Method and system for monitoring ash removal pulse valve of dust remover

Abstract

The embodiment of the invention provides a method and system for monitoring an ash removal pulse valve of a dust remover, and the method comprises the steps: triggering a high-frequency pressure sensor to collect real-time pressure data in a compressed air main pipeline in response to a starting signal; determining an inflection point change point in the pressure change curve based on the real-time pressure data; if the deviation between the actual value of the inflection point change point and the preset inflection point value exceeds a first preset threshold value, it is determined that the device is in an open fault state; if the deviation between the pressure value, corresponding to the inflection point change point, in the pulse valve air bag and the preset pressure value is larger than a second preset threshold value, the leakage state is determined; calculating a pressure change rate based on the end point position of the real-time pressure data, and judging a fault type state according to a comparison result of the change rate and a third preset threshold value; and determining a target monitoring result based on the opening fault state, the leakage state and the fault type state of the electromagnetic pulse valve. According to the method, the fault type of the pulse valve can be timely identified, timely troubleshooting is ensured, and the energy-saving effect is achieved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, specifically to a method and system for monitoring dust collector cleaning pulse valves within the field of data processing technology. Background Technology

[0002] The electromagnetic pulse valve is a core component of baghouse dust collectors in flue gas dust removal systems, serving as the generator for the cleaning airflow in pulse-jet baghouse dust collectors. Among common cleaning methods, pulse-jet cleaning has the strongest cleaning capability; however, if the electromagnetic pulse valve malfunctions and fails to meet the jetting requirements, the cleaning effect will be significantly reduced. Within the controllable range of dust removal system operation, if electromagnetic pulse valve malfunctions can be quickly and proactively detected and resolved, the dust removal efficiency of the dust removal system can be improved, effectively preventing production downtime and reducing production losses.

[0003] Currently, fault diagnosis of electromagnetic pulse valves mainly relies on offline diagnosis of a limited number of typical faults. This method cannot pinpoint the specific location or understand the type of pulse valve fault. It is also difficult to monitor in a timely manner during the operation of the dust removal system. Therefore, it is necessary to check each electromagnetic pulse valve individually, which is time-consuming and labor-intensive, and greatly affects the normal production efficiency of enterprises. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for monitoring dust collector cleaning pulse valves, and the specific technical solution adopted is as follows: In a first aspect, embodiments of the present invention provide a method for monitoring a dust collector's cleaning pulse valve, the method comprising: Secondly, a dust collector cleaning pulse valve monitoring system is provided, the system comprising: a distributed control system, a pulse monitoring device, a high-frequency pressure sensor, and an electromagnetic pulse valve; wherein: Thirdly, a computer program product is provided, comprising: computer program code, which, when run on a computer, causes the computer to perform the method described in the first aspect.

[0005] Fourthly, a computer-readable storage medium is provided that stores computer program code, which, when executed on a computer, causes the computer to perform the method described in the first aspect.

[0006] This invention has the following beneficial effects: In response to a start signal sent by a distributed control system, a high-frequency pressure sensor is triggered to collect real-time pressure data within the main compressed air pipeline. The start signal is used to open the electromagnetic pulse valve, injecting compressed air stored in the corresponding air tank into the dust collector filter bag, facilitating subsequent accurate analysis of the electromagnetic pulse valve's status using the real-time pressure data. Subsequently, based on the real-time pressure data, inflection points in the pressure change curve are obtained. If the deviation between the actual value of the inflection point and a preset inflection point value exceeds a first preset threshold, the electromagnetic pulse valve is determined to be in an open fault state. Then, by analyzing whether the deviation between the pressure value in the pulse valve's air tank corresponding to the inflection point and a preset pressure value is greater than a second preset threshold, it is determined whether the electromagnetic pulse valve is in a leaking state. The pressure value in the pulse valve's air tank is used to characterize the average pressure change value at the inflection point. Based on the end position of the real-time pressure data, the pressure change rate is calculated using high-order polynomial fitting, and the fault type of the electromagnetic pulse valve is determined based on the comparison result between the change rate and a third preset threshold. In this way, by dynamically setting different preset inflection point values, preset pressure values, and a third preset threshold, the opening fault state, leakage state, and fault type state of the electromagnetic pulse valve can be accurately analyzed. Finally, by combining the opening fault state, leakage state, and fault type state of the electromagnetic pulse valve, the target monitoring result of the electromagnetic pulse valve is determined and fed back to the distributed control system. In this way, the fault type of the pulse valve can be identified in a timely manner, the location can be accurately located before failure, the electromagnetic pulse valve fault can be quickly eliminated, and the expansion of the fault can be effectively prevented. This reduces the energy consumption increased by the deterioration of the dust removal effect, and ensures that timely fault diagnosis achieves energy-saving effects or reduces losses from production accidents. Attached Figure Description

