Calcium coke oven flue gas data monitoring method and system

Abstract

The present application belongs to the technical field of coking production management and control, and specifically relates to a calcium coke oven flue gas data monitoring method and system. In the present application, a pyrolysis consistency index is calculated by combining multiple parameters to judge the synchronization of pyrolysis in the whole oven. The equivalent combustion load and interlayer balance degree are calculated based on the temperature and pressure data of each flue to accurately locate the abnormal heating points in the combustion chamber. The leakage amplitude of raw coal gas is measured by the change rate of residual oxygen per unit fuel, and the leakage early warning is divided in combination with the balance degree fluctuation. The working conditions are visually displayed by trend curves and thermal diagrams, and hierarchical audible and visual alarms are automatically stored with operation logs. Without the need for additional hardware investment, the present application can accurately identify pyrolysis imbalance, flue uneven burning and oven leakage hazards, facilitate timely process control, and stabilize the production quality of coke.

Description

Technical Field

[0001] This invention relates to the field of coking production control technology, specifically a method and system for monitoring flue gas data in a calcium coke oven. Background Technology

[0002] The calcium coke oven is the core thermal equipment in briquette coking production. The high-temperature pyrolysis of briquettes in the carbonization chamber and the fuel-air combustion in the combustion chamber constitute the entire production process. The sealing status of the furnace body and the heating uniformity of each combustion chamber directly affect the quality of the finished coke. Once the furnace wall is damaged and raw coal gas leaks, it will not only disrupt the combustion balance in the furnace, but also pose a safety risk of coal gas leakage and fire. Multiple operating data such as gas composition, flue gas temperature, and pipeline static pressure in the flue are important characterizing parameters that reflect the overall production status of the furnace.

[0003] With the continuous advancement of intelligent transformation in the coal chemical industry, production management is gradually abandoning the manual management model. The demand for flue gas monitoring is constantly increasing, shifting from simple data collection to multi-indicator linkage and quantitative analysis. However, current flue gas monitoring of calcium coke ovens only achieves independent collection and display of various parameters. It cannot link multiple types of flue gas monitoring data to establish standardized quantitative analysis logic. It cannot reuse existing DCS measurement point data on site to achieve consistent calculation of pyrolysis across the entire furnace, location of combustion point deviations, and quantitative assessment of leakage risks. Furnace condition judgment highly depends on the on-site experience of operation and maintenance personnel, and the timeliness and accuracy of the judgment cannot meet the needs of modern coking refined production management.

[0004] Therefore, developing a data monitoring system for flue gas in coke ovens that can achieve multi-parameter quantitative analysis based on existing collected data has become an urgent technical problem to be solved in the field of coking production control. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for monitoring flue gas data in a calcium coke oven, so as to solve the technical defects mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a gas data monitoring system for calcium coke oven flue gas, comprising a pyrolysis consistency quantification module, a combustion deviation location module, a raw coal gas leakage early warning module, and a monitoring result output module; the pyrolysis consistency quantification module calculates and quantifies the pyrolysis consistency index and compares it with the corresponding preset steady-state threshold; The combustion deviation positioning module calculates the equivalent combustion load of a single fire channel and the interlayer balance of the combustion chamber based on the temperature and static pressure data of each fire channel and the branch pipe. It also uses the pyrolysis consistency index to distinguish between carbonization chamber leakage faults and individual fire channel heating abnormalities and pinpoints the fault location. The raw coal gas leakage early warning module calculates the unit fuel oxygen consumption parameter based on the residual oxygen content of flue gas and the total fuel flow rate, and divides the leakage early warning level by combining the parameter reduction and the pulse fluctuation characteristics of the combustion chamber balance; the monitoring result output module completes the time sequence alignment of all monitoring data, displays the furnace condition parameters through multi-dimensional visualization charts, executes differentiated audible and visual reminders according to the early warning level, and automatically archives and generates a traceable operation log. This system breaks through the limitations of traditional methods that rely on a single flue gas component to simply judge the furnace condition, cannot distinguish between pyrolysis anomalies and flue combustion faults, and can only investigate leakage risks after the fact. It establishes an integrated intelligent monitoring architecture that combines pyrolysis index quantitative calculation, layered combustion load analysis, leakage risk classification and judgment, and multimodal visualization output, realizing intelligent online monitoring of the entire process and improving the accuracy of fault identification.

