Safety monitoring method and system based on coal yard of thermal power plant

Abstract

The invention discloses a safety monitoring method and system based on a coal yard of a thermal power plant, and relates to the technical field of safety monitoring of the coal yard of the thermal power plant. Infrasonic wave sensors and optical fiber transmitting units are arranged around the coal yard, infrasonic wave and stress wave information is collected, and then the cross correlation coefficient of the stress wave event rate and infrasonic wave energy is calculated; judging whether the mechanical motion is strongly correlated with the thermal reaction or not, setting degradation and acceleration coefficients according to the mechanical motion and the thermal reaction, and constructing a mutual feedback model of a stress state index and a thermal stability index; the method comprises the following steps: firstly, calculating a model, then evaluating a risk early warning level according to a model calculation result, finally analyzing an early warning operation execution process, and through multi-physics field signal coupling analysis and dynamic mutual feedback modeling, realizing accurate early warning of risks of collapse, spontaneous combustion and the like of the coal yard, solving the defects of traditional single monitoring, improving timeliness and accuracy of potential safety hazard identification, and improving the safety hazard identification efficiency. And a scientific technical scheme is provided for safety management of the coal yard of the thermal power plant.

Description

Technical Field

[0001] The present invention relates to the technical field of safety monitoring of coal yards in thermal power plants, and in particular to a safety monitoring method and system based on coal yards in thermal power plants. Background Art

[0002] Coal yards in thermal power plants face safety risks such as collapse and spontaneous combustion. Traditional monitoring methods have limitations in multi-parameter coupling analysis. With technological development, more precise monitoring methods are needed. This safety monitoring method combines infrasound and stress wave monitoring to construct a mutual feedback model, providing a new path for coal yard safety monitoring and ensuring the safe operation of thermal power plants.

[0003] Existing technologies such as the invention patent application with publication number CN119916720A disclose an intelligent safety monitoring method and system for a coal yard of a thermal power plant. The method includes: performing multi-dimensional safety monitoring analysis based on infrared thermal images of coal piles, coal yard monitoring images, and environmental monitoring data, and determining the results of the multi-dimensional safety monitoring analysis. When the result of the multi-dimensional safety monitoring analysis is abnormal, emergency processing analysis is performed based on the abnormal data, emergency measures information is determined, and the emergency measures information is sent to the corresponding linkage equipment to control the linkage equipment to automatically execute emergency measures. In the process of safety monitoring of the coal yard of a thermal power plant, by integrating a variety of monitoring means and data resources, a multi-dimensional monitoring and analysis of the safety of the coal yard is realized, which solves the limitations of the single monitoring method in the relevant technology, and improves the efficiency of discovering and handling safety hazards, providing strong technical support for the safety management of the coal yard of a thermal power plant.

[0004] There are at least the following technical problems with the above scheme: 1. The above scheme lacks an in-depth monitoring and analysis mechanism for changes in the physical properties inside the coal yard. It only relies on infrared thermal images, monitoring images and environmental data. It is unable to deeply perceive the interaction between changes in stress distribution inside the coal body and thermal reactions, and it is difficult to discover potential risks of coupling between mechanical structure changes and thermal reactions. It is easy to miss the best early warning opportunity. At the same time, the above scheme does not elaborate on the scientific deployment basis and parameter setting of monitoring equipment. If the equipment deployment position and spacing are unreasonable, monitoring blind spots are likely to occur, resulting in the collected data being unable to fully reflect the coal yard conditions, affecting the reliability of multi-dimensional safety monitoring and analysis.

[0005] 2. The above scheme lacks quantitative analysis methods for the correlation between mechanical movement and thermal reaction in the coal yard. It only analyzes factors such as infrared thermal images, personnel and equipment behavior, and environmental data in isolation, without considering the inherent connection and mutual influence between these factors. It is difficult to accurately assess the safety risk level of the coal yard. When faced with complex coupled risk scenarios, it is impossible to accurately judge the severity and development trend of the risk.

[0006] 3. The above scheme lacks the ability to dynamically adjust the parameters of the early warning mechanism and risk assessment model, and cannot adapt to changes in the coal yard environment. The fixed analysis model and early warning threshold are prone to false alarms or missed alarms when the coal yard environment and coal quality characteristics change. At the same time, the above scheme has not yet mathematically modeled and dynamically simulated the evolution process of coal yard safety risks. It only processes current status data, making it difficult to predict the direction and speed of risk development, which is not conducive to the formulation of forward-looking safety management strategies and emergency plans. Summary of the Invention

[0007] The purpose of the present invention is to provide a safety monitoring method and system based on a coal yard of a thermal power plant, which solves the problems existing in the background technology.

[0008] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a safety monitoring method based on a coal yard of a thermal power plant, including: S1, hardware deployment: deploying monitoring equipment at a set distance around the designated coal yard of a thermal power plant, and collecting the corresponding infrasound wave information and stress wave information inside the coal yard of the designated thermal power plant within a set time window.

[0009] S2. Establishing a coupled feature space: Based on the corresponding infrasound and stress wave information within the coal yard of a specified thermal power plant within a set time window, the correlation coefficient between the stress wave event rate and the infrasound wave energy within the set time window is calculated to determine whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard.

[0010] S3. Two-variable dynamic early warning analysis: Based on the judgment result of whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard, the thermal degradation coefficient of the mechanical effect and the mechanical acceleration coefficient of the thermal effect are set, thereby constructing a feedback model of the stress state index and the thermal stability index.