[0007] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0008] Figure 1 This is a schematic diagram of the composition structure of a dust collector cleaning pulse valve monitoring system provided in an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the implementation process of a dust collector cleaning pulse valve monitoring method provided in an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating an application scenario of a dust collector cleaning pulse valve monitoring method provided in an embodiment of the present invention; Figure 4This is a schematic diagram of another implementation process of a dust collector cleaning pulse valve monitoring method provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of another implementation process of a dust collector cleaning pulse valve monitoring method provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of the composition of a pulse monitoring device in a dust collector cleaning pulse valve monitoring system provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of the structure of a computer block device provided in an embodiment of the present invention. Detailed Implementation

[0009] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a dust collector cleaning pulse valve monitoring method proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments may be combined from any suitable form.

[0010] In the description of the embodiments of the present invention, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of the present invention, "multiple" means two or more.

[0011] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0012] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0013] This invention provides a dust collector cleaning pulse valve monitoring system. The specific solution of this dust collector cleaning pulse valve monitoring system is described below with reference to the accompanying drawings. Please refer to... Figure 1The diagram shows a schematic of the composition of a dust collector cleaning pulse valve monitoring system according to an embodiment of the present invention. The system includes: a distributed control system 100, a pulse monitoring device 101, a high-frequency pressure sensor 102, and an electromagnetic pulse valve 103. It may also include a compressed air main pipeline 104 and an air tank 105. The distributed control system is communicatively connected to the electromagnetic pulse valve and the pulse monitoring device, respectively; the pulse monitoring device is communicatively connected to the high-frequency pressure sensor. Here, the baghouse dust collector, as the core dust removal equipment, directly affects the dust removal efficiency and stability of the flue gas dust removal system. To ensure effective cleaning of dust from the surface of the dust collector, the flue gas dust removal system typically uses compressed air injected through a solenoid pulse valve to remove dust from the filter bags row by row. However, in related technologies, solenoid pulse valves face problems such as indistinct fault states, ambiguous fault categories, inaccurate fault locations, and difficulty in fault diagnosis and repair. These problems not only affect the normal operation of the pulse solenoid valve but also directly threaten the dust removal effect and long-term stable operation of the dust collector, seriously impacting the dust removal performance of the flue gas dust removal system.

[0014] This application provides an electromagnetic pulse valve fault status monitoring system, and the electromagnetic pulse valve fault status monitoring method is applied to the distributed control system of a flue gas dust removal system; the system also includes a high-frequency dynamic pressure sensor installed on the compressed air main pipeline, an electromagnetic pulse valve mechanically connected to the compressed air main pipeline, and a pulse monitoring device; the pulse monitoring device is communicatively connected to the high-frequency dynamic pressure sensor and the distributed system respectively. The distributed control system 100 is used to send a start signal to the electromagnetic pulse valve to drive the electromagnetic pulse valve to open, so as to inject the compressed air stored in the air tank corresponding to the electromagnetic pulse valve into the dust collector filter bag; and to synchronously send the start signal to the pulse monitoring device.

[0015] Here, multiple electromagnetic pulse valves are arranged and distributed on multiple air tanks; the distributed control system is also used to locate the fault location by driving the starting sequence of the multiple electromagnetic pulse valves. A high-frequency pressure sensor is installed in the main compressed air pipeline, and an electromagnetic pulse valve is mechanically connected to the main compressed air pipeline; the high-frequency pressure sensor is also used to monitor the real-time pressure data of the compressed air in the main pipeline.

[0016] The pulse monitoring device, in response to the start signal, uses the high-frequency pressure sensor to collect real-time pressure data within the compressed air main pipeline; based on the real-time pressure data, it determines the inflection point in the pressure change curve; if the deviation between the actual value of the inflection point and a preset inflection point value exceeds a first preset threshold, it determines that the electromagnetic pulse valve is in an open fault state; if the deviation between the pressure value in the pulse valve's air tank corresponding to the inflection point and a preset pressure value is greater than a second preset threshold, it determines that the electromagnetic pulse valve is in a leaking state; wherein, the pressure value in the pulse valve's air tank is used to characterize the average pressure change value at the inflection point; based on the end position of the real-time pressure data, it calculates the pressure change rate through high-order polynomial fitting, and determines the fault type state of the electromagnetic pulse valve based on the comparison result of the change rate and a third preset threshold; based on the open fault state, leaking state, and fault type state of the electromagnetic pulse valve, it determines the target monitoring result of the electromagnetic pulse valve.

