A pneumatic conveying optimization control method and system based on conveying state recognition

Abstract

The application discloses a kind of pneumatic conveying optimization control method and system based on conveying state identification, pneumatic conveying state includes dilute phase, critical and dense phase, including steps: definition calculation index, set up pressure classification standard and flow classification standard in system design stage;The control unit of system receives activation sensor module after starting instruction, initializes key parameter, and establishes initial judgment benchmark, enters waiting conveying state;System enters conveying state, and control unit determines current conveying mode according to initial judgment benchmark, and the pressure and flow data of real-time acquisition are stored into memory;After each conveying ends, according to the pressure and flow data of acquisition, the pressure of conveying peak value section and the flow of conveying peak value section are taken out, and corresponding average value is stored into memory by conversion;Control unit is executed control strategy according to current conveying mode, the application has the characteristics of system stability improvement, not easy to block pipe.

Description

Technical Field

[0001] This application relates to the field of pneumatic conveying technology, specifically to a pneumatic conveying optimization control method and system based on conveying state recognition. Background Technology

[0002] Pneumatic conveying, also known as airflow conveying, utilizes the energy of airflow to transport granular materials along the airflow direction within a closed pipeline. It is a specific application of fluidization technology. Pneumatic conveying devices have a simple structure and are easy to operate. They can be used for horizontal, vertical, or inclined conveying. During the conveying process, physical operations such as heating, cooling, drying, and airflow classification of materials, or certain chemical operations, can also be performed simultaneously.

[0003] However, existing pneumatic conveying systems have the following drawbacks: In the existing technology, many pneumatic conveying systems still rely on static, preset mode switching rules, or are adjusted based solely on experience. This makes it difficult to cope with the changing material characteristics, pipeline conditions, and environmental factors, resulting in low conveying efficiency, frequent pipe blockages, and even production interruptions. Summary of the Invention

[0004] One objective of this application is to provide a pneumatic conveying optimization control method and system based on conveying state recognition that can automatically adjust the conveying mode.

[0005] To achieve the above objectives, the technical solution adopted in this application is: a pneumatic conveying optimization control method based on conveying state identification, wherein the pneumatic conveying state includes dilute phase, critical phase, and dense phase, and includes the following steps:

[0006] S100 defines the calculation indicators and establishes pressure classification standards and flow classification standards during the system design phase. The pressure classification standards and flow classification standards are planned into three levels: low, medium and high, respectively, based on the fluctuation range of pressure and flow.

[0007] S200: After receiving the start command, the system control unit activates the sensor module, initializes key parameters, establishes initial judgment criteria, and enters the waiting-for-transmission state.

[0008] S300, the system enters the conveying state. The control unit determines the current conveying mode based on the initial judgment criteria and stores the real-time collected pressure and flow data into the memory.

[0009] S400: After each delivery is completed, based on the collected pressure and flow data, extract the pressure and flow rate of the peak delivery segment, convert them into the corresponding average values, and store them in the memory.

[0010] S500, based on the current conveying mode, causes the control unit to execute a control strategy. The control strategy is based on the level of the average pressure of one or two consecutive conveying peak segments, combined with the level change trend or level distribution ratio of the average flow rate of the conveying peak segments in the most recent historical conveying records, to identify and analyze the current pneumatic conveying status, and causes the control unit to switch the conveying mode, adjust the conveying mode, or maintain the current conveying mode.

[0011] In some embodiments, when the current transport mode is dilute phase, step S500 includes:

[0012] S501, the measurement data shows that the average pressure of the peak delivery segment is at a low level. Observe the recent historical delivery records. If the average flow rate of the peak delivery segment shows a trend of gradually decreasing from high, medium and low, or the flow rate in the preset proportion of historical delivery is at a low and medium level, it indicates that the current pneumatic delivery state is in a dilute phase state. The system allows the delivery mode to be switched to a dense phase mode and stores the mode switching record in the memory.

[0013] S502, the measurement data shows that the average pressure of the peak delivery segment is at a medium level. Observe the recent historical delivery records. If the average flow rate of the peak delivery segment shows a trend of gradually decreasing from high, medium and low, or the flow rate in the preset proportion of historical delivery records is at a low and medium level, it indicates that the current pneumatic delivery state is in a dilute phase state. The system allows the delivery mode to be switched to the critical mode, while trying to move closer to the dense phase mode, and stores the mode switching record in the memory.

[0014] S503 If two consecutive measurement data show that the average pressure of the peak delivery segment is at a high level, the system will clear the previous mode switching history data and re-record it, indicating that the current pneumatic delivery state is in a dilute phase state. The system will maintain the current mode and will not switch.

