Boiler fault detection method, device, equipment, storage medium and computer program product

Abstract

The application relates to the technical field of boilers, and discloses a boiler fault detection method, device, equipment, storage medium and computer program product, which comprises the following steps: in a boiler starting process, the main steam pressure and the tube bundle heating time of the boiler are monitored in real time; when the main steam pressure is lower than a minimum pressure threshold value and the tube bundle heating time exceeds a first preset threshold value, the bypass valve opening value and the through-flow valve position setting value of the boiler are acquired; and the fault detection result of the boiler is determined according to the main steam pressure, the bypass valve opening value and the through-flow valve position setting value. According to the application, the main steam pressure and the tube bundle heating time of the boiler in the starting process are monitored in real time and synchronously, the monitoring result is associated with the deviation of the bypass valve opening and the through-flow valve setting value, the accurate determination of the low-pressure and overtime heating load faults in the starting stage of the boiler is realized, and the false detection problem caused by isolated analysis of parameters is avoided.

Description

Technical Field

[0001] The present application relates to the field of boiler technology, and in particular to a boiler fault detection method, device, equipment, storage medium, and computer program product. Background Art

[0002] Boilers, as critical equipment for energy conversion and industrial production, operate under complex conditions of high temperature, high pressure, and multi-variable coupling. Failures can lead to safety incidents, downtime losses, and increased economic costs. Existing boiler systems have strong coupling and nonlinear characteristics. Traditional detection methods often rely on isolated parameter analysis or delayed dynamic response, resulting in delayed fault identification and failing to meet the requirements for high precision, real-time, and comprehensive detection. Summary of the Invention

[0003] The main purpose of this application is to provide a boiler fault detection method, device, equipment, storage medium and computer program product, aiming to solve the technical problem that traditional boiler detection methods often fail to identify faults in a timely manner due to isolated parameter analysis or delayed dynamic response.

[0004] To achieve the above objectives, the present application proposes a boiler fault detection method, which includes:

[0005] During the boiler startup process, real-time monitoring of the main steam pressure and tube bundle heating time of the boiler;

[0006] When the main steam pressure is lower than a minimum pressure threshold and the tube bundle heating time exceeds a first preset threshold, obtaining a bypass valve opening value and a flow valve position setting value of the boiler;

[0007] The fault detection result of the boiler is determined according to the main steam pressure, the bypass valve opening value and the flow valve position setting value.

[0008] Optionally, the step of determining the fault detection result of the boiler according to the main steam pressure, the bypass valve opening value and the flow valve position setting value includes:

[0009] Calculating a basic deviation based on a real-time difference between the bypass valve opening value and the flow valve position setting value;

[0010] determining fluctuation data of the main steam flow of the boiler within a specified time window according to the main steam pressure, and calculating a load change rate based on the fluctuation data;

[0011] Normalizing the basic deviation, the main steam pressure, and the load change rate, and mapping the processing results to a three-dimensional space coordinate system to generate a dynamic feature vector;

[0012] A fault detection result of the boiler is determined according to the dynamic feature vector.

[0013] Optionally, the step of determining the fault detection result of the boiler according to the dynamic feature vector includes:

[0014] Performing cluster analysis on historical fault data of the boiler to obtain fault mode clusters, wherein each cluster in the fault mode clusters represents a fault mode;

[0015] Calculating the Euclidean distance between the dynamic feature vector and each fault mode cluster to obtain a distance detection result;

[0016] The fault type of the boiler is determined according to the distance detection result, and a boiler emergency pressure relief instruction is generated.

[0017] Optionally, after the step of determining the fault detection result of the boiler according to the main steam pressure, the bypass valve opening value and the flow valve position setting value, the method further includes:

[0018] When the boiler enters the boost mode, collecting the actual main steam pressure change rate during the boiler boost process;

[0019] Calculating a dynamic deviation coefficient between the actual main steam pressure change rate and a preset pressure increase rate curve;

[0020] When the dynamic deviation coefficient exceeds the tolerance threshold and the bypass valve opening value reaches the tolerance range of the flow valve position setting value, it is determined that the boiler has a pressure combustion mismatch fault, and a fault flag is set, and a fuel supply amount correction instruction is generated.

[0021] Optionally, after the steps of determining that a pressure combustion mismatch fault occurs in the boiler, setting a fault flag, and generating a fuel supply amount correction instruction when the dynamic deviation coefficient exceeds a tolerance threshold and the bypass valve opening value reaches a tolerance range of the flow valve position setting value, the method further includes:

[0022] sending the fuel supply amount correction instruction to a target terminal;

[0023] After receiving the correction signal returned by the target terminal, collecting multiple pressure recovery values ​​from a preset adjustment period;

[0024] When all the pressure recovery values ​​meet the preset recovery conditions, the fault flag is reset and a boost process recovery confirmation signal is generated.

[0025] Optionally, after the step of determining the fault detection result of the boiler according to the main steam pressure, the bypass valve opening value and the flow valve position setting value, the method further includes:

[0026] When the boiler enters a constant pressure operation stage, a fluctuation range of a main steam pressure and a rising gradient of a turbine rotating speed are collected;

[0027] When the fluctuation range is higher than a preset fluctuation range and the rising gradient of the turbine rotating speed is lower than a preset gradient setting value, it is determined that a pressure rotating speed imbalance fault occurs in the boiler, and a rotating speed adjustment instruction is generated.

