Mining intrinsic safety type nitrogen dioxide sensor control system

Abstract

The invention relates to the technical field of mining equipment, in particular to a mining intrinsic safety type nitrogen dioxide sensor control system, which comprises an intrinsic safety type nitrogen dioxide sensor, adopts a high-sensitivity semiconductor material or electrochemical gas sensing, can detect the concentration of nitrogen dioxide in a mine in real time, and has anti-interference capability; the signal acquisition module is connected with the nitrogen dioxide sensor, has a multi-channel signal receiving function, acquires a sensor signal, performs preliminary filtering, and performs digital processing on the signal; according to the system, a multi-path signal separation algorithm and a Kalman filtering technology are adopted, the signal processing precision is effectively improved, multi-path interference signals generated by reflection and refraction reasons can be removed, accurate measurement of direct signals is ensured, the noise suppression technology based on an ARMA model is adopted, and the noise suppression precision is improved. Noise interference in the mine environment is effectively eliminated, and especially under the complex climate condition, the system can still keep high precision.

Description

Technical Field

[0001] The invention relates to the technical field of mining equipment, in particular to a mining intrinsically safe nitrogen dioxide sensor control system. Background Art

[0002] Mining gas detection equipment is crucial in mine safety management. It is mainly used to monitor the concentration of harmful gases in the mine environment in real time, especially the detection of harmful gases such as nitrogen dioxide, methane, and hydrogen sulfide. Traditional gas detection systems mostly rely on electrochemical or semiconductor sensors to measure gas concentrations. However, in complex mine environments, these devices often face problems such as signal interference and insufficient accuracy.

[0003] Noise, electromagnetic interference and multipath effects in the mine environment greatly reduce the accuracy and stability of gas sensor signals. Especially in the case of rapid changes in high-concentration gas, existing gas detection systems are difficult to achieve high-precision real-time monitoring and positioning. In addition, most traditional systems lack the ability to predict the trend of gas concentration changes and cannot promptly warn of potential safety risks.

[0004] The existing mining gas detection system has many technical difficulties in the mine environment. First, due to multi-path signal interference and environmental noise, traditional signal processing algorithms are difficult to effectively distinguish between effective signals and interference signals, which affects the measurement accuracy of gas concentration. Secondly, the existing noise suppression technology is insufficient to suppress high-frequency noise and non-ideal signals in complex environments, resulting in unstable measurement data. Thirdly, the existing gas monitoring system mostly relies on triggering alarms when gas concentration exceeds the standard, lacks real-time prediction and early warning mechanisms for concentration change trends, and cannot identify potential safety hazards in a timely manner. Finally, changes in temperature, humidity and air pressure in the mine environment will affect the response of the gas sensor. The existing system cannot automatically adapt to these environmental changes, resulting in poor adaptability of the system in a dynamic environment and insufficient operational stability. Therefore, a mining intrinsically safe nitrogen dioxide sensor control system is proposed to address the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide a mining intrinsically safe nitrogen dioxide sensor control system to solve multiple technical problems existing in existing mining gas detection systems in mine environments. First, due to multi-path signal interference and environmental noise, traditional signal processing algorithms are difficult to effectively distinguish between effective signals and interference signals, thereby affecting the measurement accuracy of gas concentration. Secondly, existing noise suppression technologies are insufficient to suppress high-frequency noise and non-ideal signals in complex environments, resulting in unstable measurement data. Thirdly, existing gas monitoring systems mostly rely on triggering alarms when gas concentrations exceed the standard, lack a real-time prediction and early warning mechanism for concentration change trends, and are unable to identify potential safety hazards in a timely manner. Finally, changes in temperature, humidity, and air pressure in the mine environment will affect the response of the gas sensor, and the existing system cannot automatically adapt to these environmental changes, resulting in poor adaptability of the system in a dynamic environment and insufficient operational stability.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A mine-use intrinsically safe nitrogen dioxide sensor control system, the system comprising an intrinsically safe nitrogen dioxide sensor, using a highly sensitive semiconductor material or an electrochemical gas sensor, capable of detecting the nitrogen dioxide concentration in the mine in real time, and having anti-interference capability;

[0008] A signal acquisition module is connected to the nitrogen dioxide sensor and has a multi-channel signal receiving function. After collecting the sensor signal, it performs preliminary filtering and digitally processes the signal.

