Prevention and control early warning method for spontaneous combustion of bituminous coal in silo

Abstract

The invention discloses a silo bituminous coal spontaneous combustion prevention and control early warning method, and relates to the field of silo bituminous coal spontaneous combustion early warning. A prevention and control risk level of bituminous coal in the silo is set by combining a loading coal quality report and detection data during ship unloading, and temperature, gas components and humidity information of different depth areas in the silo are monitored in real time by using multiple groups of sensing units. Based on the real-time data, real-time physical parameters such as compaction density, coal pile heat conductivity coefficient and coal oxygen reaction heat release rate are calculated, and then the critical temperature rise rate of each monitoring area is determined. And setting an early warning threshold according to the prevention and control risk grade and the critical temperature rise rate, and when the actual temperature rise rate of any monitoring area reaches or exceeds the early warning threshold, automatically matching and starting corresponding prevention and control measures by the system according to the temperature rise rate over-limit amplitude and the gas component data. According to the method for setting the early warning threshold value of each monitoring area in combination with the real-time physical parameters, accurate monitoring of each monitoring area is realized.

Description

Technical Field

[0001] This invention relates to the field of early warning of spontaneous combustion of bituminous coal in silos, and in particular to a method for preventing and warning of spontaneous combustion of bituminous coal in silos. Background Technology

[0002] Spontaneous combustion of coal is a phenomenon of heat accumulation caused by the complex oxidation reaction between coal and oxygen. In silo coal storage scenarios, due to the difficulty of heat dissipation in the enclosed space and the high concentration of coal piles, the risk of spontaneous combustion is significantly higher than in open-pit coal yards. Existing technologies still have many shortcomings in the prevention and control of spontaneous combustion of bituminous coal: First, traditional monitoring methods rely on manual inspections or single-point temperature sensors, which are difficult to detect abnormal temperature rises in the deep layers of coal piles in a timely manner, resulting in significant monitoring lag; Second, most post-warning measures mainly involve spraying flame retardants (such as halogenated hygroscopic agents and silicone-based gels), but such methods have side effects such as easy loss of retardants, corrosion of equipment, and increased coal ash content; Third, inventory management strategies are generally relatively crude, lacking a dynamic control mechanism linked to coal characteristics (such as volatile matter, particle size, and moisture), which easily leads to the over-storage of high-volatile bituminous coal (Vad > 28%), further exacerbating the risk of spontaneous combustion; In addition, existing devices mostly focus on local heat treatment and fail to achieve full-process risk tracking and linkage control from port arrival and transportation to silo storage. Therefore, there is currently a lack of a comprehensive prevention and control method for spontaneous combustion of bituminous coal in silos that can integrate multi-source data and achieve early prediction and proactive intervention. Summary of the Invention

[0003] To address the technical problems of monitoring lag and passive handling in existing bituminous coal storage processes, this invention proposes a method for preventing and warning of spontaneous combustion of bituminous coal in silos, comprising:

[0004] Based on the port coal quality report and unloading test data corresponding to the bituminous coal in the controlled silos, the prevention and control risk level corresponding to the bituminous coal in the controlled silos is set.

[0005] Based on multiple sets of sensing units installed inside the silo, real-time temperature data, gas composition information, and real-time humidity information are detected in different depth areas inside the silo.

[0006] The real-time physical parameters of the bituminous coal in the controlled silo are calculated based on the real-time temperature data, gas composition information, and real-time humidity information detected by the sensing unit. The critical heating rate of the monitoring area corresponding to the sensing unit is then calculated based on the real-time physical parameters. The real-time physical parameters include compaction density, thermal conductivity of the coal pile, and exothermic rate of the coal-oxygen reaction.

[0007] Based on the risk level of the controlled bituminous coal in the silos and the critical temperature rise rate of each monitoring area, an early warning threshold is set for each monitoring area.

[0008] The actual temperature rise rate of the corresponding monitoring area is calculated based on the real-time temperature data detected by the sensing unit.

[0009] When the actual temperature rise rate of any monitoring area reaches or exceeds its corresponding warning threshold, the corresponding prevention and control measures will be automatically matched and activated based on the extent of the temperature rise rate exceeding the limit and the gas composition data.

[0010] Based on the real-time temperature data and gas composition information detected by the sensing unit, the current thermal risk level is determined, and corresponding prevention and control measures are triggered according to the preset multi-level early warning rules.

[0011] Furthermore, the specific steps for setting the risk level corresponding to the controlled bituminous coal in the silo are as follows:

[0012] The bituminous coal risk coefficient of the controlled silo bituminous coal is calculated based on the bituminous coal benchmark parameters in the loading port coal quality report and the test data at the time of unloading; the bituminous coal benchmark parameters include: volatile matter reference value, sulfur reference value and moisture content reference value; the test data at the time of unloading includes: actual measured volatile matter, actual measured sulfur content and actual measured moisture content;

[0013] The risk level of the controlled bituminous coal in the silos is set according to the calculated risk coefficient of bituminous coal.

[0014] The formula for calculating the risk coefficient of bituminous coal is as follows:

[0015]

[0016] In the formula, V ref S represents a reference value for volatile matter. ref Indicates the reference value for sulfur content; M ref Indicates the reference value for moisture content; V ar S represents the actual measured volatile matter. t,d Indicates the actual measured sulfur content; M t This indicates the actual measured moisture content; R represents the risk coefficient of bituminous coal.

[0017] The risk levels mentioned include:

[0018] The first level of prevention and control corresponds to a risk coefficient range of R<0.8 for bituminous coal.

[0019] The second prevention and control level corresponds to a risk coefficient range of 0.8 ≤ R < 1.2 for bituminous coal.

[0020] The third prevention and control level corresponds to a risk coefficient range of R≥1.2 for bituminous coal.

[0021] Furthermore, the multiple sets of sensing units are arranged at predetermined height intervals along the silo axis; wherein: each set of sensing units includes a corrosion-resistant thermocouple and a multi-parameter gas probe, which are used to detect temperature data at different depths and gas composition information including carbon monoxide concentration, oxygen concentration and humidity.