[0017] In this embodiment of the invention, the dust collector cleaning pulse valve monitoring system can timely and effectively identify the early minor fault types of the electromagnetic pulse valve in the dust collection system, and accurately locate its position before the pulse valve completely fails. This solves the problem that the electromagnetic pulse valve has an extremely short conduction time and the fault state is difficult to capture, and eliminates the problem of installing motion state monitoring sensors inside the pulse valve and the large number of cumbersome sensors.

[0018] This invention provides a method for monitoring the cleaning pulse valve of a dust collector. The specific solution of this method is described below with reference to the accompanying drawings. Please refer to... Figure 2 The diagram illustrates a flowchart of a dust collector cleaning pulse valve monitoring method according to an embodiment of the present invention. This method can be implemented through the following steps: 201, in response to the start signal sent by the distributed control system, triggers the high-frequency pressure sensor to collect real-time pressure data in the main compressed air pipeline.

[0019] Here, after receiving the synchronization signal from the upper-level distributed control system, the pulse monitoring device triggers the pulse monitoring device data acquisition module to collect real-time pressure data of the compressed air main pipeline at high frequency.

[0020] Driven by the start signal from the distributed control system, the electromagnetic pulse valve begins operation. The distributed control system then sends a pulse valve start synchronization signal to the pulse valve intelligent monitoring device. At this time, after receiving the synchronization signal from the upper-level distributed system, the pulse monitoring device initializes the fault monitoring of the electromagnetic pulse valve, triggers the data acquisition module of the pulse monitoring device, and collects real-time pressure data in the main pipeline, thereby ensuring the real-time performance and accuracy of the compressed air pressure.

[0021] In baghouse dust collectors, a large number of electromagnetic pulse valves are usually arranged and distributed on multiple air tanks. The electromagnetic pulse valve fault monitoring method of this application can accurately locate the fault location based on the start-up sequence of the electromagnetic pulse valves driven by the distributed controller system.

[0022] After the distributed control system issues a start signal, the pulse valve opens and injects the compressed air stored in the air tank into the dust collector filter bag. The pulse width is usually 150 milliseconds (ms). The pulse valve monitoring device starts simultaneously and collects compressed air data from the high-frequency pressure sensor installed on the main pipeline at a frequency of 1000 Hz, with a collection width of X ms.

[0023] The compressed air pressure change curve collected by the high-frequency pressure sensor is shown in the figure. Figure 3 As shown, the high-frequency pressure sensor installed on the main compressed air pipeline can detect that the current pressure of the compressed air is continuously decreasing until the electromagnetic pulse valve switches from the start state to the closed state, and the pressure of the compressed air in the air tank slowly rises again as it is replenished.

[0024] 202. Based on real-time pressure data, determine the inflection point in the pressure change curve.

[0025] Here, during the continuous period of the pulse valve start signal, the real-time air pressure in the main compressed air pipeline is continuously collected by a pressure transmitter, providing accurate and reliable data support for subsequent fault monitoring of the pulse solenoid valve. The use of a high-frequency pressure sensor overcomes the problem of the extremely short pulse solenoid valve turn-on time, which makes it difficult to capture the state. It also avoids the problem of mechanical structure limiting the installation of sensors for monitoring valve movement, thus realizing effective monitoring of the pulse solenoid valve's operating status, ensuring the normal operation of the pulse solenoid valve, and maintaining the dust removal efficiency and long-term stable operation of the dust collector, ultimately significantly improving the overall dust removal performance of the flue gas dust removal system.

[0026] 203. If the deviation between the actual value of the inflection point and the preset inflection point value exceeds the first preset threshold, the electromagnetic pulse valve is determined to be in an open fault state.

[0027] Here, the high-frequency pressure sampling data from the compressed air main pipeline is cleaned to eliminate interference. The inflection point P of the pressure data from the high-frequency pressure sensor in the compressed air main pipeline is obtained, and the corresponding real-time change value is extracted. The first preset threshold can be a custom value, for example, 30%. The actual value of the inflection point is compared with the preset inflection point value of the high-frequency pressure sensor under normal conditions. If the deviation from the preset inflection point value is more than 30%, it is considered to be in a fault state.

[0028] In some possible implementations, multiple weighting factors are determined based on the number of air tanks corresponding to the electromagnetic pulse valve and the position information of the high-frequency pressure sensor (the value of the weighting factor is different depending on the number of air tanks and the position of the high-frequency pressure sensor), and a first coefficient matrix is ​​constructed using the multiple weighting factors. Finally, a preset inflection point value is calculated by combining the first coefficient matrix and the inflection point change point.