[0011] S4. Risk warning level assessment: The stress state index and thermal stability index corresponding to the coal yard of the designated thermal power plant are calculated based on the mutual feedback model, and the corresponding risk warning level within the coal yard of the designated thermal power plant is assessed.

[0012] S5. Analysis of the execution process of early warning operations: Based on the corresponding risk warning levels in the coal yard of a designated thermal power plant, analyze the execution process of early warning operations corresponding to the risk warning levels.

[0013] In a second aspect, the present invention provides a safety monitoring system based on a coal yard of a thermal power plant, including: a hardware deployment module for deploying monitoring equipment at a set distance around a designated coal yard of a thermal power plant, and collecting corresponding infrasound wave information and stress wave information inside the designated coal yard of a thermal power plant within a set time window.

[0014] A coupled characteristic space module is established to calculate the correlation coefficient between the stress wave event rate and the infrasound wave energy within a set time window based on the corresponding infrasound wave information and stress wave information within the coal yard of a specified thermal power plant within a set time window, and then determine whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard.

[0015] The dual-variable dynamic early warning analysis module is used to set the thermal degradation coefficient of the mechanical effect and the mechanical acceleration coefficient of the thermal effect based on the judgment result of whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard, thereby constructing a feedback model between the stress state index and the thermal stability index.

[0016] The risk warning level assessment module is used to calculate the stress state index and thermal stability index corresponding to the coal yard of a specified thermal power plant based on the mutual feedback model, and to assess the corresponding risk warning level within the coal yard of the specified thermal power plant;

[0017] The early warning operation execution process analysis module is used to analyze the early warning operation execution process corresponding to the risk early warning level in the coal yard of a designated thermal power plant.

[0018] The beneficial effects of the present invention are: 1. The safety monitoring method and system based on the coal yard of a thermal power plant provided by the embodiment of the present invention, during the hardware deployment process, scientifically sets the deployment interval of the infrasound sensor and the optical fiber transmitting unit based on the propagation characteristics and frequency range of infrasound waves and stress waves, and strictly controls the spatial co-location error and the acquisition timestamp synchronization error, which is conducive to ensuring that the monitoring equipment can comprehensively and accurately collect infrasound information and stress wave information inside the coal yard, which not only helps to completely cover the coal yard area, but also helps to ensure that the two types of data are highly consistent in time and space, providing reliable and effective basic data for subsequent in-depth analysis, and avoiding data loss or deviation due to unreasonable equipment deployment.

[0019] 2. During the data acquisition process, the embodiment of the present invention collects infrasound signals and stress wave signals at specific frequencies respectively, and converts them into multi-dimensional quantifiable parameters such as infrasound wave energy value, average infrasound wave energy, number of stress wave events, and average stress wave event rate. This is conducive to comprehensively capturing the signal characteristics generated by thermal reactions and mechanical movements in the coal yard. Infrasound waves focus on reflecting low-frequency energy changes related to thermal reactions, while stress waves focus on high-frequency dynamic characteristics generated by mechanical movements. The simultaneous acquisition and processing of multi-dimensional characteristics can detect subtle changes in mechanical-thermal coupling within the coal yard earlier, perceive potential safety hazards in advance, and buy time for risk warnings.

[0020] 3. In the process of establishing the coupled characteristic space, the embodiment of the present invention calculates the correlation coefficient between the stress wave event rate and the infrasound wave energy within a set time window and compares it with a preset standard threshold. This is conducive to accurately judging whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard. It breaks the limitations of traditional independent analysis of mechanical movement and thermal reaction, reveals the co-evolution mechanism of the two, avoids misjudgment or missed judgment caused by single parameter anomalies, improves the ability to identify the real risks of the coal yard, and provides an accurate basis for the subsequent construction of early warning models.

[0021] 4. In the dual-variable dynamic early warning analysis process, the embodiment of the present invention dynamically sets the thermal degradation coefficient of the mechanical effect and the mechanical acceleration coefficient of the thermal effect based on the judgment result of the correlation between mechanical motion and thermal reaction, and constructs a mutual feedback model between the stress state index and the thermal stability index. This is conducive to achieving dynamic and accurate quantitative assessment of coal yard risks. The model fully considers the mutually reinforcing relationship between mechanical and thermal processes, and automatically adjusts the coefficient when a strong correlation is detected to reflect the accelerating effect of the coupling on the evolution of risks. It adapts to the complex physical and chemical changes within the coal yard, avoids the lag of traditional single indicator calculations, and realizes forward-looking assessment of complex risks such as collapse and spontaneous combustion.

[0022] 5. In the risk warning level assessment process, the embodiment of the present invention jointly solves the stress state index and the thermal stability index based on the mutual feedback model, and combines them with specific collapse thresholds and spontaneous combustion thresholds. The cross-warning response is initiated only when both conditions are met simultaneously. This is conducive to improving the accuracy and reliability of risk warnings, avoiding false alarms caused by warnings triggered by a single indicator, and ensuring that the issued warnings truly reflect the actual risks in the coal yard, allowing staff to more accurately judge the risk status and take effective response measures.

[0023] 6. During the execution process of the warning operation, the embodiment of the present invention queries the corresponding warning operation according to the risk warning level, and dynamically adjusts the execution time of the warning operation based on the comparison result of the mutual feedback risk factor and the preset threshold. This is beneficial to improving the flexibility and effectiveness of emergency response, shortening the execution time under high coupling risk conditions, and giving priority to controlling key risk points to prevent accidents from expanding. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 Schematic diagram of the implementation steps of the present invention.