[0007] Furthermore, the pyrolysis consistency quantification module uses 800℃ as the flue gas reference temperature, employs a fixed correction coefficient to complete temperature compensation calculations, and compares the pyrolysis consistency index with a preset steady-state threshold ranging from 0.02 to 0.07 to accurately quantify the degree of synchronization of the pyrolysis of coal briquettes throughout the furnace.

[0008] Furthermore, the combustion deviation positioning module uses the dispersion of equivalent combustion load of all fire channels inside a single combustion chamber to characterize the interlayer balance level, and combines the numerical characteristics of the pyrolysis consistency index to distinguish between fire channel gas supply failure and carbonization chamber raw coal gas leakage failure, thereby achieving accurate positioning of fault type and fault location.

[0009] Furthermore, the raw coal gas leakage early warning module divides the warning levels into three levels: attention, warning, and danger, based on the magnitude of the decrease in residual oxygen and the characteristic of frequent short-term spikes in the combustion chamber equilibrium index. This allows for early prediction of potential leakage hazards and timely intervention in production conditions.

[0010] Furthermore, the monitoring result output module is configured with a pyrolysis index trend chart, a flue load thermal chart, and a residual oxygen change curve, respectively. Different warning levels correspond to different light and sound prompts. The system automatically generates an operational archive record every hour and supports historical data retrieval and report export, making it convenient for maintenance personnel to intuitively view the furnace status and facilitate post-event review and analysis.

[0011] The present invention also proposes a method for monitoring flue gas data in a calcium coke oven, comprising the following steps: Step 1: Collect flue data; Step 2: Determine the consistency of pyrolysis; Step 3: Combustion deviation location; Step 4: Risk warning of leakage; Step 5: Output the results.

[0012] Compared with the prior art, the beneficial effects of the present invention are: In this invention, monitoring is achieved by collecting data from existing sensors in the coke oven's DCS, saving on retrofitting costs. Furthermore, through multi-parameter coupling and quantitative calculation, it can accurately distinguish between three types of faults: overall furnace pyrolysis imbalance, uneven heating in a single fire channel, and leakage of raw coal gas in the furnace body, thus solving the problem of difficulty in identifying the causes of faults.

[0013] In this invention, a graded early warning mechanism combined with visual charts and graded audible and visual alarms intuitively presents abnormal furnace conditions, facilitating precise process adjustments during operation and maintenance. Simultaneously, it automatically stores operation logs and supports historical data retrieval and review, which is beneficial for stabilizing coke production quality and improving the efficiency of daily safety management of coke ovens. Attached Figure Description

[0014] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings; Figure 1 This is a schematic diagram of the overall system structure of the present invention; Figure 2 This is a schematic diagram of the operation method of the present invention. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] Example 1: Refer to Figure 1 As shown in this embodiment, a gas data monitoring system for a calcium coke oven flue is proposed. This system directly calls the sensor data installed along different sections of the flue in the traditional DCS system of the calcium coke oven (such as the branch pipes before the horizontal fire channels of each combustion chamber merge into the main flue, the main flue outlet, etc.), including the flue gas temperature of each branch pipe, the flue gas temperature of the main flue, the CO concentration, CO2 concentration, O2 concentration in the flue gas, the static pressure of the flue gas, and the flow rate at the flue outlet. Breaking away from the limitations of common technologies that rely on simple assessments of furnace conditions based on a single flue gas component, cannot distinguish between pyrolysis anomalies and flue gas combustion faults, and can only investigate potential leaks after the fact, this technology achieves in-depth analysis from data to furnace conditions through the coordinated efforts of a pyrolysis consistency quantification module, a combustion deviation location module, a raw coal gas leak early warning module, and a monitoring result output module.