[0015] In some embodiments, when the current delivery mode is dense phase, step S500 includes:

[0016] S504, the measurement data shows that the average pressure of the peak delivery segment is at a low level. If the average flow rate of the peak delivery segment shows a trend of gradually decreasing from high to medium to low, or if the flow rate in the preset proportion of historical delivery is at a low or medium level, it indicates that the current pneumatic delivery state is in a dilute phase state, and the system maintains its current state.

[0017] S505, the measurement data shows that the average pressure of the peak delivery segment is at a medium level. Observe the recent historical delivery records. If the average flow rate of the peak delivery segment shows a trend of gradually decreasing from high, medium and low, or the flow rate in the preset proportion of historical delivery records is at a low and medium level, it indicates that the current pneumatic delivery state is in a dilute phase state and is closer to the critical state. The system maintains the current state.

[0018] S506 If two consecutive measurement data show that the average pressure of the peak section of the conveying is at a high level, the system will clear the previous mode switching history data and re-record, and allow the conveying mode to actively switch to the critical mode.

[0019] S507 If pipe blockage occurs twice in a row, the system will clear the previous mode switching history data and record it again, and allow the transport mode to actively switch to dilute phase mode.

[0020] In some embodiments, when the current delivery mode is critical, step S500 includes:

[0021] S508, the measurement data shows that the average pressure of the peak delivery segment is at a low level. Observe the recent historical delivery records. If the average flow rate of the peak delivery segment shows a trend of gradually decreasing from high, medium and low, or the flow rate in the preset proportion of historical delivery records is at a low and medium level, it indicates that the current pneumatic delivery state is in a dilute phase state. The system allows the delivery mode to actively switch to a dense phase mode and stores the mode switching record in the memory.

[0022] S509, the measurement data shows that the average pressure of the peak delivery segment is at a medium level. Observing the most recent historical delivery records, if the average flow rate of the peak delivery segment shows a trend of gradually decreasing from high, medium and low, or the flow rate in the preset proportion of historical delivery records is at a low and medium level, it indicates that the current pneumatic delivery state is in a dilute phase state and is closer to the critical state. The system allows the delivery mode to actively switch to a dense phase mode and stores the mode switching record in the memory.

[0023] S510 If two consecutive measurement data show that the average pressure of the peak delivery segment is at a high level, the system will clear the previous mode switching history data and re-record it. Based on the newly recorded data, if the flow rate does not decrease significantly, the system allows the delivery mode to actively move towards the dense phase mode without triggering mode switching.

[0024] S511 If pipe blockage occurs twice in a row, the system will clear the previous mode switching history data and re-record it, and switch the delivery mode to dilute phase mode.

[0025] In some embodiments, the most recent historical transport record is required to have at least 10 data entries; if 40%-60% of the historical transport records show flow rates at low and medium levels, it indicates that the current state is dilute phase.

[0026] In some embodiments, when a blockage occurs during delivery, the pressure tends to rise, and there is no tendency for the pressure to drop throughout the process.

[0027] In some embodiments, after the system enters the delivery state, it ensures that the sum of the fluidizing gas and the delivery gas is equal to the preset delivery gas volume. Subsequently, the system converts the calculated delivery gas volume into the corresponding valve opening, while ensuring that the ratio of the delivery gas to the delivery gas volume is not less than 60%, or meets the preset minimum ratio requirement and is not less than 60%.

[0028] In some embodiments, the pressure grading standard classifies pressure fluctuation ranges [x1, x2] as medium level, pressure fluctuation ranges less than x1 as low level, and pressure fluctuation ranges greater than x2 as high level; the flow grading standard classifies flow fluctuation ranges [y1, y2] as medium level, flow fluctuation ranges less than y1 as low level, and flow fluctuation ranges greater than y2 as high level.

[0029] In some embodiments, the upper limit of flow rate when the conveying mode is dense phase < the upper limit of flow rate when the conveying mode is critical phase < the upper limit of flow rate when the conveying mode is dilute phase; the key parameters initialized by the system after receiving the start command include pressure, flow rate, valve status and conveyed gas volume; when the system initializes the key parameters, if there is historical conveying data, the historical conveying data is loaded at the same time, and an initial judgment benchmark is established; the initial judgment benchmark includes design gas volume, design output and ash gas ratio.

[0030] A pneumatic conveying system that applies any of the above-described pneumatic conveying optimization control methods based on conveying state recognition.

