitution process can be achieved by means of curve look-up tables, that is, finding the point on the equipment attenuation characteristic curve with the abscissa being the current usage duration and reading the corresponding ordinate value as the equipment attenuation coefficient. Or it can be achieved by means of function calculation, that is, substituting the current usage duration into the mathematical function expression of the equipment attenuation characteristic curve to calculate the corresponding equipment attenuation coefficient. Through the query method based on the equipment attenuation characteristic curve, the equipment attenuation coefficient of the gas detector in the current state can be obtained quickly and accurately, providing reliable equipment characteristic parameters for subsequent data correction.

[0049] Furthermore, obtaining the real-time environmental data of the target area and determining the environmental impact coefficient of the gas detector under the equipment attenuation coefficient based on the real-time environmental data includes: S31. Vectorize the real-time environmental data to obtain a real-time environmental vector; S32. Retrieve the environmental impact analyzer corresponding to the gas detector; S33. Analyze the real-time environmental vector and the equipment attenuation coefficient through the environmental impact analyzer to obtain the environmental impact coefficient.

[0050] In a preferred embodiment, first, the real-time environmental data is vectorized to obtain a real-time environmental vector. Vectorization is the process of converting multi-dimensional real-time environmental data into a standardized mathematical vector. Specifically, first, data preprocessing is performed on each environmental parameter in the real-time environmental data, including operations such as data cleaning, outlier detection, and missing value supplementation; then, the environmental parameters are standardized or normalized to unify parameters with different dimensions and value ranges into the same numerical interval. For example, parameters such as temperature, humidity, air pressure, and dust concentration are all mapped to the range of 0 to 1. Next, the standardized environmental parameters are organized into a vector form in a preset order to form a real-time environmental vector. This vector is usually represented in the mathematical form of [temperature value, humidity value, air pressure value, dust concentration value,...], and each component of the vector corresponds to a specific environmental parameter, and the dimension of the vector is equal to the number of types of monitored environmental parameters.

[0051] Then, the environmental impact analyzer corresponding to the gas detector is retrieved. This environmental impact analyzer is an intelligent analysis model pre-trained for a specific model of gas detector. According to the device model information of the current gas detector, the environmental impact analyzer corresponding to this model is retrieved. Due to differences in sensor principles, structural designs, material properties, etc. among different models of gas detectors, their sensitivities and response characteristics to environmental factors are also different. Therefore, an environmental impact analyzer specifically trained for this model needs to be used.

[0052] Subsequently, the environmental impact analyzer analyzes the real-time environmental vector and the device attenuation coefficient to obtain the environmental impact coefficient. Specifically, multiple environmental impact sub-analyzers are integrated inside the environmental impact analyzer, and each environmental impact sub-analyzer corresponds to a different device attenuation interval. The analysis process first determines the attenuation interval to which the input device attenuation coefficient belongs, and then selects the corresponding environmental impact sub-analyzer for processing. For example, when the device attenuation coefficient is 0.95, it is determined that this value belongs to the "mild attenuation interval" (such as 0.9 - 1.0), and then the environmental impact sub-analyzer corresponding to this interval is called; when the device attenuation coefficient is 0.75, the environmental impact sub-analyzer corresponding to the "moderate attenuation interval" (such as 0.7 - 0.9) is selected. After selecting the corresponding environmental impact sub-analyzer, the real-time environmental vector is input into this environmental impact sub-analyzer for processing. Since gas detectors in different attenuation states have different sensitivities to environmental factors, each environmental impact sub-analyzer is trained based on historical data in a specific attenuation interval and can accurately reflect the influence law of environmental factors in this attenuation state. The environmental impact sub-analyzer analyzes and calculates the real-time environmental vector through an internal machine learning algorithm and outputs the environmental impact coefficient for the current attenuation state and environmental conditions. Through the method of processing in intervals, the environmental impact analyzer can provide a more accurate environmental impact assessment, ensuring that the calculation of the environmental impact coefficient fully considers the current attenuation state characteristics of the device.