[0022] Furthermore, based on the real-time temperature data, gas composition information, and real-time humidity information detected by the sensing unit, the real-time physical parameters of the bituminous coal in the controlled silo are calculated, specifically:

[0023] Calculate the current compaction density of the controlled silo based on its total coal loading, geometric dimensions, and current stacking height.

[0024] The thermal conductivity of the coal pile in the monitoring area corresponding to the sensing unit is calculated based on the real-time humidity information detected by the sensing unit.

[0025] The exothermic rate of the coal-oxygen reaction in the monitored area is calculated based on the real-time temperature data and gas composition information detected by the sensing unit.

[0026] Furthermore, the critical heating rate of the monitoring area corresponding to the sensing unit is calculated based on real-time physical parameters using the following formula:

[0027]

[0028] In the formula, λ represents the thermal conductivity of the coal pile, and δ c The critical Frank-Kamenetskii parameter is a dimensionless parameter ranging from 2.0 to 3.5; Q ox The ρ represents the exothermic rate of the coal-oxygen reaction; ρ represents the current compacted density; c p represents the specific heat capacity of coal; r represents the equivalent radius of the coal pile, which is 0.7 times the radius of the silo; CTR represents the critical heating rate.

[0029] Furthermore, based on the risk level of the controlled bituminous coal in the silos and the critical temperature rise rate of each monitoring area, a warning threshold is set for each monitoring area, specifically as follows:

[0030] When the risk level of the controlled bituminous coal in the silo is the first level, the difference between the critical heating rate of the monitoring area and the first fine-tuning value is set as the early warning threshold of the corresponding monitoring area.

[0031] When the risk level of the controlled bituminous coal in the silo is the second level, the difference between the critical heating rate of the monitoring area and the second fine-tuning value is set as the early warning threshold of the corresponding monitoring area.

[0032] When the risk level of the controlled bituminous coal in the silo is the third level, the difference between the critical heating rate of the monitoring area and the third fine-tuning value is set as the early warning threshold of the corresponding monitoring area.

[0033] The third fine-tuning value is greater than the second fine-tuning value, which is greater than the first fine-tuning value.

[0034] Furthermore, when the actual temperature rise rate of any monitored area reaches or exceeds its corresponding warning threshold, the corresponding prevention and control measures are automatically matched and activated based on the extent of the temperature rise rate exceeding the limit and gas composition data, specifically:

[0035] When the actual temperature rise rate is within the range (warning threshold, first-level warning upper limit), first-level prevention and control measures are activated, including the transfer and conveying operation; wherein, the first-level warning upper limit is the sum of the warning threshold and the first adjustment value, and the first adjustment value is 2℃ / h;

[0036] When the actual rate of temperature rise is within the range (upper limit of Level 1 warning, upper limit of Level 2 warning), Level 2 prevention and control measures will be activated:

[0037] If the carbon monoxide concentration at the top of the controlled silo is detected to be greater than 200 ppm, an emergency unloading operation will be triggered; if the carbon monoxide concentration does not exceed 200 ppm, the first-level prevention and control measures will be maintained and the monitoring frequency will be increased; wherein, the upper limit of the second-level warning is the sum of the upper limit of the first-level warning and the second adjustment value;

[0038] When the actual rate of temperature rise continues to increase and exceeds the upper limit of the Level II warning, Level III prevention and control measures will be activated, i.e., emergency unloading operations will be carried out.

[0039] Furthermore, the step of determining the current thermal risk level based on real-time temperature data and gas composition information detected by the sensing unit, and triggering corresponding prevention and control measures according to preset multi-level early warning rules, specifically includes:

[0040] When the real-time temperature data of any monitoring area exceeds the first warning value, the injection of inert gas into the chamber is initiated.

[0041] When the real-time temperature data of any monitoring area exceeds the second warning value, and the carbon monoxide concentration is detected to be greater than or equal to 200 ppm, the transfer and conveying operation is initiated.

[0042] When the real-time temperature data of any monitoring area exceeds the third warning value, the fire linkage mechanism is triggered, and the silo ventilation openings and entrances / exits are closed.

[0043] Wherein: the third warning value is greater than the second warning value, which is greater than the first warning value.

[0044] Furthermore, the method also includes:

[0045] Construct a prediction model for bituminous coal storage cycles;

[0046] Continuously collect real-time data on environmental factors, coal quality parameters, and storage status of the controlled bituminous coal in the silos;

[0047] At preset time intervals, the continuously collected data is used as input to predict the storage period of bituminous coal in the controlled silo through a bituminous coal storage period prediction model.

[0048] The storage period is adjusted based on the risk level of the bituminous coal in the controlled silo, thus obtaining the current safe storage period for the bituminous coal in the controlled silo.

[0049] An alert is triggered when the actual storage period exceeds the current safe storage period.

[0050] Furthermore, the construction of the bituminous coal storage cycle prediction model specifically involves:

[0051] Obtain historical data sets of single-batch storage of bituminous coal from multiple silos;

[0052] The recorded data set includes multiple feature variables extracted from the following three categories of factors:

[0053] Environmental factors include: air humidity values ​​measured at different time points throughout the entire single-batch storage period and temperature changes recorded during the storage period, and the calculated statistical variance of temperature fluctuations;

[0054] Coal quality parameters include: volatile matter, sulfur content, and particle size distribution data detected and recorded at the loading port;

[0055] The storage status includes: the stacking height set when the coal is put into the silo, the initial compaction density, and the historical temperature rise data recorded from the time the coal is put into the silo to the time it is taken out of the silo;

[0056] A training sample is generated based on each set of recorded data. Each training sample is marked with the number of days after the bituminous coal is put into storage and the first temperature rise rate is greater than 1℃ / h, which is taken as the actual safe storage days.

[0057] A training set is formed based on all training samples;

[0058] The LightGBM model was trained using the training set to obtain a prediction model for the storage cycle of bituminous coal.

