A pneumatic material intelligent conveying control system

Abstract

The present invention discloses a pneumatic material intelligent conveying control system, which relates to the technical field of intelligent material conveying. The pneumatic material intelligent conveying control system includes: a gas data real-time acquisition module for acquiring gas data in the conveying pipeline in real time; a gas data analysis module for calculating the airflow stability index and the comprehensive airflow resistance index; a gas data anomaly monitoring module for analyzing anomalies based on preset rules; and a gas adjustment module for calculating the gas flow rate and compressed air flow adjustment value based on the anomaly and performing adjustment control. The present invention can fully reflect the dynamic interaction state of the gas and material by acquiring multiple data of the conveying gas and material particles in real time and comprehensively analyzing the airflow stability index and airflow resistance index based on these data. Through preset index discrimination rules and anomaly monitoring functions, it can accurately identify problems of abnormal airflow stability or resistance, so that targeted adjustment measures can be taken in a timely manner.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent material conveying, and in particular to a pneumatic material intelligent conveying control system. Background Art

[0002] Pneumatic conveying technology is an industrial conveying technology that uses gas as a carrier to transport granular or powdered materials from one location to another. It is widely used in the chemical, pharmaceutical, food, building materials, electric power and other industries. During the pneumatic conveying process, the efficiency, stability and reliability of the conveying system directly affect the overall operation of the production line. Traditional pneumatic conveying systems usually adopt fixed parameter design and control methods, which have the following limitations: the airflow state during the conveying process is complex, monitoring and adjustment are difficult, airflow anomalies are difficult to accurately identify, which can easily cause unstable system operation, high energy consumption of the conveying system, and lack of intelligent optimization and adjustment.

[0003] Therefore, an intelligent pneumatic conveying control system is needed that can monitor the conveying airflow status in real time during the conveying process, accurately identify anomalies, and improve system efficiency, stability and energy saving by dynamically optimizing and adjusting airflow parameters (such as airflow velocity and compressed air flow) to meet the needs of modern industry for efficient conveying technology.

[0004] During the operation of the pneumatic conveying system, existing technologies are usually limited to evaluating the system operating status through simple airflow parameter monitoring, but lack real-time analysis of the complex interaction between airflow and conveyed materials. It is easy for the airflow parameters to appear normal but the actual conveying efficiency is low. This monitoring method is difficult to fully reflect the dynamic characteristics of the gas during the conveying process, which can easily lead to problems such as insufficient airflow stability or excessive airflow resistance not being discovered and adjusted in time, thereby affecting the conveying efficiency and stability. Secondly, the existing technologies are mostly based on static rules or fixed parameter correction models in terms of gas adjustment strategies, and fail to dynamically adjust the airflow according to changes in real-time gas data, which can easily cause a lag in the airflow adjustment response, further causing problems such as blockage of conveyed materials and excessive energy consumption, which is not conducive to the efficient operation of the system. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a pneumatic material intelligent conveying control system, which solves the problems in the existing technology of one-sided monitoring, inaccurate abnormality positioning and delayed adjustment of the pneumatic conveying system, and the difficulty in fully reflecting the complex interaction between airflow and materials, which easily leads to airflow abnormalities not being discovered in time.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a pneumatic material intelligent conveying control system, comprising: a gas data real-time acquisition module, a gas data analysis module, a gas data anomaly monitoring module, and a gas adjustment module; the gas data real-time acquisition module is used to acquire the conveying gas data in the conveying pipeline in real time when the conveying pipeline conveys materials; the gas data analysis module is used to perform data analysis on the conveying gas data in the conveying pipeline to obtain the real-time airflow stability index and real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline; the gas data anomaly monitoring module is used to perform anomaly analysis on the real-time airflow stability index and real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline based on preset index judgment rules; the gas adjustment module is used to analyze the gas flow rate adjustment value and the compressed air flow adjustment value of the conveying gas in the conveying pipeline when the real-time airflow stability index and the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline are abnormal, and control and adjust the conveying gas in the conveying pipeline.