[0026] Figure 2 This is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0028] See also Figure 1 As shown, the present invention provides a safety monitoring method based on a coal yard of a thermal power plant, which includes: S1, hardware deployment: deploying monitoring equipment at a set distance around the designated coal yard of the thermal power plant, and collecting the corresponding infrasound wave information and stress wave information inside the designated coal yard of the thermal power plant within a set time window.

[0029] In a specific embodiment, the monitoring equipment is deployed at a set distance around the coal yard of a designated thermal power plant. The specific process is as follows: the monitoring equipment includes an infrasound sensor and an optical fiber transmitting unit, and the frequency range of the infrasound signal is obtained. The maximum value of the frequency range is recorded as f max , the deployment interval of the infrasound sensors deployed at a set distance around the coal yard of a designated thermal power plant is set to L meters, where L satisfies v is the propagation velocity of infrasound in the coal yard environment of a specified thermal power plant.

[0030] The propagation velocity v′ and frequency range of stress waves in coal bodies are obtained through experimental measurements, rock mechanics theory derivation and industrial engineering practice. The minimum value of the stress wave frequency range is recorded as f min , calculated by the wavelength formula: Obtain the stress wave wavelength λ, and set the deployment interval of the optical fiber transmission units deployed at a set distance around the coal yard of the designated thermal power plant to d meters, where d satisfies

[0031] Based on the deployment interval of the infrasound sensor and the optical fiber transmitting unit, during the deployment process of the infrasound sensor and the optical fiber transmitting unit, the deployment positions of the infrasound sensor and the optical fiber transmitting unit must meet the spatial co-location error less than or equal to the set a meter, and the acquisition time stamp synchronization error of the infrasound sensor and the optical fiber transmitting unit Where Δt represents the acquisition timestamp synchronization error, f′ min Expressed as the minimum value of the frequency range in which the infrasound signal is effectively monitored.

[0032] It should be noted that by calibrating the frequency response characteristics of the infrasound sensor in the laboratory, such as inputting a standard infrasound signal from 1 Hz to 200 Hz and measuring the output sensitivity, combined with the actual environmental noise spectrum analysis of the coal yard, such as using fast Fourier transform to identify the dominant frequency of the background noise, it is determined that the signal-to-noise ratio of the sensor in the range of 3 Hz to 60 Hz is ≥ 3 dB, thus demarcating this frequency range as the effective monitoring range. max When the value is 10 Hz and v is 340 meters per second, L≤17 meters. However, in practical applications, considering the deployment cost of infrasound sensors, the deployment interval L can be set to 15 meters.

[0033] It should also be noted that the spatial co-location error refers to the distance deviation between the actual deployment position of the infrasonic sensor and the optical fiber transmitting unit and the target monitoring point, which must be ≤a meters. For example, if a is 0.5 meters, it ensures that the signals collected by the two come from the same coal body microelement. For example, if the distance difference between the two and a certain spontaneous combustion point in the coal pile exceeds 0.5 meters, the signals will be mistakenly judged to come from different locations. The acquisition timestamp synchronization error refers to the time tag difference of the recorded data of the two, which must meet the system requirements, such as ≤5 seconds, to avoid the failure of the mutual feedback analysis due to time misalignment of the signals. For example, if the stress wave is collected at 12:00:00 and the infrasound wave is collected at 12:00:06, the mutual feedback events that occurred simultaneously are mistakenly judged as independent events.

[0034] In a specific embodiment, the infrasound wave information and stress wave information corresponding to the coal yard of a specified thermal power plant are collected within a set time window. The specific process is as follows: the infrasound wave information includes the infrasound wave energy value and the average value of the infrasound wave energy, and the stress wave information includes the number of stress wave events and the average value of the stress wave event rate. Each collection time point is set within the set time window, and the optical fiber transmitting unit collects the stress wave signal in the coal yard of the specified thermal power plant at each collection time point at a frequency of 10 Hz to 100 Hz. When the collected stress wave signal meets the preset stress wave characteristic signal, it is determined to be a stress wave event and counted, thereby obtaining the number of stress wave events collected at the i-th collection time point within the set time window, which is recorded as C i , i is the number corresponding to each acquisition time point, i = 1, 2, ..., N, N is the total number of acquisition time points in the set time window, and the value of N is a positive integer. The number of stress wave events corresponding to each acquisition time point in the set time window is accumulated, and the accumulated result is divided by N. The result is the average value of the stress wave event rate

[0035] The infrasound sensor synchronously collects infrasound signals at a frequency of 0.1 Hz to 10 Hz within a set time window and converts the infrasound signals into infrasound energy values, thereby obtaining the infrasound energy value collected at the i-th collection time point within the set time window, which is recorded as E i, and then the average value of the infrasound energy collected at i collection time points within the set time window is obtained by averaging, which is

[0036] It should be noted that "synchronous acquisition" means that the infrasound sensor continuously samples the 0.1 Hz to 10 Hz frequency band signal within a set time window according to a unified time base, such as 10 times per second, to ensure that the data timing at each time point is consistent. Assuming that the set time window is 1 second, the infrasound time domain signal collected at a certain moment is a sequence of discrete sample points. When the sampling frequency is 100 Hz, the conversion is performed by first squaring each sample value, and then accumulating the 100 square values ​​and dividing them by the number of sampling points to obtain the time domain energy value within that 1 second.

[0037] It should also be noted that the calculation process of the average value of the infrasound energy collected at i collection time points within the set time window is the same as The calculation process is the same as that of , so I will not go into details here.