[0059] Compared with the prior art, the present invention has at least the following beneficial effects:

[0060] (1) This invention sets the risk level of bituminous coal in silos by combining port coal quality reports with unloading detection data, and uses multiple sets of sensing units to monitor the temperature, gas composition, and humidity information of different depth areas inside the silos in real time. Based on these real-time data, real-time physical parameters such as compaction density, coal pile thermal conductivity, and coal-oxygen reaction exothermic rate are calculated, thereby determining the critical temperature rise rate of each monitoring area. Warning thresholds are set according to the risk level and critical temperature rise rate. When the actual temperature rise rate of any monitoring area reaches or exceeds its warning threshold, the system automatically matches and activates corresponding prevention and control measures based on the temperature rise rate exceeding the limit and gas composition data. This method of setting warning thresholds for each monitoring area by combining real-time physical parameters achieves precise monitoring of each monitoring area, significantly improving the accuracy and timeliness of warnings. Compared with traditional single temperature monitoring methods, this invention can detect potential spontaneous combustion hazards earlier, effectively avoiding risk loss of control due to monitoring lag.

[0061] (2) This invention sets the risk level for prevention and control based on the coal quality report at the loading port and the detection data at the time of unloading, and comprehensively assesses the spontaneous combustion risk in different depth areas inside the silo by combining the real-time monitoring information of temperature, gas composition and humidity inside the silo. Compared with the traditional single temperature monitoring method, this multi-dimensional risk assessment can detect potential spontaneous combustion hazards earlier, greatly improving the timeliness and accuracy of early warning.

[0062] (3) This invention uses multiple sets of sensing units installed inside the silo to collect and analyze key parameters such as temperature, gas composition, and humidity in real time. It calculates the real-time physical parameters of the bituminous coal in the controlled silo (such as compaction density, thermal conductivity, and the rate of exothermic reaction between coal and oxygen), and sets the critical heating rate and early warning threshold for each monitoring area accordingly. This method not only dynamically tracks changes inside the coal pile but also dynamically adjusts the early warning threshold based on real-time physical parameters, achieving dynamic and accurate prediction within a small area (monitoring zone).

[0063] (4) This invention establishes a multi-level early warning mechanism based on different risk levels and actual temperature rise rates. When the monitored actual temperature rise rate reaches or exceeds the corresponding early warning threshold, the system automatically matches and activates corresponding prevention and control measures, such as warehouse transfer and emergency unloading, based on the extent of the temperature rise rate exceeding the limit and gas composition data. This tiered early warning and proactive intervention strategy effectively avoids problems such as equipment corrosion and increased ash content caused by traditional passive handling methods (such as spraying flame retardants), while reducing the probability of spontaneous combustion accidents.

[0064] (5) This invention dynamically adjusts the safe storage period of bituminous coal in silos based on a predictive model and risk control levels, and triggers an early warning when the actual storage period exceeds the safe storage period. This function enables warehouse managers to arrange coal storage and scheduling more scientifically and rationally, especially for easily spontaneously combustible coals such as high-volatile bituminous coal (Vad>28%), which can effectively prevent safety hazards caused by overdue storage and improve the overall level of precision in inventory management. Attached Figure Description

[0065] Figure 1 This is a flowchart of a method for preventing and issuing early warnings of spontaneous combustion of bituminous coal in silos. Detailed Implementation

[0066] The following are specific embodiments of the present invention, which are described in conjunction with the accompanying drawings. However, the present invention is not limited to these embodiments.

[0067] To address the technical problems existing in the current silo-based bituminous coal storage process, such as monitoring lag and passive handling, Figure 1 As shown, this invention proposes a method for preventing and warning of spontaneous combustion of bituminous coal in silos, comprising:

[0068] Based on the port coal quality report and unloading test data corresponding to the bituminous coal in the controlled silos, the prevention and control risk level corresponding to the bituminous coal in the controlled silos is set and written into the RFID electronic tag;

[0069] The specific steps for setting the risk level for the controlled bituminous coal in the silos are as follows:

[0070] The bituminous coal risk coefficient of the controlled silo bituminous coal is calculated based on the bituminous coal benchmark parameters in the loading port coal quality report and the test data at the time of unloading; the bituminous coal benchmark parameters include: volatile matter reference value, sulfur reference value and moisture content reference value; the test data at the time of unloading includes: actual measured volatile matter, actual measured sulfur content and actual measured moisture content;

[0071] The risk level of the controlled bituminous coal in the silos is set according to the calculated risk coefficient of bituminous coal.

[0072] The formula for calculating the risk coefficient of bituminous coal is as follows:

[0073]

[0074] In the formula, V ref The reference value for volatile matter (28%); S ref This indicates a reference value for sulfur content (1.2%); m ref This indicates the reference value for moisture content (10%); V ar S represents the actual measured volatile matter. t,d This indicates the actual measured sulfur content; mt This indicates the actual measured moisture content; R represents the risk coefficient of bituminous coal.

[0075] The risk levels mentioned include:

[0076] The first level of prevention and control corresponds to a risk coefficient range of R<0.8 for bituminous coal.

[0077] The second prevention and control level corresponds to a risk coefficient range of 0.8 ≤ R < 1.2 for bituminous coal.

[0078] The third prevention and control level corresponds to a risk coefficient range of R≥1.2 for bituminous coal.

[0079] Based on multiple sets of sensing units installed inside the silo, real-time temperature data, gas composition information, and real-time humidity information are detected in different depth areas inside the silo.

[0080] In this embodiment, the data detection frequency is less than or equal to 15 minutes.

[0081] The multiple sets of sensing units are arranged at predetermined height intervals along the silo axis; wherein: each set of sensing units includes a corrosion-resistant thermocouple and a multi-parameter gas probe, which are used to detect temperature data at different depths and gas composition information including carbon monoxide concentration, oxygen concentration and humidity.

[0082] To achieve comprehensive monitoring of the state of bituminous coal inside the silo, this invention employs an optimized sensor unit layout strategy. Specifically, a group of sensor units is arranged every 5 meters along the silo's axial direction. Each sensor unit includes a corrosion-resistant thermocouple and a multi-parameter gas probe, used to detect temperature data at different depths and gas composition information, including carbon monoxide concentration, oxygen concentration, and humidity. The sensor burial depth is gradient-distributed according to the surface (2 meters), middle (5 meters), and bottom (8 meters) layers to ensure accurate capture of temperature rise changes and gas composition fluctuations at each level within the coal pile.

[0083] This multi-layered, high-density sensor layout has the following advantages:

[0084] Improve monitoring accuracy: By setting up sensors at different depths, the temperature and gas composition changes inside the coal pile can be obtained more accurately, avoiding errors caused by monitoring at a single level.