[0017] Among them, the pyrolysis consistency quantification module directly calls the CO volume concentration (denoted as C1, unit ppm) and CO2 volume concentration (denoted as C2, unit ppm) measured in real time by the online infrared flue gas analyzer located at the main flue outlet. It should be noted that during the stable production period of the calcium coke oven, the CO concentration in the flue gas produced by the complete combustion of fuel in the combustion chamber is extremely low. The CO in the flue gas mainly comes from the raw coal gas produced by the pyrolysis of coal briquettes in the carbonization chamber, which leaks into the combustion chamber through the gaps in the furnace wall. Its combustible components undergo incomplete oxidation in a high-temperature and oxygen-rich environment. To remove trace amounts of CO generated during the combustion process and eliminate the influence of temperature on the CO oxidation rate, a method for calculating the pyrolysis consistency index H is constructed, as follows: When calculating the pyrolysis consistency index H, first calculate the ratio of C1 to (C1+C2). This ratio reflects the proportion of CO in carbon oxides. When the pyrolysis progress of each carbonization chamber is consistent and the furnace wall is well sealed, the leakage of raw coal gas is small and stable, and this ratio is low and stable (preferably, usually below 0.05). When there is local pyrolysis over-speed or furnace wall damage that causes a large amount of raw coal gas to enter, the local lack of oxygen in the combustion chamber will cause incomplete oxidation of CO, and this ratio will increase. Then, a temperature correction term (1+k×(T-800)) is introduced: when the flue gas temperature T is higher than 800℃, the correction factor is greater than 1, and the CO ratio is appropriately amplified to reflect the situation that the CO oxidation rate is fast at high temperature and the actual leakage may be underestimated; when T is lower than 800℃, the correction factor is less than 1, which is used to compensate for the falsely high concentration caused by insufficient CO oxidation at low temperature.

[0018] That is, H = C1 / (C1+C2)×[1+k×(T-800)]; where C1 and C2 are the CO and CO2 concentrations at the main flue outlet, respectively; T is the average temperature of the mixed flue gas in the main flue, obtained by inserting a thermocouple array at the main flue outlet (average of three measurements); 800 is the reference temperature, representing the median of the typical flue gas temperature range under normal operating conditions of the calcium coke oven combustion chamber; k is the temperature correction coefficient, with a value of 0.003 / ℃ (obtained by fitting prior experimental data); The pyrolysis consistency quantification module calculates the pyrolysis consistency index H value in real time and compares the H value with the preset steady-state threshold range (preferably 0.02 to 0.07). If the H value is consistently higher than 0.07, it is determined that there is significant inconsistency in the pyrolysis of the entire furnace coal. If the H value is lower than 0.02, it may indicate that the excess air coefficient in the combustion chamber is too large or the overall pyrolysis of the coal briquette is too slow. Finally, the H value is output and transmitted to the combustion deviation positioning module.

[0019] The combustion deviation positioning module first calls the real-time temperature measured by the armored thermocouples installed at the outlet branch pipes of each horizontal fire channel (L layers) in each of the M combustion chambers of the calcium coke oven, forming an M-row L-column temperature matrix Fij, where i={1,2,...,M} is the combustion chamber index; j={1,2,...,L} is the fire channel layer index (increasing from top to bottom); Meanwhile, the static pressure of flue gas Pij of each branch pipe is obtained (obtained by the pressure transmitter installed on the branch pipe). In order to eliminate the influence of flue gas flow difference on temperature reading and highlight the essential difference of heating intensity, the "equivalent combustion load" Lij of each measuring point is calculated: Lij=(Fij-Mj)×[1+b×(Pij / Po-1)]; Where, Fij is the flue gas temperature at the outlet branch pipe of the j-th layer of the i-th combustion chamber; Mj is the median value of the flue gas temperature of the same layer of the combustion chamber (i.e., fixed j) in the entire furnace range, that is, the median value is first calculated by layer and then used for comparison of different combustion chambers in that layer; Pij is the static pressure of the flue gas at the same measuring point (Pa), Po is the standard atmospheric pressure (taken as 101325Pa); b is the pressure influence coefficient, preferably taken as 0.2.

[0020] Furthermore, in this formula, (Fij-Mj) represents the deviation of the heating intensity of the fire channel from other fire channels in the same layer. A positive value indicates that the heating is too strong, and a negative value indicates that the heating is too weak. Multiplying by the pressure correction term [1+b×(Pij / Po-1)]: when Pij is higher than the standard atmospheric pressure, the correction term is greater than 1, which means that the flue gas flow rate of the fire channel is large and the temperature is higher, which is more likely to be due to actual overheating. When Pij is lower than the standard atmospheric pressure, the correction term is less than 1, which discounts the temperature deviation.