[0038] During the data acquisition process, the embodiment of the present invention collects infrasound signals and stress wave signals at specific frequencies respectively, and converts them into multi-dimensional quantifiable parameters such as infrasound wave energy value, infrasound wave energy average value, number of stress wave events, and stress wave event rate average value. This is conducive to comprehensively capturing the signal characteristics generated by thermal reactions and mechanical movements in the coal yard. Infrasound waves focus on reflecting low-frequency energy changes related to thermal reactions, and stress waves focus on high-frequency dynamic characteristics generated by mechanical movements. Multi-dimensional characteristics are collected and processed simultaneously, which can detect subtle changes in mechanical-thermal coupling effects inside the coal yard earlier, perceive potential safety hazards in advance, and buy time for risk warnings.

[0039] S2. Establishing a coupled feature space: Based on the corresponding infrasound and stress wave information within the coal yard of a specified thermal power plant within a set time window, the correlation coefficient between the stress wave event rate and the infrasound wave energy within the set time window is calculated to determine whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard.

[0040] In a specific embodiment, the calculation of the correlation coefficient between the stress wave event rate and the infrasound wave energy within the set time window is performed as follows: by coupling formula:

[0041] The correlation coefficient α(T) between the stress wave event rate and the infrasound wave energy within the set time window is obtained, where T in α(T) represents the number corresponding to the set time window.

[0042] In a specific embodiment, the process of determining whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard is as follows: a preset standard threshold value for the strong correlation between mechanical movement and thermal reaction is queried from a database, and α(T) is compared with the preset standard threshold value for the strong correlation between mechanical movement and thermal reaction. If α(T) is greater than or equal to the preset standard threshold value for the strong correlation between mechanical movement and thermal reaction, it is determined to be a mechanical-thermal coupling event, indicating that there is a strong correlation between mechanical movement and thermal reaction in the coal yard. If α(T) is less than the preset standard threshold value for the strong correlation between mechanical movement and thermal reaction, it is determined not to be a mechanical-thermal coupling event, indicating that there is no strong correlation between mechanical movement and thermal reaction in the coal yard.

[0043] It should be noted that the pre-set standard threshold for the strong correlation between mechanical motion and thermal reaction is used as the basis for evaluating whether there is a strong correlation between mechanical motion and thermal reaction in the coal yard. The setting process of the standard threshold for the strong correlation between mechanical motion and thermal reaction is consistent with the threshold calibration method based on signal correlation in the existing technology, that is, through the correlation distribution statistics of mutual feedback events and non-mutual feedback events in a large amount of historical data, the intersection of the probability density functions of the two types of events is taken as the threshold, so it will not be elaborated here.

[0044] In the process of establishing the coupled characteristic space, the embodiment of the present invention calculates the correlation coefficient between the stress wave event rate and the infrasound wave energy within a set time window and compares it with a preset standard threshold. This is conducive to accurately judging whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard, breaking the limitations of traditional independent analysis of mechanical movement and thermal reaction, revealing the coordinated evolution mechanism of the two, avoiding misjudgment or missed judgment caused by single parameter anomalies, improving the ability to identify the real risks of the coal yard, and providing an accurate basis for the subsequent construction of early warning models.

[0045] S3. Two-variable dynamic early warning analysis: Based on the judgment result of whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard, the thermal degradation coefficient of the mechanical effect and the mechanical acceleration coefficient of the thermal effect are set, thereby constructing a feedback model of the stress state index and the thermal stability index.

[0046] In a specific embodiment, the setting of the thermal degradation coefficient of the machine and the mechanical acceleration coefficient of the heat is as follows: the preset default values ​​of the thermal degradation coefficient of the machine and the mechanical acceleration coefficient of the heat are queried from the database; when there is a strong correlation between the mechanical movement and the thermal reaction in the coal yard, the default value of the thermal degradation coefficient of the machine is adjusted according to the preset thermal increase amplitude, and the default value of the mechanical acceleration coefficient of the heat is adjusted according to the preset mechanical increase amplitude; if there is no strong correlation between the mechanical movement and the thermal reaction in the coal yard, the preset default values ​​of the thermal degradation coefficient of the machine and the mechanical acceleration coefficient of the heat are not adjusted.

[0047] It should be noted that the default values ​​of the thermal degradation coefficient k for mechanical effects and the mechanical acceleration coefficient k′ for thermal effects are obtained through laboratory simulation and reverse deduction of historical accident data. For example, when a coal sample is heated to 50°C in the laboratory, its compressive strength is measured to decrease by 15%. Therefore, k is determined to be 0.15, indicating that the degree of stress degradation is 15% for every unit increase in temperature. By reviewing a coal yard collapse accident, it was found that the oxidation rate of the coal pile increased by 20% after the collapse. Therefore, k′ is set to 0.2, indicating that the oxidation is accelerated by 20% for every unit increase in mechanical disturbance.

[0048] It should also be noted that the default value of the thermal-to-mechanical degradation coefficient adjusted according to the preset thermal-to-mechanical enhancement range means that if the default value of the thermal-to-mechanical degradation coefficient is 0.15 and the preset thermal-to-mechanical enhancement range is 25%, then the default value of the adjusted thermal-to-mechanical degradation coefficient is 0.1875.

