Intelligent pneumatic ash conveying automatic anti-blocking control system

Abstract

The invention relates to the technical field of pneumatic conveying, and discloses an intelligent pneumatic ash conveying automatic anti-blocking control system which comprises a modeling module for establishing a mathematical model for describing system behaviors based on system analysis and data preparation results by adopting a numerical simulation method, such as computational fluid dynamics (CFD) simulation, and a self-induction module for establishing an anti-blocking control module based on the established mathematical model. A self-induction boosting system is designed, the conveying state is automatically judged according to pressure changes, a self-induction boosting valve module enables a pneumatic boosting valve to automatically judge the conveying state based on data of a self-induction module, an external electric loop is not needed in the process, self-induction and action control are achieved only through internal air pressure changes, and the conveying state is automatically judged through the self-induction boosting valve module. The intelligent pneumatic ash conveying automatic anti-blocking control system achieves the effects of automatically detecting and automatically sensing the state of the ash conveying system and forming a self-sensing pilot valve through the self-sensing module and the self-sensing boosting valve module, and achieves the effects of effectively preventing and conveying no blockage.

Description

Technical Field

[0001] The invention relates to the technical field of pneumatic conveying, in particular to an intelligent automatic anti-blocking control system for pneumatic ash conveying. Background Art

[0002] Pneumatic conveying, also known as air flow conveying, uses the energy of air flow to convey granular materials along the direction of air flow in a closed pipe. It is a specific application of fluidization technology. The pneumatic conveying system has a simple structure and is easy to operate. It can be used for horizontal, vertical or inclined conveying. During the conveying process, physical operations such as heating, cooling, drying and air flow classification of materials or certain chemical operations can also be performed simultaneously. Therefore, the ash conveying system of power plants currently mostly uses silo pumps for conveying.

[0003] Although the existing silo pump pneumatic ash conveying system is relatively mature, in actual operation, it often causes pipe blockage due to air source problems, ash source characteristics, sedimentation ash accumulation and air supply system failure, affecting system efficiency and safe operation of the unit. Traditional methods are difficult to effectively prevent and deal with pipe blockage problems. Therefore, we urgently need an intelligent pneumatic ash conveying automatic anti-blocking control system to optimize system operation and improve stability and reliability. Summary of the invention

[0004] In view of the above technical deficiencies, the purpose of the present invention is to provide an intelligent automatic anti-blocking control system for pneumatic ash conveying, which is used to solve the problem that the existing silo pump pneumatic ash conveying system proposed in the above background technology is relatively mature, but in actual operation, it often causes pipe blockage due to air source problems, ash source characteristics, sedimentation ash accumulation and air supply system failure, affecting system efficiency and safe operation of the unit. Traditional methods are difficult to effectively prevent and deal with pipe blockage.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent automatic anti-blocking control system for pneumatic ash conveying, comprising: Pressure detection module: Install high-precision pressure sensors at key locations of the pneumatic ash conveying system to collect pressure data during the conveying process in real time; Processing and analysis module: Process and analyze the collected pressure data, remove noise, detect and eliminate outliers, etc., to improve data quality; Modeling module: Use numerical simulation methods, such as computational fluid dynamics (CFD) simulation, to establish a mathematical model describing the system behavior based on the results of system analysis and data preparation; Self-sensing module: Based on the established mathematical model, a self-sensing booster system is designed to automatically determine the delivery status according to pressure changes; Self-sensing booster valve module: Based on the data from the self-sensing module, the pneumatic booster valve can automatically determine the delivery status. This process does not require an external electrical circuit, and self-perception and action control can be achieved only through changes in internal air pressure.

[0006] Preferably, the pressure detection module installs high-precision pressure sensors at key locations of the pneumatic ash conveying system (such as pipeline inlets, elbows, and points prone to clogging, etc.) to collect pressure data during the conveying process in real time and continuously, ensuring that the data used in the modeling process is the latest and most accurate, thereby improving the prediction accuracy and reliability of the model.

[0007] Preferably, the processing and analysis module pre-processes the collected data, including noise removal, outlier detection and elimination, etc., to improve data quality and lay the foundation for subsequent analysis.

[0008] Preferably, the processing and analysis module improves the accuracy of subsequent modeling and state identification input data by extracting characteristic parameters that can reflect changes in the delivery state, such as pressure peak value, pressure fluctuation frequency, pressure change trend, etc., from the pre-processed pressure data.

