Intelligent analysis and detection system for coal mine environment

Abstract

The invention relates to the technical field of analysis and detection, in particular to an intelligent coal mine environment analysis and detection system. The system comprises a data analysis unit, a filtering effect evaluation unit and a data detection unit, and the data analysis unit obtains related coal mine environment data through a sensor to analyze the coal dust particle concentration, judges the standard exceeding condition according to the analyzed coal dust particle concentration and filters air according to the judged standard exceeding condition of the coal dust particle concentration. The filtering effect evaluation unit is used for analyzing the coal dust particle concentration again according to the filtered air data and evaluating the filtering effect, the reliability and accuracy of data can be verified in a cross mode by evaluating the air data before and after filtering, the accuracy of a detection result is ensured, and when the filtering effect is evaluated to be high, the filtering effect is evaluated. And then carbon monoxide index analysis is performed on the filtered air data, and the influence of interfering substances in the environment on carbon monoxide measurement can be reduced through the filtered air data, so that the accuracy of a measurement result is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of analytical detection, in particular to a coal mine environment intelligent analysis and detection system. BACKGROUND

[0002] The coal mine environment intelligent analysis and detection is a comprehensive integration of multiple sensing technologies, data processing and analysis algorithms, and communication technologies, which is used for real-time monitoring and analysis of various key parameters in the coal mine environment to ensure the safety of miners and improve the production efficiency of coal mines. This coal mine environment intelligent analysis and detection can significantly improve the safety management level of coal mines, reduce accidents, and improve production efficiency. At the same time, through data-driven intelligent analysis, it can realize the all-round monitoring and scientific management of the coal mine environment. Since workers work in the coal mine environment, there are a large number of coal dust particles in the air adsorbed on the surface of the sensor, which hinders the contact of carbon monoxide gas, reduces the sensitivity of the sensor to carbon monoxide gas, and thus causes the gas sensor to misjudge or the accuracy to decrease, which cannot reflect the true carbon monoxide gas concentration, resulting in a decrease in the accuracy of detecting carbon monoxide concentration. In order to avoid the decrease in the accuracy of carbon monoxide concentration caused by a large number of coal dust particles in the coal mine environment during the detection of carbon monoxide gas concentration, we provide a coal mine environment intelligent analysis and detection system. SUMMARY

[0003] The purpose of the present application is to provide a coal mine environment intelligent analysis and detection system to solve the problems raised in the background.

[0004] To achieve the above purpose, the present application provides a coal mine environment intelligent analysis and detection system, comprising a data analysis unit, a filtering effect evaluation unit, and a data detection unit. The data analysis unit uses sensors to obtain real-time related coal mine environment data for analysis of coal dust particle concentration, and then judges the over-standard situation according to the analyzed coal dust particle concentration, and filters the air according to the judged coal dust particle concentration over-standard situation. The filtering effect evaluation unit is used to receive the filtered air data in the data analysis unit, analyze the coal dust particle concentration again according to the filtered air data, and evaluate the filtering effect. The evaluated filtering effect is transmitted to the data analysis unit, and the data analysis unit receives the evaluated filtering effect data and analyzes the carbon monoxide index of the filtered air data. The data detection unit is used to receive the carbon monoxide index data analyzed by the filtering effect evaluation unit, and detect the carbon monoxide concentration according to the analyzed carbon monoxide index data.

[0005] As a further improvement of the present technical solution, the data analysis unit comprises a concentration analysis module and an index analysis module. The concentration analysis module acquires relevant coal mine environment data by using the sensor, analyzes the coal dust particle concentration according to the acquired relevant coal mine environment data, and judges the analyzed coal dust particle concentration by using the set standard coal dust particle concentration.