[0049] In a specific embodiment, the mutual feedback model of the stress state index and the thermal stability index is constructed as follows: the mutual feedback model is constructed based on the default values ​​of the thermal-to-mechanical degradation coefficient and the default values ​​of the mechanical-to-heat acceleration coefficient. The mutual feedback model expression is as follows:

[0050] in They are respectively represented by the derivative of the stress state index C with respect to the set time window T and the derivative of the thermal stability index E with respect to the set time window T within the set time window T. C and E represent the stress state index and the thermal stability index, k and k′ represent the default values ​​of the set thermal-mechanical degradation coefficient and the default value of the mechanical-thermal acceleration coefficient, respectively. μ and μ′ represent the mechanical self-restraint coefficient and the oxidation reaction rate coefficient determined by experiments, respectively. C′ and E′ represent the critical stress threshold of coal structure destruction in the coal yard of a specified thermal power plant and the oxidation equilibrium temperature corresponding to the thermal state after the coal body is oxidized and stabilized, respectively. C″ and E″ represent the set environmental disturbance influence factor and the ambient temperature disturbance influence factor, respectively.

[0051] It should be noted that when experimentally determining the mechanical self-constraint coefficient and the oxidation reaction rate coefficient, it is necessary to first construct a coal body simulation environment, apply different stresses to the coal sample and monitor the deformation. When the stress approaches the critical value of collapse, the negative correlation between the change in internal porosity of the coal body and the stress growth rate is recorded, and the mechanical self-constraint coefficient is obtained through nonlinear fitting. For example, when the stress of a certain coal sample reaches 0.8 MPa, the self-constraint effect reduces the stress growth rate by 20%, corresponding to μ equal to 0.08. The oxidation reaction rate coefficient is obtained by simulating the oxidation process of the coal pile in a temperature-controlled box, measuring the oxygen consumption rate at different temperatures such as 25 to 60°C, and using the Arrhenius equation to fit the correlation parameters between the reaction rate and the temperature difference. For example, for every 1°C deviation of the temperature from the oxidation equilibrium temperature, the oxidation rate changes by 5%, corresponding to μ′ of 0.05.

[0052] It should also be noted that axial stress is applied to the coal sample through a triaxial compression test, and the strain-stress curve is recorded. When the curve shows a steep stress drop, such as a sudden change in the slope exceeding 30%, the corresponding stress value is the critical stress threshold. For example, a coal sample shows macro cracks at 0.75 MPa, and the critical stress is set to 0.7 MPa. The oxidation equilibrium temperature is determined by a constant-temperature oxidation experiment. The coal sample is placed in a closed container and heated. When the oxygen consumption rate and the carbon monoxide generation rate reach dynamic equilibrium, such as a change of less than 5% for 24 consecutive hours, the temperature is the equilibrium temperature. For example, the oxidation heat generation and heat dissipation of lignite are balanced at 35°C, and the equilibrium temperature is set to 35°C.

[0053] It should also be noted that the setting process of the environmental disturbance influence factor and the environmental temperature disturbance influence factor is as follows: high-frequency noise data of the environmental vibration sensor in the coal yard of a specified thermal power plant within one year is collected, and the standard deviation of the stress wave fluctuation amplitude is calculated using the standard deviation calculation formula. After confirming that it conforms to the Gaussian distribution through a normality test, such as the Shapiro-Wilk test, 0.02 is taken as the value of the environmental disturbance influence factor. For example, if the daily noise fluctuation standard deviation of a certain sensor is between 0.018 and 0.022, the average value is 0.02. The environmental temperature disturbance influence factor is set to 0.015. The minute-level data from the coal yard temperature sensor is used. After removing the trend item, the standard deviation of random fluctuations is calculated. For example, the fluctuation standard deviation of the temperature sensor in a certain area during non-abnormal periods is stable at around 0.015°C. The standard deviation calculation formula is the square root of the arithmetic mean of the squares of the deviations of the sample data from its mean. I will not go into details here.

[0054] In the dual-variable dynamic early warning analysis process, the embodiment of the present invention dynamically sets the thermal degradation coefficient of the mechanical effect and the mechanical acceleration coefficient of the heat effect based on the judgment result of the correlation between mechanical motion and thermal reaction, and constructs a mutual feedback model of the stress state index and the thermal stability index, which is conducive to realizing dynamic and accurate quantitative assessment of coal yard risks. The model fully considers the mutually reinforcing relationship between mechanical and thermal processes, and automatically adjusts the coefficient when a strong correlation is detected to reflect the accelerating effect of the coupling on the risk evolution, adapt to the complex physical and chemical changes inside the coal yard, avoid the lag of traditional single indicator calculation, and realize forward-looking assessment of complex risks such as collapse and spontaneous combustion.

[0055] S4. Risk warning level assessment: The stress state index and thermal stability index corresponding to the coal yard of the designated thermal power plant are calculated based on the mutual feedback model, and the corresponding risk warning level within the coal yard of the designated thermal power plant is assessed.

[0056] In a specific embodiment, the evaluation of the corresponding risk warning level in the coal yard of a designated thermal power plant is carried out as follows: according to the mutual feedback model expression, the stress state index C and the thermal stability index E are solved simultaneously. Based on the conclusion that there is a strong correlation between mechanical movement and thermal reaction in the coal yard, the collapse threshold and the spontaneous combustion threshold corresponding to the strong correlation between mechanical movement and thermal reaction in the coal yard of the designated thermal power plant are queried from the database. Only when the stress state index C is greater than or equal to the collapse threshold and the thermal stability index E is greater than or equal to the spontaneous combustion threshold, the cross warning response is initiated, and the risk warning level is obtained.