[0085] Expanded monitoring range: A set of sensor units is placed every 5 meters to ensure that the entire interior of the silo can be effectively monitored without leaving any blind spots.

[0086] Early warning capability: A multi-layered sensor layout helps to detect potential spontaneous combustion hazards earlier, especially in the initial temperature rise stage, so that timely prevention and control measures can be taken to prevent the accident from escalating.

[0087] In summary, this optimized sensor unit layout not only improves the reliability and accuracy of the monitoring system, but also provides a solid technical guarantee for the safe storage of bituminous coal in silos.

[0088] In this embodiment, to avoid the risk of cross-oxidation between different batches of bituminous coal, new batches of bituminous coal are only injected into completely emptied silos. By thoroughly emptying the silos, it is ensured that no residual coal remains, thereby effectively preventing cross-oxidation reactions between old and new coal. This measure not only reduces the potential risk of spontaneous combustion but also improves the safety and reliability of the silo storage system.

[0089] The real-time physical parameters of the bituminous coal in the controlled silo are calculated based on the real-time temperature data, gas composition information, and real-time humidity information detected by the sensing unit. The critical heating rate of the monitoring area corresponding to the sensing unit is then calculated based on the real-time physical parameters. The real-time physical parameters include compaction density, thermal conductivity of the coal pile, and exothermic rate of the coal-oxygen reaction.

[0090] The real-time physical parameters of the bituminous coal in the controlled silo are calculated based on the real-time temperature data, gas composition information, and real-time humidity information detected by the sensing unit. Specifically:

[0091] Calculate the current compaction density of the controlled silo based on its total coal loading, geometric dimensions, and current stacking height.

[0092] In this embodiment, the formula for calculating the current compaction density is:

[0093]

[0094] In the formula, M(t) represents the real-time data from the weighing system; V(t) represents the volume of the coal pile.

[0095] If a weighing system is unavailable, dynamic correction can be made using the historical average density ρ0 combined with an empirical compaction coefficient.

[0096] ρ real (t)=ρ0+k compaction ·t;

[0097] In the formula, t represents the time variable, usually in days.

[0098] Specifically, t represents the time elapsed from the start of storage or monitoring of the coal pile to the current time. As t increases, the compaction density of the coal pile gradually increases due to gravity and the mutual compression between coal particles.

[0099] kcompaction is an empirical compaction coefficient (kg / m³) set according to coal type and particle size. 3 / day), can be calibrated experimentally. ρ real(t) represents the current compaction density.

[0100] The thermal conductivity of the coal pile in the monitoring area corresponding to the sensing unit is calculated based on the real-time humidity information detected by the sensing unit.

[0101] Thermal conductivity reflects the ability of a coal pile to conduct heat, and is greatly affected by the coal quality and moisture content.

[0102] The formula used to calculate the thermal conductivity of a coal pile is:

[0103] λ real =λ0·(1-a·w+b·w) 2 );

[0104] In the formula, λ0 represents the thermal conductivity under standard dry conditions (W / (m·K), obtained from a table or experiment); w represents the current humidity (mass percentage, %); a and b represent fitting coefficients, set according to the type of coal (e.g., for bituminous coal: a = 0.03, b = 0.0015).

[0105] The exothermic rate of the coal-oxygen reaction in the monitored area is calculated based on the real-time temperature data and gas composition information detected by the sensing unit.

[0106] In this embodiment, the formula for calculating the exothermic rate of the coal-oxygen reaction is:

[0107]

[0108] In the formula:

[0109] Q ox (T, [CO]) represents the exothermic rate of the coal-oxygen reaction at the current temperature T and CO concentration (J / kg·s);

[0110] Q ox，0 This represents the basic heat release rate at the reference temperature T0 (obtained through experimental calibration or by referring to a table);

[0111] E a The activation energy (J / mol) represents the reaction between coal and oxygen; for typical bituminous coal, it is approximately 80,000 to 120,000.

[0112] R represents the gas constant, which has a value of 8.314 J / (mol·K) and is a physical constant used to describe the behavior of an ideal gas.

[0113] T represents the real-time monitored temperature (unit: K);

[0114] T0 represents the reference temperature (e.g., 300K);

[0115] [CO] indicates the CO concentration (ppm) detected in real time;

[0116] [CO]0 indicates the initial background CO concentration (e.g., 10 ppm);

[0117] [CO] ref Indicates the reference concentration difference (e.g., 100 ppm);

[0118] k CO This represents the CO impact coefficient (an empirical parameter, recommended to be initially set to 0.2).

[0119] in:

[0120] The initial background CO concentration refers to the initial concentration of carbon monoxide (CO) in the environment at the start of monitoring. This value is typically used to set a baseline so that any subsequent changes or anomalies can be accurately measured and assessed. For example, in the prevention and control of spontaneous combustion of bituminous coal in silos, the initial background CO concentration can help determine if there are early signs of spontaneous combustion, as the carbon monoxide concentration usually increases as the coal oxidizes.

[0121] In this embodiment, the formula for calculating the exothermic rate of the coal-oxygen reaction consists of two parts:

[0122] The first part is the classic Arrhenius equation, which describes the exponential effect of temperature on the reaction rate;

[0123] The second part is the linear correction term, which takes into account the trend that an increase in CO concentration reflects an enhanced oxidation reaction.

[0124] Relying solely on CO concentration may lead to inaccurate calculations (for example, local ventilation disturbances can also cause CO to rise); or relying solely on temperature may fail to reflect differences in coal quality and the oxidation process; this formula combines both to improve the accuracy of the calculations.

[0125] The critical heating rate of the monitoring area corresponding to the sensing unit is calculated based on real-time physical parameters using the following formula:

[0126]

[0127] In the formula, λ represents the thermal conductivity of the coal pile (unit: W / (m·K)), δ c The critical Frank-Kamenetskii parameter is a dimensionless parameter ranging from 2.0 to 3.5; Q ox ρ represents the exothermic rate of the coal-oxygen reaction (in J / (kg·s)); ρ represents the current compaction density (in kg / m³). 3 );c p The value represents the specific heat capacity of coal (in J / (kg·K), with a typical value of (1200~1400)); r represents the equivalent radius of the coal pile (in meters), which is 0.7 times the radius of the silo; CTR represents the critical heating rate.