[0007] Furthermore, the transported gas data includes a real-time gas density value, a real-time gas flow rate value, and a real-time gas dynamic viscosity value.

[0008] Furthermore, the specific steps for obtaining the real-time airflow stability index of the conveying gas in the conveying pipeline are as follows: obtaining the particle surface area equivalent spherical diameter value and the actual particle diameter value of several material particles in the conveying material, and performing a comprehensive analysis to obtain the particle shape factor and the average particle diameter value in the conveying material; obtaining the material humidity value in the conveying material, and performing a comprehensive analysis in combination with the particle shape factor, the average particle diameter value, the real-time gas density value, the real-time gas flow rate value, and the real-time dynamic viscosity value of the conveying gas in the conveying pipeline to obtain the real-time airflow stability index of the conveying gas in the conveying pipeline.

[0009] Furthermore, the specific formula for calculating the real-time airflow stability index of the conveying gas in the conveying pipeline is as follows: ;in, is the real-time air flow stability index of the gas transported in the transport pipeline, It is the real-time density value of the gas transported in the pipeline. is the real-time flow rate of the gas transported in the transport pipeline, is the particle shape factor of the conveying material, is the average diameter of particles in the conveyed material, It is the real-time dynamic viscosity value of the gas transported in the pipeline. is the humidity correction factor stored in the database, It is the material humidity value in the conveyed material.

[0010] Furthermore, the specific steps for obtaining the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline are as follows: obtaining the pipeline length value and the pipeline diameter value of the conveying pipeline; comprehensively analyzing the real-time gas density value, the real-time gas flow rate value, and the average diameter value of the particles in the conveying material of the conveying gas in the conveying pipeline in combination with the pipeline length value and the pipeline diameter value of the conveying pipeline to obtain the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline.

[0011] Furthermore, the specific formula for calculating the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline is as follows: ;in, It is the real-time comprehensive air flow resistance index of the gas transported in the transport pipeline. is the friction coefficient stored in the database, is the length of the transmission pipeline, is the pipe diameter value of the transmission pipeline, It is the real-time density value of the gas transported in the pipeline. is the real-time flow rate of the gas transported in the transport pipeline, is the average diameter of particles in the conveyed material, is the particle impact factor stored in the database.

[0012] Furthermore, the specific steps for performing abnormal analysis on the real-time airflow stability index and the real-time comprehensive airflow resistance index of the transported gas in the transport pipeline are as follows: comparing and analyzing the real-time airflow stability index and the real-time comprehensive airflow resistance index of the transported gas in the transport pipeline with the preset airflow stability threshold and the airflow resistance threshold respectively; when the real-time airflow stability index of the transported gas in the transport pipeline is higher than the preset airflow stability threshold, the real-time airflow stability index of the transported gas in the transport pipeline is regarded as an airflow stability abnormality; when the real-time comprehensive airflow resistance index of the transported gas in the transport pipeline is higher than the preset airflow resistance threshold, the real-time comprehensive airflow resistance index of the transported gas in the transport pipeline is regarded as an airflow resistance abnormality.

[0013] Furthermore, the specific steps of analyzing the gas flow rate adjustment value of the conveying gas in the conveying pipeline are as follows: reading the real-time gas flow stability index of the conveying gas in the conveying pipeline, the preset gas flow stability threshold, and the real-time gas flow rate value of the conveying gas in the conveying pipeline, and performing comprehensive analysis to obtain the gas flow rate adjustment value of the conveying gas in the conveying pipeline; wherein, the specific formula for calculating the gas flow rate adjustment value of the conveying gas in the conveying pipeline is as follows: ;in, is the gas flow rate adjustment value of the gas transported in the transport pipeline, is the flow rate adjustment coefficient stored in the database, is the real-time air flow stability index of the gas transported in the transport pipeline, is the preset airflow stability threshold, It is the real-time flow rate of the gas transported in the transport pipeline.