[0009] The signal preprocessing unit includes a multi-path signal separation algorithm and a signal denoising module. By analyzing the delay characteristics of signals on different paths, it removes the interference of reflection and refraction multi-paths and performs noise suppression on sensor signals to ensure that the transmitted data has high accuracy.

[0010] The multipath signal separation algorithm compares the delays of different paths and adopts the strategy of selecting the direct signal with the minimum delay, specifically: setting the delay threshold T th ∈R, for the path signal delay T i When it is greater than the threshold, the path signal is discarded and the global signal delay sequence T is set to [T1, T2, ..., T n ], the direct signal selection criteria are:

[0011] T direct =arg min(|T i -Tmin(T1, T2, ..., T n )|)forT i <T th

[0012] Among them, T iis the delay of different paths, T th is the set threshold, T direct is the optimal direct signal path delay selected;

[0013] The data processing module performs in-depth analysis of pre-processed signals, including signal smoothing based on the Kalman filter algorithm to further improve positioning accuracy, and uses machine learning algorithms to perform trend analysis and prediction of nitrogen dioxide concentration in the mine, provide real-time alarms and optimize control parameters;

[0014] The Kalman filter algorithm formula is:

[0015] X k =A·X k-1 +B·uk+wk

[0016] Z k =H·X k +vk

[0017] Among them, X k is the current state, A is the state transfer matrix, B is the control matrix, uk is the control input, wk is the process noise, Z k is the measurement value, H is the measurement matrix, and vk is the measurement noise;

[0018] The alarm module, when the nitrogen dioxide concentration exceeds the set safety threshold, promptly issues an alarm to the mine workers through multiple means such as sound and light alarm, vibration alarm and wireless notification, and automatically adjusts the alarm intensity and frequency according to the concentration change to ensure the safety of the personnel;

[0019] The wireless communication module supports multiple wireless communication protocols, including Wi-Fi, LoRa, and NB-IoT. It can achieve stable data transmission in the complex environment of the mine and transmit the processed data to the remote monitoring center, cloud platform or local terminal for remote monitoring and data archiving.

[0020] As further optimized content of the present invention, the data processing module further includes: a multipath signal separation algorithm, which uses a multipath minimum method based on time delay analysis, combined with angle arrival estimation, accurately distinguishes direct signals from multipath signals, retains direct signals and discards reflected signals with larger delays;

[0021] The noise suppression module based on adaptive filtering dynamically filters the noise through the autoregressive model based on the collected signal;

[0022] The machine learning prediction module uses regression analysis and time series models to predict the trend of changes in nitrogen dioxide concentration, identify possible sharp changes in concentration in advance and issue warnings.

[0023] As a further optimized content of the present invention, the intrinsically safe nitrogen dioxide sensor has a temperature compensation module, which can automatically adjust the response characteristics of the sensor according to changes in the ambient temperature.

[0024] As a further optimized content of the present invention, the signal acquisition module further includes a high-precision data cache unit, which caches the positioning data from the sensor in real time, and the cache time does not exceed 5 seconds, and collects 10-20 data points per second.

[0025] As a further optimization of the present invention, the alarm module adjusts the alarm volume, light intensity, vibration frequency and alarm mode switching in real time according to the nitrogen dioxide concentration data through the automatic signal strength adjustment function.

[0026] As a further optimization of the present invention, the system further includes an environmental monitoring module, which not only monitors the nitrogen dioxide concentration, but also can simultaneously monitor other gas concentrations and environmental parameters in the mine, and correct the nitrogen dioxide data according to changes in environmental parameters.

[0027] As further optimized content of the present invention, the system adopts an adaptive power consumption adjustment module to automatically reduce power consumption when the change trend of sensor data is relatively stable; when the concentration changes drastically or the system detects a fault signal, the system power is automatically increased.

[0028] As a further optimized content of the present invention, the signal processing module adopts a real-time beamforming algorithm to optimize the signal directivity by adjusting the phase of the received signal.