[0031] Compared with the prior art, the beneficial effects of this application are as follows: The pneumatic conveying optimization control method and system based on conveying state identification of this application intelligently identifies the conveying state (dilute phase, critical phase, dense phase) by introducing trend analysis of historical conveying data and dynamic monitoring of real-time conveying state, and optimizes the conveying mode in the pneumatic conveying system. This ensures that the system can automatically adjust the conveying mode under complex and variable operating conditions, so that different conveying modes can be smoothly transitioned, improving system stability and effectively preventing pipe blockage. At the same time, this technology can also automatically identify and adjust the strategy when the risk of pipe blockage increases, and dynamically optimize the conveying parameters when the conveying system is unstable, significantly improving the system's adaptability, stability and working efficiency. Detailed Implementation

[0032] The present application will be further described below with reference to specific embodiments. It should be noted that, without conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.

[0033] The terms “comprising” and “having”, and any variations thereof, in the specification and claims of this application are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0034] The following is a further explanation of this application:

[0035] This application provides a pneumatic conveying optimization control method based on conveying state identification. The pneumatic conveying state includes dilute phase, critical phase, and dense phase. Correspondingly, the conveying mode set by the system also includes dilute phase, critical phase, and dense phase. The identification and setting are mainly based on flow rate, pressure, and pipe blockage status. Theoretically, the corresponding conveying mode is suitable for forming the corresponding pneumatic conveying state in the pipeline. In actual practice, due to the influence of material characteristics, environmental conditions, and changes in pipeline status, the pneumatic conveying state may deviate from the conveying mode. Moreover, the existing technology cannot identify and control the conveying mode in a timely and accurate manner, which in turn affects the conveying efficiency and stability.

[0036] Inflexible conveying mode switching strategies can further destabilize the system. Existing pneumatic conveying systems typically employ simple setpoint control or fixed rules during mode switching, failing to make intelligent adjustments based on dynamic changes in the conveying state. For example, in critical conveying mode, the system may not adjust the airflow in time, leading to material sedimentation or a decrease in pneumatic conveying efficiency. Furthermore, it may not fully consider changes in material characteristics, which can easily affect conveying stability. Changes in parameters such as particle size, moisture content, and density of the material directly affect the selection and switching of conveying modes. Without considering changes in material characteristics, improper mode switching can easily occur, increasing the risk of pipe blockage and conveying instability.

[0037] In addition, traditional mode switching methods are prone to sudden changes in pressure and flow rate when switching from dilute phase to critical phase to dense phase, which can cause excessive impact on pipelines and equipment, shorten the service life of pipelines and valves. At the same time, sudden switching may lead to unstable delivery and even the risk of instantaneous long material plugs blocking the pipe and causing pressure buildup.

[0038] Existing pneumatic conveying systems cannot detect pipe blockage risks in real time, and their early warning mechanisms are insufficient. Traditional conveying systems mainly rely on preset thresholds to judge pipe blockage risks. However, due to the influence of various factors during the conveying process (such as pipe wear, changes in material moisture content, etc.), fixed thresholds are often difficult to adapt to complex working conditions, resulting in the system being unable to provide early warnings before pipe blockage occurs.

[0039] Existing pneumatic conveying systems lack self-adaptive and self-adjusting capabilities, making continuous optimization difficult. The control strategies of traditional pneumatic conveying systems are usually preset with fixed parameters, which cannot be optimized based on historical conveying conditions. Furthermore, they fail to fully consider energy consumption optimization, typically operating at a fixed flow rate or pressure. This may result in high energy consumption even under low load conditions, leading to energy waste. Even if the system has some abnormal or inefficient conditions, it cannot be adjusted through data, resulting in long-term low operating efficiency.

[0040] This application addresses the shortcomings of traditional pneumatic conveying systems in terms of state recognition and mode switching, pipe blockage early warning, energy consumption optimization, and material characteristic adaptability. It proposes an optimized control method and system based on conveying state recognition, which significantly improves the intelligence level and adaptability of pneumatic conveying systems.

[0041] Specifically, this application establishes a multi-dimensional transport state characteristic model by collecting key parameters such as peak average pressure, peak average flow rate, and fluidizing gas ratio during the real-time transport process and combining them with trend analysis of historical data. This model accurately identifies the three transport states: dilute phase, critical phase, and dense phase, effectively avoiding the misjudgment and switching lag problems caused by traditional systems relying on fixed thresholds or human experience. In terms of mode switching, the system adopts strategy recognition to achieve a smooth transition between states.

[0042] When the system detects that the conveying state is tilting towards a certain mode, it can dynamically adjust the air volume and air speed according to real-time monitoring data and historical conveying records to achieve a smooth transition from each mode to the optimal operating state. At the same time, when the risk of pipe blockage increases or the material characteristics change, the system can issue a timely warning and adjust the conveying parameters to reduce the pipe blockage rate and system energy consumption, and ensure the continuous and stable conveying process.