[0028] In addition, to achieve the above object, the present application further provides a boiler fault detection device, which comprises:

[0029] A data monitoring module is configured to monitor a main steam pressure and a tube bundle heating time of the boiler in real time during a boiler starting process.

[0030] A data acquisition module is configured to acquire a bypass valve opening value and a flow valve position setting value of the boiler when the main steam pressure is lower than a minimum pressure threshold value and the tube bundle heating time exceeds a first preset threshold value.

[0031] A fault judgment module is configured to determine a fault detection result of the boiler according to the main steam pressure, the bypass valve opening value and the flow valve position setting value.

[0032] In addition, to achieve the above object, the present application further provides a boiler fault detection device, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the above boiler fault detection method.

[0033] In addition, to achieve the above object, the present application further provides a storage medium, which is a computer readable storage medium, and a computer program is stored in the storage medium, and the computer program is executed by a processor to implement the steps of the above boiler fault detection method.

[0034] In addition, to achieve the above object, the present application further provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the steps of the above boiler fault detection method.

[0035] Disclosed in the application is a method for monitoring the main steam pressure and the tube bundle heating time of a boiler in a boiler startup process; when the main steam pressure is lower than a minimum pressure threshold and the tube bundle heating time exceeds a first preset threshold, obtaining the bypass valve opening value and the flow valve position setting value of the boiler; and determining the fault detection result of the boiler according to the main steam pressure, the bypass valve opening value and the flow valve position setting value. The application realizes accurate determination of low pressure and overtime heating load faults in the startup stage of the boiler by synchronously monitoring the main steam pressure and the tube bundle heating time of the boiler in the startup process in real time, and correlating the monitoring result with the deviation of the bypass valve opening and the flow valve setting value, thereby avoiding the false detection problem caused by isolated analysis of parameters. BRIEF DESCRIPTION OF DRAWINGS

[0036] The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate embodiments consistent with the present application and, together with the description, further serve to explain the principles of the application.

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced here. Obviously, for those skilled in the art, other drawings can also be obtained based on these drawings without creative labor.

[0038] Figure 1 Flowchart of the first embodiment of the boiler fault detection method of the present application;

[0039] Figure 2 Flowchart of the second embodiment of the boiler fault detection method of the present application;

[0040] Figure 3 Flowchart of the third embodiment of the boiler fault detection method of the present application;

[0041] Figure 4 Module structure diagram of the boiler fault detection device of the embodiment of the present application;

[0042] Figure 5 Device structure diagram of the hardware operating environment involved in the boiler fault detection method in the embodiment of the present application.

[0043] The object implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0044] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application, and are not used to limit the present application.

[0045] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0046] The main solution of the embodiment of the present application is: during the boiler startup process, the main steam pressure and tube bundle heating time of the boiler are monitored in real time; when the main steam pressure is lower than the minimum pressure threshold and the tube bundle heating time exceeds a first preset threshold, the bypass valve opening value and the flow valve position setting value of the boiler are obtained; and the fault detection result of the boiler is determined based on the main steam pressure, the bypass valve opening value, and the flow valve position setting value.

[0047] As key equipment for energy conversion and industrial production, boilers operate under complex conditions of high temperature, high pressure, and multi-variable coupling for extended periods. Failures can lead to safety incidents, downtime losses, and increased economic costs. With growing electricity demand and heightened environmental protection requirements, boiler systems are becoming increasingly complex, making it difficult for traditional detection methods to meet the demands for high precision, real-time performance, and comprehensiveness. For example, frequent failures such as boiler heating surface tube leakage, unstable combustion, and pressure-combustion mismatches necessitate more intelligent detection technologies to ensure safe operation. Existing detection methods, which rely on physical models or manual experience and judge faults through threshold comparison, are unable to address multi-variable coupling issues.

[0048] Therefore, this application provides a new boiler fault detection method. By real-time monitoring of main steam pressure and tube bundle heating time, and promptly obtaining relevant parameters of the bypass valve and flow valve when an anomaly occurs, this method can detect potential faults as early as possible during the boiler startup phase. Detection and early warning can be performed when a fault has just occurred or has not yet fully developed, giving operators more time to take action, preventing the fault from further deteriorating, and reducing downtime and repair costs.

[0049] It should be noted that the execution subject of this embodiment may be a computing service device with data processing and program execution functions, such as a monitoring computer, or an electronic device capable of performing the aforementioned functions. This embodiment and the following embodiments will be described below using an online boiler status detection system as an example.

[0050] Based on this, the embodiment of the present application provides a boiler fault detection method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the boiler fault detection method of the present application.

[0051] In this embodiment, the boiler fault detection method includes:

[0052] Step S10: During the boiler startup process, the main steam pressure and tube bundle heating time of the boiler are monitored in real time.