[0029] Here, a preset inflection point value is used to monitor abnormal opening states of the pulse valve. After obtaining the inflection point change values ​​(P1, P2, ..., Pn), it is compared with the coefficient matrix (H1, H2, ..., Hn (Hn=1- ... , Values ​​range from 0 to 1; weighting factor The value is related to the number of air bags and the location of the high-frequency pressure sensor. The initial threshold is obtained by fuzzy weighting. The preset inflection point value is the initial threshold plus the correction value. The correction value is an empirical observation value.

[0030] 204. If the deviation between the pressure value inside the pulse valve air tank corresponding to the inflection point is greater than the preset pressure value, it is determined that the electromagnetic pulse valve is in a leaking state.

[0031] In some possible implementations, candidate change points that satisfy a preset order are obtained from the inflection point change points; the data averaging of the candidate change points is performed to obtain the pressure value inside the pulse valve air tank.

[0032] The pressure value inside the pulse valve's air reservoir is used to characterize the average pressure change at the inflection point. The pressure change values ​​are obtained by extracting the first X1 data points from the high-frequency pressure sensor in the main compressed air pipeline, and then averaging these values ​​to obtain the pressure value J inside the pulse valve's air reservoir.

[0033] The second preset threshold can be a custom threshold, for example, set to 30%. The pressure value J inside the pulse valve's air reservoir is compared with the preset pressure value J of the high-frequency pressure sensor under normal conditions. If the deviation from the preset pressure value exceeds 30%, a leak is identified. During the duration of the pulse valve pressure acquisition signal triggered by the pulse monitoring device, the high-frequency pressure sensor acquires real-time compressed air pressure values ​​at a set acquisition frequency. The preset inflection point value, preset pressure value, and third preset threshold are all dynamically changing values.

[0034] In this embodiment of the invention, when the inflection point deviates from the preset inflection point value by more than 30%, the electromagnetic pulse valve is determined to be in an open fault state; when the pressure sensor pressure value deviates from the preset pressure value by more than 30%, a leakage state is determined. The pulse fault monitoring device can promptly identify the existing problems. These situations may affect the normal operation of the dust collector. This embodiment of the application sets up a fault warning to be issued in a timely manner when the pulse electromagnetic valve is in a faulty operating state, which can prompt maintenance personnel to take measures quickly, avoid potential safety hazards, ensure the dust removal capacity and dust collection efficiency of the dust collector, and thus significantly improve the overall dust removal performance of the flue gas dust removal system.

[0035] In some possible implementations, the preset pressure value can be achieved through the following process: First, determine the difference between the pressure value inside the pulse valve air tank and the preset initial value; second, perform fuzzy weighting processing on the difference using a second coefficient matrix to obtain a threshold difference; finally, superimpose the threshold difference with the preset initial value to obtain the preset pressure value. For example, the preset pressure value is used to monitor abnormal air tank leakage. After obtaining the pressure values ​​(J1, J2, ..., Jn) inside the pulse valve air tank, the difference obtained by comparing them with the preset initial value (Pset, i.e., the engineering setting value) is compared with the second coefficient matrix I1, I2, ..., In (In = 1- , The threshold difference is obtained by fuzzy weighting processing (values ​​0-1); the preset pressure value is the preset initial value Pset superimposed with the correction value and the threshold difference; the threshold difference value is an empirical observation value.

[0036] 205. Based on the end position of the real-time pressure data, the pressure change rate is calculated by high-order polynomial fitting, and the fault type status of the electromagnetic pulse valve is determined according to the comparison result of the change rate and the third preset threshold.

[0037] Here, data is collected and processed by a pulse monitoring device to obtain the end value Q of real-time pressure data and the corresponding pressure data. Data processing between P and Q is performed, and the pulse valve blockage fault status is analyzed by comparing the obtained value with the third preset threshold.

[0038] In some possible implementations, the third preset threshold can be set through the following process: First, obtain multiple fitting results of the electromagnetic pulse valve in the current state; second, perform fuzzy weighting processing on the multiple fitting results and the first coefficient matrix to obtain an initial threshold; finally, superimpose the correction value on the initial threshold to obtain the third preset threshold.

[0039] Here, the third preset threshold is used to monitor the blockage fault state of the electromagnetic pulse valve, and it is a range. When the electromagnetic pulse valve is in the state of pore blockage, after obtaining the above multiple end point values ​​(i.e., Qx1, Qx2, ..., Qxn), it is compared with the first coefficient matrix (i.e., K1, K2, ..., Kn (Kn=1- ... , Values ​​range from 1 to 0; Parameter The value of is related to the number of air bags and the location of the high-frequency pressure sensor. The initial threshold Bth_1' is obtained through fuzzy weighting. The third preset threshold Bth_1 is the initial threshold Bth_1' plus the correction value Bbias_1. The correction value Bbias_1 is an empirical observation value.