[0043] This application, through an adaptive optimization mechanism, can not only adjust parameters such as particle size, moisture content, and density of different materials in real time, but also continuously correct and optimize design parameters based on historical conveying data, thereby achieving optimal energy consumption and enhanced system adaptability during long-term operation.

[0044] In summary, this invention provides an advanced, intelligent, and efficient pneumatic conveying optimization control solution that improves conveying efficiency and equipment lifespan while significantly reducing the risk of pipe blockage and energy consumption. It provides a reliable guarantee for the stable operation of pneumatic conveying systems under complex and variable operating conditions. Through innovative methods such as conveying status recognition, intelligent mode switching, historical data analysis, and real-time data monitoring, it solves several key problems, including misjudgment of conveying modes, large impacts during mode switching, insufficient pipe blockage warnings, inadequate energy consumption optimization, and poor adaptability to material characteristics. Ultimately, it enables pneumatic conveying systems to possess higher stability, adaptability, and energy efficiency optimization capabilities, ensuring efficient, stable, and energy-saving conveying processes under various operating conditions.

[0045] To address the shortcomings of traditional pneumatic conveying systems, the optimized control method designed in this application includes the following steps.

[0046] S100 defines the calculation indicators. During the system design phase, pressure grading standards and flow grading standards are established through calculation and named as system design pressure parameters. The pressure grading standards and flow grading standards are planned into three levels: low, medium, and high, respectively, based on the fluctuation range of pressure and flow, to assist the system in identifying the delivery mode.

[0047] In some embodiments, the pressure grading standard classifies pressure fluctuation ranges [x1, x2] as medium level, pressure fluctuation ranges less than x1 as low level, and pressure fluctuation ranges greater than x2 as high level. In this application, x1 and x2 are percentage values. For example, fluctuation ranges of 90% to 115% are classified as medium level, fluctuation ranges less than 90% are classified as low level, and fluctuation ranges greater than 115% are classified as high level.

[0048] In some embodiments, the traffic grading standard classifies the traffic fluctuation range [y1, y2] as medium level, the traffic fluctuation range less than y1 as low level, and the traffic fluctuation range greater than y2 as high level. In this application, y1 and y2 are percentage values. For example, the fluctuation range of 90% to 115% is classified as medium level, the fluctuation range less than 90% is classified as low level, and the fluctuation range greater than 115% is classified as high level.

[0049] It is worth noting that the above-mentioned classification range is based on engineering experience and the perception of the degree of fluctuation in actual applications. It can be adjusted according to specific application scenarios, equipment characteristics or control precision requirements. For example, in some systems that are more sensitive to fluctuations, a narrower range (such as 95%~105%) may be used, while in systems with higher fluctuation tolerance, it may be appropriately relaxed.

[0050] S200: After receiving the start command, the system control unit enters the preparation mode, activates the sensor module, initializes key parameters, and establishes initial judgment benchmarks. The system then enters the waiting-to-convey state to respond to material conveying needs at any time.

[0051] The key parameters initialized by the system after receiving the start command include pressure, flow rate, valve status, and gas delivery volume.

[0052] When initializing key parameters of the system, if there is historical transmission data, the historical transmission data will be loaded at the same time, and an initial judgment benchmark will be established.

[0053] In this application, the initial judgment criteria include design gas volume, design output, and ash-to-gas ratio. Each system has design gas volume, design output, and ash-to-gas ratio during the design phase. The initial delivery mode can be confirmed through the above design parameters.

[0054] S300, the system enters the conveying state. The control unit determines the current conveying mode (dilute phase, critical or dense phase) based on the initial judgment criteria, and stores the real-time collected pressure and flow data into the memory for subsequent trend analysis and mode optimization adjustment.

[0055] In some embodiments, after the system enters the conveying state, it ensures that the sum of the fluidizing gas and the conveying gas is equal to the preset conveying gas volume. Subsequently, the system converts the calculated conveying gas volume into the corresponding valve opening, while ensuring that the ratio of the conveying gas to the conveying gas volume is not less than 60%, or meets the preset minimum ratio requirement and is not less than 60%, thereby ensuring the stability and efficiency of the conveying process. Since the sum of the fluidizing gas and the conveying gas is equal to the preset conveying gas volume, when the conveying gas volume value is very large, directly using 60% will make the conveying gas seem very small. In this case, using the minimum ratio is more appropriate. Generally, the design can apply the data of 60%.