[0053] Furthermore, the construction steps of the environmental impact analyzer include: S321. Obtain the detector model of the gas detector; S322. Based on the detector model, conduct data retrieval to obtain detector acquisition records, where the detector acquisition records include gas concentration detection records, environmental data records, actual gas concentration records, and corresponding device attenuation coefficient records; S323. According to the numerical range of the device attenuation coefficient records, divide the device attenuation coefficient records into multiple attenuation intervals; S324. Classify the detector acquisition records according to the multiple attenuation intervals to obtain multiple device state classification data sets. Each device state classification data set includes gas concentration detection records, environmental data records, and actual gas concentration records, and has an attenuation interval identifier; S325. Based on the multiple device state classification data sets, construct multiple environmental impact sub-analyzers. Among them, the environmental impact sub-analyzer is trained based on a sample environmental vector set and a sample environmental impact coefficient set. The sample environmental vector set is constructed according to the environmental data records, and the sample environmental impact coefficient set is constructed according to the gas concentration detection records and the actual gas concentration records; S326. Integrate the multiple environmental impact sub - analyzers according to the attenuation interval identifiers corresponding to the multiple environmental impact sub - analyzers to obtain the environmental impact analyzer.

[0054] In a preferred implementation, first, extract the detector model from the device identification information of the gas detector. The detector model usually contains key identifiers such as manufacturer information, product series, technical specifications, etc., for example, "XX - GAS - 001" or "YY - CH4 - Pro", etc. The detector model is an important indexing condition for subsequent data retrieval and model construction because gas detectors of the same model have the same sensor principle, structural design, and performance characteristics, and their environmental response characteristics and attenuation laws are consistent.

[0055] Then, retrieve all historical acquisition data that matches the current detector model in the historical database to obtain the detector acquisition records. The detector acquisition records are a comprehensive data set that contains four types of key information: gas concentration detection records (the actual detection output values of the gas detector), environmental data records (environmental parameters such as temperature, humidity, and air pressure during detection), actual gas concentration records (the corresponding true gas concentration values), and device attenuation coefficient records (the attenuation state of the gas detector during the corresponding period). These records form a complete data sample, providing a data basis for subsequent machine - learning model training.

[0056] Next, conduct statistical analysis on the collected device attenuation coefficient records to determine the distribution range and change characteristics of the values, and divide the device attenuation coefficient records into multiple attenuation intervals. The method of dividing the attenuation intervals uses a method based on the inflection points of the attenuation characteristic curve. Determine the interval boundaries according to the key inflection point positions on the device attenuation characteristic curve, and use the points with significant slope changes on the curve as the interval demarcation points. For example, the multiple attenuation intervals divided include: mild attenuation interval (0.9 - 1.0), moderate attenuation interval (0.7 - 0.9), severe attenuation interval (0.5 - 0.7), etc. Each attenuation interval represents a different attenuation state stage of the gas detector.

[0057] Subsequently, according to the device attenuation coefficient value in each detector acquisition record, determine the attenuation interval it belongs to, and then classify the record into the corresponding device status classification data set. The classification process ensures that each device status classification data set only contains data records belonging to a specific attenuation interval. Each device status classification data set retains the complete information of the original record, including gas concentration detection records, environmental data records, and actual gas concentration records, and at the same time adds an attenuation interval identifier to each device status classification data set to indicate the device attenuation state range corresponding to this data set.

[0058] Next, a dedicated environmental impact sub - analyzer is constructed for each device - state classification data set. During the construction process, first, the environmental data records are vectorized to form a sample environmental vector set; then, by calculating the deviation relationship between the gas concentration detection records and the actual gas concentration records, a sample environmental impact coefficient set is obtained, which reflects the degree of influence of environmental factors on the detection results. Among them, the calculation of the sample environmental impact coefficient is based on the normalized deviation analysis method, that is, the environmental impact coefficient is equal to 1 plus the result of dividing the difference between the gas concentration detection record and the actual gas concentration record by the actual gas concentration record. For example, when the gas concentration detection record is 0.72% and the actual gas concentration record is 0.78%, by calculating 1+(0.72 - 0.78) / 0.78, the environmental impact coefficient is approximately 0.92, indicating that the current environmental conditions cause the detection value to be about 8% lower; when the gas concentration detection record is 1.31% and the actual gas concentration record is 1.21%, by calculating 1+(1.31 - 1.21) / 1.21, the environmental impact coefficient is approximately 1.08, indicating that the environmental factors make the detection value about 8% higher; when the gas concentration detection record is 0.45% and the actual gas concentration record is 0.50%, by calculating 1+(0.45 - 0.50) / 0.50, the environmental impact coefficient is 0.90, indicating that the environmental factors cause the detection value to be 10% lower. Next, machine learning algorithms (such as neural networks, support vector machines, or random forests, etc.) are used to train a model with the sample environmental vector set as the input and the sample environmental impact coefficient set as the output label, and an environmental impact sub - analyzer that can accurately predict the environmental impact degree under a specific attenuation state is obtained.