[0009] Preferably, the modeling module adopts numerical simulation methods, such as computational fluid dynamics (CFD) simulation, to establish a mathematical model that describes the system behavior and reflects the state changes during pneumatic conveying, so as to understand the changes in pressure during the whole process.

[0010] Preferably, the modeling module inputs the real-time collected pressure data into the trained model, and the model outputs the current delivery status judgment result based on the input data.

[0011] Preferably, the self-sensing module can perform in-depth analysis of the pressure data based on the modeling data of the modeling module, so as to accurately determine and identify the states of pneumatic conveying such as the start of conveying, normal conveying, blockage and end of conveying.

[0012] Preferably, the self-sensing booster valve module uses a pneumatic booster valve as an actuator, and based on the judgment result of the self-sensing module, it automatically starts and performs high-pressure impact to clear the blocked part.

[0013] Preferably, the self-sensing booster valve module does not require an external electrical circuit, and achieves self-sensing and action control only through changes in internal air pressure; it has a precise pneumatic control mechanism that can quickly respond to blockage signals and complete unblocking.

[0014] Compared with the prior art, the beneficial effects achieved by the present invention are: First, the present invention collects the pressure states of the pneumatic ash conveying pipeline at the beginning, normal conveying, blockage and end of conveying, and analyzes and processes the pressure data in combination with a processing and analysis module, thereby continuously improving the accuracy and real-time performance of the data, providing effective data for computer modeling, and improving the accuracy and reliability of modeling data.

[0015] Second, the present invention uses a modeling module to make the detected pressure data into a data model, which is convenient for understanding the pressure changes in the whole process of pneumatic ash conveying, and forms a self-sensing module based on these data. Then, by cooperating with the self-sensing module and the self-sensing booster valve module, the self-sensing module can detect the pressure conditions in the pneumatic ash conveying pipeline in real time, and then start the pneumatic booster valve according to the detected pressure conditions, so that the pneumatic booster valve can quickly respond to the blockage signal and perform an instantaneous high-pressure impact on the blocked part to effectively clear the blockage, thereby achieving the effect of automatic detection and automatic sensing of the ash conveying system status and forming a self-sensing pilot valve through the self-sensing module and the self-sensing booster valve module, thereby achieving the effect of effective prevention and transportation without blockage. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flowchart of the overall process of the present invention; Figure 2 This is a flowchart of the pressure detection module of the present invention; Figure 3 This is a flowchart of the processing and analysis module of the present invention; Figure 4 It is a flowchart of the modeling module of the present invention; Figure 5 This is a flowchart of the self-sensing module of the present invention; Figure 6 This is a flow chart of the self-sensing boost valve module of the present invention; DETAILED DESCRIPTION

[0017] The specific implementation modes of the present invention will be further described in detail below with reference to the accompanying drawings. Specific implementation method 1 The following is a specific implementation method of the intelligent pneumatic ash conveying automatic anti-blocking control system.

[0019] See also Figure 1-6 , intelligent pneumatic ash conveying automatic anti-blocking control system, including; 1. Pressure detection module: Install high-precision pressure sensors at key locations of the pneumatic ash conveying system to collect pressure data during the conveying process in real time; The pressure detection module installs high-precision pressure sensors at key locations of the pneumatic ash conveying system (such as pipeline inlets, elbows, and points prone to blockage, etc.) to collect pressure data during the conveying process in real time and continuously, ensuring that the data used in the modeling process is the latest and most accurate, thereby improving the prediction accuracy and reliability of the model.

[0020] By installing high-precision pressure sensors at key locations of the pneumatic ash conveying system (such as pipeline inlets, elbows, and points prone to blockage, etc.), real-time and continuous pressure data during the conveying process can be collected to provide the latest and most accurate modeling data for computer modeling, thereby improving the prediction accuracy and reliability of the model.

[0021] 2. Processing and analysis module: Process and analyze the collected pressure data, remove noise, detect and eliminate outliers, etc. to improve data quality; The processing and analysis module pre-processes the collected data, including noise removal, outlier detection and elimination, to improve data quality and lay the foundation for subsequent analysis; The processing and analysis module improves the accuracy of subsequent modeling and state identification input data by extracting characteristic parameters that can reflect changes in the delivery state, such as pressure peak, pressure fluctuation frequency, pressure change trend, etc., from the pre-processed pressure data.