[0056] After each delivery, the S400 extracts the pressure and flow rate of the peak delivery segment based on the collected pressure and flow data, converts them into corresponding average values, and stores them in the memory.

[0057] The peak delivery segment is defined as follows: within a complete delivery cycle, the change in delivery pressure can be roughly divided into three stages: first, the pressure gradually rises from 0; when the pressure approaches its maximum value, it remains relatively stable in the high-pressure zone for a period of time; finally, the pressure gradually decreases until it returns to 0, completing the entire delivery process; therefore, the peak delivery segment can be taken from the time during which the high-pressure zone remains relatively stable and continuous.

[0058] S500, based on the current conveying mode, causes the control unit to execute a control strategy. The control strategy is based on the level of the average pressure of one or two consecutive conveying peak segments, combined with the level change trend or level distribution ratio of the average flow rate of the conveying peak segments in the most recent historical conveying records (each complete conveying cycle is considered as one statistic), to identify and analyze the current pneumatic conveying status, and causes the control unit to switch the conveying mode, adjust the conveying mode, or maintain the current conveying mode.

[0059] In some embodiments, at least 10 recent historical delivery records are required. If the sample size is too small, the representativeness of the data will be reduced, the data will fluctuate greatly, and it will be difficult to reflect the true operating trend of the system, which may easily lead to misjudgment. Considering the periodicity and phased characteristics of the delivery task, 10 or more data records are needed to cover the fluctuation characteristics of a complete work cycle.

[0060] If 40%-60% of the historical transport records show flow rates at low and medium levels, it indicates that the current condition is dilute phase.

[0061] In some embodiments, if 45%-55% of the historical transport records show flow rates at low and medium levels, it indicates that the current state is sparse. Preferably, it is 50%, which can reflect recent operating trends while filtering out older data that is too early and has no reference value. 50% is an empirical value that strikes a balance between stability and real-time performance.

[0062] In this application, the corresponding relationship between the upper limit of flow rate for each transport mode is as follows: upper limit of flow rate when transport mode is dense phase < upper limit of flow rate when transport mode is critical phase < upper limit of flow rate when transport mode is dilute phase.

[0063] When the current transport mode is dilute phase, step S500 includes the following steps.

[0064] S501, the measurement data shows that the average pressure of the peak delivery segment is at a low level. Observing the most recent historical delivery records, if the average flow rate of the peak delivery segment shows a trend of gradually decreasing from high to medium to low (specifically, it can be a trend of gradually decreasing from high to medium and then to low), or the flow rate of a preset proportion (nearly 50%) of the historical delivery is at a low or medium level, it indicates that the current pneumatic delivery state is in a dilute phase state. The system allows the delivery mode to be switched to a dense phase mode (which can be switched or not). By reducing the gas velocity and appropriately increasing the material supply, the high concentration delivery demand can be met. At the same time, pipe blockage control measures are strengthened, and the mode switching record is stored in the memory.

[0065] S502, the measurement data shows that the average pressure of the peak delivery segment is at a medium level. Observing the most recent historical delivery records, if the average flow rate of the peak delivery segment shows a trend of gradually decreasing from high to medium to low (specifically, it can be a trend of gradually decreasing from high to medium and then to low), or if the flow rate in a preset proportion (nearly 50%) of the historical delivery records is at a low or medium level, it indicates that the current pneumatic delivery state is in a dilute phase state. The system allows the delivery mode to be switched to the critical mode (which can be switched or not). By reducing the gas velocity and appropriately increasing the material supply, the system can meet the high concentration delivery demand, while trying to move closer to the dense phase mode, and storing the mode switching record in the memory.

[0066] S503 If two consecutive measurement data show that the average pressure of the peak delivery segment is at a high level (regardless of whether the flow rate remains high or slightly decreases), the system will clear the previous mode switching history data and re-record. This indicates that the current pneumatic delivery state is in a dilute phase state. At this time, it means that the pressure in the dilute phase mode is generally high, and the pressure in other modes is even higher. Therefore, the system should maintain the current mode and not switch. In addition, if a single measurement data shows that the average pressure of the peak delivery segment is at a high level, it will be treated as an accidental event and no operation will be performed.

[0067] It is worth noting that if it is the first delivery, or the first delivery after clearing the switching history, and the flow rate in the historical delivery is at a low or medium level according to the preset ratio, the number of delivery records does not meet the judgment logic at this time, so no operation is performed. The system should maintain the current mode and continue delivery until the delivery records meet the judgment logic. The same applies to the control strategy for other delivery modes.

[0068] When the current transport mode is dense phase, step S500 includes the following steps.