[0059] After that, each environmental impact sub - analyzer is organized and integrated according to its corresponding attenuation interval identifier to construct a unified environmental impact analyzer. The integration process establishes a mapping relationship between the attenuation intervals and the corresponding environmental impact sub - analyzers to form a hierarchical call mechanism. When the environmental impact analyzer receives the device attenuation coefficient input, it automatically determines the attenuation interval to which the device attenuation coefficient belongs, and then calls the corresponding environmental impact sub - analyzer for processing. Through this integration method, the environmental impact analyzer has the ability to provide differentiated environmental impact assessments for different device attenuation states, and realizes more accurate calculation of environmental impact coefficients.

[0060] Embodiment 2, as Figure 2 shown, based on the same inventive concept as the data analysis method for coal mine safety monitoring provided in Embodiment 1, the embodiment of the present invention also provides a data analysis system for coal mine safety monitoring, including: A data acquisition module 11, configured to acquire the original acquisition data of the gas detectors in the target area to obtain the acquired gas concentration; an attenuation impact analysis module 12, configured to collect multiple sets of attenuation detection data of the gas detector, establish a device attenuation characteristic curve of the gas detector based on the multiple sets of attenuation detection data, and obtain a device attenuation coefficient of the gas detector according to the device attenuation characteristic curve; An environmental impact analysis module 13 is configured to obtain real-time environmental data of the target area and determine an environmental impact coefficient of the gas detector under the device attenuation coefficient based on the real-time environmental data; The data correction module 14 is used to correct the collected gas concentration according to the environmental impact coefficient to obtain the actual gas concentration of the target area.

[0061] Furthermore, the attenuation impact analysis module 12 includes the following execution steps: According to a preset detection cycle, a gas concentration detection experiment is performed on the gas detector at multiple usage time nodes to obtain multiple sets of attenuation detection data, each set of attenuation detection data including a usage time node, a detection concentration value, and an actual concentration value; Obtaining a device attenuation coefficient corresponding to each usage time node according to the detected concentration value and the actual concentration value of each usage time node; Using each of the usage duration nodes and the corresponding device attenuation coefficient as search conditions, extract the attenuation characteristic records of multiple gas detectors of the same model to obtain an attenuation characteristic dataset, wherein the attenuation characteristic dataset includes the correspondence between the historical usage duration and the historical device attenuation coefficient of the multiple gas detectors of the same model within a complete usage cycle; With the usage time as the horizontal axis and the device attenuation coefficient as the vertical axis, an equipment attenuation characteristic curve of the gas detector is established based on the attenuation characteristic data set.

[0062] Furthermore, the attenuation impact analysis module 12 further includes the following execution steps: Extracting a first usage duration node from the plurality of usage duration nodes, and obtaining a detected concentration value and an actual concentration value corresponding to the first usage duration node as a first detected concentration value and a first actual concentration value; Obtaining a device attenuation coefficient corresponding to the first usage duration node according to the first detected concentration value and the first actual concentration value; In the same manner as that of obtaining the device attenuation coefficient corresponding to the first usage duration node, the device attenuation coefficients of other usage duration nodes are obtained, and the device attenuation coefficients corresponding to each usage duration node are obtained.