[0021] Then, the "interlayer uniformity" Ei of each combustion chamber is calculated, defined as the standard deviation of the Lij values ​​of all fire channels in that combustion chamber: Ei = standard deviation (Li1, Li2, ..., LiL). It should be noted that the larger the Ei value, the more uneven the vertical heating of the combustion chamber. Furthermore, the Ei value is jointly analyzed with the H value from the pyrolysis consistency quantification module, as shown in the following example: If H rises abnormally (greater than 0.07) and at the same time a certain Ei (e.g., the No. 3 combustion chamber) also increases abnormally (e.g., more than twice the historical average), it is determined that the overheating of a certain fire channel in the combustion chamber caused the local pyrolysis of the adjacent carbonization chamber to be too fast, which in turn caused the raw coal gas to leak. If H is normal (between 0.02 and 0.07) but a certain Ei is abnormal, it is determined that the combustion chamber itself is not heating evenly (such as a blockage of a horizontal burner or fluctuation in gas pressure), which is unrelated to the carbonization chamber. The corresponding burner needs to be adjusted separately. Finally, the Ei value of each combustion chamber and the index of the burner with abnormality are output.

[0022] The raw coal gas leakage early warning module calls upon the dry basis O2 volume concentration W (unit: %) measured by the online zirconia oxygen analyzer located at the main flue outlet, and obtains the total dry flue gas flow rate S (unit: Nm³) from the main flue gas flow meter. 3 / h), and the total fuel gas (net gas) flow rate Q (in Nm³) entering all combustion chambers obtained from the fuel supply system DCS. 3 / h); First, calculate the actual oxygen volumetric flow rate Orem in the flue gas: Orem = S × W / 100; where, dividing by 100 is because W is a percentage concentration and needs to be converted to a decimal (e.g., 5% corresponds to 0.05). Then, calculate the residual oxygen coefficient V for each unit of fuel: V=Orem / Q; where V directly reflects the air supply and oxygen consumption balance characteristics of the combustion system; it should be noted that under normal operating conditions without raw coal gas leakage, V will remain stable within a relatively narrow range because the excess coefficient of combustion air usually remains constant. Next, retrieve the corresponding baseline value Vo and calculate the relative decrease rate R: R = (Vo - V) / Vo; It should be noted that R > 0 means that V is less than the baseline value, that is, the amount of residual oxygen in the flue gas corresponding to a unit of fuel has decreased. The reason for the decrease can only be that in addition to the normal combustion of fuel, there are additional combustible substances (i.e., leaked raw coal gas) that consume oxygen, resulting in less residual oxygen in the flue gas under the same amount of fuel and air. Therefore, the magnitude of R directly reflects the intensity of raw coal gas leakage.

[0023] Simultaneously, the Ei data between each combustion chamber is received from the combustion deviation positioning module. If R > 0.1 (i.e., V decreases by more than 10%), and the Ei of any combustion chamber shows a pulse-like increase (i.e., Ei repeatedly rises and falls over a period of time, for example, more than 3 peaks exceeding twice the average value occur within 1 hour), it is determined that there is a periodic opening and closing of thermal stress cracks caused by uneven heating, which leads to intermittent raw coal gas leakage.

[0024] Furthermore, the raw coal gas leakage early warning module can also output multi-level early warnings. Preferably, the early warning information can be directly interlocked to the combustion control system to automatically increase the excess air coefficient of the corresponding combustion chamber or reduce the heating intensity to suppress the impact of leakage. An example of the early warning output strategy is as follows: Level 1 (Caution): 0.10 < R ≤ 0.20, and all Ei fluctuations are stable, indicating a slight deviation in oxygen levels and a low risk of leakage; Level 2 (Warning): 0.20 < R ≤ 0.40, or any Ei shows a pulse-like increase, indicating a significant leakage, requiring enhanced monitoring; Level 3 (Danger): R > 0.40, or R continues to rise and any Ei remains above twice the historical average, indicating a serious leakage, requiring immediate action.