[0014] Furthermore, the specific steps for analyzing the compressed air flow adjustment value of the conveying gas in the conveying pipeline are: obtaining the compressed air flow of the conveying gas in the conveying pipeline; comprehensively analyzing the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline, the preset airflow resistance threshold, and the compressed air flow of the conveying gas in the conveying pipeline to obtain the compressed air flow adjustment value of the conveying gas in the conveying pipeline.

[0015] Furthermore, the specific formula for calculating the compressed air flow adjustment value of the conveying gas in the conveying pipeline is as follows: ;in, It is the compressed air flow adjustment value of the gas transported in the transport pipeline. is the flow adjustment coefficient stored in the database, It is the real-time comprehensive air flow resistance index of the gas transported in the transport pipeline. is the preset airflow resistance threshold, It is the compressed air flow rate that transports gas in the delivery pipeline.

[0016] The present invention has the following beneficial effects:

[0017] (1) The pneumatic material intelligent conveying control system obtains multiple data of conveying gas and material particles in real time, such as gas density, flow rate, particle diameter, material humidity, etc., and comprehensively analyzes the airflow stability index and airflow resistance index based on these data. It can fully reflect the dynamic interaction state of gas and material. Through the preset index judgment rules and abnormality monitoring function, it can accurately identify the problems of abnormal airflow stability or abnormal resistance, so as to take targeted adjustment measures in time. This real-time monitoring and intelligent adjustment method can significantly improve the stability and safety of the pneumatic conveying system and avoid system failures caused by unstable airflow or excessive resistance.

[0018] (2) The pneumatic material intelligent conveying control system dynamically calculates the gas flow rate adjustment value and the compressed air flow rate adjustment value, and adjusts the gas flow rate and the compressed air flow rate according to the actual conveying status. By introducing the airflow stability index and the comprehensive airflow resistance index, it can accurately evaluate the impact of abnormalities on gas flow and dynamically optimize the system operating parameters according to the adjustment formula. This optimization strategy not only improves the efficiency of material conveying, but also reduces the waste of gas energy and significantly reduces the energy consumption of system operation.

[0019] (3) The pneumatic material intelligent conveying control system realizes a comprehensive analysis of the complex abnormal conditions of the conveying system by introducing the real-time airflow stability index and the comprehensive airflow resistance index. For example, when the airflow stability is insufficient, the airflow velocity can be reduced by adjusting the flow rate value to avoid unstable particle flow. When the airflow resistance exceeds the standard, the airflow volume can be increased by adjusting the compressed air flow value to restore the normal state of the airflow. This abnormal analysis and adjustment method based on real-time data can quickly respond to and solve abnormal problems in the pneumatic conveying process, significantly improving the reliability of the system operation, while reducing the maintenance cost caused by system abnormalities and improving the overall economic benefits.

[0020] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a block diagram of a pneumatic material intelligent conveying control system of the present invention.

[0022] Figure 2 The present invention provides a flowchart of the specific steps for obtaining a real-time airflow stability index of a conveying gas in a conveying pipeline in a pneumatic material intelligent conveying control system.

[0023] Figure 3 The present invention provides a flowchart of the specific steps for obtaining a real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline in a pneumatic material intelligent conveying control system. DETAILED DESCRIPTION

[0024] The overall approach to the problems in the embodiments of this application is as follows:

[0025] First, the real-time gas data acquisition module is used to obtain real-time gas data in the conveying pipeline, including gas density value, gas flow rate value, gas dynamic viscosity value, and material-related data (such as the equivalent spherical diameter of the particle surface area, the actual particle diameter, and the material humidity value). After these data are processed by the gas data analysis module, the airflow stability index and the comprehensive airflow resistance index are calculated. Then, the gas data anomaly monitoring module is used to compare and analyze the real-time calculated airflow stability index and the comprehensive airflow resistance index with the preset airflow stability threshold and airflow resistance threshold. When any index exceeds the preset threshold, it is marked as an abnormal state, and the specific type of the problem (airflow stability anomaly or airflow resistance anomaly) is further analyzed. Finally, the gas adjustment module is used to calculate the gas flow rate adjustment value and the compressed air flow adjustment value according to the anomaly type, and dynamically adjust the conveying gas flow rate and compressed air flow according to the adjustment results to restore the normal operation of the conveying system and ensure the stability and efficiency of pneumatic conveying.