[0006] As a further improvement of the technical solution, the specific judgment conditions in the concentration analysis module include: Condition one: when the analyzed coal dust particle concentration is greater than or equal to the set standard coal dust particle concentration, it is judged that the analyzed coal dust particle concentration is over standard, and the high-efficiency particulate air filter is used to filter the coal dust particles on the surface of the sensor, filter out the coal dust particles with a diameter less than or equal to 0.3 microns, and obtain filtered air data. Condition two: when the analyzed coal dust particle concentration is less than or equal to the set standard coal dust particle concentration, it is judged that the analyzed coal dust particle concentration is not over standard.

[0007] As a further improvement of the technical solution, the index analysis module is used to receive the data that the analyzed coal dust particle concentration is not over standard in the concentration analysis module, and acquire the relevant coal mine environment data from the concentration analysis module, and analyze the carbon monoxide index according to the acquired relevant coal mine environment data.

[0008] As a further improvement of the technical solution, the filtering effect evaluation unit is used to receive the filtered air data in the concentration analysis module, and analyze the coal dust particle concentration of the filtered air data again, and evaluate the filtering effect by using the analyzed coal dust particle concentration and the coal dust particle concentration analyzed again, and the specific conditions of the evaluation include: Condition one: when the analyzed coal dust particle concentration is greater than the coal dust particle concentration analyzed again, it means that the filtering effect is high, and the filtering effect high command data is transmitted into the filtering effect evaluation unit; Condition two: when the analyzed coal dust particle concentration is less than or equal to the coal dust particle concentration analyzed again, it means that the filtering effect is low, the filtering effect low command data is transmitted into the concentration analysis module, the concentration analysis module receives the filtering effect low command data, and uses the high-efficiency particulate air filter to filter the coal dust particles on the surface of the sensor again, filters out the coal dust particles with a diameter less than or equal to 0.3 microns, and obtains the air data filtered again.

[0009] As a further improvement of the technical solution, the index analysis module is used to receive the filtering effect high command data in the filtering effect evaluation unit, the index analysis module acquires the filtered air data from the concentration analysis module, and analyzes the carbon monoxide index according to the filtered air data.

[0010] As a further improvement to this technical solution, the data detection unit is used to receive carbon monoxide index data analyzed in the index analysis module, and to detect the carbon monoxide concentration based on the analyzed carbon monoxide index data using infrared absorption method.

[0011] As a further improvement to this technical solution, the data detection unit utilizes infrared absorption to detect carbon monoxide concentration in the following steps: Step ①: First, obtain the carbon monoxide index data for analysis. Pass the carbon monoxide index data for analysis through an infrared absorption measurement device and record the infrared spectrum. Step 2: Use a carbon monoxide standard sample of known concentration to record its infrared absorption spectrum, especially the absorbance or transmittance corresponding to the carbon monoxide absorption peak, and establish a calibration curve based on the absorbance or transmittance. The steps to establish a calibration curve are as follows: S1. Measure the absorbance of a set of carbon monoxide standard samples with known concentrations and obtain the data. ,in, This refers to the first one having a known concentration. This refers to the nth element having a known concentration. The first corresponding absorbance, The absorbance of the nth corresponding element; S2, based on the known concentration , ... Add them together to obtain the known total concentration. Then, based on the corresponding absorbance , ... Add them together to obtain the corresponding total absorbance. n refers to the number of known concentrations and their corresponding absorbances; S3, based on the known concentration , ... and the corresponding absorbance , ... Perform a product summation to obtain the sum of products of known concentrations and their corresponding absorbances. ; S4. Based on the known concentration , ... Perform sum of squares to obtain the sum of squares of known concentrations. Then, based on the corresponding absorbance , ... Perform a sum of squares to obtain the sum of squares of absorbance. ; S5. Using the known total concentration The corresponding total absorbance The sum of the products of known concentrations and their corresponding absorbances Given the sum of squares of concentrations and the sum of squares of absorbance The specific algorithm formula for calculating parameter K is as follows: ; S6. Using the known total concentration The corresponding total absorbance The parameter b is calculated based on parameter K, known concentration, and the corresponding absorbance quantity n. The specific algorithm formula is as follows: ; S7. Using known concentrations The calibration curve is established using parameters b and K, and the specific calculation formula is as follows: ; in This corresponds to the absorbance; Step 3: Measure the absorbance of the carbon monoxide index data and substitute it into the calibration curve formula, based on the corresponding absorbance... The concentration of carbon monoxide in the analyzed carbon monoxide index data is calculated using parameters b and K. The calculated carbon monoxide concentration is the same as the detected carbon monoxide concentration. The specific algorithm formula is as follows: .