[0057] It should be noted that according to the mutual feedback model expression, the specific process of solving the stress state index C and the thermal stability index E is as follows: first, based on the initial data collected by the sensor in real time, such as stress wave energy and temperature gradient, C(0) and E(0) are determined, and the fourth-order Runge-Kutta method is used to numerically iterate the differential equations, and the time step of each step is calculated with a time step of 10 seconds. and The thermal degradation term k*E and the mechanical acceleration term k′*C form a bidirectional coupling. At the same time, the environmental disturbance influencing factor and the ambient temperature disturbance influencing factor are introduced to simulate the environmental disturbance. The calculated results are corrected by fusing the measured data through the extended Kalman filter until the C and E values ​​at the current moment are obtained.

[0058] It should also be noted that the collapse threshold and spontaneous combustion threshold corresponding to the presence of a strong correlation between mechanical movement and thermal reaction in the coal yard of a designated thermal power plant are used as the basis for evaluating whether to initiate a cross-warning response. The setting process of the collapse threshold and spontaneous combustion threshold corresponding to the presence of a strong correlation between mechanical movement and thermal reaction in the coal yard of a designated thermal power plant is the same as the setting process of the standard threshold corresponding to the strong correlation between mechanical movement and thermal reaction, and will not be elaborated on here.

[0059] In the risk warning level assessment process, the embodiment of the present invention jointly solves the stress state index and the thermal stability index according to the mutual feedback model, and combines them with specific collapse thresholds and spontaneous combustion thresholds. The cross-warning response is initiated only when both conditions are met at the same time. This is beneficial to improving the accuracy and reliability of risk warnings, avoiding false alarms caused by warnings triggered by a single indicator, ensuring that the issued warnings truly reflect the actual risks in the coal yard, and allowing staff to more accurately judge the risk status and take effective response measures.

[0060] S5. Analysis of the execution process of early warning operations: Based on the corresponding risk warning levels in the coal yard of a designated thermal power plant, analyze the execution process of early warning operations corresponding to the risk warning levels.

[0061] In a specific embodiment, the analysis of risk warning level corresponds to the warning operation execution process, the specific process is as follows: according to the corresponding risk warning level in the coal yard of the designated thermal power plant Query the corresponding risk warning level in the coal yard of a specified thermal power plant from the database: The early warning operation is to calculate the corresponding mutual feedback risk factor in the coal yard of the specified thermal power plant. When the mutual feedback risk factor is greater than or equal to the preset mutual feedback risk factor threshold, the risk warning level is set to The risk status is determined to be a risk coupling state, and the execution time of the warning operation is shortened to 50% of the original set execution time. Otherwise, the warning operation is executed according to the original set execution time.

[0062] It should be noted that the specific calculation process of the corresponding mutual feedback risk factor in the coal yard of a specified thermal power plant is as follows: Where β represents the corresponding mutual feedback risk factor in the coal yard of a specified thermal power plant. The stress state index and thermal stability index are dimensionless indices that characterize the system state. The value range is set to [0, 1]. Therefore, E max and C max The value of is 1.

[0063] During the execution process of the warning operation, the embodiment of the present invention queries the corresponding warning operation according to the risk warning level, and dynamically adjusts the execution time of the warning operation based on the comparison result of the mutual feedback risk factor and the preset threshold. This is beneficial to improving the flexibility and effectiveness of emergency response, shortening the execution time under high coupling risk conditions, and giving priority to controlling key risk points to prevent accidents from expanding.

[0064] See also Figure 2 As shown in FIG, the safety monitoring system based on the coal yard of a thermal power plant includes the following modules: hardware deployment module, coupling feature space establishment module, dual-variable dynamic early warning analysis module, risk early warning level assessment module, early warning operation execution process analysis module and database.

[0065] The hardware deployment module is connected to the coupling feature space establishment module, the coupling feature space establishment module is respectively connected to the dual-variable dynamic warning analysis module and the database, the dual-variable dynamic warning analysis module is respectively connected to the risk warning level assessment module and the database, the risk warning level assessment module is respectively connected to the warning operation execution process analysis module and the database, and the warning operation execution process analysis module is connected to the database.

[0066] The hardware deployment module is used to deploy monitoring equipment at a set distance around the coal yard of a designated thermal power plant to collect infrasound and stress wave information corresponding to the coal yard of the designated thermal power plant within a set time window;

[0067] A coupled feature space module was established to calculate the correlation coefficient between the stress wave event rate and the infrasound wave energy within a set time window based on the corresponding infrasound and stress wave information within the coal yard of a specified thermal power plant. This was used to determine whether there was a strong correlation between mechanical motion and thermal reaction in the coal yard.

[0068] The dual-variable dynamic early warning analysis module is used to determine whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard. It sets the thermal degradation coefficient of the mechanical effect and the mechanical acceleration coefficient of the thermal effect, thereby constructing a feedback model between the stress state index and the thermal stability index.

[0069] The risk warning level assessment module is used to calculate the stress state index and thermal stability index corresponding to the coal yard of a specified thermal power plant based on the mutual feedback model, and to assess the corresponding risk warning level within the coal yard of the specified thermal power plant;

[0070] The early warning operation execution process analysis module is used to analyze the early warning operation execution process corresponding to the risk early warning level in the coal yard of a designated thermal power plant.

[0071] The database is used to store the preset standard thresholds for the strong correlation between mechanical movement and thermal reaction, the preset default values ​​for the thermal degradation coefficient of the mechanical effect and the default values ​​for the mechanical acceleration coefficient of the thermal effect, the corresponding collapse thresholds and spontaneous combustion thresholds when there is a strong correlation between mechanical movement and thermal reaction in the coal yard of a specified thermal power plant, and the corresponding risk warning levels in the coal yard of a specified thermal power plant. Early warning operation.