[0025] The monitoring results output module receives key indicators from the aforementioned three modules (e.g., the H value output by the pyrolysis consistency quantification module, the Ei value and abnormal fire channel index of each combustion chamber output by the combustion deviation location module, the relative decrease rate R, warning level, and associated combustion chamber number output by the raw coal gas leakage early warning module, etc.). First, it aligns all data by timestamp to form a unified monitoring data frame. Then, the monitoring results output module plots multiple trend charts on the human-machine interface (HMI) in the main control room, as shown below: The first trend chart shows the curve of H value change over the past 8 hours, and marks two threshold lines of 0.02 and 0.07. When the H value exceeds the threshold range, the curve changes color (red indicates too high, blue indicates too low). The second trend chart is in the form of a heat map. The vertical axis represents the combustion chamber number (1 to M), and the horizontal axis represents the fire channel layer number (1 to L). The color intensity of each cell represents the degree of deviation of the equivalent combustion load Lij of that fire channel from 0 (red indicates excessive heating, and blue indicates insufficient heating). At the same time, the borders of combustion chambers with Ei values ​​exceeding the threshold are thickened and flashed. The third trend chart shows the curves of V and R values ​​over the past 8 hours.

[0026] Furthermore, when a Level 3 warning is received, the monitoring result output module simultaneously triggers an audible and visual alarm: the main control room console emits a buzzer sound, the corresponding combustion chamber flashes brightly on the thermal map, and the text "Level 3 Leakage Warning - Immediate Action" is displayed in the alarm bar; a Level 2 warning triggers a flashing yellow warning light, while a Level 1 warning is only recorded in the alarm bar without triggering an sound.

[0027] In addition, the monitoring results output module automatically generates and saves an operation summary log every hour, including the average H value, the maximum Ei value and corresponding index of each combustion chamber, the maximum R value and warning level for that hour; furthermore, the monitoring results output module also provides a historical query function: operators can select any time range to replay the trends of H value, Ei heat map and R value during that period, and can export reports.

[0028] Example 2: Refer to Figure 2 As shown, the difference between this embodiment and Embodiment 1 lies in the proposed method for monitoring flue gas data in a calcium coke oven. This method utilizes sensor data from different cross-sections of the existing DCS system of the calcium coke oven, and through multi-module progressive analysis, achieves a consistent assessment of the pyrolysis of briquettes throughout the oven, locates abnormal combustion heating, and provides early warning of raw coal gas leakage risks. Finally, the monitoring results are output in a visualized form to guide operators in timely adjustments to process parameters, ensuring coke quality and production safety. The specific operation steps are as follows: Step 1: Collect flue data: Directly call up the sensor data installed along different sections of the flue in the DCS system of the calcium coke oven.

[0029] Step 2, Pyrolysis Consistency Judgment: Calculate the pyrolysis consistency index H using the CO concentration, CO2 concentration and flue gas temperature at the main flue outlet, and compare it with the preset threshold range to determine the degree of consistency of the pyrolysis of coal briquettes in the whole furnace, and output the H value.

[0030] Step 3: Combustion Deviation Location: Based on the flue gas temperature and static pressure data of each horizontal flue outlet in each combustion chamber, calculate the equivalent combustion load of each flue and the interlayer balance Ei of each combustion chamber. Combined with the H value analysis, locate the specific combustion chamber and flue layer with heating abnormality, and output the Ei value of each combustion chamber and the index of abnormal flue.

[0031] Step 4, Leakage Risk Warning: By calculating the residual oxygen content in the flue gas corresponding to each unit of fuel and its relative decrease rate R, and combining the fluctuation characteristics of the Ei value, the risk of leakage of raw coal gas is quantified.

[0032] Step 5: Output Results: Display the furnace status to the operator in the form of visual charts and audible and visual alarms, and generate an operation log for subsequent analysis.

[0033] The working principle of this invention is as follows: When in use, the pyrolysis synchronization index is calculated based on the flue gas composition and temperature. Local heating faults are identified by using the temperature and pressure data of the flue. The potential for raw coal gas leakage is quantified by combining changes in oxygen consumption with the furnace operating conditions. The monitoring data is visualized and archived with graded alarms. The entire monitoring system is based on existing on-site sensing equipment, saving the cost of adding new equipment. It can accurately identify problems such as pyrolysis imbalance, flue uneven burning, and furnace leakage, guide the dynamic optimization of combustion parameters on-site, facilitate timely optimization of the process during operation and maintenance, reduce raw coal gas leakage losses, stabilize the quality of coke production, and strengthen safety control capabilities.

