Mine dynamic disaster information dynamic sensing method

Abstract

The invention relates to the technical field of mine safety, and discloses a mine dynamic disaster information dynamic sensing method, which comprises the following steps: acquiring environment parameter data monitored by a plurality of underground sensors in real time, and carrying out primary processing through an adaptive regulation and control algorithm to improve the disaster early warning accuracy; performing integrated processing on the primarily processed multi-source sensor data based on a data fusion mechanism, and adjusting fusion parameters to reduce information one-sidedness and redundancy; and a weak signal identification algorithm is applied to a result after data fusion, and an identification threshold value is dynamically regulated and controlled, so that early-stage pre-disaster symptoms are accurately captured. According to the dynamic sensing method for the mine dynamic disaster information, the disaster early warning accuracy is improved, possible disaster hidden dangers in an underground changeable environment can be found more timely and accurately, false alarm and missing alarm conditions are reduced, more reliable safety guarantee is provided for underground operating personnel, and the possibility and the hazard degree of disasters are reduced.

Description

Technical Field

[0001] The present application relates to the technical field of mine safety, and in particular to a method for dynamically sensing mine power disaster information. Background Art

[0002] A method for dynamic perception of mine power disaster information aims to conduct real-time monitoring and dynamic analysis of potential power disaster information in mines by comprehensively applying a variety of advanced sensing technologies and data analysis methods. This method can predict disaster risks in advance through dynamic perception and analysis of underground environmental parameters (such as temperature, humidity, gas concentration, etc.), thereby providing a scientific basis for taking timely and effective disaster prevention measures. However, this method faces multiple challenges in practical applications. First, the underground environment is complex and changeable, and it is difficult to use the real-time data obtained by sensors to accurately control and warn of disasters. Secondly, sensors from different sources will generate a large amount of data, and the data fusion mechanism must be optimized to reduce information one-sidedness and redundancy. In addition, for the identification of early weak signals, appropriate thresholds need to be set to avoid misjudgment and neglect. Under complex geological conditions, it is also necessary to ensure the stability of signal transmission and prevent information delays caused by communication interruptions. Finally, in response to the rapid changes in the environment, it is necessary to flexibly adjust the update frequency of the dynamic risk assessment model to overcome the problem of delayed assessment results. By solving these problems in a targeted manner, the performance and reliability of the dynamic perception system of mine power disaster information can be further improved. Summary of the invention

[0003] In order to solve the problems raised by the above background technology, the present application provides a method for dynamic perception of mine power disaster information.

[0004] The present application provides a method for dynamically sensing mine power disaster information, which adopts the following technical solutions: A method for dynamically sensing mine power disaster information, comprising: S101, collect environmental parameter data monitored in real time by multiple sensors underground, and perform preliminary processing through adaptive control algorithms to improve the accuracy of disaster warning; S102, integrating and processing the preliminarily processed multi-source sensor data based on a data fusion mechanism, and adjusting fusion parameters to reduce information partiality and redundancy; S103, applying a weak signal recognition algorithm to the result after data fusion, and dynamically adjusting the recognition threshold, so as to accurately capture early pre-disaster signs; S104. Based on the dynamic risk assessment model, the update frequency of the model is adjusted, and the stability of signal transmission is ensured under complex geological conditions to avoid information delay problems.

[0005] Preferably, the method comprises the following steps: Control underground environmental parameters, including temperature, humidity and gas concentration, based on real-time monitoring data streams; The formula is used to determine whether the current sensor data conforms to the expected pattern. The calculation method is: if P = T * (H + G) is greater than the preset threshold TH (where P is the comprehensive evaluation value, T is the temperature change, H is the humidity change, G is the gas concentration change, and TH is the warning threshold); Comprehensively integrate and filter information from multiple types of sensors based on data fusion mechanisms; Regular updates are used to dynamically assess risk models to adapt to the speed at which the downhole environment changes.

[0006] Preferably, the method further comprises the following steps: Achieve multi-dimensional analysis based on information collected by different sensors from multiple sources; The weighted average method is applied to combine all the collected related indicators, that is, W = ∑(Xi / Si), where W represents the final fusion weight result, Xi refers to the specific value output by a single sensor, and Si is the standard deviation of the measurement error of each sensor, thereby ensuring the integrity of information while reducing redundancy; On this basis, a more accurate and reliable rule base for identifying weak early signals was established; Perform performance monitoring tasks on key communication paths to ensure the security and reliability of communication links in complex underground environments.

