A mine-used intrinsically safe nitrogen dioxide sensor control system

Abstract

The present invention relates to the technical field of mining equipment, and in particular to a mining intrinsically safe nitrogen dioxide sensor control system. The system comprises an intrinsically safe nitrogen dioxide sensor, which adopts a high-sensitivity semiconductor material or an electrochemical gas sensor, can detect the nitrogen dioxide concentration in the mine in real time, and has anti-interference capability; a signal acquisition module, which is connected to the nitrogen dioxide sensor and has a multi-channel signal receiving function, performs preliminary filtering after collecting the sensor signal, and digitally processes the signal; and a signal preprocessing unit. In the present invention, the system adopts a multi-path signal separation algorithm and Kalman filtering technology, which effectively improves the signal processing accuracy, can remove multi-path interference signals caused by reflection and refraction, ensures the accurate measurement of direct signals, and adopts noise suppression technology based on an ARMA model to effectively eliminate noise interference in the mine environment. In particular, under complex climatic conditions, the system can still maintain a high accuracy.

Description

Technical Field

[0001] The present 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 to mine safety management. It is primarily used to monitor the concentration of hazardous gases in the mine environment in real time, particularly 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 mine environments significantly reduce the accuracy and stability of gas sensor signals. Existing gas detection systems struggle to achieve high-precision real-time monitoring and positioning, especially in situations where high-concentration gas concentrations are rapidly changing. Furthermore, most traditional systems lack the ability to predict gas concentration trends, preventing them from providing timely warnings of potential safety risks.

[0004] Existing mining gas detection systems face multiple technical difficulties in mine environments. First, due to multipath signal interference and environmental noise, traditional signal processing algorithms are difficult to effectively distinguish between valid signals and interference signals, which affects the measurement accuracy of gas concentration. Second, existing noise suppression technologies are insufficient to suppress high-frequency noise and non-ideal signals in complex environments, resulting in unstable measurement data. Third, 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. The existing system cannot automatically adapt to these environmental changes, resulting in poor adaptability of the system in dynamic environments and insufficient operational stability. Therefore, a mine-used 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 difficulties 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 valid signals and interference signals, thereby affecting the measurement accuracy of gas concentration. Second, existing noise suppression technologies are insufficient to suppress high-frequency noise and non-ideal signals in complex environments, resulting in unstable measurement data. Third, existing gas monitoring systems mostly rely on triggering alarms when gas concentrations exceed the standard, lack real-time prediction and early warning mechanisms 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. The existing system cannot automatically adapt to these environmental changes, resulting in poor adaptability of the system in dynamic environments 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 including an intrinsically safe nitrogen dioxide sensor that uses highly sensitive semiconductor materials or electrochemical gas sensors, capable of real-time detection of nitrogen dioxide concentrations within the mine, and having anti-interference capabilities;

[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 digital processing on the signal.

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

[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, the delay threshold T is set. th ∈R, for the path signal delay T i When the delay 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. It also uses a machine learning algorithm to analyze and predict nitrogen dioxide concentration trends within the mine, providing real-time alarms and optimizing 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 alerts mine workers through multiple means such as sound and light alarms, vibration alarms, and wireless notifications, and automatically adjusts the alarm intensity and frequency according to changes in concentration to ensure personnel safety;

[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 processed data to the remote monitoring center, cloud platform or local terminal for remote monitoring and data archiving.

[0020] As a further optimization of the present invention, the data processing module further includes: a multipath signal separation algorithm, which uses a multipath minimization method based on time delay analysis, combined with angle of arrival estimation, to accurately distinguish direct signals from multipath signals, retain direct signals and discard 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 early 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 optimization 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 uses the signal strength automatic 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.