[0072] The safety monitoring method and system based on the coal yard of a thermal power plant provided by the embodiment of the present invention scientifically sets the deployment interval of the infrasound sensor and the optical fiber transmitting unit based on the propagation characteristics and frequency range of infrasound waves and stress waves during the hardware deployment process, and strictly controls the spatial co-location error and the acquisition timestamp synchronization error. This is conducive to ensuring that the monitoring equipment can comprehensively and accurately collect infrasound wave information and stress wave information inside the coal yard, which not only helps to completely cover the coal yard area, but also helps to ensure that the two types of data are highly consistent in time and space, providing reliable and effective basic data for subsequent in-depth analysis, and avoiding data loss or deviation due to unreasonable equipment deployment.

[0073] The above content is merely an example and explanation of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the scope of protection of the present invention.

Claims

1. A safety monitoring method based on a coal yard of a thermal power plant, characterized in that: include: S1. Hardware deployment: Deploy monitoring equipment at a set distance around the coal yard of a designated thermal power plant to collect infrasound and stress wave information corresponding to the coal yard of the designated thermal power plant within a set time window; S2. Establishing a coupled feature space: Based on the corresponding infrasound wave information and stress wave information within the coal yard of a specified thermal power plant within a set time window, the correlation coefficient between the stress wave event rate and the infrasound wave energy within the set time window is calculated to determine whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard; S3. Dual-variable dynamic early warning analysis: Based on the determination of whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard, the thermal degradation coefficient of the mechanical effect and the mechanical acceleration coefficient of the thermal effect are set, thereby constructing a feedback model between the stress state index and the thermal stability index; S4. Risk warning level assessment: Calculate the stress state index and thermal stability index corresponding to the coal yard of a designated thermal power plant based on the mutual feedback model, and assess the corresponding risk warning level within the coal yard of the designated thermal power plant; S5. Analysis of the execution process of early warning operations: Based on the corresponding risk warning levels in the coal yard of a designated thermal power plant, analyze the execution process of early warning operations corresponding to the risk warning levels.

2. The safety monitoring method based on the coal yard of a thermal power plant according to claim 1 is characterized in that: The monitoring equipment is deployed at a set distance around the coal yard of a designated thermal power plant. The specific process is as follows: The monitoring equipment includes an infrasound sensor and an optical fiber transmitting unit. The frequency range of the infrasound signal is effectively monitored, and the maximum value of the frequency range is recorded as f max , the deployment interval of the infrasound sensors deployed at a set distance around the coal yard of a designated thermal power plant is set to L meters, where L satisfies v is the propagation velocity of infrasound in the coal yard environment of a specified thermal power plant; The propagation velocity v′ and frequency range of stress waves in coal bodies are obtained through experimental measurements, rock mechanics theory derivation and industrial engineering practice. The minimum value of the stress wave frequency range is recorded as f min , calculated by the wavelength formula: Obtain the stress wave wavelength λ, and set the deployment interval of the optical fiber transmission units deployed at a set distance around the coal yard of the designated thermal power plant to d meters, where d satisfies Based on the deployment interval of the infrasound sensor and the optical fiber transmitting unit, during the deployment process of the infrasound sensor and the optical fiber transmitting unit, the deployment positions of the infrasound sensor and the optical fiber transmitting unit must meet the spatial co-location error less than or equal to the set a meter, and the acquisition time stamp synchronization error of the infrasound sensor and the optical fiber transmitting unit Where Δt represents the acquisition timestamp synchronization error, f′ min Expressed as the minimum value of the frequency range in which the infrasound signal is effectively monitored.

3. The safety monitoring method based on the coal yard of a thermal power plant according to claim 2 is characterized in that: The specific process of collecting the infrasound wave information and stress wave information corresponding to the coal yard of a specified thermal power plant within a set time window is as follows: The infrasound wave information includes the infrasound wave energy value and the average value of the infrasound wave energy. The stress wave information includes the number of stress wave events and the average value of the stress wave event rate. Each acquisition time point is set within the set time window. The optical fiber transmitting unit collects the stress wave signal in the coal yard of the specified thermal power plant at each acquisition time point at a frequency of 10 Hz to 100 Hz. When the collected stress wave signal meets the preset stress wave characteristic signal, it is determined to be a stress wave event and counted. Then, the number of stress wave events collected at the i-th acquisition time point within the set time window is obtained, which is recorded as C i , i is the number corresponding to each acquisition time point, i = 1, 2, ..., N, N is the total number of acquisition time points in the set time window, and the value of N is a positive integer. The number of stress wave events corresponding to each acquisition time point in the set time window is accumulated, and the accumulated result is divided by N. The result is the average value of the stress wave event rate The infrasound sensor synchronously collects infrasound signals at a frequency of 0.1 Hz to 10 Hz within a set time window and converts the infrasound signals into infrasound energy values, thereby obtaining the infrasound energy value collected at the i-th collection time point within the set time window, which is recorded as E i , and then the average value of the infrasound energy collected at i collection time points within the set time window is obtained by averaging, which is 4. The safety monitoring method based on the coal yard of a thermal power plant according to claim 3 is characterized in that: The specific process of calculating the correlation coefficient between the stress wave event rate and the infrasound wave energy within the set time window is as follows: Through the coupling formula: The correlation coefficient α(T) between the stress wave event rate and the infrasound wave energy within the set time window is obtained, where T in α(T) represents the number corresponding to the set time window.