[0040] When the electromagnetic pulse valve is in a spring-blocked state, after obtaining the above multiple endpoint values ​​(i.e., Qy1, Qy2, ..., Qyn), they are compared with the first coefficient matrix (i.e., K1, K2, ..., Kn (Kn=1- )). , Values ​​range from 1 to 0; Parameter The value of Bth is related to the number of air bags and the location of the high-frequency pressure sensor. The initial threshold Bth_2' is obtained by fuzzy weighting. The third preset threshold Bth_2 is the initial threshold Bth_2' plus the correction value Bbias_2. The correction value Bbias_2 is an empirical observation value. The initial thresholds Bbias_1 and Bbias_2 are the upper and lower limits of the third preset threshold Bth.

[0041] In some possible implementations, firstly, polynomial fitting is performed on the final value of the real-time pressure data to obtain a fitting result. For example, PQ data processing is performed on the final value of the real-time pressure data to achieve polynomial fitting and obtain a fitting result. Secondly, based on the fitting result and weighting factors, the rate of change of the high-frequency pressure sensor is determined. Finally, based on the rate of change and the third preset threshold, the fault type state of the electromagnetic pulse valve is determined, wherein the fault type state is an air hole blockage or a spring blockage fault state.

[0042] Here, the position of the final point value Q in the real-time pressure data of the high-frequency pressure sensor in the main compressed air pipeline is obtained, the corresponding sampled real-time change value is extracted, and the corresponding pressure value is calculated; high-order polynomial fitting processing is performed on the real-time pressure sensor pressure data between P and Q, and weighting factors are used. Calculate the rate of change of the pressure sensor during this process: p(x) = p(1)*x^n + p(2)*x^(n-1) + ... + p(n)*x + p(n+1). Where, the weighting factor... It can be set based on experience or specific working conditions.

[0043] In some possible implementations, if the rate of change is greater than a preset proportion of the third preset threshold, the electromagnetic pulse valve is determined to be in a pore blockage fault state; if the rate of change is less than a preset proportion of the third preset threshold, the spring of the electromagnetic pulse valve is determined to be in a blockage fault state.

[0044] The preset ratio can be a custom ratio, for example, a preset ratio of 30%.

[0045] In one working condition of this invention embodiment, when the rate of change is greater than 30% of the third preset threshold deviation, the pulse valve is considered to be in a vent blockage fault state. The vent blockage state is caused by the pressure imbalance between the inner and outer air chambers due to the throttling guide hole of the pulse valve being blocked by dirt or the like, and the normal state is not restored in time during the pulse valve blowing process, resulting in an increase in the jet volume.

[0046] In another operating condition of this invention embodiment, when the rate of change is less than 30% of the third preset threshold deviation, it is considered a pulse valve spring blockage fault state. The spring blockage occurs when the pulse valve moving iron core is lifted under the action of electromagnetic force, the diaphragm opens, the spring extends and retracts to perform blowing. In the above situation, the spring fails to extend and retract normally, resulting in a reduction in the amount of air jet after the pulse valve starts blowing, thus failing to achieve the expected effect. The third preset threshold can be taken from an empirical value or a dynamically changing value. In this way, this invention embodiment can promptly identify the fault problem of the pulse valve, improve the identification accuracy of the pulse monitoring device, and enhance dust removal efficiency and performance.

[0047] 206. Based on the opening fault status, leakage status, and fault type status of the electromagnetic pulse valve, determine the target monitoring result of the electromagnetic pulse valve.

[0048] Here, after steps 201 to 205 above, the pulse valve monitoring device may include performing N AND operations on the fault monitoring results to obtain the target monitoring result.

[0049] In some possible implementations, multiple opening fault states, multiple leakage states, and multiple fault type states of the electromagnetic pulse valve are acquired during multiple continuous monitoring processes; the multiple opening fault states, multiple leakage states, and multiple fault type states are merged to obtain the target monitoring result and fed back to the distributed control system, so that the distributed control system outputs a reset signal; and in response to the reset signal, the electromagnetic pulse valve is reset.

[0050] Here, by performing an automatic reset operation for the solenoid pulse valve malfunction, the normal operation of the solenoid pulse valve can be quickly restored, reducing downtime caused by malfunctions.

[0051] During the N AND operations on the fault monitoring results, the results include N1 monitoring results before the pulse valve, N2 monitoring results of the pulse valve under the same operating conditions, or a mixture of N3 monitoring results.