[0007] Preferably, further actions taken based on the above are: Set reasonable initial alarm thresholds based on historical data accumulated in the early stage and actual operation conditions; By introducing an adaptive learning algorithm to optimize the pre-disaster weak signal recognition strategy, and setting conditional judgment, if ΔR = Rcurrent Rprior > R0 (ΔR is the relative rate of change difference, Rcurrent represents the physical quantity or signal strength measured at the current moment, Rprior is the value corresponding to the previous moment, and R0 is the reference increment benchmark), the warning action is triggered to avoid missing possible disaster signs; Use anti-interference technology to improve the data exchange efficiency between devices under special geological conditions; The automated system can intelligently decide when it is necessary to accelerate the frequency of iterative dynamic risk assessment cycles.

[0008] Preferably, the following specific embodiments are included to further define the characteristics of the project.name system: Build a distributed data processing framework based on the existing architecture to support large-scale node collaboration; Rely on advanced edge computing capabilities to quickly analyze information packets collected on-site; Establish a dedicated security module to encrypt and protect sensitive messages in transit from malicious attacks; Make real-time adjustments to the parameters of the dynamic risk assessment model, such as recalculating the evaluation weight when Vr < α * Ve (Vr represents the actual observation rate, α is the adjustment coefficient, and Ve predicts the frequency of event occurrence).

[0009] Preferably, a more specific requirement is made for the above-mentioned method: Continuously improve and perfect the core algorithm of this patent and its supporting facilities based on the latest research results and technological development; Deploy specialized instruments with automatic calibration capabilities to ensure that the series of readings obtained are accurate; It enables effective tracking and early internal response to any abnormal activities; A feedback loop mechanism is introduced to verify the prediction accuracy in time, for example, verify the prediction model after each iteration, and use Mse = (∑di^2) / n (Mse is the mean square error, di is the i-th prediction error, and n is the total number of samples) as the error evaluation criterion.

[0010] Preferably, the requirements at a higher level also include the following four considerations: A more complete mine hazard identification system was established based on deep learning algorithms; Developed an intelligent operating platform to make the entire operation process convenient, safe and reliable; Focusing on long-term planning for the future, a series of long-term stable operation and maintenance systems have been formulated; When C(T) = K1 * S1(T)+K2*S2(T)>CL (C is the total cost function, T is the operating cost curve under the influence of time factors, K1 is the fixed cost coefficient, K2 is the variable cost ratio; S1 is the fixed fee, S2 is priced according to workload, and CL is the cost control line), the system will give corresponding suggestions to reduce cost expenditure and optimize resource allocation.

[0011] In order to fully meet the actual needs and exceed expectations, we emphasize the following on the basis of the above: Guidelines based on the research results of previous accident cases are incorporated into the design of new technical solutions; Use renewable energy to supply the electricity required for the entire project as much as possible to reduce carbon emissions footprint; The physical and mental health of the workers is taken into consideration, and the design is more humane, which improves the comfort and safety level of the work. Based on local specific conditions, we actively seek a path for technological upgrading that suits national conditions and development trends.

[0012] In summary, the present application includes at least one of the following beneficial technical effects: This method of dynamic perception of mine power disaster information improves the accuracy of disaster warnings, can more timely and accurately detect potential disaster hazards in the changing underground environment, reduce false alarms and missed alarms, provide more reliable safety protection for underground workers, and reduce the possibility and degree of harm of disasters.

[0013] This method of dynamic perception of mine power disaster information solves the problem of one-sided information, making the underground information obtained more comprehensive and complete, and helping to understand the actual situation underground more accurately; eliminating information redundancy can improve data processing efficiency, reduce unnecessary waste of data storage and transmission resources, reduce system burden, and make subsequent analysis and decision-making more efficient and accurate.

[0014] This dynamic perception method of mine power disaster information can avoid early signs from being ignored and can capture subtle changes and weak signals before underground disasters occur, buying more time for taking preventive measures in advance; reducing misjudgments, preventing unnecessary panic or wrong decisions caused by misjudgments, and ensuring the normal progress of underground operations.

[0015] This method of dynamic perception of mine power disaster information ensures smooth communication, solves the problem of information delay, and enables real-time data and information underground to be transmitted to the monitoring center and relevant personnel in a timely and accurate manner, facilitating timely decision-making and response measures, improving emergency response speed, and enhancing the reliability and stability of the entire underground safety monitoring system.

[0016] This method of dynamic perception of mine power disaster information can effectively respond to sudden environmental changes, enable the risk assessment model to timely reflect the dynamic changes of the underground environment, avoid assessment lags, and provide more real-time and accurate risk assessment results for underground operations. It is helpful to formulate corresponding preventive measures in advance, reduce the risk of disasters caused by sudden environmental changes, and ensure the safety of underground workers and the smooth progress of production activities. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The present invention is a flow chart of a method for dynamically sensing mine power disaster information. DETAILED DESCRIPTION

[0018] Embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings.