[0026] See also Figure 1, an embodiment of the present invention provides a technical solution: a pneumatic material intelligent conveying control system, comprising: a gas data real-time acquisition module, a gas data analysis module, a gas data anomaly monitoring module, and a gas adjustment module; the gas data real-time acquisition module is used to acquire the conveying gas data in the conveying pipeline in real time when the conveying pipeline conveys materials; the gas data analysis module is used to perform data analysis on the conveying gas data in the conveying pipeline to obtain the real-time airflow stability index and real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline; the gas data anomaly monitoring module is used to perform anomaly analysis on the real-time airflow stability index and real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline based on preset index judgment rules; the gas adjustment module is used to analyze the gas flow rate adjustment value and the compressed air flow adjustment value of the conveying gas in the conveying pipeline when the real-time airflow stability index and the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline are abnormal, and control and adjust the conveying gas in the conveying pipeline.

[0027] The transported gas data includes the real-time gas density value, the real-time gas flow rate value, and the real-time gas dynamic viscosity value.

[0028] The real-time density value of the gas can be calculated by measuring the pressure and temperature of the gas and combining it with the gas state equation.

[0029] The real-time gas flow rate value can be measured in real time by a flow rate measuring device.

[0030] The real-time dynamic viscosity of the gas can be calculated based on the temperature of the gas and the known physical properties.

[0031] Specifically, if Figure 2 As shown, the specific steps for obtaining the real-time airflow stability index of the conveying gas in the conveying pipeline are as follows: obtaining the particle surface area equivalent spherical diameter value (which can be measured and obtained by a specific surface area meter) and the actual particle diameter value (which can be measured and obtained by a particle size analyzer) of several material particles in the conveying material, and performing a comprehensive analysis to obtain the particle shape factor and the average particle diameter value in the conveying material; obtaining the material humidity value in the conveying material (which can be measured and obtained by an infrared humidity meter), and performing a comprehensive analysis based on the particle shape factor, the average particle diameter value, the real-time gas density value, the real-time gas flow rate value, and the real-time gas dynamic viscosity value of the conveying gas in the conveying pipeline to obtain the real-time airflow stability index of the conveying gas in the conveying pipeline.

[0032] The specific formula for calculating the real-time airflow stability index of the conveying gas in the conveying pipeline is as follows: ;in, is the real-time air flow stability index of the gas transported in the transport pipeline, It is the real-time density value of the gas transported in the pipeline. is the real-time flow rate of the gas transported in the transport pipeline, is the particle shape factor of the conveying material, is the average diameter of particles in the conveyed material, It is the real-time dynamic viscosity value of the gas transported in the pipeline. is the humidity correction factor stored in the database, It is the material humidity value in the conveyed material.

[0033] It should be explained that the humidity correction factor stored in the database The specific calculation process is:

[0034] Obtain particle samples at different humidity levels (e.g., 0%, 10%, 20%, etc.).

[0035] The flow behavior of particles at different humidity levels (e.g., critical suspension velocity, pressure loss, and other key indicators) is measured in an experimental setup.

[0036] Fitting these data to the Reynolds number relationship in the formula yields the humidity correction factor: ,in, is the humidity correction factor stored in the database, is the preset correction coefficient (determined through experiments, different values for different materials), The moisture content of the conveyed material (ranges from 0 to 1, and has no unit).

[0037] Moreover, the greater the humidity, The larger the value, the more significant the effect of humidity on fluidity.

[0038] The specific formula for calculating the particle shape factor and average particle diameter value in the conveyed material is as follows: ;in, is the particle shape factor of the conveying material, For conveying materials The equivalent sphere diameter value of the particle surface area of each material particle, For conveying materials The actual diameter value of each material particle, is the average diameter of particles in the conveyed material, , To obtain the number of material particles in the conveyed material.