[0052] In step 206 above, the fault monitoring results are compared, that is, the N fault monitoring results are ANDed to obtain the target monitoring result.

[0053] In this embodiment of the invention, the pulse monitoring device triggers the acquisition module to collect the pressure value of the main pipeline. When the electromagnetic pulse valve is detected to be in a fault state, the current action state of the pulse valve can be recorded as F[0]. The continuous action state of the electromagnetic pulse valve is monitored cyclically (i.e., F[1]...F[N]). The 'AND' operation is taken from the N state monitoring results, and the analysis results are further transmitted to the distributed operating system. This ensures that the state of the electromagnetic pulse valve will not interfere with the monitoring results during the evaluation of pressure change values, thereby improving the accuracy and reliability of fault monitoring. Afterwards, the fault monitoring results are reset.

[0054] In this embodiment of the invention, the pulse monitoring device receives a preset reset signal from the distributed control system and can perform an automatic reset operation of the electromagnetic pulse valve to restore its normal operation. This reduces downtime caused by malfunctions, improves the dust removal efficiency of the dust collector for the flue gas dust removal system, and reduces the need for manual intervention, thus optimizing the maintenance process.

[0055] In some possible implementations, the process for determining the target monitoring results is as follows: Figure 4 As shown: First, the distributed control system outputs a fault monitoring threshold processing signal; second, the pulse monitoring device collects real-time pressure data and processes it, executing fault monitoring steps 201 to 205; third, an AND operation is performed on the obtained multiple states to obtain the target monitoring result. If the target monitoring result indicates that the electromagnetic pulse valve is not in a fault state, the current pulse fault monitoring state ends, and the process proceeds to the next step to continue fault monitoring. If the target monitoring result indicates that the electromagnetic pulse valve is in a fault state, the process returns directly to the previous step.

[0056] In some possible implementations, the monitoring process of the electromagnetic pulse valve can also be achieved through... Figure 5 The steps shown are to be implemented as follows: The first step involves the pulse monitoring device receiving a synchronization signal, which triggers the pulse monitoring device's data acquisition module to start, and it then collects real-time pressure data from the main compressed air pipeline at high frequency.

[0057] The second step involves acquiring the inflection point P and its corresponding pressure data. Based on this acquired value, a comparative analysis of the pulse valve opening failure state is performed with the preset inflection point value. Simultaneously, the first X1 pressure data points are acquired and their average is calculated. Based on this acquired value, a comparative analysis of the leakage state is performed with the preset pressure value.

[0058] The third step is to obtain the endpoint value Q and the corresponding pressure data, and then perform data processing between P and Q.

[0059] The fourth step involves comparing the values ​​obtained from the PQ data processing with the third preset threshold to analyze the pulse valve's fault status. If the rate of change exceeds 30% of the deviation from the third preset threshold, the pulse valve is considered to be in a state of pore blockage. Simultaneously, the pulse valve's fault status is also analyzed by comparing the values ​​obtained from the PQ data processing with the third preset threshold. If the rate of change is less than 30% of the deviation from the third preset threshold, the pulse valve spring is considered to be in a state of blockage.

[0060] In some possible implementations, the pulse monitoring device is structured as follows: Figure 6 As shown, the pulse monitoring device includes: a control module 101a, a power supply module 101b, a data acquisition module 101c, a display module 101d, a storage module 101e, a trigger module 101f, and a communication module 101g. The control module 101a controls other modules and receives signals from the distributed control system. The trigger module 101f triggers the data acquisition module 101c to acquire real-time pressure data in response to a start signal from the distributed control system. The storage module 101e stores data from the pulse monitoring device during pulse valve monitoring. The display module 101d, implemented via a screen, displays the current status of the electromagnetic pulse valve for user viewing.

[0061] The distributed control system sends a start signal to drive the electromagnetic pulse valve to perform dust cleaning, and then sends a pulse valve start synchronization signal to the pulse monitoring device. At this time, after receiving the synchronization signal from the upper distributed system, the pulse monitoring device begins to initialize the electromagnetic pulse valve fault monitoring, triggers the pulse monitoring device data acquisition module, and continuously collects the compressed air main pipeline pressure data in real time within a preset time. After the preset acquisition time is completed, the pressure data is calculated and cleaned, the pulse valve monitoring device extracts the pressure data feature points, performs fault state analysis, and further stores the monitoring result R[1,1] into a recoverable storage medium (for example, stored in the storage module of the pulse monitoring device).

[0062] The distributed control system sequentially sends drive signals to drive M electromagnetic pulse valves to operate, and can monitor M results (e.g., R[1,1]-R[M,y]), which are stored sequentially in the storage module. These R[1,1]-R[M,y] monitored feature values ​​can be used as preset thresholds.