[0019] In the description of this specification, the description with reference to the terms "certain embodiments", "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0020] The present application embodiment discloses a method for dynamically sensing mine power disaster information, referring to Figure 1 ,include: S101, collect environmental parameter data monitored in real time by multiple sensors underground, and perform preliminary processing through adaptive control algorithms to improve the accuracy of disaster warning; S102, integrating and processing the preliminarily processed multi-source sensor data based on a data fusion mechanism, and adjusting fusion parameters to reduce information partiality and redundancy; S103, applying a weak signal recognition algorithm to the result after data fusion, and dynamically adjusting the recognition threshold, so as to accurately capture early pre-disaster signs; S104. Based on the dynamic risk assessment model, the update frequency of the model is adjusted, and the stability of signal transmission is ensured under complex geological conditions to avoid information delay problems.

[0021] In order to improve the recognition of weak early symptoms before a disaster and avoid misjudgment, an adaptive dynamic adjustment scheme has been specially formulated to address this problem. It is used to set the boundary range of threshold values ​​to match the demand characteristics of actual working conditions in a specific period. The initial reference datum plane is determined in advance based on historical accident records and statistical laws, and the online feedback mechanism is used to continuously track the latest development trends and automatically update the critical limit interval. While ensuring sufficient sensitivity, it also avoids triggering the sound alarm too early to cause excessive response and waste of rescue resources. In addition, an intelligent prediction model is incorporated, so that even in the face of more complex disturbances, the true signs and symptoms can be identified in a very short time without being misled by too much irrelevant external noise, further enhancing the robustness of the forecast system.

[0022] In order to enhance the robustness and stability of signal transmission links under complex conditions, targeted improvements have been made to address the problems of traditional wired cables being easily damaged and interrupted, and radio electromagnetic waves being easily affected by shielding and difficult to maintain continuous connectivity. On the one hand, the industrial Internet of Things communication protocol with strong self-organizing network characteristics is actively adopted to build a direct interaction bridge channel between nodes covering all important locations. On the other hand, a device with a two-way power amplification function is equipped to compensate for the loss of part of the power intensity in the fading channel so as to extend the maximum visible range. A dedicated redundant backup routing structure is then established to ensure that once a trunk line fails, the backup path is immediately switched to enable without causing the key intelligence flow to lose the timely transmission performance requirements. In this way, the requirements of stable and efficient two-way communication tasks in harsh working scenarios are met, ensuring that the warning notification information is conveyed to the relevant personnel without obstruction in the first time, guiding the emergency evacuation action to be quickly launched and gaining precious escape time.

[0023] In terms of frequency control for rapid response adjustment to the changing trend of risk situation level that changes with actual conditions in a dynamic environment, an iterative upgrade version of risk management assessment platform architecture supported by an integrated fuzzy logic rule base under the framework of evidence theory is proposed. It can fully absorb the recently discovered research results and external industry dynamic information knowledge while also taking into account the evolution law of its own operating mode mechanism. It reviews and verifies the degree of coupling and the closeness of the interaction between the elements within each unit module from the bottom up at fixed periodic intervals, and then re-plans the weight distribution method. The final output meets the expected purpose and can better adapt to the existence of nonlinear mutation impact interference. Through this mechanism, the conclusion report after each regular refresh can always keep up with the cutting-edge level and synchronized follow-up pace, and the embarrassing situation that the established protective measures are delayed and unable to play a role due to the sudden emergence of unexpected unknown dangerous factors will not recur.

[0024] The present invention aims to construct a safety monitoring solution suitable for China's coal mines and other similar industry demand scenarios, integrating the above-mentioned multiple technological innovation breakthroughs, not only achieving technical feasibility, reliability and practicality, but also taking into account the broad potential for long-term development in the future. It can effectively respond to the various severe challenges under the current background of increasingly stringent domestic safety and environmental protection supervision, protect the health and life and property safety rights and interests of the majority of practitioners from the risk of damage and infringement, and at the same time promote sustainable scientific development in related fields.

[0025] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for dynamic perception of mine power disaster information, characterized in that: include: S101, collect environmental parameter data monitored in real time by multiple sensors underground, and perform preliminary processing through adaptive control algorithms to improve the accuracy of disaster warning; S102, integrating and processing the preliminarily processed multi-source sensor data based on a data fusion mechanism, and adjusting fusion parameters to reduce information partiality and redundancy; S103, applying a weak signal recognition algorithm to the result after data fusion, and dynamically adjusting the recognition threshold, so as to accurately capture early pre-disaster signs; S104. Based on the dynamic risk assessment model, the update frequency of the model is adjusted, and the stability of signal transmission is ensured under complex geological conditions to avoid information delay problems.