[0128] Based on the risk level of the controlled bituminous coal in the silos and the critical temperature rise rate of each monitoring area, an early warning threshold is set for each monitoring area.

[0129] This invention utilizes multiple sets of sensing units installed within the silo to collect and analyze key parameters such as temperature, gas composition, and humidity in real time. It calculates the real-time physical parameters of the bituminous coal in the controlled silo (such as compaction density, thermal conductivity, and the exothermic rate of the coal-oxygen reaction), and accordingly sets the critical temperature rise rate and early warning threshold for each monitoring area. This method not only dynamically tracks changes within the coal pile but also dynamically adjusts the early warning threshold based on real-time physical parameters, achieving dynamic and accurate prediction within a small area (monitoring zone), thus providing a highly personalized risk assessment within a limited scope.

[0130] The method involves setting an early warning threshold for each monitoring area based on the risk level of the controlled bituminous coal in the silos and the critical temperature rise rate of each monitoring area. Specifically:

[0131] When the risk level of the controlled bituminous coal in the silo is the first level, the difference between the critical heating rate of the monitoring area and the first fine-tuning value is set as the early warning threshold of the corresponding monitoring area.

[0132] When the risk level of the controlled bituminous coal in the silo is the second level, the difference between the critical heating rate of the monitoring area and the second fine-tuning value is set as the early warning threshold of the corresponding monitoring area.

[0133] When the risk level of the controlled bituminous coal in the silo is the third level, the difference between the critical heating rate of the monitoring area and the third fine-tuning value is set as the early warning threshold of the corresponding monitoring area.

[0134] The third fine-tuning value is greater than the second fine-tuning value, which is greater than the first fine-tuning value.

[0135] The actual temperature rise rate of the corresponding monitoring area is calculated based on the real-time temperature data detected by the sensing unit.

[0136] To monitor the temperature changes inside the bituminous coal silo in real time, this invention employs a method for calculating the temperature rise rate based on time-series data. The specific formula is as follows:

[0137]

[0138] In the formula, α represents the actual temperature rise rate per unit time, expressed in degrees Celsius per hour (°C / h). This parameter is used to quantify the rate of temperature change over time and is an important indicator for determining whether a coal pile is in the initial stage of spontaneous combustion.

[0139] T tThe temperature value (°C) at the current time t is collected in real time by a sensing unit located inside the silo.

[0140] T t-6h The temperature value (°C) is represented by the time point t-6h, which was 6 hours ago. This value is also provided by historical data recorded by the sensor.

[0141] ΔT represents the temperature T at the current time point t. t The temperature T at time t-6h 6 hours ago t-6h The difference (°C) between these two time points can be used to assess whether there is an abnormal temperature rise inside the coal pile.

[0142] Δt: Fixed at 6 hours. This time interval was chosen to balance the impact of short-term fluctuations and long-term trends, ensuring high stability and accuracy in the temperature rise rate calculation.

[0143] When the actual temperature rise rate of any monitoring area reaches or exceeds its corresponding warning threshold, the corresponding prevention and control measures will be automatically matched and activated based on the extent of the temperature rise rate exceeding the limit and the gas composition data.

[0144] When the actual temperature rise rate of any monitoring area reaches or exceeds its corresponding warning threshold, the system automatically matches and activates corresponding prevention and control measures based on the extent of the temperature rise rate exceeding the limit and gas composition data. Specifically:

[0145] When the actual temperature rise rate is within the range (early warning threshold, first-level early warning upper limit), first-level prevention and control measures are activated, including the transfer and conveying operation; wherein, the first-level early warning upper limit is the sum of the early warning threshold and the first adjustment value;

[0146] The first adjustment value is 2℃ / h;

[0147] When the actual rate of temperature rise is within the range (upper limit of Level 1 warning, upper limit of Level 2 warning), Level 2 prevention and control measures will be activated:

[0148] If the carbon monoxide concentration at the top of the controlled silo is detected to be greater than 200 ppm, an emergency unloading operation will be triggered; if the carbon monoxide concentration is less than 200 ppm, the first-level prevention and control measures will be maintained and the monitoring frequency will be increased; wherein, the upper limit of the second-level warning is the sum of the upper limit of the first-level warning and the second adjustment value;

[0149] In this embodiment, the second adjustment value is 3℃ / h.

[0150] When the actual rate of temperature rise continues to increase and exceeds the upper limit of the Level II warning, Level III prevention and control measures will be activated, i.e., emergency unloading operations will be carried out.

[0151] In the silo-based bituminous coal spontaneous combustion prevention and early warning system, there is a clear operational logic and response mechanism between primary control measures (such as silo transfer and conveying operations) and secondary control measures. Although theoretically, implementing primary control measures should help alleviate the temperature rise trend, in practical applications, the temperature rise rate may still continue to climb to the range of [primary warning upper limit, secondary warning upper limit]. This is mainly because:

[0152] The effect of transfer conveying is limited: While transfer conveying can break up local heat accumulation and provide a cooling opportunity, it cannot immediately stop the oxidation reaction that has already occurred or completely eliminate the potential risk of spontaneous combustion. Especially for high-volatile bituminous coal, the internal chemical reaction may still be continuing, causing the temperature to rise further.

[0153] Environmental factors: Newly injected air or other environmental factors may exacerbate the oxidation reaction of the coal pile, leading to a continued increase in the rate of temperature rise.

[0154] Furthermore, once the transfer operation is completed, if the monitored carbon monoxide concentration does not exceed 200 ppm, the system maintains Level 1 control measures and increases monitoring frequency. "Maintaining Level 1 control" here does not mean repeating the transfer operation, but rather:

[0155] Maintain the current handling strategy: do not escalate to higher-level intervention measures (such as emergency unloading), but continue to closely monitor changes in the condition of the coal pile.

[0156] Increase monitoring frequency: By increasing the frequency of sensor data collection, we can ensure that any new anomalies can be captured in a timely manner and that prevention and control measures can be dynamically adjusted based on the latest data.

[0157] This tiered response mechanism not only improves the system's flexibility and adaptability, but also avoids unnecessary frequent operations and resource waste while ensuring safety, thus ensuring the efficient operation of the silo storage system.