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: In this intelligent analysis and detection system for coal mine environment, the filtration effect evaluation unit is used to re-analyze the coal dust particle concentration based on the filtered air data and evaluate the filtration effect. By evaluating the air data before and after filtration, the reliability and accuracy of the data can be cross-validated, ensuring the precision of the detection results. When the filtration effect is evaluated as high, the carbon monoxide index is then analyzed on the filtered air data. The filtered air data can reduce the influence of interfering substances in the environment on carbon monoxide measurement, thereby improving the accuracy of the measurement results. Attached Figure Description

[0013] Fig. 1 This is an overall block diagram of the present invention; Fig. 2 This is a block diagram of the data analysis unit of the present invention.

[0014] The meanings of the labels in the diagram are as follows: 1. Data Analysis Unit; 11. Concentration Analysis Module; 12. Index Analysis Module; 2. Filtration effect evaluation unit; 3. Data detection unit. Detailed Implementation

[0015] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. 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.

[0016] Example 1: This invention provides an intelligent analysis and detection system for coal mine environments. Please refer to [link / reference]. Figs. 1-2 It includes a data analysis unit 1, a filtering effect evaluation unit 2, and a data detection unit 3; Data analysis unit 1 uses sensors to acquire relevant coal mine environmental data in real time to analyze coal dust particle concentration, then determines whether the concentration exceeds the standard, and performs air filtration based on the determined coal dust particle concentration exceeding the standard. Filtration effect evaluation unit 2 receives the filtered air data from data analysis unit 1, re-analyzes the coal dust particle concentration based on the filtered air data, evaluates the filtration effect, and transmits the evaluated filtration effect to data analysis unit 1. Data analysis unit 1 receives the evaluated filtration effect data and analyzes the carbon monoxide index of the filtered air data. Data detection unit 3 receives the carbon monoxide index data analyzed by filtration effect evaluation unit 2 and detects the carbon monoxide concentration based on the analyzed carbon monoxide index data.

[0017] The following is a more detailed explanation of the above units; please refer to [link / reference]. Figs. 1-2 ; Data analysis unit 1 includes a concentration analysis module 11 and an index analysis module 12; The concentration analysis module 11 uses sensors to acquire relevant coal mine environmental data and analyzes the concentration of coal dust particles based on the acquired data. By analyzing the concentration of coal dust particles, measures can be taken in advance to prevent the spread of pollution, thereby saving cleaning and treatment costs. The analyzed coal dust particle concentration is then compared with the set standard coal dust particle concentration for judgment.

[0018] The specific judgment conditions in concentration analysis module 11 include: Scenario 1: When the concentration of coal dust particles being analyzed is greater than or equal to the set standard concentration of coal dust particles, it is determined that the concentration of coal dust particles being analyzed exceeds the standard. A high-efficiency particulate air filter is then used to filter the coal dust particles on the sensor surface, filtering out coal dust particles with a diameter of less than or equal to 0.3 micrometers, and obtaining the filtered air data. Scenario 2: When the concentration of coal dust particles analyzed is less than or equal to the set standard concentration of coal dust particles, it is determined that the concentration of coal dust particles analyzed does not exceed the standard.