2. A method for dynamic perception of mine power disaster information according to claim 1, characterized in that: The following steps are involved: Control underground environmental parameters, including temperature, humidity and gas concentration, based on real-time monitoring data streams; The formula is used to determine whether the current sensor data conforms to the expected pattern. The calculation method is: if P = T * (H +G) is greater than the preset threshold TH (where P is the comprehensive evaluation value, T is the temperature change, H is the humidity change, G is the gas concentration change, and TH is the warning threshold); Comprehensively integrate and filter information from multiple types of sensors based on data fusion mechanisms; Regular updates are used to dynamically assess risk models to adapt to the speed at which the downhole environment changes.

3. A method for dynamic perception of mine power disaster information according to claim 1, characterized in that: The specific steps include the following further refinements: Achieve multi-dimensional analysis based on information collected by different sensors from multiple sources; The weighted average method is applied to combine all the collected related indicators, that is, W = ∑(Xi / Si), where W represents the final fusion weight result, Xi refers to the specific value output by a single sensor, and Si is the standard deviation of the measurement error of each sensor, thereby ensuring the integrity of information while reducing redundancy; On this basis, a more accurate and reliable rule base for identifying weak early signals was established; Perform performance monitoring tasks on key communication paths to ensure the security and reliability of communication links in complex underground environments.

4. A method for dynamic perception of mine power disaster information according to claim 1, characterized in that: Specifically, further actions taken based on the above include: Set reasonable initial alarm thresholds based on historical data accumulated in the early stage and actual operation conditions; By introducing an adaptive learning algorithm to optimize the pre-disaster weak signal recognition strategy, and setting conditional judgment, if ΔR = Rcurrent Rprior > R0 (ΔR is the relative rate of change difference, Rcurrent represents the physical quantity or signal strength measured at the current moment, Rprior is the value corresponding to the previous moment, and R0 is the reference increment benchmark), the warning action is triggered to avoid missing possible disaster signs; Use anti-interference technology to improve the data exchange efficiency between devices under special geological conditions; The automated system can intelligently decide when it is necessary to accelerate the frequency of iterative dynamic risk assessment cycles.

5. A method for dynamic perception of mine power disaster information according to claim 1, characterized in that: The following specific examples are included to further define the features of the project .name system: Build a distributed data processing framework based on the existing architecture to support large-scale node collaboration; Rely on advanced edge computing capabilities to quickly analyze information packets collected on-site; Establish a dedicated security module to encrypt and protect sensitive messages in transit from malicious attacks; Make real-time adjustments to the parameters of the dynamic risk assessment model, such as recalculating the evaluation weight when Vr < α * Ve (Vr represents the actual observation rate, α is the adjustment coefficient, and Ve predicts the frequency of event occurrence).

6. A method for dynamic perception of mine power disaster information according to claim 1, characterized in that: Once again, we would like to make more specific requirements for the methods mentioned above: Continuously improve and perfect the core algorithm of this patent and its supporting facilities based on the latest research results and technological development; Deploy specialized instruments with automatic calibration capabilities to ensure that the series of readings obtained are accurate; It enables effective tracking and early internal response to any abnormal activities; A feedback loop mechanism is introduced to verify the prediction accuracy in time, for example, verify the prediction model after each iteration, and use Mse = (∑di^2) / n (Mse is the mean square error, di is the i-th prediction error, and n is the total number of samples) as the error evaluation criterion.

7. A method for dynamic perception of mine power disaster information according to claim 1, characterized in that: The requirements at a higher level also include the following four considerations: A more complete mine hazard identification system was established based on deep learning algorithms; Developed an intelligent operating platform to make the entire operation process convenient, safe and reliable; Focusing on long-term planning for the future, a series of long-term stable operation and maintenance systems have been formulated; When C(T) = K1 * S1(T)+K2*S2(T)>CL (C is the total cost function, T is the operating cost curve under the influence of time factors, K1 is the fixed cost coefficient, K2 is the variable cost ratio; S1 is a fixed fee, S2 is priced according to workload, and CL is the cost control line. When the system determines the cost, it will give corresponding suggestions to reduce cost expenditure and optimize resource allocation.

8. A method for dynamic perception of mine power disaster information according to claim 1, characterized in that: In order to fully meet actual needs and exceed expectations, we emphasize the following on the basis of the above: Guidelines based on the research results of previous accident cases are incorporated into the design of new technical solutions; Use renewable energy to supply the electricity required for the entire project as much as possible to reduce carbon emissions footprint; The physical and mental health of the workers is taken into consideration, and the design is more humane, which improves the comfort and safety level of the work. Based on local specific conditions, we actively seek a path for technological upgrading that suits national conditions and development trends.

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