[0069] S504, the measurement data shows that the average pressure of the peak delivery segment is at a low level. Observing the most recent historical delivery records, if the average flow rate of the peak delivery segment shows a trend of gradually decreasing from high to medium to low (specifically, it can be a trend of gradually decreasing from high to medium and then to low), or if the flow rate of a preset proportion (nearly 50%) of the historical delivery is at a low or medium level, it indicates that the current pneumatic delivery state is in a dilute phase state. At this time, the system believes that such a low pressure and flow rate distribution should not occur in a dense phase state, so the delivery mode is not switched and the system maintains the current state.

[0070] S505, the measurement data shows that the average pressure of the peak delivery segment is at a medium level. Observing the most recent historical delivery records, if the average flow rate of the peak delivery segment shows a trend of gradually decreasing from high to medium to low (specifically, it can be a trend of gradually decreasing from high to medium and then to low), or if the flow rate in a preset proportion (nearly 50%) of the historical delivery records is at a low or medium level, it indicates that the current pneumatic delivery state is in a dilute phase state and is closer to the critical state. At this time, the system considers the state to be within a controllable range, does not trigger mode switching, and the system maintains the current state.

[0071] S506 If two consecutive measurement data show that the average pressure of the peak delivery segment is at a high level (regardless of whether the flow rate remains high or slightly decreases), the system will clear the previous mode switching history data and re-record. At this time, it indicates that the pressure in the current dense phase mode is generally high. The system judges that the risk of overload is increasing and allows the delivery mode to actively switch to the critical mode to reduce the pressure risk of the delivery system and improve the delivery status. In addition, if a single measurement data shows that the average pressure of the peak delivery segment is at a high level, it will be treated as an accidental event and no operation will be performed.

[0072] S507 If two consecutive pipe blockages occur (regardless of whether the flow rate remains high or slightly decreases, when a pipe blockage occurs during the conveying process, the pressure curve usually shows a continuous upward trend: the pressure gradually increases from zero in the initial stage, there may be a brief period of stability, but it will continue to rise afterward; there will be no downward pressure trend throughout the process, and the system can judge the pipe blockage based on this logic), the system will clear the previous mode switching history data and re-record. At this time, it indicates that the pressure is abnormal and the risk of pipe blockage is extremely high in the dense phase mode. The system judges that the overload is too large and allows the conveying mode to actively switch to the dilute phase mode to quickly stabilize the conveying process. In addition, if only one pipe blockage occurs, it is treated as an accidental event and no operation is performed.

[0073] When the current conveying mode is critical, step S500 includes the following steps.

[0074] S508, the measurement data shows that the average pressure of the peak delivery segment is at a low level. Observing the most recent historical delivery records, if the average flow rate of the peak delivery segment shows a trend of gradually decreasing from high to medium to low (specifically, it can be a trend of gradually decreasing from high to medium and then to low), or if the flow rate in a preset proportion (nearly 50%) of the historical delivery records is at a low or medium level, it indicates that the current pneumatic delivery state is in a dilute phase state. The system allows the delivery mode to actively switch to a dense phase mode, by reducing the gas velocity and appropriately increasing the material supply to meet the high concentration delivery demand, while strengthening the pipe blockage control measures, and storing the mode switching record in the memory.

[0075] S509, the measurement data shows that the average pressure of the peak delivery segment is at a medium level. Observing the most recent historical delivery records, if the average flow rate of the peak delivery segment shows a trend of gradually decreasing from high to medium to low (specifically, it can be a trend of gradually decreasing from high to medium and then to low), or if the flow rate in a preset proportion (nearly 50%) of the historical delivery records is at a low or medium level, it indicates that the current pneumatic delivery state is in a dilute phase state and is closer to the critical state. The system allows the delivery mode to actively switch to a dense phase mode, by reducing the gas velocity and appropriately increasing the material supply to meet the high concentration delivery demand, while strengthening the pipe blockage control measures, and storing the mode switching record in the memory.

[0076] S510 If two consecutive measurement data show that the average pressure of the peak delivery segment is at a high level (regardless of whether the flow rate remains high or slightly decreases), the system will clear the previous mode switching history data and re-record. This indicates that the current delivery state is gradually tilting towards the dense phase, and the risk of pressure overload is increasing. Based on the newly recorded data, if the flow rate does not decrease significantly, the system allows the delivery mode to actively move towards the dense phase mode without triggering mode switching, maintaining the current state unchanged.