[0034] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, enabling those skilled in the art to better understand and utilize it. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A data monitoring system for flue gas in a calcium coke oven, characterized in that, It includes a pyrolysis consistency quantification module, a combustion deviation location module, a raw coal gas leakage early warning module, and a monitoring result output module; The pyrolysis consistency quantification module calculates the quantified pyrolysis consistency index and compares it with the corresponding preset steady-state threshold. The combustion deviation positioning module calculates the equivalent combustion load of a single fire channel and the interlayer balance of the combustion chamber based on the temperature and static pressure data of each fire channel and the branch pipe. It also uses the pyrolysis consistency index to distinguish between carbonization chamber leakage faults and individual fire channel heating abnormalities and pinpoints the fault location. The raw coal gas leakage early warning module calculates the unit fuel oxygen consumption parameter based on the residual oxygen content of flue gas and the total fuel flow rate, and divides the leakage early warning level by combining the parameter reduction and the pulse fluctuation characteristics of the combustion chamber balance. The monitoring results output module completes the time-series alignment of all monitoring data, displays furnace condition parameters through multi-dimensional visualization charts, executes differentiated audible and visual alerts based on the warning level, and automatically archives and generates traceable operation logs.

2. The gas data monitoring system for a calcium coke oven as described in claim 1, characterized in that, The pyrolysis consistency quantification module uses 800℃ as the flue gas reference temperature, employs a fixed correction coefficient to complete the temperature compensation calculation, and compares the pyrolysis consistency index with a preset steady-state threshold ranging from 0.02 to 0.

07.

3. The gas data monitoring system for a calcium coke oven as described in claim 1, characterized in that, The combustion deviation positioning module uses the dispersion of equivalent combustion load of all fire channels inside a single combustion chamber to characterize the interlayer balance level, and combines the numerical characteristics of the pyrolysis consistency index to distinguish between fire channel gas supply failure and carbonization chamber raw coal gas leakage failure.

4. The gas data monitoring system for a calcium coke oven as described in claim 1, characterized in that, Based on the magnitude of the decrease in residual oxygen and the characteristic of frequent short-term spikes in the combustion chamber equilibrium index, the raw coal gas leakage early warning module divides the warning levels into three levels: attention, warning, and danger.

5. The gas data monitoring system for a calcium coke oven as described in claim 1, characterized in that, The monitoring result output module is configured with a pyrolysis index trend chart, a flue load thermal chart, and a residual oxygen change curve. Different warning levels correspond to different light and sound prompts. It automatically generates an operational archive record every hour and supports historical data retrieval and report export.

6. A method for monitoring flue gas data in a calcium coke oven, employing the flue gas data monitoring system for calcium coke ovens as described in any one of claims 1-5, characterized in that, Includes the following steps: Step 1: Collect flue data: Directly call up the sensor data installed along different sections of the flue in the DCS system of the calcium coke oven; Step 2, Pyrolysis Consistency Judgment: Calculate the pyrolysis consistency index H using the CO concentration, CO2 concentration and flue gas temperature at the main flue outlet, and compare it with the preset threshold range to determine the degree of consistency of the pyrolysis of coal briquettes in the whole furnace, and output the H value; Step 3: Combustion Deviation Location: Based on the flue gas temperature and static pressure data of each horizontal fire channel outlet in each combustion chamber, calculate the equivalent combustion load of each fire channel and the interlayer balance Ei of each combustion chamber. Combined with the H value analysis, locate the specific combustion chamber and fire channel layer with heating abnormality, and output the Ei value of each combustion chamber and the index of abnormal fire channel. Step 4, Leakage Risk Warning: By calculating the residual oxygen content in the flue gas corresponding to each unit of fuel and its relative decrease rate R, and combining the fluctuation characteristics of Ei value, the risk of leakage of raw coal gas is quantified. Step 5: Output Results: Display the furnace status to the operator in the form of visual charts and audible and visual alarms, and generate an operation log for subsequent analysis.

Images