[0019] The index analysis module 12 is used to receive data from the concentration analysis module 11 indicating that the concentration of coal dust particles does not exceed the standard, and to take relevant coal mine environmental data from the concentration analysis module 11. Then, it analyzes the carbon monoxide index based on the relevant coal mine environmental data to ensure that the carbon monoxide concentration in the coal mine environment is within a safe range, protect the health of miners, improve work efficiency, and reduce production interruptions caused by accidents or environmental pollution.

[0020] The filtration effect evaluation unit 2 receives the filtered air data from the concentration analysis module 11 and re-analyzes the coal dust particle concentration in the filtered air data. It then uses the analyzed coal dust particle concentration and the re-analyzed coal dust particle concentration to evaluate the filtration effect. By evaluating the filtration effect under different conditions, factors affecting the coal dust particle filtration efficiency can be identified, providing data support for equipment optimization and improvement, and further enhancing the filtration effect. Specific evaluation criteria include: Situation ①: When the concentration of coal dust particles analyzed is greater than the concentration of coal dust particles analyzed again, it indicates that the filtration effect is high. The high filtration effect command data is transmitted to the filtration effect evaluation unit 2. Scenario 2: When the concentration of coal dust particles analyzed is less than or equal to the concentration of coal dust particles analyzed again, it indicates that the filtration effect is low. The low filtration effect command data is transmitted to the concentration analysis module 11. The concentration analysis module 11 receives the low filtration effect command data and uses a high-efficiency particulate air filter to filter the coal dust particles on the sensor surface again, filtering out coal dust particles with a diameter of less than or equal to 0.3 micrometers, and obtaining the air data after the second filtration.

[0021] The index analysis module 12 is used to receive the high filtration effect command data from the filtration effect evaluation unit 2. The index analysis module 12 obtains the filtered air data from the concentration analysis module 11, and then analyzes the carbon monoxide index based on the filtered air data. By analyzing the carbon monoxide index, the degree of air pollution can be understood, which helps to assess environmental quality and protect public health.

[0022] The data detection unit 3 is used to receive carbon monoxide index data analyzed in the index analysis module 12, and to detect carbon monoxide concentration based on the analyzed carbon monoxide index data using infrared absorption method. The analyzed carbon monoxide index data can provide real-time or near-real-time information to help detect changes in carbon monoxide concentration in a timely manner, so as to take necessary measures in a timely manner to protect public health. The implementation steps of detecting carbon monoxide concentration using infrared absorption in data detection unit 3 are as follows: Step ①: First, obtain the carbon monoxide index data for analysis. Pass the carbon monoxide index data for analysis through an infrared absorption measurement device and record the infrared spectrum. Step 2: Use a carbon monoxide standard sample of known concentration to record its infrared absorption spectrum, especially the absorbance or transmittance corresponding to the carbon monoxide absorption peak, and establish a calibration curve based on the absorbance or transmittance. The steps to establish a calibration curve are as follows: S1. Measure the absorbance of a set of carbon monoxide standard samples with known concentrations and obtain the data. ,in, This refers to the first one having a known concentration. This refers to the nth element having a known concentration. The first corresponding absorbance, The absorbance of the nth corresponding element; S2, based on the known concentration , ... Add them together to obtain the known total concentration. Then, based on the corresponding absorbance , ... Add them together to obtain the corresponding total absorbance. n refers to the number of known concentrations and their corresponding absorbances; S3, based on the known concentration , ... and the corresponding absorbance , ... Perform a product summation to obtain the sum of products of known concentrations and their corresponding absorbances. ; S4. Based on the known concentration , ... Perform sum of squares to obtain the sum of squares of known concentrations. Then, based on the corresponding absorbance , ... Perform a sum of squares to obtain the sum of squares of absorbance. ; S5. Using the known total concentration The corresponding total absorbance The sum of the products of known concentrations and their corresponding absorbances Given the sum of squares of concentrations and the sum of squares of absorbance The specific algorithm formula for calculating parameter K is as follows: ; This formula is used to calculate parameter K. The parameter K calculated using data from multiple standard samples is more in line with the actual situation, thereby improving the accuracy of subsequent concentration detection. S6. Using the known total concentration The corresponding total absorbance The parameter b is calculated based on parameter K, known concentration, and the corresponding absorbance quantity n. The specific algorithm formula is as follows: ; This formula is used to calculate parameter b. By using data from multiple standard samples, parameter b of the calibration curve can be calculated more accurately, thereby improving the accuracy of carbon monoxide concentration in subsequent detection and analysis data. S7. Using known concentrations The calibration curve is established using parameters b and K, and the specific calculation formula is as follows: ; in, The formula is used to establish the calibration curve, which provides a standardized reference and can accurately convert absorbance values ​​into corresponding concentration values, ensuring the accuracy and reliability of the detection results. Step 3: Measure the absorbance of the carbon monoxide index data and substitute it into the calibration curve formula, based on the corresponding absorbance... The concentration of carbon monoxide in the analyzed carbon monoxide index data is calculated using parameters b and K. The calculated carbon monoxide concentration is the same as the detected carbon monoxide concentration. The specific algorithm formula is as follows: ; This formula is used to detect carbon monoxide concentration. Using carbon monoxide index data can improve the accuracy of detection. By detecting index data, the concentration of carbon monoxide can be estimated more accurately, thereby reducing errors.