[0158] This invention achieves dynamic response to the risk of spontaneous combustion of bituminous coal in silos by setting up a multi-level early warning mechanism. Level 1 prevention is used for early intervention, level 2 prevention combines gas composition for precise judgment, and level 3 prevention serves as the final line of defense, ensuring system safety under extreme temperature conditions. This method not only improves the accuracy of early warning but also enhances the system's fault tolerance and emergency response capabilities.

[0159] Based on the real-time temperature data and gas composition information detected by the sensing unit, the current thermal risk level is determined, and corresponding prevention and control measures are triggered according to the preset multi-level early warning rules.

[0160] The process involves determining the current thermal risk level based on real-time temperature data and gas composition information detected by the sensing unit, and triggering corresponding prevention and control measures according to preset multi-level early warning rules. Specifically:

[0161] When the real-time temperature data of any monitoring area exceeds the first warning value (50℃), the injection of inert gas into the chamber is initiated.

[0162] When the real-time temperature data of any monitoring area is greater than the second warning value (60℃) and the carbon monoxide (CO) concentration is greater than or equal to 200ppm, the transfer and conveying operation is initiated.

[0163] When the real-time temperature data of any monitoring area exceeds the third warning value (80℃), the fire linkage mechanism is triggered, and the silo ventilation openings and entrances / exits are closed.

[0164] Wherein: the third warning value is greater than the second warning value, which is greater than the first warning value.

[0165] This invention employs a dual-layer prevention and control mechanism combining automatic matching control measures based on the temperature rise rate exceeding limits and gas composition data with multi-level early warning rules, significantly improving the monitoring accuracy and response efficiency of spontaneous combustion risk in siloed bituminous coal. First, when the actual temperature rise rate in any monitored area reaches or exceeds its corresponding early warning threshold, the system automatically matches and activates corresponding prevention and control measures based on the temperature rise rate exceeding limits and gas composition data, such as silo transfer operations and emergency unloading. This real-time dynamic response mechanism can quickly identify and handle potential spontaneous combustion hazards, avoiding the lag and passive handling problems caused by traditional single-temperature monitoring methods. Second, through real-time temperature data and gas composition information detected by the sensor unit, the system can determine the current thermal risk level and trigger corresponding prevention and control measures according to preset multi-level early warning rules. This multi-level risk assessment system not only improves the accuracy and timeliness of early warnings but also enables flexible and appropriate intervention measures at different risk levels, maximizing the safety and management efficiency of the silo storage system. In summary, the dual-layer prevention and control mechanism of this invention effectively solves the problems of monitoring lag and passive handling in existing technologies, significantly improving the safety and intelligent management level of siloed bituminous coal storage.

[0166] This invention sets risk levels based on coal quality reports at loading ports and testing data during unloading, and comprehensively assesses the spontaneous combustion risk at different depths within the silos by combining real-time monitoring of temperature, gas composition, and humidity information. Compared to traditional single-temperature monitoring methods, this multi-dimensional risk assessment can detect potential spontaneous combustion hazards earlier, greatly improving the timeliness and accuracy of early warnings.

[0167] The method further includes:

[0168] Construct a prediction model for bituminous coal storage cycles;

[0169] Continuously collect real-time data on environmental factors, coal quality parameters, and storage status of the controlled bituminous coal in the silos;

[0170] At preset time intervals, the continuously collected data is used as input to predict the storage period of bituminous coal in the controlled silo through a bituminous coal storage period prediction model.

[0171] The storage period is adjusted based on the risk level of the bituminous coal in the controlled silo, thus obtaining the current safe storage period for the bituminous coal in the controlled silo.

[0172] This invention dynamically adjusts the storable period of bituminous coal in the controlled silo by combining the risk level of the controlled coal, thereby obtaining a more accurate current safe storage period. This mechanism significantly improves the flexibility and accuracy of the system, specifically in the following aspects:

[0173] Personalized risk assessment: Different coal qualities have different spontaneous combustion risk characteristics. For example, high-volatile bituminous coal is more prone to spontaneous combustion than low-volatile bituminous coal. By combining coal quality parameters with risk control levels, a personalized safe storage period can be provided for each batch of bituminous coal, avoiding misjudgments caused by a one-size-fits-all fixed period.

[0174] Dynamic adjustment mechanism: The model considers real-time monitored environmental factors and storage status, and the risk level control takes into account coal quality characteristics. Based on the risk level control corresponding to the bituminous coal in the controlled silo, the model adjusts the predicted storage period. This means that as storage time increases and environmental conditions change, the system can dynamically adjust the safe storage period. For example, in high-temperature and high-humidity environments, the system will shorten the safe storage period to improve early warning sensitivity, while in low-temperature and dry environments, it will appropriately extend it.

[0175] Precise early warning and intervention: Through real-time monitoring and dynamic adjustment, the system can issue timely warnings when the actual storage period approaches or exceeds the current safe storage period. This enables managers to take necessary preventative measures in advance, effectively preventing spontaneous combustion accidents caused by overdue storage.

[0176] Enhancing overall safety and management efficiency: This dynamic adjustment mechanism based on risk levels not only improves the accuracy and timeliness of early warnings but also optimizes inventory management strategies. By rationally arranging the storage time and location of different batches of bituminous coal, storage space can be maximized, unnecessary transfers can be reduced, thereby lowering operating costs and improving overall management levels.

[0177] An alert is triggered when the actual storage period exceeds the current safe storage period.

[0178] The construction of the bituminous coal storage cycle prediction model is specifically as follows:

[0179] Obtain historical data sets of single-batch storage of bituminous coal from multiple silos;

[0180] The recorded data set includes multiple feature variables extracted from the following three categories of factors:

[0181] Environmental factors include: air humidity values ​​measured at different time points throughout the entire single-batch storage period and temperature changes recorded during the storage period, and the calculated statistical variance of temperature fluctuations;

[0182] Coal quality parameters include: volatile matter, sulfur content, and particle size distribution data detected and recorded at the loading port;

[0183] The storage status includes: the stacking height set when the coal is put into the silo, the initial compaction density, and the historical temperature rise data recorded from the time the coal is put into the silo to the time it is taken out of the silo;

[0184] A training sample is generated based on each set of recorded data. Each training sample is marked with the number of days after the bituminous coal is put into storage and the first temperature rise rate is greater than 1℃ / h, which is taken as the actual safe storage days.