[0029] As a further optimized content of the present invention, the wireless communication module supports multi-band communication function and automatically switches different communication frequency bands according to the signal strength and communication environment in the mine.

[0030] As further optimized content of the present invention, the system includes a cloud analysis platform, which can perform data modeling and big data analysis based on historical data, real-time data and environmental parameters, and provide optimized nitrogen dioxide concentration prediction and trend analysis.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] In the present invention, firstly, the system adopts a multi-path signal separation algorithm and Kalman filtering technology, which effectively improves the signal processing accuracy, can remove the multi-path interference signals caused by reflection and refraction, and ensure the accurate measurement of the direct signal. Secondly, the noise suppression technology based on the ARMA model is adopted to effectively eliminate the noise interference in the mine environment, especially under complex climatic conditions, the system can still maintain a high accuracy. Thirdly, the system predicts the trend of nitrogen dioxide concentration through a machine learning algorithm, identifies abnormal changes in gas concentration in advance, and issues early warnings in time, which greatly enhances the intelligence and safety of the system. The system has adaptive power consumption adjustment and environmental parameter correction functions, and can automatically adjust the working state according to the changes in temperature, humidity and air pressure in the mine, ensuring stability and reliability in a dynamic environment. Finally, it supports a variety of wireless communication protocols to ensure the real-time transmission of system data, facilitate remote monitoring and management, and improve the efficiency of mine safety management. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 The system block diagram of the mine-used intrinsically safe nitrogen dioxide sensor control system of the present invention. DETAILED DESCRIPTION

[0034] Example

[0035] See also Figure 1 , the present invention provides a technical solution:

[0036] The intrinsically safe nitrogen dioxide sensor control system for mining, the intrinsically safe nitrogen dioxide sensor control system for mining of this embodiment is mainly composed of the following modules: intrinsically safe nitrogen dioxide sensor: adopts semiconductor gas sensor, which has strong anti-interference ability;

[0037] Signal acquisition module: responsible for acquiring signals from sensors and performing preliminary filtering and digital processing;

[0038] Signal preprocessing unit: includes multipath signal separation algorithm and noise suppression module, used to remove environmental interference signals;

[0039] Data processing module: Kalman filtering is performed to further optimize signal quality and predict nitrogen dioxide concentration trends through machine learning;

[0040] Alarm module: issues an alarm based on changes in nitrogen dioxide concentration and has the function of intensity adjustment;

[0041] Wireless communication module: supports Wi-Fi, LoRa and NB-IoT communication modes, and transmits data to the remote monitoring center in real time;

[0042] Environmental monitoring module: monitors other harmful gases (such as methane and hydrogen sulfide) and environmental parameters (such as temperature, humidity, and air pressure) in the mine to enhance the adaptability of the system;

[0043] Specific implementation process: Data acquisition: The system collects the nitrogen dioxide concentration signal in the mine in real time through the intrinsically safe nitrogen dioxide sensor. The sensor automatically calibrates its response speed and sensitivity according to the different gas characteristics in the mine environment, and connects with the signal acquisition module through analog signal output;

[0044] Signal preprocessing: The signal acquisition module converts the analog signal output by the sensor into a digital signal and performs preliminary filtering. The signal preprocessing unit uses a multipath signal separation algorithm to select the most suitable signal path through delay analysis. The system first calculates the delay of each path signal and uses the set delay threshold T th To determine whether to retain the path signal, discard the signal whose delay exceeds the set threshold and retain the direct signal. The algorithm formula is as follows:

[0045] T direct =arg min(|T i -min(T1, T2, ..., T n )|)forT i <T th

[0046] Among them, T i is the delay of different paths, T th is the set threshold, T direct is the optimal direct signal path delay selected;

[0047] Data processing: After preprocessing, the signal is transmitted to the data processing module. The data processing module uses the Kalman filter algorithm to further smooth the signal, thereby eliminating the influence of noise and obtaining more accurate nitrogen dioxide concentration data. The update equation of the Kalman filter is:

[0048] X k =A·X k-1 +B·uk+wk

[0049] Z k =H·X k +vk

[0050] Among them, X k is the current state, A is the state transfer matrix, B is the control matrix, uk is the control input, wk is the process noise, Z k is the measurement value, H is the measurement matrix, and vk is the measurement noise;