[0053] It's important to understand that main steam pressure refers to the pressure of steam in the main steam line during boiler operation, measured in megapascals (MPa). Tube bundle heat-up time refers to the time it takes for the tube bundles (such as superheaters and reheaters) to reach their desired temperature during boiler startup, from ignition. This measures the efficiency of heat transfer during boiler startup. Excessive heat-up time can lead to energy waste or the risk of equipment overheating.

[0054] It is understandable that the collection of boiler data such as main steam pressure and tube bundle heating time can be carried out through various sensors configured in the boiler.

[0055] In one example, the main steam pressure can be measured using a high-precision pressure transmitter (such as a capacitive pressure sensor) to collect real-time pressure signals within the main steam pipeline. This transmitter should be installed in the straight section of the main steam pipeline at the boiler outlet, avoiding areas prone to pressure fluctuations, such as elbows or valves. The tube bundle heating time can be measured by placing temperature measurement devices such as thermocouples or RTDs at key locations in the tube bundle (such as the superheater outlet and reheater inlet), although this embodiment does not limit this.

[0056] Step S20 : ​​When the main steam pressure is lower than a minimum pressure threshold and the tube bundle heating time exceeds a first preset threshold, obtaining a bypass valve opening value and a flow valve position setting value of the boiler.

[0057] It should be noted that the minimum pressure threshold is the minimum safe value that the main steam pressure should reach during boiler startup, such as 70% to 80% of the rated pressure. The first preset threshold is typically the upper limit of the tube bundle heating time, such as 110% to 120% of the designed heating time. The bypass valve opening value is the percentage of the bypass valve actually open. The flow valve position setting value is the target bypass valve opening value calculated by the control system based on the current load demand.

[0058] It is understandable that during the actual startup of the boiler, the main steam pressure and the tube bundle heating time may deviate from the preset pressure value and heating time due to different faults. The deviation values ​​may occur in various situations, such as the main steam pressure being lower than the minimum pressure threshold, the tube bundle heating time exceeding the first preset threshold, or both occurring simultaneously.

[0059] It should be understood that when the main steam pressure is lower than the minimum pressure threshold and the tube bundle heating time exceeds the first preset threshold, the boiler may have different failure scenarios. For example, after the boiler is ignited, the main steam pressure rises slowly but is always lower than the minimum pressure threshold. The reasons may include: insufficient fuel supply, soot accumulation in the tube bundle resulting in reduced heat exchange efficiency, erroneous opening of the bypass valve, diversion of the main steam flow, etc.

[0060] It should be understood that when the main steam pressure is lower than the minimum pressure threshold and the tube bundle heating time exceeds the first preset threshold, the cause of the boiler failure may also be leakage in the main steam pipeline or the flow valve setting value is too high, resulting in insufficient actual opening, etc.

[0061] Specifically, after detecting that the main steam pressure is lower than the minimum pressure threshold and the tube bundle heating time exceeds the first preset threshold, the valve opening can be read in real time through a position sensor (such as a linear potentiometer or encoder) deployed in the boiler, and the flow valve position setting value can be directly retrieved from the database.

[0062] Step S30: determining a fault detection result of the boiler according to the main steam pressure, the bypass valve opening value, and the flow valve position setting value.

[0063] It is understandable that the fault detection results include the judgment conclusion on whether there is a fault in the boiler and the type and severity of the fault, which can provide a basis for subsequent maintenance and adjustments.

[0064] It should be understood that fault detection results are based on a comprehensive analysis of the main steam pressure, actual bypass valve opening, and target setpoint. If the actual bypass valve opening deviates from the setpoint by more than a preset value, the fault detection may indicate a failure in diverter control due to valve jamming, actuator failure, or signal transmission lag. If the flow valve position setpoint does not match the actual load demand—for example, if the setpoint is not adjusted simultaneously with a load reduction—this can cause main steam pressure regulation to lag or overshoot.

[0065] It is understood that determining the boiler fault detection result based on the main steam pressure, the bypass valve opening value, and the flow valve position setting value can be achieved by analyzing historical data to establish a mathematical relationship model between the main steam pressure, the bypass valve opening value, and the flow valve position setting value. Based on the mathematical model and actual operating experience, thresholds corresponding to different fault types are set. When the combination of the three parameters exceeds the corresponding threshold range, a fault is determined to be present.

[0066] It is understood that the boiler fault detection result can also be determined based on an established fault rule library, associating different parameter combinations with corresponding fault types. For example, when the main steam pressure is too low and the bypass valve opening is abnormally large, a bypass valve leakage fault is determined. Of course, classification algorithms can also be used to classify faults, automatically identifying different fault modes by learning from a large amount of historical fault data.

[0067] In one example, after obtaining the bypass valve opening value and the flow valve position setting, data such as main steam pressure, bypass valve opening, combustion parameters (coal flow, air volume), and tube bundle wall temperature are input into a real-time database for feature extraction via edge computing nodes. Next, the pressure fluctuation amplitude and heating time are compared with historical operating curves to eliminate false sensor alarms and generate fault codes (such as F001 for bypass valve failure and F002 for combustion anomaly) and maintenance recommendations (such as "Check the coal feeder inverter" and "Clean superheater screens 3-5").