[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 a further optimization of the present invention, 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, 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 degree of accuracy. Thirdly, the system predicts the trend of nitrogen dioxide concentration through machine learning algorithms, 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 temperature, humidity and air pressure changes in the mine, ensuring stability and reliability in a dynamic environment. Finally, it supports multiple wireless communication protocols to ensure 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 This is a 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 mine intrinsically safe nitrogen dioxide sensor control system of this embodiment is mainly composed of the following modules: Intrinsically safe nitrogen dioxide sensor: uses semiconductor gas sensing and 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 to remove environmental interference signals;

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

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

[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 uses an intrinsically safe nitrogen dioxide sensor to collect real-time nitrogen dioxide concentration signals in the mine. The sensor automatically calibrates its response speed and sensitivity according to the different gas characteristics in the mine environment, and connects to 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 multi-path signal separation algorithm to select the most appropriate 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, the signal with a delay exceeding the set threshold is discarded and the direct signal is retained. 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 early warning: The data processing module uses machine learning algorithms to predict nitrogen dioxide concentration trends, identify potential concentration anomalies or sudden changes, and issue early warnings. For example, if the system predicts that nitrogen dioxide concentrations 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 via 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 a wireless communication module. The wireless communication module supports Wi-Fi, LoRa, and NB-IoT protocols and can automatically select the most suitable communication method based on 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 within the mine.

[0054] Environmental monitoring: The system also integrates an environmental monitoring module that can simultaneously monitor the concentrations 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 this data, the system can automatically correct the nitrogen dioxide concentration data, thereby improving the accuracy and reliability of the data;

[0055] System optimization and power consumption management: To ensure the system can operate for long periods without malfunctioning in a mine environment, an adaptive power consumption adjustment module has been designed. Under normal circumstances, the system automatically adjusts power consumption based on changes in nitrogen dioxide concentration and the mine environment. When the environment is stable, the system enters a low-power mode; when nitrogen dioxide concentration fluctuates significantly, the system switches to a high-power mode to ensure accurate 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, allowing safety measures to be taken in advance when concentration changes abnormally. The system can also automatically adjust power consumption and signal processing strategies according to mine environmental conditions, extending 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 of the present invention and its core ideas. The above is only a preferred implementation method of the present invention. It should be pointed out that due to the limitations of textual expression, there are objectively infinite specific structures. For ordinary technicians in this technical field, without departing from the principles of the present invention, they can make several improvements, modifications or changes, 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 scope of protection of the present invention.

Claims

1. A mine-used intrinsically safe nitrogen dioxide sensor control system, characterized by: The system includes an intrinsically safe nitrogen dioxide sensor that uses highly sensitive semiconductor materials or electrochemical gas sensing, 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 digital processing on the signal. The signal preprocessing unit includes a multipath signal separation algorithm and a signal denoising module. By analyzing the delay characteristics of signals on different paths, it removes reflection and refraction multipath interference and performs noise suppression on sensor signals to ensure the high accuracy of the transmitted data. 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, the delay threshold T is set. th ∈R, for the path signal delay T i When the delay 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. It also uses a machine learning algorithm to analyze and predict nitrogen dioxide concentration trends within the mine, providing real-time alarms and optimizing 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 alerts mine workers through multiple means such as sound and light alarms, vibration alarms, and wireless notifications, and automatically adjusts the alarm intensity and frequency according to changes in concentration to ensure personnel safety; 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 processed data to the remote monitoring center, cloud platform or local terminal for remote monitoring and data archiving.

2. The mine-used 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 that uses a multipath minimization method based on time delay analysis, combined with angle of arrival estimation, to accurately distinguish direct signals from multipath signals, retaining direct signals and discarding 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 early warnings.

3. The mine-use 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-use 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 that 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-used intrinsically safe nitrogen dioxide sensor control system according to claim 1, characterized in that: The system further includes an environmental monitoring module that not only monitors nitrogen dioxide concentration, but also simultaneously monitors other gas concentrations and environmental parameters in the mine, and corrects nitrogen dioxide data according to changes in environmental parameters.

7. The mine-used intrinsically safe nitrogen dioxide sensor control system according to claim 1, characterized in that: The system uses 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, it automatically increases system power.

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

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

10. The mine-used intrinsically safe nitrogen dioxide sensor control system according to claim 1, 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, providing optimized nitrogen dioxide concentration forecasts and trend analysis.

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