[0077] S511 If two consecutive pipe blockages occur (regardless of whether the flow rate remains high or slightly decreases), the system will clear the previous mode switching history data and re-record. At this time, it indicates that the pressure is abnormal and the risk of pipe blockage is extremely high in the dense phase mode. The system judges that the overload is too large and switches the conveying mode to the dilute phase mode to quickly stabilize the conveying process.

[0078] This application also provides a pneumatic conveying system that applies the pneumatic conveying optimization control method based on conveying state recognition of any of the above embodiments.

[0079] The control unit collects conveying data in real time through pressure and flow sensors, and combines historical conveying trend analysis and dynamic monitoring to achieve intelligent identification and optimization of the conveying mode. When the material characteristics change, the system can adaptively adjust and precisely control the gradual transition from dilute phase to critical phase to dense phase, dense phase to critical phase to dilute phase, dilute phase to dense phase, and dense phase to dilute phase. At the same time, it can detect the risk of pipe blockage in real time, ensuring stable and efficient conveying process, optimizing energy consumption, and improving the system's self-adjustment capability, so that the conveying mode is always in the best operating state.

[0080] This optimized configuration enables the present application to accurately and efficiently implement a pneumatic conveying optimization control method and system based on conveying state recognition, providing a more stable and efficient intelligent control scheme for the conveying process. By integrating the dynamic change patterns of pressure, flow rate and system design parameters, the present application ensures that the pneumatic conveying system can autonomously identify and optimize the conveying mode under different operating conditions, thereby improving the system's adaptability and enhancing the stability and efficiency of the conveying process.

[0081] The basic principles, main features, and advantages of this application have been described above. Those skilled in the art should understand that this application is not limited to the above embodiments. The embodiments and descriptions in the specification are only the principles of this application. Various changes and modifications can be made to this application without departing from the spirit and scope of this application. All such changes and modifications fall within the scope of this application as claimed. The scope of protection claimed by this application is defined by the appended claims and their equivalents.

Claims

1. A method of pneumatic conveying optimization control based on conveying regime identification, the pneumatic conveying regimes comprising dilute, critical and dense phases, the conveying modes comprising dilute, critical and dense phases, characterized in that, The method comprises the steps of: S100, defining a calculation index, setting a pressure grading standard and a flow grading standard in a system design stage, the pressure grading standard and the flow grading standard being respectively planned into three levels of low, medium and high according to fluctuation ranges of pressure and flow; S200, after receiving a starting instruction, a control unit of the system activates a sensor module, initializes key parameters, and establishes an initial judgment benchmark, and enters a waiting conveying state; S300, the system enters a conveying state, the control unit determines a current conveying mode according to the initial judgment benchmark, and stores real-time collected pressure and flow data into a storage; S400, after each conveying is completed, according to the collected pressure and flow data, pressure of a conveying peak value section and flow of the conveying peak value section are taken out and converted into corresponding average values and stored into the storage; S500, the control unit executes a control strategy according to the current conveying mode, the control strategy is based on the average pressure level of the conveying peak value section once or twice in succession, and combines the average flow level change trend or level distribution proportion of the conveying peak value section in the recent historical conveying record, to identify and analyze the current pneumatic conveying state, and to make the control unit switch the conveying mode, adjust the conveying mode or keep the current conveying mode.

2. The pneumatic conveying optimization control method based on conveying state recognition of claim 1, wherein, When the current conveying mode is a dilute phase, the step S500 comprises: S501, the measurement data show that the average pressure of the conveying peak value section is at a low level, the recent historical conveying record is observed, if the average flow of the conveying peak value section presents a gradually descending trend from high, medium to low, or the flow in a preset proportion of historical conveyings is at a low level and a medium level, it is indicated that the current pneumatic conveying state is in a dilute phase state, the system allows the conveying mode to be switched to a dense phase mode, and records the mode switching in the storage; S502, the measurement data show that the average pressure of the conveying peak value section is at a medium level, the recent historical conveying record is observed, if the average flow of the conveying peak value section presents a gradually descending trend from high, medium to low, or the flow in a preset proportion of historical conveyings is at a low level and a medium level, it is indicated that the current pneumatic conveying state is in a dilute phase state, the system allows the conveying mode to be switched to a critical mode, while trying to approach the dense phase mode, and records the mode switching in the storage; S503, the measurement data of two times in succession show that the average pressure of the conveying peak value section is at a high level, the system will clear the previous mode switching historical data and record again, it is indicated that the current pneumatic conveying state is in a dilute phase state, and the system maintains the current mode without switching.