[0068] Furthermore, in order to synchronously monitor the main steam pressure fluctuation and turbine speed gradient during the constant pressure operation phase, identify the hidden fault of pressure-speed imbalance, generate dynamic speed control instructions to restore system balance, and avoid control lag caused by staged detection, after step S30, it also includes:

[0069] When the boiler enters the constant pressure operation stage, the fluctuation amplitude of the main steam pressure and the rising gradient of the turbine speed are collected; when the fluctuation amplitude is higher than the preset fluctuation range and the rising gradient of the turbine speed is lower than the preset gradient setting value, it is determined that the boiler has a pressure-speed imbalance fault and a speed adjustment instruction is generated.

[0070] It should be noted that the constant pressure operation stage is when the boiler reaches the rated pressure and maintains a stable main steam pressure by adjusting the fuel amount and steam flow rate, such as stable load operation of the power station boiler after being connected to the grid. The main steam pressure fluctuation amplitude is the maximum change difference of the main steam pressure per unit time, and this maximum change difference can be adjusted according to the boiler capacity and design parameters. The turbine speed rise gradient is the rate of change of the turbine speed over time. When the boiler load increases, the speed gradient should match the steam flow rate increase rate. The pressure-speed imbalance fault is a fault that occurs simultaneously with abnormal fluctuations in the main steam pressure and insufficient turbine speed response. It is usually caused by fuel regulation lag or a stuck turbine control system.

[0071] It's understood that when the boiler enters the constant-pressure operation phase, the dynamic pressure sensor records the rate of pressure change. If the rate exceeds a fixed percentage of the rated pressure for a continuous period, it is considered pressure instability. Simultaneously, the turbine speed gradient must match the load command. If the gradient falls below a preset value, it indicates a decrease in steam efficiency. The cause of the fault could be main steam valve throttling or blade fouling.

[0072] It should be understood that after determining that a pressure-speed imbalance fault occurs in the boiler, a fuzzy PID controller can be used to adjust the turbine throttle opening in real time according to the pressure-speed deviation, and simultaneously optimize boiler combustion (such as increasing the secondary air volume) to restore energy balance.

[0073] In one example, when a power plant boiler entered constant-pressure operation and the grid load suddenly increased, a piezoelectric dynamic pressure sensor detected a rapid drop in main steam pressure from 16.5 MPa (rated pressure) to 16.2 MPa. The pressure then fluctuated between 16.1 and 16.4 MPa, with a fluctuation range of 0.3 MPa, exceeding the preset ±0.1 MPa range. A magnetoelectric speed probe on the turbine shaft also monitored the speed gradient. The turbine speed increased from 3000 rpm to 3015 rpm in 10 seconds, representing a speed gradient of 1.5 rpm, below the preset 30 rpm. The system immediately identified a pressure-speed imbalance fault, presumably caused by a stuck fuel control valve, resulting in insufficient steam supply, and a delayed response from the turbine governor. The DCS then generated a speed adjustment command: a fuzzy-PID controller reduced the turbine inlet valve opening by 5% to suppress the speed increase. This control also adjusted the boiler burner's secondary air volume and triggered a variable frequency acceleration signal for the fuel pump.

[0074] In this embodiment, during boiler startup, the boiler's main steam pressure and tube bundle heat-up time are monitored in real time. When the main steam pressure falls below a minimum pressure threshold and the tube bundle heat-up time exceeds a first preset threshold, the boiler's bypass valve opening and flow valve position setting are obtained. A boiler fault detection result is determined based on the main steam pressure, bypass valve opening, and flow valve position setting. By synchronously monitoring the main steam pressure and tube bundle heat-up time during the startup process and correlating the monitoring results with the deviations between the bypass valve opening and flow valve setting, accurate detection of low pressure and excessive heating load faults during the boiler startup phase is achieved, avoiding false detections caused by isolated parameter analysis.

[0075] Reference Figure 2 , Figure 2 This is a flow chart of a second embodiment of the boiler fault detection method of the present application. Based on the above-mentioned first embodiment, the second embodiment of the boiler fault detection method of the present application is proposed.

[0076] In the second embodiment, step S30 includes:

[0077] Step S301 : calculating a basic deviation based on a real-time difference between the bypass valve opening value and the flow valve position setting value.

[0078] It should be noted that the basic deviation can quantify the severity of the bypass valve execution deviation and is used to determine whether there is valve sticking, actuator failure or control signal abnormality.

[0079] It should be understood that when collecting the bypass valve opening value, mechanical vibration interference can be eliminated through sliding average filtering.

[0080] It is understood that the basic deviation can be determined by the ratio of the difference between the bypass valve opening value and the flow valve position setting value to the flow valve position setting value. The bypass valve opening value can be obtained in real time via a position sensor, while the flow valve position setting value can be read from a database such as a DCS system or controller memory. In actual calculations, if the flow valve position setting value is 0, it is necessary to determine whether the bypass valve is mistakenly opened based on historical data and the current boiler mode.

[0081] Step S302 : determining fluctuation data of the main steam flow of the boiler within a specified time window according to the main steam pressure, and calculating the load change rate based on the fluctuation data.