[0023] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A coal mine environmental intelligent analysis and detection system, characterized in that: It includes a data analysis unit (1), a filtering effect evaluation unit (2), and a data detection unit (3); The data analysis unit (1) uses sensors to acquire relevant coal mine environmental data in real time to analyze the concentration of coal dust particles, then judges the exceedance of the standard based on the analyzed coal dust particle concentration, and performs air filtration based on the judged exceedance of the coal dust particle concentration. The filtration effect evaluation unit (2) is used to receive the filtered air data in the data analysis unit (1), analyze the coal dust particle concentration again based on the filtered air data and evaluate the filtration effect, and transmit the evaluated filtration effect to the data analysis unit (1). The data analysis unit (1) receives the evaluated filtration effect data and analyzes the carbon monoxide index of the filtered air data. The data detection unit (3) is used to receive carbon monoxide index data analyzed by the filtration effect evaluation unit (2) and to detect carbon monoxide concentration based on the analyzed carbon monoxide index data.

2. The intelligent analysis and detection system for coal mine environment according to claim 1, characterized in that: The data analysis unit (1) includes a concentration analysis module (11) and an index analysis module (12). The concentration analysis module (11) uses sensors to acquire relevant coal mine environmental data, analyzes the concentration of coal dust particles based on the acquired coal mine environmental data, and then uses the analyzed coal dust particle concentration to make a judgment with the set standard coal dust particle concentration.

3. The intelligent analysis and detection system for coal mine environment according to claim 2, characterized in that: The specific judgment conditions in the concentration analysis module (11) include: Scenario 1: When the concentration of coal dust particles being analyzed is greater than or equal to the set standard concentration of coal dust particles, it is determined that the concentration of coal dust particles being analyzed exceeds the standard. A high-efficiency particulate air filter is then used to filter the coal dust particles on the sensor surface, filtering out coal dust particles with a diameter of less than or equal to 0.3 micrometers, and obtaining the filtered air data. Scenario 2: When the concentration of coal dust particles analyzed is less than or equal to the set standard concentration of coal dust particles, it is determined that the concentration of coal dust particles analyzed does not exceed the standard.

4. The intelligent analysis and detection system for coal mine environment according to claim 3, characterized in that: The index analysis module (12) is used to receive data from the concentration analysis module (11) indicating that the concentration of coal dust particles does not exceed the standard, and to obtain relevant coal mine environmental data from the concentration analysis module (11), and then to analyze the carbon monoxide index based on the obtained relevant coal mine environmental data.