3. The pneumatic conveying optimization control method based on conveying state recognition of claim 1, wherein, When the current conveying mode is a dense phase, the step S500 comprises: S504, the measurement data show that the average pressure of the conveying peak value section is at a low level, the recent historical conveying record is observed, if the average flow of the conveying peak value section presents a gradually descending trend from high, medium to low, or the flow in a preset proportion of historical conveyings is at a low level and a medium level, it is indicated that the current pneumatic conveying state is in a dilute phase state, and the system maintains the current state. S505, the measurement data shows that the average pressure of the conveying peak section is at the medium level, the recent history conveying record is observed, if the average flow of the conveying peak section presents a gradually descending trend from high, medium to low, or the flow in a preset proportion of the history conveying record is at the low and medium levels, it indicates that the current pneumatic conveying state is in the dilute phase state and is closer to the critical state, and the system keeps the existing state; S506, if the measurement data of the two consecutive times shows that the average pressure of the conveying peak section is at the high level, the system will clear the previous mode switching history data and re-record, and allow the conveying mode to actively switch to the critical mode; S507, if the pipe blockage occurs for two consecutive times, the system will clear the previous mode switching history data and re-record, and allow the conveying mode to actively switch to the dilute phase mode.

4. The pneumatic conveying optimization control method based on conveying state recognition of claim 1, wherein, When the current conveying mode is the critical mode, the step S500 includes: S508, the measurement data shows that the average pressure of the conveying peak section is at the low level, the recent history conveying record is observed, if the average flow of the conveying peak section presents a gradually descending trend from high, medium to low, or the flow in a preset proportion of the history conveying record is at the low and medium levels, it indicates that the current pneumatic conveying state is in the dilute phase state, the system allows the conveying mode to actively switch to the dense phase mode, and stores the mode switching record into the memory; S509, the measurement data shows that the average pressure of the conveying peak section is at the medium level, the recent history conveying record is observed, if the average flow of the conveying peak section presents a gradually descending trend from high, medium to low, or the flow in a preset proportion of the history conveying record is at the low and medium levels, it indicates that the current pneumatic conveying state is in the dilute phase state and is closer to the critical state, the system allows the conveying mode to actively switch to the dense phase mode, and stores the mode switching record into the memory; S510, if the measurement data of the two consecutive times shows that the average pressure of the conveying peak section is at the high level, the system will clear the previous mode switching history data and re-record, according to the new record data, if the flow does not obviously decrease, the system allows the conveying mode to actively approach the dense phase mode, and does not trigger the mode switching; S511, if the pipe blockage occurs for two consecutive times, the system will clear the previous mode switching history data and re-record, and switches the conveying mode to the dilute phase mode.

5. A method of pneumatic conveying optimization control based on conveying regime identification as claimed in any one of claims 2 to 4, characterized in that: The recent history conveying record requires at least 10 data; 40%-60% of the flow in the history conveying record is at the low and medium levels, which indicates that the current is in the dilute phase state.

6. The pneumatic conveying optimization control method based on conveying state recognition according to claim 3 or 4, characterized in that: When the pipe blockage occurs in the conveying process, the pressure presents an ascending trend, and there is no descending trend in the whole process.

7. The pneumatic conveying optimization control method based on conveying state recognition of claim 1, wherein: After the system enters the conveying state, the sum of the fluidizing gas and the conveying gas is ensured to be equal to the preset conveying gas amount, then the system converts the calculated conveying gas amount into the corresponding valve opening, and simultaneously ensures that the ratio of the conveying gas to the conveying gas amount is not less than 60%, or meets the preset minimum proportion requirement and is not less than 60%.

8. The pneumatic conveying optimization control method based on conveying state recognition of claim 1, wherein: The pressure grading standard plans the pressure fluctuation range [x1, x2] as a medium level, plans the pressure fluctuation range less than x1 as a low level, and plans the pressure fluctuation range greater than x2 as a high level; the flow grading standard plans the flow fluctuation range [y1, y2] as a medium level, plans the flow fluctuation range less than y1 as a low level, and plans the flow fluctuation range greater than y2 as a high level.

9. The pneumatic conveying optimization control method based on conveying state recognition of claim 1, wherein: The upper limit of the flow when the conveying mode is dense phase < the upper limit of the flow when the conveying mode is critical < the upper limit of the flow when the conveying mode is dilute phase; the key parameters initialized by the system after receiving the start instruction include pressure, flow, valve state and conveying gas volume; when the system initializes the key parameters, if there is historical conveying data, the historical conveying data is loaded at the same time, and an initial judgment benchmark is established; the initial judgment benchmark includes design gas volume, design output and ash gas ratio.

10. A pneumatic conveying system characterized by: The pneumatic conveying optimization control method based on conveying state identification according to any one of claims 1 to 9.