[0082] It should be noted that the main steam flow rate can be calculated using a pressure-flow correlation model or determined by the main steam pressure based on historical data. The specified time window must cover the boiler load regulation cycle. For boilers that require rapid response to load changes, a shorter time window can be selected, while for boilers with relatively stable operation, a longer time window can be selected.

[0083] It can be understood that the fluctuation data can reflect the change of the main steam flow relative to its average value within a specified time window, and can be expressed as a collection of various data, such as the maximum value, minimum value, difference value, etc. of the main steam flow.

[0084] In one example, the main steam flow rate Q of the boiler is calculated using a pressure-flow correlation model using the following formula:

[0085]

[0086] Where P is the main steam pressure (MPa), T is the steam temperature (K), ρ is the steam density (kg / m 3 ), K is the flow coefficient, which is calibrated by the pipeline characteristics.

[0087] For the fluctuation data in a specified time window, the quantification method can be used to calculate the standard deviation (σ) of the flow data in the window and the peak difference (Q max -Q min ), evaluate the flow stability.

[0088] The specific load change rate is expressed as the percentage of load change per unit time, and the formula is:

[0089]

[0090] Among them, Q rated is the rated flow rate, Δt is the sampling interval. t and Q t-ΔtThe higher the load change rate, the more significant the load adjustment of the boiler is. At this time, it is necessary to pay close attention to the operating status of the boiler to ensure that all parameters are within the safe range.

[0091] Step S303 : normalizing the basic deviation, the main steam pressure, and the load change rate, and mapping the processing results to a three-dimensional space coordinate system to generate a dynamic feature vector.

[0092] It should be understood that normalization eliminates dimensional differences between parameters, bringing them to the same scale, facilitating multidimensional feature fusion and pattern recognition. A three-dimensional vector composed of normalized parameters, such as V = (x, y, z), can characterize the instantaneous characteristics of the boiler's operating state.

[0093] It's understandable that in a three-dimensional coordinate system, different coordinate axes can represent different processing results. For example, the x-axis can be defined as the normalized base deviation, the y-axis as the normalized main steam pressure, and the z-axis as the normalized load change rate. Based on the normalized results, corresponding coordinate points can be determined in the three-dimensional coordinate system. Based on these coordinate points, a dynamic feature vector can be constructed. This vector changes dynamically with the boiler's operating status, reflecting the boiler's operating characteristics in real time.

[0094] Step S304: determining a fault detection result of the boiler according to the dynamic feature vector.

[0095] It's understandable that for the three-dimensional spatial coordinate system where the dynamic eigenvectors reside, regional clustering can be performed using historical data, dividing fault mode regions and identifying the most typical fault types. Of course, to determine the severity of a fault, convolutional neural networks can also be used to analyze images of dynamic eigenvector changes and identify complex fault combinations. Furthermore, theoretical eigenvectors can be reverse-calculated using the boiler's heat balance equation and compared with actual values ​​to verify the authenticity of the fault.

[0096] Furthermore, in order to shorten the diagnosis delay, an emergency pressure relief instruction is generated to block the spread of the fault.

[0097] The step S304 may include:

[0098] Cluster analysis is performed on the historical fault data of the boiler to obtain fault mode clusters, wherein each cluster in the fault mode clusters represents a fault mode; the Euclidean distance between the dynamic feature vector and each fault mode cluster is calculated to obtain a distance detection result; the fault type of the boiler is determined based on the distance detection result, and a boiler emergency pressure relief instruction is generated.

[0099] It should be noted that the boiler's historical fault data includes pressure, temperature, valve opening, load change rate, and corresponding fault type labels. The command parameters in the boiler emergency pressure relief command include the target opening of the pressure relief valve and the pressure relief duration.

[0100] In one example, the K-means algorithm is used to cluster historical fault data (including dynamic feature vectors, pressure relief operation records, etc.), and each cluster represents a typical fault mode (such as "bypass valve stuck", "main steam leakage", "combustion oscillation", etc.).

[0101] Each cluster is described by its centroid Ci = (xi, yi, zi) and radius Ri, for example:

[0102] Cluster 1 (bypass valve stuck): C1 = (0.38, 0.92, 0.55), R1 = 0.12;

[0103] Cluster 2 (main steam leakage): C2 = (0.05, 0.65, 0.82), R2 = 0.08.

[0104] The radius Ri represents the maximum Euclidean distance within the cluster. The distance di between the real-time dynamic feature vector V = (x, y, z) and the centroid of each cluster is calculated as follows:

[0105]

[0106] If <Ri,则判定当前状态属于第i类故障模式;若同时满足多簇条件,则取最小距离的簇为优先诊断结果。

[0107] Among them, in this mode, the pressure relief triggering conditions are: 1. The fault mode is "main steam overpressure" (cluster 3) and d3<0.5R3; 2. The dynamic characteristic vector is located in the "burst risk area" (cluster 4) for 10 seconds.

[0108] The target opening of the pressure relief valve can be determined based on the fault pattern, and the pressure relief duration needs to be dynamically adjusted based on the rate of pressure drop. During the pressure relief period, the vector trajectory must be monitored in real time. If the fault cluster has not been broken, the boost stage is triggered. If the pressure relief valve fails to execute, it automatically switches to the backup pressure relief channel.