[0051] Prediction and warning: The data processing module uses machine learning algorithms to predict the trend of nitrogen dioxide concentration, identify potential concentration anomalies or sharp changes in concentration, and issue warnings. For example, if the system predicts that the nitrogen dioxide concentration will exceed the safety threshold within the next 10 minutes, the system will activate the alarm module in advance and send the alarm information to the mine control center through the wireless communication module;

[0052] Real-time alarm: When the nitrogen dioxide concentration exceeds the set safety threshold, the alarm module triggers an audible and visual alarm and automatically adjusts the alarm intensity according to the concentration change. If the concentration continues to rise, the alarm volume and light intensity will increase. At the same time, the vibration alarm system will enhance the vigilance of mine workers.

[0053] Data transmission and remote monitoring: The system transmits filtered and analyzed data to the remote monitoring platform in real time through the wireless communication module. The wireless communication module supports Wi-Fi, LoRa and NB-IoT protocols and can automatically select the most suitable communication method according to the internal network environment of the mine. The remote monitoring platform can not only receive data in real time, but also conduct a comprehensive analysis of other harmful gas concentrations and environmental parameters in the mine;

[0054] Environmental monitoring: The system also integrates an environmental monitoring module that can simultaneously monitor the concentration of methane and hydrogen sulfide harmful gases in the mine, as well as the temperature, humidity and air pressure environmental parameters of the mine. By comprehensively analyzing these data, the system can automatically correct the concentration data of nitrogen dioxide, thereby improving the accuracy and reliability of the data;

[0055] System optimization and power consumption management: In order to ensure that the system can run for a long time without failure in the mine environment, the system is designed with an adaptive power consumption adjustment module. Under normal circumstances, the system will automatically adjust the power consumption according to the changes in nitrogen dioxide concentration and the changes in the mine environment. When the environment is stable, the system will enter a low power consumption mode; when the nitrogen dioxide concentration fluctuates greatly, the system will switch to a high power consumption mode to ensure the accuracy of signal acquisition and processing;

[0056] The system uses multi-path signal separation and Kalman filtering algorithms to effectively improve the accuracy of nitrogen dioxide concentration data. At the same time, it uses machine learning algorithms to predict trends and dynamically adjust alarm intensity, so that safety measures can be taken in advance when concentration changes abnormally. The system can automatically adjust power consumption and signal processing strategies according to mine environmental conditions to extend the service life of the equipment. It also supports multiple wireless communication protocols to ensure real-time data transmission and remote monitoring.

[0057] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only used to help understand the method and core ideas of the present invention. The above is only a preferred implementation of the present invention. It should be pointed out that due to the limitations of textual expression and the objective existence of infinite specific structures, ordinary technicians in this technical field can make several improvements, modifications or changes without departing from the principles of the present invention, and can also combine the above technical features in an appropriate manner; these improvements, modifications, changes or combinations, or the direct application of the inventive concept and technical solution to other occasions without improvement, should be regarded as the protection scope of the present invention.