[0039] In this embodiment, by obtaining the equivalent spherical diameter value and actual diameter value of the particle surface area, and combining the calculation formula of the particle shape factor and the average particle diameter value, the geometric properties of the material particles can be comprehensively and accurately characterized. This method helps to better analyze the dynamic interaction process between particles and airflow, especially the flow state of particles under different humidity conditions. The calculation of the real-time airflow stability index combines the airflow parameters with the particle characteristics, which helps to accurately evaluate the operating status of the conveying system and avoid airflow instability or material accumulation problems caused by the failure to consider the particle characteristics. The experimental fitting method of the humidity correction factor can dynamically reflect the effect of particle humidity on fluidity, and by adjusting the parameters in the formula, directly incorporate the significant effect of humidity on the flow state into the calculation. The higher the humidity, the more likely the particles are to stick. Attachment agglomeration, and the introduction of humidity correction factor in the formula can effectively adjust the calculation of airflow stability index, help to evaluate and optimize the system operation status in real time, this method avoids the problem of low conveying efficiency in traditional systems due to failure to consider the influence of humidity, and measures key parameters (such as the influence of particle humidity on pressure loss and critical suspension velocity) through experimental equipment and combines the Reynolds number relationship to fit the formula, and constructs a scientific calculation framework. Core parameters such as humidity correction factor and particle shape factor are obtained based on experimental results, which can truly reflect the interaction characteristics of materials and airflow. This data-driven calculation method provides strong theoretical support for real-time monitoring and adjustment of the conveying system, which can significantly improve the system operation efficiency and reduce energy consumption and maintenance costs caused by inaccurate parameters during the conveying process.

[0040] Specifically, if Figure 3 As shown, the specific steps for obtaining the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline are as follows: obtaining the pipeline length value (which can be measured by a laser rangefinder) and the pipeline diameter value (which can be measured by an ultrasonic thickness gauge) of the conveying pipeline; comprehensively analyzing the real-time gas density value, the real-time gas flow rate value, and the average diameter value of the particles in the conveying material in combination with the pipeline length value and the pipeline diameter value of the conveying pipeline to obtain the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline.

[0041] The specific formula for calculating the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline is as follows: ;in, It is the real-time comprehensive air flow resistance index of the gas transported in the transport pipeline. The friction coefficient stored in the database is used to describe the effect of the friction of the inner wall of the pipe on the airflow. is the length of the transmission pipeline, is the pipe diameter value of the transmission pipeline, It is the real-time density value of the gas transported in the pipeline. is the real-time flow rate of the gas transported in the transport pipeline, is the average diameter of particles in the conveyed material, is the particle impact factor stored in the database.

[0042] It should be explained that the friction coefficient stored in the database The specific calculation process is:

[0043] Obtain the pipeline roughness and inner diameter of the pipeline and the Reynolds number of the gas in the pipeline, and bring them into the friction coefficient analysis model for iterative analysis. The friction coefficient analysis model is specifically as follows: ;in, is the friction coefficient stored in the database, is the pipeline roughness of the transmission pipeline, is the inner diameter of the delivery pipeline, is the Reynolds number of the gas in the delivery pipeline.

[0044] Particle impact factors stored in the database The specific calculation process is:

[0045] By measuring the pressure loss experimentally and comparing it with the pressure loss considering only the friction of the airflow, the additional contribution of particles to the pressure loss is calculated, and it is concluded that , and its calculation formula is: ;in, is the particle impact factor stored in the database, is the total pressure loss measured experimentally, The pressure loss when only air flow friction is considered (through the friction factor calculate), is the average diameter of particles in the conveyed material, is the pipe diameter value of the delivery pipeline.

[0046] The following is an implementation example of calculating the real-time comprehensive airflow resistance index of the gas conveyed in the conveying pipeline, with the following data:

[0047] The friction coefficient stored in the database is: 0.0165.

[0048] The pipeline length value of the transmission pipeline is: 50m.

[0049] The pipe diameter value of the conveying pipeline is: 0.2m.

[0050] The real-time density of the gas transported in the pipeline is: 1.2kg / m 3 .