[0109] It can be understood that the rapid matching of fault modes is achieved based on the Euclidean distance calculation between the real-time dynamic feature vector and the historical fault cluster, which can shorten the diagnosis delay compared with the offline clustering method and generate emergency pressure relief instructions to block the spread of faults.

[0110] In the embodiment, a basic deviation degree is calculated based on a real-time difference between the bypass valve opening value and the bypass valve position setting value; fluctuation data of a main steam flow of the boiler in a specified time window is determined according to the main steam pressure, and a load change rate is calculated based on the fluctuation data; the basic deviation degree, the main steam pressure and the load change rate are normalized, and a processing result is mapped into a three-dimensional space coordinate system to generate a dynamic feature vector; and a fault detection result of the boiler is determined according to the dynamic feature vector. By introducing the three-dimensional dynamic feature vector, multi-dimensional parameters are normalized and mapped into a unified space, the limitation of single parameter analysis is overcome, and the sensitivity and comprehensiveness of fault detection are improved.

[0111] With reference to Figure 3 , Figure 3 FIG. 3 is a flowchart of a third embodiment of a boiler fault detection method according to the present application, which is based on the second embodiment.

[0112] In the third embodiment, after the step S30, the method further comprises:

[0113] In step S401, when the boiler enters the pressure boosting mode, an actual main steam pressure change rate in a pressure boosting process of the boiler is collected.

[0114] It can be understood that in the pressure boosting mode, the main steam pressure of the boiler increases continuously per unit time, and in an initial stage, the boiler can be allowed to rapidly boost pressure to shorten the starting time; in a middle stage, the growth rate needs to be reduced to avoid over-limiting of the tube bundle thermal stress; and in a final stage, the main steam pressure needs to be finely controlled to ensure that the pressure stably approaches a target value.

[0115] It should be understood that the pressure boosting rate needs to be matched with a tube wall temperature rise rate to prevent fatigue cracks caused by excessive temperature difference.

[0116] In an example, in the pressure boosting mode, the growth value of the main steam pressure per unit time is MPa / min. The calculation formula is:

[0117]

[0118] wherein Pt is the main steam pressure at the current time, and Pt+Δt is the main steam pressure after Δt time.

[0119] In step S402, a dynamic deviation coefficient of the actual main steam pressure change rate and a preset pressure boosting rate curve is calculated.

[0120] It should be noted that the dynamic deviation coefficient is an index that reflects the deviation degree of the actual main steam pressure change rate from the preset pressure boosting curve in real time, and can be calculated by a weighted sliding root mean square error. The preset pressure boosting rate curve is a pressure boosting rate curve determined by the system through historical data.

[0121] In one example, the actual main steam pressure change rate (dP / dt real ) and the preset curve (dP / dt set ), the weighted sliding root mean square error (RMSE) is mainly used to calculate the dynamic deviation coefficient Kd, and the formula is as follows:

[0122]

[0123] Where T is the time window, which represents the time range of the deviation coefficient; τ is the integral variable, which represents the time point from the current time t back to tT. and are the real-time boost rate and the preset boost rate at the time point τ, respectively.

[0124] w(τ) is the weight function, usually an exponential decay function w(τ) = e -0.5(t-τ) , which can give higher weight to recent deviations.

[0125] Step S403: When the dynamic deviation coefficient exceeds the tolerance threshold and the bypass valve opening value reaches the tolerance range of the flow valve position setting value, it is determined that the boiler has a pressure combustion mismatch fault, a fault flag is set, and a fuel supply amount correction instruction is generated.

[0126] It should be noted that the tolerance threshold is a pre-set allowable range of deviation coefficients, typically derived from historical empirical data. The bypass valve opening tolerance range represents the permissible deviation between the actual bypass valve opening and the set flow valve position. A pressure-combustion mismatch fault is a pressure runaway phenomenon caused by a mismatch between fuel supply and steam demand. The fault flag can indicate whether a boiler fault has occurred. Fuel supply correction instructions can include sending an opening correction signal to the fuel control valve and interlocking the activation of auxiliary burners (such as fuel oil guns) to quickly respond to pressure demands.

[0127] It can be understood that the fault flag is represented by a Boolean value stored in the control system.

[0128] Furthermore, in order to ensure the reliability of fault repair and prevent premature resetting of the fault flag from causing secondary loss of control, after step S403, the following steps are further included:

[0129] The fuel supply quantity correction instruction is sent to the target terminal; after receiving the correction signal returned by the target terminal, multiple pressure recovery values ​​are collected from a preset adjustment period; when each of the pressure recovery values ​​meets the preset recovery working condition, the fault flag is reset and a boost process recovery confirmation signal is generated.

[0130] It should be noted that the pressure recovery value is the main steam pressure value collected after the fuel correction command is executed and is used to verify whether the fault has been resolved. The preset recovery condition represents the set of conditions that the pressure recovery value must meet, including rate regression, pressure stability, and valve opening deviation compliance. The boost process recovery confirmation signal notifies the DCS system to resume the boost process.