5. The intelligent analysis and detection system for coal mine environment according to claim 3, characterized in that: The filtration effect evaluation unit (2) is used to receive the filtered air data from the concentration analysis module (11), and to analyze the coal dust particle concentration again on the filtered air data. Then, the filtration effect is evaluated by comparing the analyzed coal dust particle concentration with the re-analyzed coal dust particle concentration. The specific evaluation includes: Situation ①: When the concentration of coal dust particles analyzed is greater than the concentration of coal dust particles analyzed again, it indicates that the filtration effect is high. The high filtration effect command data is transmitted to the filtration effect evaluation unit (2). Situation ②: When the concentration of coal dust particles analyzed is less than or equal to the concentration of coal dust particles analyzed again, it indicates that the filtration effect is low. The low filtration effect command data is transmitted to the concentration analysis module (11). The concentration analysis module (11) receives the low filtration effect command data and uses a high-efficiency particulate air filter to filter the coal dust particles on the sensor surface again, filtering out coal dust particles with a diameter of less than or equal to 0.3 micrometers, and obtaining the air data after the second filtration.

6. The intelligent analysis and detection system for coal mine environment according to claim 5, characterized in that: The index analysis module (12) is used to receive high filtration effect command data from the filtration effect evaluation unit (2). The index analysis module (12) obtains the filtered air data from the concentration analysis module (11) and then analyzes the carbon monoxide index based on the filtered air data.

7. The intelligent analysis and detection system for coal mine environment according to claim 6, characterized in that: The data detection unit (3) is used to receive carbon monoxide index data analyzed in the index analysis module (12) and to detect carbon monoxide concentration based on the analyzed carbon monoxide index data using infrared absorption method.

8. The intelligent analysis and detection system for coal mine environment according to claim 7, characterized in that: The implementation steps of detecting carbon monoxide concentration using infrared absorption method in the data detection unit (3) are as follows: Step ①: First, obtain the carbon monoxide index data for analysis. Pass the carbon monoxide index data for analysis through an infrared absorption measurement device and record the infrared spectrum. Step 2: Use a carbon monoxide standard sample of known concentration to record its infrared absorption spectrum, especially the absorbance or transmittance corresponding to the carbon monoxide absorption peak, and establish a calibration curve based on the absorbance or transmittance. The steps to establish a calibration curve are as follows: S1. Measure the absorbance of a set of carbon monoxide standard samples with known concentrations and obtain the data. ,in, This refers to the first known concentration. This refers to the nth known concentration. The first corresponding absorbance, The absorbance of the nth corresponding element; S2, based on the known concentration , ... Add them together to obtain the known total concentration. Then, based on the corresponding absorbance , ... Add them together to obtain the corresponding total absorbance. n refers to the number of known concentrations and their corresponding absorbances; S3, based on the known concentration , ... and the corresponding absorbance , ... Perform a product summation to obtain the sum of products of known concentrations and their corresponding absorbances. ; S4. Based on the known concentration , ... Perform sum of squares to obtain the sum of squares of known concentrations. Then, based on the corresponding absorbance , ... Perform a sum of squares to obtain the sum of squares of absorbance. ; S5. Using the known total concentration The corresponding total absorbance The sum of the products of known concentrations and their corresponding absorbances Given the sum of squares of concentrations and the sum of squares of absorbance The specific algorithm formula for calculating parameter K is as follows: ; S6. Using the known total concentration The corresponding total absorbance The parameter b is calculated based on parameter K, known concentration, and the corresponding absorbance quantity n. The specific algorithm formula is as follows: ； S7. Using known concentrations The calibration curve is established using parameters b and K, and the specific calculation formula is as follows: ； in This corresponds to the absorbance; Step 3: Measure the absorbance of the carbon monoxide index data and substitute it into the calibration curve formula, based on the corresponding absorbance... The concentration of carbon monoxide in the analyzed carbon monoxide index data is calculated using parameters b and K. The calculated carbon monoxide concentration is the same as the detected carbon monoxide concentration. The specific algorithm formula is as follows: .

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