5. The safety monitoring method based on the coal yard of a thermal power plant according to claim 4 is characterized in that: The specific process of judging whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard is as follows: The preset standard threshold for the strong correlation between mechanical motion and thermal reaction is queried from the database, and α(T) is compared with the preset standard threshold for the strong correlation between mechanical motion and thermal reaction. If α(T) is greater than or equal to the preset standard threshold for the strong correlation between mechanical motion and thermal reaction, it is determined to be a mechanical-thermal coupling event, indicating that there is a strong correlation between mechanical motion and thermal reaction in the coal yard. If α(T) is less than the preset standard threshold for the strong correlation between mechanical motion and thermal reaction, it is determined not to be a mechanical-thermal coupling event, indicating that there is no strong correlation between mechanical motion and thermal reaction in the coal yard.

6. The safety monitoring method based on the coal yard of a thermal power plant according to claim 5 is characterized in that: The specific process of setting the thermal degradation coefficient of the machine and the mechanical acceleration coefficient of the heat is as follows: The preset default values ​​of the thermal-to-mechanical degradation coefficient and the mechanical-to-heat acceleration coefficient are queried from the database. When there is a strong correlation between mechanical movement and thermal reaction in the coal yard, the default value of the thermal-to-mechanical degradation coefficient is adjusted according to the preset thermal-to-mechanical enhancement amplitude, and the default value of the mechanical-to-heat acceleration coefficient is adjusted according to the preset mechanical-to-heat enhancement amplitude. If there is no strong correlation between mechanical movement and thermal reaction in the coal yard, the preset default values ​​of the thermal-to-mechanical degradation coefficient and the mechanical-to-heat acceleration coefficient are not adjusted.

7. The safety monitoring method based on the coal yard of a thermal power plant according to claim 6 is characterized in that: The specific process of constructing the mutual feedback model of stress state index and thermal stability index is as follows: The mutual feedback model is constructed based on the default values ​​of the thermal-to-mechanical degradation coefficient and the mechanical-to-heat acceleration coefficient. The mutual feedback model expression is as follows: in They are respectively represented by the derivative of the stress state index C with respect to the set time window T and the derivative of the thermal stability index E with respect to the set time window T within the set time window T. C and E represent the stress state index and the thermal stability index, k and k′ represent the default values ​​of the set thermal-mechanical degradation coefficient and the default value of the mechanical-thermal acceleration coefficient, respectively. μ and μ′ represent the mechanical self-restraint coefficient and the oxidation reaction rate coefficient determined by experiments, respectively. C′ and E′ represent the critical stress threshold of coal structure destruction in the coal yard of a specified thermal power plant and the oxidation equilibrium temperature corresponding to the thermal state after the coal body is oxidized and stabilized, respectively. C″ and E″ represent the set environmental disturbance influence factor and the ambient temperature disturbance influence factor, respectively.

8. The safety monitoring method based on the coal yard of a thermal power plant according to claim 7 is characterized in that: The assessment specifies the corresponding risk warning level within the coal yard of a thermal power plant. The specific process is as follows: According to the mutual feedback model expression, the stress state index C and the thermal stability index E are solved simultaneously. Based on the conclusion that there is a strong correlation between mechanical movement and thermal reaction in the coal yard, the collapse threshold and spontaneous combustion threshold corresponding to the strong correlation between mechanical movement and thermal reaction in the coal yard of a specified thermal power plant are queried from the database. Only when the stress state index C is greater than or equal to the collapse threshold and the thermal stability index E is greater than or equal to the spontaneous combustion threshold, the cross warning response is initiated, and the risk warning level is obtained.

9. The safety monitoring method based on the coal yard of a thermal power plant according to claim 8 is characterized in that: The analysis risk warning level corresponds to the warning operation execution process, the specific process is as follows: According to the corresponding risk warning level in the coal yard of the designated thermal power plant Query the corresponding risk warning level in the coal yard of a specified thermal power plant from the database: The early warning operation is to calculate the corresponding mutual feedback risk factor in the coal yard of the specified thermal power plant. When the mutual feedback risk factor is greater than or equal to the preset mutual feedback risk factor threshold, the risk warning level is set to The risk status is determined to be a risk coupling state, and the execution time of the warning operation is shortened to 50% of the original set execution time. Otherwise, the warning operation is executed according to the original set execution time.

10. A safety monitoring system for a coal yard of a thermal power plant that implements the safety monitoring method for a coal yard of a thermal power plant according to any one of claims 1 to 9, characterized in that: Includes the following modules: The hardware deployment module is used to deploy monitoring equipment at a set distance around the coal yard of a designated thermal power plant to collect infrasound and stress wave information corresponding to the coal yard of the designated thermal power plant within a set time window; A coupled feature space module was established to calculate the correlation coefficient between the stress wave event rate and the infrasound wave energy within a set time window based on the corresponding infrasound and stress wave information within the coal yard of a specified thermal power plant. This was used to determine whether there was a strong correlation between mechanical motion and thermal reaction in the coal yard. The dual-variable dynamic early warning analysis module is used to determine whether there is a strong correlation between mechanical movement and thermal reaction in the coal yard. It sets the thermal degradation coefficient of the mechanical effect and the mechanical acceleration coefficient of the thermal effect, thereby constructing a feedback model between the stress state index and the thermal stability index. The risk warning level assessment module is used to calculate the stress state index and thermal stability index corresponding to the coal yard of a specified thermal power plant based on the mutual feedback model, and to assess the corresponding risk warning level within the coal yard of the specified thermal power plant; The early warning operation execution process analysis module is used to analyze the early warning operation execution process corresponding to the risk early warning level in the coal yard of a designated thermal power plant.

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