[0131] In this embodiment, when the boiler enters boost mode, the actual main steam pressure change rate during the boiler boost process is collected; the dynamic deviation coefficient between the actual main steam pressure change rate and a preset boost rate curve is calculated; and when the dynamic deviation coefficient exceeds a tolerance threshold and the bypass valve opening value reaches the tolerance range of the flow valve position setting value, the boiler is determined to have a pressure-combustion mismatch fault, a fault flag is set, and a fuel supply correction instruction is generated. By quantifying the difference between the actual boost rate and the preset curve using the dynamic deviation coefficient and combining it with dual verification of the bypass valve opening tolerance range, a pressure-combustion mismatch fault is accurately determined, avoiding misjudgments caused by single parameter jumps, and simultaneously generating a fuel correction instruction to optimize combustion efficiency.

[0132] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the boiler fault detection method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0133] This application also provides a boiler fault detection device, please refer to Figure 4 , the boiler fault detection device comprises:

[0134] The data monitoring module 10 is used to monitor the main steam pressure and tube bundle heating time of the boiler in real time during the boiler startup process;

[0135] a data acquisition module 20 for acquiring a bypass valve opening value and a flow valve position setting value of the boiler when the main steam pressure is lower than a minimum pressure threshold and the tube bundle heating time exceeds a first preset threshold;

[0136] The fault judgment module 30 is used to determine the fault detection result of the boiler according to the main steam pressure, the bypass valve opening value and the flow valve position setting value.

[0137] The boiler fault detection device provided in this application utilizes the boiler fault detection method of the aforementioned embodiment, resolving the technical issues with conventional boiler fault detection methods, which often result in delayed fault identification due to isolated parameter analysis or delayed dynamic response. Compared to the prior art, the beneficial effects of the boiler fault detection device provided in this application are the same as those of the boiler fault detection method provided in the aforementioned embodiment. Other technical features of the boiler fault detection device are the same as those disclosed in the aforementioned embodiment and are not further elaborated here.

[0138] The present application provides a boiler fault detection device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the boiler fault detection method in the above-mentioned embodiment 1.

[0139] Reference below Figure 5 , which shows a schematic diagram of the structure of a boiler fault detection device suitable for implementing an embodiment of the present application. The boiler fault detection device in the embodiment of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 5 The boiler fault detection device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0140] like Figure 5 As shown, the boiler fault detection device may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in a read-only memory 1002 or programs loaded from a storage device 1003 into a random access memory 1004. The random access memory 1004 also stores various programs and data required for the operation of the boiler fault detection device. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are interconnected via a bus 1005. An input / output interface 1006 is also connected to the bus. Typically, the following systems may be connected to the input / output interface 1006: an input device 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, hard disk, etc.; and a communication device 1009. Communication device 1009 can allow the boiler fault detection device to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a boiler fault detection device with various systems, it should be understood that it is not required to implement or have all of the systems shown. More or fewer systems may be implemented or provided instead.

[0141] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are performed.

[0142] The boiler fault detection device provided in this application utilizes the boiler fault detection method of the aforementioned embodiment, resolving the technical issues with conventional boiler fault detection methods, which often result in delayed fault identification due to isolated parameter analysis or delayed dynamic response. Compared to the prior art, the beneficial effects of the boiler fault detection device provided in this application are the same as those of the boiler fault detection method provided in the aforementioned embodiment. Other technical features of this boiler fault detection device are the same as those disclosed in the aforementioned embodiment and are not further elaborated here.

[0143] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0144] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0145] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, a computer program) stored thereon, wherein the computer-readable program instructions are used to execute the boiler fault detection method in the above embodiment.

[0146] The computer readable storage medium provided in the present application may, for example, be a U disk, but is not limited to an electric, magnetic, optical, electromagnetic, infrared, or semiconductor system, system, or device, or any combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to, an electric connection with one or more conductive wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present embodiment, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer readable storage medium can be transmitted in any suitable medium, including but not limited to an electric wire, an optical cable, an RF (Radio Frequency), and the like, or any suitable combination of the above.

[0147] The above computer readable storage medium can be included in the boiler fault detection device, or can exist separately without being assembled into the boiler fault detection device.

[0148] The above computer readable storage medium carries one or more programs, which, when executed by the boiler fault detection device, cause the boiler fault detection device to perform the above boiler fault detection method.

[0149] Computer program code for carrying out operations of the present application can be written in one or more programming languages or combinations of languages including object oriented programming languages such as Java, Smalltalk, C++ or conventional procedural programming languages such as "C" or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0150] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of code, and the module, program segment or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, as well as the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0151] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0152] The computer-readable storage medium provided herein stores computer-readable program instructions (i.e., a computer program) for executing the boiler fault detection method described above. This computer-readable storage medium can address the technical issues associated with traditional boiler fault detection methods, which often result in delayed fault identification due to isolated parameter analysis or delayed dynamic response. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided herein are similar to those of the boiler fault detection method provided in the aforementioned embodiments and are not further elaborated here.

[0153] The present application also provides a computer program product, comprising a computer program, which implements the steps of the boiler fault detection method as described above when the computer program is executed by a processor.