[0185] A training set is formed based on all training samples;

[0186] To ensure the effectiveness and reliability of the model, this invention uses abundant historical data for training. Specifically, the sample set contains storage records (15,000 data points) from 200 silos over three years. This data covers various environmental conditions, coal quality characteristics, and storage status changes, comprehensively reflecting the risk characteristics of spontaneous combustion of bituminous coal under different conditions. Through this large-scale data training, the model possesses high generalization ability and prediction accuracy, enabling it to provide reliable storage cycle prediction results in practical applications.

[0187] The LightGBM model was trained using the training set to obtain a prediction model for the storage cycle of bituminous coal.

[0188] This invention constructs a bituminous coal storage cycle prediction model based on the LightGBM algorithm and employs a rolling prediction mechanism to achieve dynamic assessment and continuous optimization of the safe storage cycle of bituminous coal in silos. Specifically, after the bituminous coal is stored, real-time data on environmental factors, coal quality parameters, and storage status are continuously collected, and the input characteristics are updated according to a preset time period (e.g., daily) to re-predict the storable cycle of the current batch of bituminous coal. Based on this, dynamic adjustments are made in conjunction with the risk control level to obtain a safe storage cycle that better reflects actual storage conditions. Once the actual storage time exceeds this cycle, an early warning is automatically triggered, reminding management personnel to take timely measures. This rolling prediction method not only overcomes the rigidity of traditional fixed-cycle management but also corrects the prediction results in real time according to the changing trend of coal condition, significantly improving the accuracy and timeliness of early warnings. It effectively prevents the risk of spontaneous combustion of high-volatile bituminous coal due to over-storage and further enhances the intelligent and refined management level of the silo coal storage process.

[0189] This invention sets the risk level for bituminous coal in silos by combining port coal quality reports with unloading inspection data, and utilizes multiple sets of sensors to monitor temperature, gas composition, and humidity at different depths within the silos in real time. Based on this real-time data, real-time physical parameters such as compaction density, coal pile thermal conductivity, and coal-oxygen reaction exothermic rate are calculated, thereby determining the critical temperature rise rate for each monitoring area. Warning thresholds are set according to the risk level and critical temperature rise rate. When the actual temperature rise rate of any monitoring area reaches or exceeds its warning threshold, the system automatically matches and activates corresponding prevention and control measures based on the extent of the temperature rise rate exceeding the limit and gas composition data. This method of setting warning thresholds for each monitoring area by combining real-time physical parameters achieves precise monitoring of each area, significantly improving the accuracy and timeliness of warnings. Compared to traditional single-temperature monitoring methods, this invention can detect potential spontaneous combustion hazards earlier, effectively avoiding risk loss of control due to monitoring lag.

[0190] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0191] Furthermore, in this invention, descriptions involving terms such as "first," "second," and "a" are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0192] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0193] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are feasible for those skilled in the art. If the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

Claims

1. A method for preventing and issuing early warning of spontaneous combustion of bituminous coal in silos, characterized in that, include: Based on the port coal quality report and unloading test data corresponding to the bituminous coal in the controlled silos, the prevention and control risk level corresponding to the bituminous coal in the controlled silos is set. Based on multiple sets of sensing units installed inside the silo, real-time temperature data, gas composition information, and real-time humidity information are detected in different depth areas inside the silo. The real-time physical parameters of the bituminous coal in the controlled silo are calculated based on the real-time temperature data, gas composition information, and real-time humidity information detected by the sensing unit. The critical heating rate of the monitoring area corresponding to the sensing unit is then calculated based on the real-time physical parameters. The real-time physical parameters include compaction density, thermal conductivity of the coal pile, and exothermic rate of the coal-oxygen reaction. Based on the risk level of the controlled bituminous coal in the silos and the critical temperature rise rate of each monitoring area, an early warning threshold is set for each monitoring area. The actual temperature rise rate of the corresponding monitoring area is calculated based on the real-time temperature data detected by the sensing unit. When the actual temperature rise rate of any monitoring area reaches or exceeds its corresponding warning threshold, the corresponding prevention and control measures will be automatically matched and activated based on the extent of the temperature rise rate exceeding the limit and the gas composition data. Based on the real-time temperature data and gas composition information detected by the sensing unit, the current thermal risk level is determined, and corresponding prevention and control measures are triggered according to the preset multi-level early warning rules.

2. The method for preventing and issuing early warning of spontaneous combustion of bituminous coal in silos according to claim 1, characterized in that, The specific steps for setting the risk level for the controlled bituminous coal in the silos are as follows: The bituminous coal risk coefficient of the controlled silo bituminous coal is calculated based on the bituminous coal benchmark parameters in the loading port coal quality report and the test data at the time of unloading. The reference parameters for bituminous coal include: reference values ​​for volatile matter, sulfur content, and moisture content; the test data at the time of unloading includes: the actual measured volatile matter, the actual measured sulfur content, and the actual measured moisture content. The risk level of the controlled bituminous coal in the silos is set according to the calculated risk coefficient of bituminous coal. The formula for calculating the risk coefficient of bituminous coal is as follows: In the formula, V ref S represents a reference value for volatile matter. ref Indicates the reference value for sulfur content; M ref Indicates the reference value for moisture content; V ar S represents the actual measured volatile matter. t,d Indicates the actual measured sulfur content; M t This indicates the actual measured moisture content; R represents the risk coefficient of bituminous coal. The risk levels mentioned include: The first level of prevention and control corresponds to a risk coefficient range of R<0.8 for bituminous coal. The second prevention and control level corresponds to a risk coefficient range of 0.8 ≤ R < 1.2 for bituminous coal. The third prevention and control level corresponds to a risk coefficient range of R≥1.2 for bituminous coal.

3. The method for preventing and warning of spontaneous combustion of bituminous coal in silos according to claim 2, characterized in that, The multiple sets of sensing units are arranged at predetermined height intervals along the silo axis; wherein: each set of sensing units includes a corrosion-resistant thermocouple and a multi-parameter gas probe, which are used to detect temperature data at different depths and gas composition information including carbon monoxide concentration, oxygen concentration and humidity.