[0051] The real-time flow rate of the gas transported in the transport pipeline is: 20m / s.

[0052] The particle impact factor stored in the database is: 0.0125.

[0053] The average diameter of the particles in the conveyed material is: 0.005m.

[0054] The above data are input into the specific formula for calculating the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline, and the result is:

[0055] The real-time comprehensive airflow resistance index of the gas transported in the transport pipeline = 0.0165*(50 / 0.2)*((1.2*20 2 ) / 2)*(1+0.0125*(0.005 / 0.2))≈990.31.

[0056] In this implementation plan, by obtaining the key parameters of the conveying pipeline (pipeline length, pipeline diameter, gas density, gas flow rate, etc.), combined with the particle characteristics (average particle diameter) and the friction coefficient and particle influence factor stored in the database, the real-time comprehensive airflow resistance index is accurately calculated. The comprehensive airflow resistance index comprehensively reflects the resistance characteristics of the airflow during the conveying process, and can be used to monitor the operating status of the pneumatic conveying system in real time, help identify potential high resistance problems in the system, thereby reducing pressure loss, improving conveying efficiency, and ensuring the stability of the conveying system. The friction coefficient stored in the database is dynamically obtained through iterative analysis of pipeline roughness, inner diameter and gas Reynolds number, and can adapt to different pipeline materials, sizes and airflow conditions. The particle influence factor is based on actual The method combines experimental measurement with scientific model calculations to quantify the additional contribution of particles to pressure loss. It takes into account both the pipeline and airflow characteristics and the impact of particles on airflow, providing a versatile and accurate resistance calculation framework for conveying systems under complex working conditions. The calculation results of the real-time integrated airflow resistance index can be used to dynamically optimize the gas flow rate and compressed air flow in the conveying system to ensure that the system operates with the lowest resistance. By optimizing the airflow parameters, it can effectively reduce energy consumption, reduce the operating burden of equipment, and extend the service life of the conveying pipeline and compressor. In addition, this dynamic adjustment can also effectively avoid problems such as material blockage and pipeline wear caused by high resistance, further improving the economic benefits and operational reliability of the system.

[0057] Specifically, the specific steps for performing abnormal analysis on the real-time airflow stability index and the real-time comprehensive airflow resistance index of the transported gas in the transport pipeline are as follows: comparing and analyzing the real-time airflow stability index and the real-time comprehensive airflow resistance index of the transported gas in the transport pipeline with the preset airflow stability threshold and the airflow resistance threshold respectively; when the real-time airflow stability index of the transported gas in the transport pipeline is higher than the preset airflow stability threshold, the real-time airflow stability index of the transported gas in the transport pipeline is regarded as an airflow stability abnormality; when the real-time comprehensive airflow resistance index of the transported gas in the transport pipeline is higher than the preset airflow resistance threshold, the real-time comprehensive airflow resistance index of the transported gas in the transport pipeline is regarded as an airflow resistance abnormality.

[0058] In this embodiment, by real-time monitoring of the airflow stability index and the comprehensive airflow resistance index in the conveying pipeline, and comparing and analyzing them with the preset airflow stability threshold and airflow resistance threshold, the abnormality of the airflow state can be accurately identified. When the airflow stability index is higher than the threshold, it is promptly judged as an airflow stability abnormality; when the comprehensive airflow resistance index exceeds the limit, it is quickly identified as a resistance abnormality. This precise abnormality identification mechanism avoids the misjudgment problem caused by the exceeding of a single parameter in traditional monitoring, and provides a strong guarantee for the safety and stability of the conveying system operation. This method divides the airflow abnormality into two categories: airflow stability abnormality and airflow resistance abnormality, and identifies the two types of problems respectively through the exceeding of limit analysis of different indexes. This hierarchical abnormality analysis method can quickly locate the cause of the abnormality (such as excessive airflow velocity leading to stability abnormality). This targeted analysis mechanism reduces the troubleshooting time caused by inaccurate anomaly positioning in traditional systems, enables more efficient formulation of adjustment strategies, and avoids greater risks of failure in the conveying system due to long-term unresolved anomalies. By introducing preset airflow stability thresholds and airflow resistance thresholds as monitoring benchmarks, these thresholds can be dynamically adjusted based on the characteristics of the actual conveyed materials and operating conditions, making anomaly monitoring more flexible and accurate. For example, for different material characteristics (such as particle moisture and particle diameter) or different pipeline operating conditions, adjusting the thresholds can better adapt to actual operating needs and avoid missed or false alarms caused by setting fixed thresholds too high or too low. This flexibility enables the system to adapt to a variety of operating conditions and ensures long-term operational reliability.