Claims

1. A mining intrinsically safe nitrogen dioxide sensor control system, characterized in that: The system includes an intrinsically safe nitrogen dioxide sensor, which uses highly sensitive semiconductor materials or electrochemical gas sensors, can detect the concentration of nitrogen dioxide in the mine in real time, and has anti-interference capabilities; A signal acquisition module is connected to the nitrogen dioxide sensor and has a multi-channel signal receiving function. After collecting the sensor signal, it performs preliminary filtering and digitally processes the signal. The signal preprocessing unit includes a multi-path signal separation algorithm and a signal denoising module. By analyzing the delay characteristics of signals on different paths, it removes the interference of reflection and refraction multi-paths and performs noise suppression on sensor signals to ensure that the transmitted data has high accuracy. The multipath signal separation algorithm compares the delays of different paths and adopts the strategy of selecting the direct signal with the minimum delay, specifically: setting the delay threshold T th ∈R, for the path signal delay T i When it is greater than the threshold, the path signal is discarded and the global signal delay sequence T is set to [T1, T2, ..., T n ], the direct signal selection criteria are: T direct =arg min(|T i -min(T1,T2,...,T n )|)forT i <T th Among them, T i is the delay of different paths, T th is the set threshold, T direct is the optimal direct signal path delay selected; The data processing module performs in-depth analysis of pre-processed signals, including signal smoothing based on the Kalman filter algorithm to further improve positioning accuracy, and uses machine learning algorithms to perform trend analysis and prediction of nitrogen dioxide concentration in the mine, provide real-time alarms and optimize control parameters; The Kalman filter algorithm formula is: X k =A·X k-1 +B·uk+wk Z k =H·X k +vk Among them, X k is the current state, A is the state transfer matrix, B is the control matrix, uk is the control input, wk is the process noise, Z k is the measurement value, H is the measurement matrix, and vk is the measurement noise; The alarm module, when the nitrogen dioxide concentration exceeds the set safety threshold, promptly issues an alarm to the mine workers through multiple means such as sound and light alarm, vibration alarm and wireless notification, and automatically adjusts the alarm intensity and frequency according to the concentration change to ensure the safety of the personnel; The wireless communication module supports multiple wireless communication protocols, including Wi-Fi, LoRa, and NB-IoT. It can achieve stable data transmission in the complex environment of the mine and transmit the processed data to the remote monitoring center, cloud platform or local terminal for remote monitoring and data archiving.

2. The mine intrinsically safe nitrogen dioxide sensor control system according to claim 1 is characterized in that: The data processing module further includes: a multipath signal separation algorithm, which uses a multipath minimum method based on time delay analysis, combined with angle arrival estimation, to accurately distinguish direct signals from multipath signals, retain direct signals and discard reflected signals with larger delays; The noise suppression module based on adaptive filtering dynamically filters the noise through the autoregressive model based on the collected signal; The machine learning prediction module uses regression analysis and time series models to predict the trend of changes in nitrogen dioxide concentration, identify possible sharp changes in concentration in advance and issue warnings.

3. The mine intrinsically safe nitrogen dioxide sensor control system according to claim 1 is characterized in that: The intrinsically safe nitrogen dioxide sensor has a temperature compensation module, which can automatically adjust the response characteristics of the sensor according to changes in the ambient temperature.

4. The mine intrinsically safe nitrogen dioxide sensor control system according to claim 1 is characterized in that: The signal acquisition module further includes a high-precision data cache unit, which caches the positioning data from the sensor in real time, and the cache time does not exceed 5 seconds, and collects 10-20 data points per second.

5. The mine-used intrinsically safe nitrogen dioxide sensor control system according to claim 1 is characterized in that: The alarm module uses the automatic signal strength adjustment function to adjust the alarm volume, light intensity, vibration frequency and alarm mode switching in real time according to the nitrogen dioxide concentration data.

6. The mine intrinsically safe nitrogen dioxide sensor control system according to claim 1 is characterized in that: The system further includes an environmental monitoring module, which not only monitors the concentration of nitrogen dioxide, but also can simultaneously monitor the concentration of other gases and environmental parameters in the mine, and correct the nitrogen dioxide data according to the changes in environmental parameters.

7. The mine intrinsically safe nitrogen dioxide sensor control system according to claim 1 is characterized in that: The system adopts an adaptive power consumption adjustment module, which automatically reduces power consumption when the change trend of sensor data is relatively stable; when the concentration changes drastically or the system detects a fault signal, it automatically increases system power.

8. The mine intrinsically safe nitrogen dioxide sensor control system according to claim 1 is characterized in that: The signal processing module adopts a real-time beamforming algorithm to optimize the signal directivity by adjusting the phase of the received signal.

9. The mine intrinsically safe nitrogen dioxide sensor control system according to claim 1 is characterized in that: The wireless communication module supports multi-band communication function and automatically switches different communication frequency bands according to the signal strength and communication environment in the mine.

10. The mine intrinsically safe nitrogen dioxide sensor control system according to claim 1 is characterized in that: The system includes a cloud-based analysis platform that can perform data modeling and big data analysis based on historical data, real-time data, and environmental parameters to provide optimized nitrogen dioxide concentration forecasts and trend analysis.

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