[0063] Optionally, the transmission medium can be a wired link (e.g., but not limited to, coaxial cable, optical fiber, and Digital Subscriber Line (DSL)) or a wireless link (e.g., but not limited to, Wireless Fidelity (WIFI), Bluetooth, and mobile block device networks). It should be noted that the control block device provided in the above embodiments is only an example illustrating the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer block device can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the method embodiments provided in the above embodiments belong to the same concept, and their specific implementation processes are detailed in the method embodiments, and will not be repeated here.

[0064] Figure 7 This is a schematic diagram of the structure of a computer block device provided in an embodiment of the present invention. For example, as shown... Figure 7 As shown, the computer block device 700 includes: a memory 701, a processor 702, and a computer program 703 stored in the memory 701 and running on the processor 702, wherein when the processor 702 executes the computer program 703, the computer block device can execute any of the dust collector cleaning pulse valve monitoring methods described above.

[0065] Furthermore, this embodiment of the invention also protects a control block device, which may include a memory and a processor. The memory stores executable program code, and the processor is used to call and execute the executable program code to perform a dust collector cleaning pulse valve monitoring method provided by this embodiment of the invention. This embodiment of the invention can divide the control block device into functional modules based on the above method example. For example, each module can correspond to a specific function, or two or more functions can be integrated into a processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment of the invention is illustrative and only represents a logical functional division; in actual implementation, there may be other division methods. It should be noted that all relevant content of each step involved in the above method embodiment can be referenced to the functional description of the corresponding functional module, and will not be repeated here. It should be understood that the control block device provided by this embodiment of the invention is used to execute the above-mentioned dust collector cleaning pulse valve monitoring method, and therefore can achieve the same effect as the above-mentioned implementation method. When using an integrated unit, the control block device may include a processing module and a storage module. When the control block device is applied to a block device, the processing module can be used to control and manage the actions of the block device. The storage module can be used to support block devices in executing mutual program code, etc. The processing module can be a processor or controller, which can implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this invention. The processor can also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of Digital Signal Processing (DSP) and microprocessors, etc., and the storage module can be a memory.

[0066] Furthermore, the control block device provided in the embodiments of the present invention may specifically be a chip, component, or module. The chip may include a connected processor and a memory; wherein, the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute the dust collector cleaning pulse valve monitoring method provided in the above embodiments. The embodiments of the present invention also provide a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the aforementioned method steps to implement the dust collector cleaning pulse valve monitoring method provided in the above embodiments.

[0067] This invention also provides a computer program product. When the computer program product is run on a computer, it causes the computer to execute the aforementioned related steps to implement the dust collector cleaning pulse valve monitoring method provided in the above embodiments. The control block device, computer-readable storage medium, computer program product, or chip provided in this invention are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they achieve can be referred to in the beneficial effects of the corresponding methods provided above, and will not be repeated here. Through the description of the above embodiments, those skilled in the art can understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the control block device can be divided into different functional modules to complete all or part of the functions described above. In the embodiments provided by this invention, it should be understood that the disclosed control block device and method can be implemented in other ways. For example, the control block device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another control block device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, control block device or unit, and can be electrical, mechanical or other forms.

[0068] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multiple task processing and parallel processing are possible or may be advantageous. The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. The above content is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for monitoring the dust collector cleaning pulse valve, characterized in that, The method includes: In response to a start signal sent by the distributed control system, a high-frequency pressure sensor is triggered to collect real-time pressure data in the main compressed air pipeline; wherein, the start signal is used to open the electromagnetic pulse valve and inject the compressed air stored in the air tank corresponding to the electromagnetic pulse valve into the dust collector filter bag. Based on the real-time pressure data, the inflection point in the pressure change curve is determined; If the deviation between the actual value of the inflection point and the preset inflection point value exceeds the first preset threshold, the electromagnetic pulse valve is determined to be in an open fault state. If the deviation between the pressure value inside the pulse valve air tank corresponding to the inflection point is greater than a second preset threshold, the electromagnetic pulse valve is determined to be in a leaking state; wherein, the pressure value inside the pulse valve air tank is used to characterize the average pressure change value at the inflection point. Based on the end point position of the real-time pressure data, the pressure change rate is calculated by high-order polynomial fitting, and the fault type status of the electromagnetic pulse valve is determined according to the comparison result of the change rate and the third preset threshold. Based on the opening fault status, leakage status, and fault type status of the electromagnetic pulse valve, the target monitoring result of the electromagnetic pulse valve is determined.