[0063] Furthermore, the attenuation impact analysis module 12 further includes the following execution steps: Obtaining, according to the first detected concentration value and the first actual concentration value, a current detection accuracy of the gas detector at the first usage duration node; Obtain the reference detection accuracy of the gas detector, where the reference detection accuracy is the detection accuracy of the gas detector in its initial use state; According to the current detection accuracy and the reference detection accuracy, obtain the device attenuation coefficient corresponding to the first usage duration node.

[0064] Furthermore, the attenuation impact analysis module 12 further includes the following execution steps: Obtain the current usage duration of the gas detector; Substitute the current usage duration as an input parameter into the device attenuation characteristic curve to obtain the device attenuation coefficient corresponding to the current usage duration.

[0065] Furthermore, the environmental impact analysis module 13 includes the following execution steps: Perform vectorization processing on the real-time environmental data to obtain a real-time environmental vector; Retrieve the environmental impact analyzer corresponding to the gas detector; Analyze the real-time environmental vector and the device attenuation coefficient through the environmental impact analyzer to obtain an environmental impact coefficient.

[0066] Furthermore, the environmental impact analysis module 13 further includes the following execution steps: Obtain the detector model of the gas detector; Based on the detector model, perform data retrieval to obtain detector acquisition records, where the detector acquisition records include gas concentration detection records, environmental data records, actual gas concentration records, and corresponding device attenuation coefficient records; According to the numerical range of the device attenuation coefficient records, divide the device attenuation coefficient records into multiple attenuation intervals; Classify the detector acquisition records according to the multiple attenuation intervals to obtain multiple device status classification data sets, where each device status classification data set includes gas concentration detection records, environmental data records, and actual gas concentration records, and has an attenuation interval identifier; Based on the multiple device status classification data sets, construct multiple environmental impact sub-analyzers, where the environmental impact sub-analyzers are trained based on a sample environmental vector set and a sample environmental impact coefficient set, the sample environmental vector set is constructed according to the environmental data records, and the sample environmental impact coefficient set is constructed according to the gas concentration detection records and the actual gas concentration records; Integrate the multiple environmental impact sub-analyzers according to the attenuation interval identifiers corresponding to the multiple environmental impact sub-analyzers to obtain the environmental impact analyzer.

[0067] It should be noted that in the above embodiments, each embodiment is described with a particular emphasis. For parts not described in detail in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0068] Those skilled in the art will understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0069] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0070] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0071] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0072] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concept.

[0073] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalent technologies, the present invention also intends to include these modifications and variations.

Claims

1. A data analysis method for coal mine safety monitoring, characterized in that The method includes: Obtaining the original acquisition data of the gas detector in the target area to obtain the collected gas concentration; Collecting multiple groups of attenuation detection data of the gas detector, establishing an equipment attenuation characteristic curve of the gas detector based on the multiple groups of attenuation detection data, and obtaining an equipment attenuation coefficient of the gas detector according to the equipment attenuation characteristic curve; Obtaining the real-time environmental data of the target area and determining an environmental impact coefficient of the gas detector under the equipment attenuation coefficient based on the real-time environmental data; Correcting the collected gas concentration according to the environmental impact coefficient to obtain the actual gas concentration in the target area.

2. The method according to claim 1, characterized in that Collecting multiple groups of attenuation detection data of the gas detector and establishing an equipment attenuation characteristic curve of the gas detector based on the multiple groups of attenuation detection data includes: Performing a gas concentration detection experiment on the gas detector at multiple usage duration nodes according to a preset detection period to obtain multiple groups of attenuation detection data, where each attenuation detection data includes a usage duration node, a detected concentration value, and an actual concentration value; Obtaining an equipment attenuation coefficient corresponding to each usage duration node according to the detected concentration value and the actual concentration value of each usage duration node; Taking each usage duration node and the corresponding equipment attenuation coefficient as retrieval conditions, extracting attenuation characteristic records of multiple gas detectors of the same model, and obtaining an attenuation characteristic data set, where the attenuation characteristic data set includes the corresponding relationship between the historical usage duration and the historical equipment attenuation coefficient of multiple gas detectors of the same model during a complete usage cycle; Taking the usage duration as the horizontal axis and the equipment attenuation coefficient as the vertical axis, establishing an equipment attenuation characteristic curve of the gas detector based on the attenuation characteristic data set.