[0022] Data processing and analysis plays a vital role in ensuring the accuracy and availability of data. In the data processing stage, outliers in pressure data are identified and processed through statistical methods (such as standard deviation test, IQR interquartile range method, etc.) or graphical tools (such as box plots). These outliers may be caused by measurement errors, equipment failures, etc., and need to be eliminated to ensure data accuracy. Due to the accuracy limitations of sensor equipment and the interference of environmental noise during pipeline transmission, some noise data will be generated. These data will interfere with subsequent modeling data. Therefore, by adopting noise reduction technology, the collected data is denoised to eliminate the impact of noise on data accuracy; In addition, statistical indicators such as the mean, median, and standard deviation of the pressure data were calculated to describe the basic characteristics and distribution of the data. Through time series analysis and other methods, the changing trend of pressure data over time was analyzed to predict future pressure changes. The analysis results were visualized in the form of charts and graphs to facilitate understanding and communication.

[0023] 3. Modeling module: numerical simulation methods, such as computational fluid dynamics (CFD) simulation, are used to establish a mathematical model describing the system behavior based on the results of system analysis and data preparation; The modeling module uses numerical simulation methods, such as computational fluid dynamics (CFD) simulation, to establish a mathematical model that describes the system behavior and reflects the state changes during pneumatic conveying, so as to understand the changes in pressure during the entire process; The modeling module inputs the real-time collected pressure data into the trained model, and the model outputs the current delivery status judgment result based on the input data.

[0024] The modeling module is one of the core components of the intelligent pneumatic ash conveying system state identification and automatic anti-blocking control device. It is responsible for processing and analyzing the real-time collected pressure data to establish a mathematical model between the conveying state and pressure changes. Based on the processed and analyzed data results, a mathematical model describing the system behavior is established to reflect the conveying state of the pneumatic ash conveying system, including changes in the conveying state, such as normal conveying, blockage state, and blockage warning state. The verified and optimized model is applied to the actual system to realize real-time monitoring of the pneumatic ash conveying system state and automatic anti-blocking control.

[0025] 4. Self-sensing module: Based on the established mathematical model, a self-sensing booster system is designed to automatically determine the delivery status according to the pressure change; The self-sensing module can conduct an in-depth analysis of the pressure data in the pipeline based on the modeling data of the modeling module, so as to accurately determine and identify the states of pneumatic conveying, such as the start of conveying, normal conveying, blockage and end of conveying.

[0026] In this link, the self-sensing module, as a triggering actuator, can detect the various states of conveying start, normal conveying, blockage and end of conveying during pneumatic ash conveying based on the data of the established digital model, and make decisions quickly based on the detected signals without manual intervention, realizing the system's autonomous judgment and decision-making capabilities. Through the application of the self-sensing boosting mechanism, the automation level of the pneumatic ash conveying system has been significantly improved. The system can autonomously judge, make decisions and execute anti-blocking measures, reducing the need and cost of manual intervention.

[0027] 5. Self-sensing booster valve module: Based on the data of the self-sensing module, the pneumatic booster valve can automatically determine the delivery status. This process does not require an external electrical circuit and only achieves self-sensing and action control through changes in internal air pressure; The self-sensing booster valve module uses a pneumatic booster valve as an actuator. Based on the judgment result of the self-sensing module, it automatically starts and performs high-pressure impact dredging on the blocked part; The self-sensing booster valve module does not require an external electrical circuit and achieves self-sensing and action control only through changes in internal air pressure. It has a precise pneumatic control mechanism that can quickly respond to blockage signals and complete unblocking.

[0028] In this link, through the combination with the self-sensing module, the pneumatic self-sensing booster valve is triggered immediately when the blockage signal is detected. The cooperation with the self-sensing module makes it unnecessary to have an external electrical circuit, and only realizes self-sensing and action control through internal air pressure changes. The booster valve is designed with a precise pneumatic control mechanism that can respond quickly to the blockage signal. Compressed air is used as the power source to perform an instantaneous high-pressure impact on the blocked part to effectively clear the blockage. After the blockage is cleared, the pneumatic self-sensing booster valve automatically resets to the initial state and waits for the next operation. This design ensures the continuity and stability of the system. The pneumatic self-sensing booster valve realizes the intelligent anti-blockage and efficient operation of the pneumatic ash conveying system by real-time monitoring of pressure changes, self-sensing judgment of the conveying status, automatic initiation of high-pressure impact dredging, and the formulation of intelligent control strategies.