[0059] Specifically, the specific steps for analyzing the gas flow rate adjustment value of the conveying gas in the conveying pipeline are as follows: reading the real-time airflow stability index of the conveying gas in the conveying pipeline, the preset airflow stability threshold, and the real-time gas flow rate value of the conveying gas in the conveying pipeline, and performing a comprehensive analysis to obtain the gas flow rate adjustment value of the conveying gas in the conveying pipeline.

[0060] The specific formula for calculating the gas flow rate adjustment value of the conveying gas in the conveying pipeline is as follows: ;in, is the gas flow rate adjustment value of the gas transported in the transport pipeline, is the flow rate adjustment coefficient stored in the database, is the real-time air flow stability index of the gas transported in the transport pipeline, is the preset airflow stability threshold, It is the real-time flow rate of the gas transported in the transport pipeline.

[0061] It should be explained that the flow rate adjustment coefficient stored in the database The specific calculation process is:

[0062] Read the historical data of system operation and record the changes in the Reynolds number of material particles under different air flow velocities;

[0063] Calculate the flow rate adjustment coefficient based on the deviation between the Reynolds number of the material particles and the air flow velocity .

[0064] In this embodiment, by reading the airflow stability index, airflow stability threshold and real-time flow rate value, and combining the flow rate adjustment coefficient to calculate the gas flow rate adjustment value, the airflow speed can be optimized in real time. When the airflow stability index exceeds the preset threshold, the flow rate adjustment amount that needs to be reduced or increased is quickly determined by the calculation formula, thereby restoring the airflow stability. This dynamic adjustment method solves the problem of airflow fluctuation caused by adjustment lag or inaccurate adjustment amplitude in traditional systems, ensuring the stability and efficiency of system operation. The flow rate adjustment coefficient is obtained by fitting historical data and experimental results, and can accurately reflect the change law of the Reynolds number of material particles under different airflow speeds. By analyzing the relationship between airflow speed and particle motion state, The adjustment coefficient can be dynamically adjusted according to different materials (such as particle shape, diameter, humidity) and pipeline conditions. This method makes the adjustment coefficient more adaptable and suitable for handling the needs of different material transportation scenarios, further improving the accuracy of the adjustment and the versatility of the system. Too fast airflow speed can easily lead to increased energy consumption and increased wear of pipeline equipment, while too slow can easily lead to particle deposition or poor transportation. This method can effectively avoid the problem of too fast or too slow airflow speed by calculating the airflow speed adjustment value. By dynamically optimizing the speed adjustment value, it can not only reduce unnecessary energy consumption and extend the service life of the equipment, but also ensure that the material is stably suspended in the airflow, improve the transportation efficiency, and reduce the safety risks caused by abnormal speed.

[0065] Specifically, the specific steps for analyzing the compressed air flow adjustment value of the conveying gas in the conveying pipeline are: obtaining the compressed air flow of the conveying gas in the conveying pipeline; comprehensively analyzing the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline, the preset airflow resistance threshold, and the compressed air flow of the conveying gas in the conveying pipeline to obtain the compressed air flow adjustment value of the conveying gas in the conveying pipeline.

[0066] The specific formula for calculating the compressed air flow adjustment value of the conveying gas in the conveying pipeline is as follows: ;in, It is the compressed air flow adjustment value of the gas transported in the transport pipeline. is the flow adjustment coefficient stored in the database, It is the real-time comprehensive air flow resistance index of the gas transported in the transport pipeline. is the preset airflow resistance threshold, It is the compressed air flow rate that transports gas in the delivery pipeline.