3. The method according to claim 2, wherein Obtaining an equipment attenuation coefficient corresponding to each usage duration node according to the detected concentration value and the actual concentration value of each usage duration node includes: Extracting a first usage duration node from the multiple usage duration nodes, and obtaining the detected concentration value and the actual concentration value corresponding to the first usage duration node as a first detected concentration value and a first actual concentration value; Obtaining an equipment attenuation coefficient corresponding to the first usage duration node according to the first detected concentration value and the first actual concentration value; Obtaining the equipment attenuation coefficients of other usage duration nodes in the same way as obtaining the equipment attenuation coefficient corresponding to the first usage duration node to obtain the equipment attenuation coefficients corresponding to each usage duration node.

4. The method according to claim 3, characterized in that Obtaining an equipment attenuation coefficient corresponding to the first usage duration node according to the first detected concentration value and the first actual concentration value includes: Obtaining the current detection accuracy of the gas detector at the first usage duration node according to the first detected concentration value and the first actual concentration value; Obtaining a reference detection accuracy of the gas detector, where the reference detection accuracy is the detection accuracy of the gas detector in the initial usage state; Obtaining an equipment attenuation coefficient corresponding to the first usage duration node according to the current detection accuracy and the reference detection accuracy.

5. The method according to claim 1, characterized in that, Obtaining an equipment attenuation coefficient of the gas detector according to the equipment attenuation characteristic curve includes: Obtaining the current usage duration of the gas detector; Substitute the current usage duration as an input parameter into the device attenuation characteristic curve to obtain the device attenuation coefficient corresponding to the current usage duration.

6. The method according to claim 1, wherein Obtain the real-time environmental data of the target area, and determine the environmental impact coefficient of the gas detector under the device attenuation coefficient based on the real-time environmental data, including: Perform vectorization processing on the real-time environmental data to obtain a real-time environmental vector; Retrieve the environmental impact analyzer corresponding to the gas detector; Analyze the real-time environmental vector and the device attenuation coefficient through the environmental impact analyzer to obtain the environmental impact coefficient.

7. The method according to claim 6, characterized in that The construction steps of the environmental impact analyzer include: Obtain the detector model of the gas detector; Based on the detector model, perform data retrieval to obtain detector acquisition records, where the detector acquisition records include gas concentration detection records, environmental data records, actual gas concentration records, and corresponding device attenuation coefficient records; According to the numerical range of the device attenuation coefficient records, divide the device attenuation coefficient records into multiple attenuation intervals; Classify the detector acquisition records according to the multiple attenuation intervals to obtain multiple device status classification data sets. Each device status classification data set includes gas concentration detection records, environmental data records, and actual gas concentration records, and has an attenuation interval identifier; Based on multiple device status classification data sets, construct multiple environmental impact sub-analyzers. Among them, the environmental impact sub-analyzers are trained based on a sample environmental vector set and a sample environmental impact coefficient set. The sample environmental vector set is constructed according to the environmental data records, and the sample environmental impact coefficient set is constructed according to the gas concentration detection records and the actual gas concentration records; Integrate the multiple environmental impact sub-analyzers according to the attenuation interval identifiers corresponding to the multiple environmental impact sub-analyzers to obtain the environmental impact analyzer.

8. A data analysis system for coal mine safety monitoring, characterized in that, For implementing the method according to any one of claims 1 to 7, the system includes: A data acquisition module, configured to acquire the original acquisition data of the gas detector in the target area to obtain the acquired gas concentration; An attenuation impact analysis module, configured to collect multiple groups of attenuation detection data of the gas detector, establish the device attenuation characteristic curve of the gas detector based on the multiple groups of attenuation detection data, and obtain the device attenuation coefficient of the gas detector according to the device attenuation characteristic curve; An environmental impact analysis module, configured to obtain the real-time environmental data of the target area, and determine the environmental impact coefficient of the gas detector under the device attenuation coefficient based on the real-time environmental data; A data correction module, configured to correct the acquired gas concentration according to the environmental impact coefficient to obtain the actual gas concentration in the target area.

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