4. The method for preventing and issuing early warning of spontaneous combustion of bituminous coal in silos according to claim 3, characterized in that, The real-time physical parameters of the bituminous coal in the controlled silo are calculated based on the real-time temperature data, gas composition information, and real-time humidity information detected by the sensing unit. Specifically: Calculate the current compaction density of the controlled silo based on its total coal loading, geometric dimensions, and current stacking height. The thermal conductivity of the coal pile in the monitoring area corresponding to the sensing unit is calculated based on the real-time humidity information detected by the sensing unit. The exothermic rate of the coal-oxygen reaction in the monitored area is calculated based on the real-time temperature data and gas composition information detected by the sensing unit.

5. The method for preventing and warning of spontaneous combustion of bituminous coal in silos according to claim 4, characterized in that, The critical heating rate of the monitoring area corresponding to the sensing unit is calculated based on real-time physical parameters using the following formula: In the formula, λ represents the thermal conductivity of the coal pile, and δ c Q represents the critical Frank-Kamenetskii parameter; ox The ρ represents the exothermic rate of the coal-oxygen reaction; ρ represents the current compacted density; c p represents the specific heat capacity of coal; r represents the equivalent radius of the coal pile; CTR represents the critical heating rate.

6. The method for preventing and issuing early warning of spontaneous combustion of bituminous coal in silos according to claim 5, characterized in that, The method involves setting an early warning threshold for each monitoring area based on the risk level of the controlled bituminous coal in the silos and the critical temperature rise rate of each monitoring area. Specifically: When the risk level of the controlled bituminous coal in the silo is the first level, the difference between the critical heating rate of the monitoring area and the first fine-tuning value is set as the early warning threshold of the corresponding monitoring area. When the risk level of the controlled bituminous coal in the silo is the second level, the difference between the critical heating rate of the monitoring area and the second fine-tuning value is set as the early warning threshold of the corresponding monitoring area. When the risk level of the controlled bituminous coal in the silo is the third level, the difference between the critical heating rate of the monitoring area and the third fine-tuning value is set as the early warning threshold of the corresponding monitoring area. The third fine-tuning value is greater than the second fine-tuning value, which is greater than the first fine-tuning value.

7. The method for preventing and issuing early warning of spontaneous combustion of bituminous coal in silos according to claim 6, characterized in that, When the actual temperature rise rate of any monitoring area reaches or exceeds its corresponding warning threshold, the system automatically matches and activates corresponding prevention and control measures based on the extent of the temperature rise rate exceeding the limit and gas composition data. Specifically: When the actual temperature rise rate is within the range (warning threshold, first-level warning upper limit), first-level prevention and control measures are activated, including the transfer and conveying operation; wherein, the first-level warning upper limit is the sum of the warning threshold and the first adjustment value, and the first adjustment value is 2℃ / h; When the actual rate of temperature rise is within the range (upper limit of Level 1 warning, upper limit of Level 2 warning), Level 2 prevention and control measures will be activated: If the carbon monoxide concentration at the top of the controlled silo is detected to be greater than 200 ppm, an emergency unloading operation will be triggered; if the carbon monoxide concentration is less than 200 ppm, the first-level prevention and control measures will be maintained and the monitoring frequency will be increased; wherein, the upper limit of the second-level warning is the sum of the upper limit of the first-level warning and the second adjustment value; When the actual rate of temperature rise continues to increase and exceeds the upper limit of the Level II warning, Level III prevention and control measures will be activated, i.e., emergency unloading operations will be carried out.

8. The method for preventing and warning of spontaneous combustion of bituminous coal in silos according to claim 7, characterized in that, The process involves determining the current thermal risk level based on real-time temperature data and gas composition information detected by the sensing unit, and triggering corresponding prevention and control measures according to preset multi-level early warning rules. Specifically: When the real-time temperature data of any monitoring area exceeds the first warning value, the injection of inert gas into the chamber is initiated. When the real-time temperature data of any monitoring area exceeds the second warning value, and the carbon monoxide concentration is detected to be greater than or equal to 200 ppm, the transfer and conveying operation is initiated. When the real-time temperature data of any monitoring area exceeds the third warning value, the fire linkage mechanism is triggered, and the silo ventilation openings and entrances / exits are closed. Wherein: the third warning value is greater than the second warning value, which is greater than the first warning value.

9. A method for preventing and warning of spontaneous combustion of bituminous coal in silos according to any one of claims 1 to 8, characterized in that, The method further includes: Construct a prediction model for bituminous coal storage cycle; Continuously collect real-time data on environmental factors, coal quality parameters, and storage status of the controlled bituminous coal in the silos; At preset time intervals, the continuously collected data is used as input to predict the storable period of bituminous coal in the controlled silo through a bituminous coal storage period prediction model. The storage period is adjusted based on the risk level of the bituminous coal in the controlled silo, thus obtaining the current safe storage period for the bituminous coal in the controlled silo. An alert is triggered when the actual storage period exceeds the current safe storage period.

10. The method for preventing and issuing early warning of spontaneous combustion of bituminous coal in silos according to claim 9, characterized in that, The construction of the bituminous coal storage cycle prediction model is specifically as follows: Obtain historical data sets of single-batch storage of bituminous coal from multiple silos; The recorded data set includes multiple feature variables extracted from the following three categories of factors: Environmental factors include: air humidity values ​​measured at different time points throughout the entire single-batch storage period and temperature changes recorded during the storage period, and the calculated statistical variance of temperature fluctuations; Coal quality parameters include: volatile matter, sulfur content, and particle size distribution data detected and recorded at the loading port; The storage status includes: the stacking height set when the coal is put into the silo, the initial compaction density, and the historical temperature rise data recorded from the time the coal is put into the silo to the time it is taken out of the silo; A training sample is generated based on each set of recorded data. Each training sample is marked with the number of days after the bituminous coal is put into storage and the first temperature rise rate is greater than 1℃ / h, which is taken as the actual safe storage days. A training set is formed based on all training samples; The LightGBM model was trained using the training set to obtain a prediction model for the storage cycle of bituminous coal.

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