[0029] Based on the above content, by collecting the pressure status of the pneumatic ash conveying pipeline at the beginning, normal conveying, blockage and end of conveying, and combining the processing and analysis module to analyze and process the pressure data, the accuracy and real-time performance of the data are continuously improved, providing effective data for computer modeling, and improving the accuracy and reliability of modeling data; The detected pressure data is made into a data model through the modeling module, which is convenient for understanding the pressure changes in the whole process of pneumatic ash conveying, and a self-sensing module is formed based on these data. Then, by cooperating with the self-sensing module and the self-sensing booster valve module, the self-sensing module can detect the pressure conditions in the pneumatic ash conveying pipeline in real time, and then the pneumatic booster valve is started according to the detected pressure conditions, so that the pneumatic booster valve can quickly respond to the blockage signal and perform an instantaneous high-pressure impact on the blocked part to effectively clear the blockage, thereby achieving the effect of automatic detection and automatic sensing of the ash conveying system status and forming a self-sensing pilot valve through the self-sensing module and the self-sensing booster valve module, thereby achieving the effect of effective prevention and transportation without blockage.

[0030] Although specific embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit thereof, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Intelligent automatic anti-blocking control system for pneumatic ash conveying, characterized by: include; Pressure detection module: Install high-precision pressure sensors at key locations of the pneumatic ash conveying system to collect pressure data during the conveying process in real time; Processing and analysis module: Process and analyze the collected pressure data, remove noise, detect and eliminate outliers, etc., to improve data quality; Modeling module: Use numerical simulation methods, such as computational fluid dynamics (CFD) simulation, to establish a mathematical model describing the system behavior based on the results of system analysis and data preparation; Self-sensing module: Based on the established mathematical model, a self-sensing booster system is designed to automatically determine the delivery status according to pressure changes; Self-sensing booster valve module: Based on the data from the self-sensing module, the pneumatic booster valve can automatically determine the delivery status. This process does not require an external electrical circuit and only achieves self-perception and action control through changes in internal air pressure.

2. The intelligent automatic anti-blocking control system for pneumatic ash conveying according to claim 1 is characterized by: The pressure detection module installs high-precision pressure sensors at key locations of the pneumatic ash conveying system (such as pipeline inlets, elbows, and points prone to blockage, etc.) to collect pressure data during the conveying process in real time and continuously, ensuring that the data used in the modeling process is the latest and most accurate, thereby improving the prediction accuracy and reliability of the model.

3. The intelligent automatic anti-blocking control system for pneumatic ash conveying according to claim 1 is characterized by: The processing and analysis module pre-processes the collected data, including noise removal, outlier detection and elimination, to improve data quality and lay the foundation for subsequent analysis.

4. The intelligent automatic anti-blocking control system for pneumatic ash conveying according to claim 1 is characterized by: The processing and analysis module improves the accuracy of subsequent modeling and state identification input data by extracting characteristic parameters that can reflect changes in the delivery state, such as pressure peak, pressure fluctuation frequency, pressure change trend, etc., from the pre-processed pressure data.

5. The intelligent automatic anti-blocking control system for pneumatic ash conveying according to claim 1 is characterized by: The modeling module uses numerical simulation methods, such as computational fluid dynamics (CFD) simulation, to establish a mathematical model that describes the system behavior and reflects the state changes during pneumatic conveying, thereby understanding the changes in pressure throughout the process.

6. The intelligent automatic anti-blocking control system for pneumatic ash conveying according to claim 1 is characterized by: The modeling module inputs the real-time collected pressure data into the trained model, and the model outputs the current delivery status judgment result based on the input data.

7. The intelligent automatic anti-blocking control system for pneumatic ash conveying according to claim 1 is characterized by: The self-sensing module can conduct an in-depth analysis of the pressure data based on the modeling data of the modeling module, so as to accurately determine and identify the states of pneumatic conveying, such as the start of conveying, normal conveying, blockage and end of conveying.

8. The intelligent automatic anti-blocking control system for pneumatic ash conveying according to claim 1 is characterized by: The self-sensing booster valve module uses a pneumatic booster valve as an actuator. Based on the judgment result of the self-sensing module, it automatically starts and performs high-pressure impact to clear the blocked area.

9. The intelligent automatic anti-blocking control system for pneumatic ash conveying according to claim 1 is characterized by: The self-sensing booster valve module does not require an external electrical circuit and achieves self-sensing and action control only through changes in internal air pressure. It has a precise pneumatic control mechanism that can quickly respond to blockage signals and complete unblocking.

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