2. The method according to claim 1, characterized in that, The method further includes: Based on the number of air tanks corresponding to the electromagnetic pulse valve and the location information of the high-frequency pressure sensor, multiple weighting factors are determined. Based on the aforementioned weighting factors, a first coefficient matrix is ​​constructed; Based on the first coefficient matrix and the inflection point, the preset inflection point value is calculated.

3. The method according to claim 1, characterized in that, The method further includes: Obtain candidate change points that satisfy a preset order from the inflection point change points; The candidate change points are averaged to obtain the pressure value inside the pulse valve air tank.

4. The method according to claim 3, characterized in that, The method further includes: Determine the difference between the pressure value inside the pulse valve air tank and the preset initial value; The difference is fuzzily weighted using a second coefficient matrix to obtain the threshold difference. The preset pressure value is obtained by superimposing the threshold difference with the preset initial value.

5. The method according to claim 1, characterized in that, The method of calculating the pressure change rate by fitting a high-order polynomial based on the end point position of the real-time pressure data, and determining the fault type status of the electromagnetic pulse valve based on the comparison result of the change rate and a third preset threshold, includes: The final value of the real-time pressure data is subjected to polynomial fitting to obtain the fitting result. Based on the fitting results and weighting factors, the rate of change of the high-frequency pressure sensor is determined; Based on the rate of change and the third preset threshold, the fault type state of the electromagnetic pulse valve is determined, and the fault type state is either vent blockage or spring blockage.

6. The method according to claim 5, characterized in that, Determining the fault type status of the electromagnetic pulse valve based on the rate of change and the third preset threshold includes: If the rate of change is greater than a preset proportion of the third preset threshold, the electromagnetic pulse valve is determined to be in a pore blockage fault state. If the rate of change is less than a preset proportion of the third preset threshold, it is determined that the spring of the electromagnetic pulse valve is in a blocked fault state.

7. The method according to claim 6, characterized in that, The method further includes: Obtain multiple fitting results of the electromagnetic pulse valve in the current state; The multiple fitting results and the first coefficient matrix are subjected to fuzzy weighting to obtain the initial threshold. The initial threshold is superimposed with the correction value to obtain the third preset threshold.

8. The method according to claim 1, characterized in that, The method further includes: Acquire multiple opening fault states, multiple leakage states, and multiple fault type states of the electromagnetic pulse valve during multiple continuous monitoring processes; The multiple open fault states, multiple leakage states, and multiple fault type states are merged to obtain the target monitoring result and fed back to the distributed control system so that the distributed control system outputs a reset signal; In response to the reset signal, the electromagnetic pulse valve is reset.

9. A dust collector cleaning pulse valve monitoring system, characterized in that, The system includes: a distributed control system, a pulse monitoring device, a high-frequency pressure sensor, and an electromagnetic pulse valve; wherein: The distributed control system is communicatively connected to the electromagnetic pulse valve and the pulse monitoring device, respectively; the pulse monitoring device is communicatively connected to the high-frequency pressure sensor. The distributed control system is used to send a start signal to the electromagnetic pulse valve to drive the electromagnetic pulse valve to open, so as to inject the compressed air stored in the air tank corresponding to the electromagnetic pulse valve into the dust collector filter bag; and to synchronously send the start signal to the pulse monitoring device. The pulse monitoring device, in response to the start signal, uses the high-frequency pressure sensor to collect real-time pressure data within the compressed air main pipeline; based on the real-time pressure data, it determines the inflection point in the pressure change curve; if the deviation between the actual value of the inflection point and a preset inflection point value exceeds a first preset threshold, it determines that the electromagnetic pulse valve is in an open fault state; if the deviation between the pressure value in the pulse valve's air tank corresponding to the inflection point and a preset pressure value is greater than a second preset threshold, it determines that the electromagnetic pulse valve is in a leaking state; wherein, the pressure value in the pulse valve's air tank is used to characterize the average pressure change value at the inflection point; based on the end position of the real-time pressure data, it calculates the pressure change rate through high-order polynomial fitting, and determines the fault type state of the electromagnetic pulse valve based on the comparison result of the change rate and a third preset threshold; based on the open fault state, leaking state, and fault type state of the electromagnetic pulse valve, it determines the target monitoring result of the electromagnetic pulse valve.

10. The system according to claim 9, characterized in that, Multiple electromagnetic pulse valves are arranged and distributed on multiple air tanks; the distributed control system is also used to locate the fault location by driving the starting sequence of the multiple electromagnetic pulse valves. The high-frequency pressure sensor is installed in the main compressed air pipeline, and the electromagnetic pulse valve is mechanically connected to the main compressed air pipeline; the high-frequency pressure sensor is also used to monitor the real-time pressure data of the compressed air in the main pipeline.

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