[0154] The computer program product provided in this application can address the technical issues with traditional boiler detection methods, which often result in delayed fault identification due to isolated parameter analysis or delayed dynamic response. Compared to existing technologies, the beneficial effects of the computer program product provided in this application are similar to those of the boiler fault detection method provided in the aforementioned embodiments and are not further elaborated here.

[0155] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A boiler fault detection method, characterized in that: The boiler fault detection method comprises: During the boiler startup process, real-time monitoring of the main steam pressure and tube bundle heating time of the boiler; When the main steam pressure is lower than a minimum pressure threshold and the tube bundle heating time exceeds a first preset threshold, obtaining a bypass valve opening value and a flow valve position setting value of the boiler; Determining a fault detection result of the boiler according to the main steam pressure, the bypass valve opening value and the flow valve position setting value; The step of determining the fault detection result of the boiler according to the main steam pressure, the bypass valve opening value and the flow valve position setting value includes: Calculating a basic deviation based on a real-time difference between the bypass valve opening value and the flow valve position setting value; determining fluctuation data of the main steam flow of the boiler within a specified time window according to the main steam pressure, and calculating a load change rate based on the fluctuation data; Normalizing the basic deviation, the main steam pressure, and the load change rate, and mapping the processing results to a three-dimensional space coordinate system to generate a dynamic feature vector; determining a fault detection result of the boiler according to the dynamic feature vector; The step of determining the fault detection result of the boiler according to the dynamic feature vector includes: Performing cluster analysis on historical fault data of the boiler to obtain fault mode clusters, wherein each cluster in the fault mode clusters represents a fault mode; Calculating the Euclidean distance between the dynamic feature vector and each fault mode cluster to obtain a distance detection result; The fault type of the boiler is determined according to the distance detection result, and a boiler emergency pressure relief instruction is generated.

2. The boiler fault detection method according to claim 1, wherein: After the step of determining the fault detection result of the boiler according to the main steam pressure, the bypass valve opening value and the flow valve position setting value, the method further includes: When the boiler enters the boost mode, collecting the actual main steam pressure change rate during the boiler boost process; Calculating a dynamic deviation coefficient between the actual main steam pressure change rate and a preset pressure increase rate curve; When the dynamic deviation coefficient exceeds the tolerance threshold and the bypass valve opening value reaches the tolerance range of the flow valve position setting value, it is determined that the boiler has a pressure combustion mismatch fault, and a fault flag is set, and a fuel supply amount correction instruction is generated.

3. The boiler fault detection method according to claim 2, wherein: After determining that a pressure combustion mismatch fault occurs in the boiler, setting a fault flag, and generating a fuel supply amount correction instruction when the dynamic deviation coefficient exceeds a tolerance threshold and the bypass valve opening value reaches a tolerance range of the flow valve position setting value, the method further includes: sending the fuel supply amount correction instruction to a target terminal; After receiving the correction signal returned by the target terminal, collecting multiple pressure recovery values ​​from a preset adjustment period; When all the pressure recovery values ​​meet the preset recovery conditions, the fault flag is reset and a boost process recovery confirmation signal is generated.

4. The boiler fault detection method according to claim 1, wherein: After the step of determining the fault detection result of the boiler according to the main steam pressure, the bypass valve opening value and the flow valve position setting value, the method further includes: When the boiler enters the constant pressure operation stage, the fluctuation amplitude of the main steam pressure and the rising gradient of the turbine speed are collected; When the fluctuation amplitude is higher than the preset fluctuation range and the turbine speed rising gradient is lower than the preset gradient setting value, it is determined that the boiler has a pressure-speed imbalance fault and a speed adjustment instruction is generated.

5. A boiler fault detection device, characterized in that: The device comprises: A data monitoring module is used to monitor the main steam pressure and tube bundle heating time of the boiler in real time during the boiler startup process; a data acquisition module, configured to acquire a bypass valve opening value and a flow valve position setting value of the boiler when the main steam pressure is lower than a minimum pressure threshold and the tube bundle heating time exceeds a first preset threshold; a fault judgment module, configured to determine a fault detection result of the boiler according to the main steam pressure, the bypass valve opening value, and the flow valve position setting value; The fault judgment module is further configured to calculate a basic deviation based on a real-time difference between the bypass valve opening value and the flow valve position setting value; determine fluctuation data of the main steam flow of the boiler within a specified time window based on the main steam pressure, and calculate a load change rate based on the fluctuation data; perform normalization processing on the basic deviation, the main steam pressure, and the load change rate, and map the processing results to a three-dimensional spatial coordinate system to generate a dynamic feature vector; and determine a fault detection result of the boiler based on the dynamic feature vector; The fault judgment module is further used to perform cluster analysis on the historical fault data of the boiler to obtain fault mode clusters, wherein each cluster in the fault mode clusters represents a fault mode; calculate the Euclidean distance between the dynamic feature vector and each fault mode cluster to obtain a distance detection result; determine the fault type of the boiler based on the distance detection result, and generate a boiler emergency pressure relief instruction.

6. A boiler fault detection device, characterized in that: The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the boiler fault detection method according to any one of claims 1 to 4.

7. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the boiler fault detection method according to any one of claims 1 to 4 are implemented.

8. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the boiler fault detection method according to any one of claims 1 to 4 are implemented.

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