[0067] It should be explained that the flow adjustment coefficient stored in the database The specific calculation process is:

[0068] Read the system's historical operating data and record the changing relationship between compressed air flow and pressure loss;

[0069] Calculated based on the adjusted compressed air flow and pressure loss deviation .

[0070] In this embodiment, by obtaining the compressed air flow and comprehensive airflow resistance index of the conveying pipeline in real time, and combining it with the preset airflow resistance threshold, the compressed air flow adjustment value is calculated, and the airflow in the conveying system can be dynamically adjusted. When the airflow resistance index exceeds the threshold, the system can quickly calculate the compressed air flow that needs to be increased or decreased, avoiding the problem of decreased conveying efficiency due to excessive resistance or increased energy consumption due to excessive airflow, thereby ensuring the efficient operation of the system. The flow adjustment coefficient is obtained based on the fitting of system historical data and experimental data, and can quantify the relationship between compressed air flow and pressure loss. This coefficient can dynamically adapt to different conveying material characteristics (such as particle size, humidity) and pipeline conditions (such as length, diameter, thickness). Roughness), accurately calculate the change in compressed air flow in the adjustment formula. This method not only improves the accuracy of adjustment, but also enhances the adaptability of the system under complex working conditions, and provides the system with a flexible flow optimization strategy. The optimized adjustment of compressed air flow effectively avoids unnecessary energy consumption. In traditional systems, due to the inability to monitor resistance changes in real time, a fixed flow rate is usually used for air supply, which easily leads to high energy consumption and low efficiency. This method ensures that the airflow supply is just right through the dynamic calculation of the compressed air flow adjustment value, which not only meets the transportation needs but also avoids excessive air supply. At the same time, the accuracy of flow regulation also reduces the wear of pipelines and equipment caused by excessive airflow, thereby extending the service life of the equipment and reducing maintenance costs.

[0071] In summary, this application has at least the following effects:

[0072] By acquiring multiple data on conveying gas and material particles in real time, such as gas density, flow rate, particle diameter, material humidity, etc., and comprehensively analyzing the airflow stability index and airflow resistance index based on these data, the dynamic interaction state of gas and material can be fully reflected. Through preset index judgment rules and abnormality monitoring functions, problems of abnormal airflow stability or abnormal resistance can be accurately identified, so that targeted adjustment measures can be taken in a timely manner. This real-time monitoring and intelligent adjustment method can significantly improve the stability and safety of the pneumatic conveying system and avoid system failures caused by unstable airflow or excessive resistance.

[0073] By dynamically calculating the gas flow rate and compressed air flow rate adjustment values, the gas flow rate and compressed air flow rate are adjusted according to the actual conveying conditions. By introducing the airflow stability index and the comprehensive airflow resistance index, the impact of abnormalities on gas flow can be accurately assessed. The system operating parameters are dynamically optimized according to the adjustment formula. This optimization strategy not only improves the efficiency of material conveying, but also reduces gas energy waste and significantly reduces system operating energy consumption.

[0074] By introducing the real-time airflow stability index and the comprehensive airflow resistance index, a comprehensive analysis of the complex abnormal conditions of the conveying system is achieved. For example, when the airflow stability is insufficient, the airflow velocity can be reduced by adjusting the flow rate value to avoid unstable particle flow. When the airflow resistance exceeds the standard, the airflow volume can be increased by adjusting the compressed air flow value to restore the normal airflow state. This abnormal analysis and adjustment method based on real-time data can quickly respond to and solve abnormal problems in the pneumatic conveying process, significantly improving the reliability of the system operation, while reducing the maintenance costs caused by system abnormalities and improving the overall economic benefits.

[0075] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0076] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A pneumatic material intelligent conveying control system, characterized in that: include: Gas data real-time acquisition module, gas data analysis module, gas data anomaly monitoring module, gas adjustment module; The gas data real-time acquisition module is used to acquire the conveying gas data in the conveying pipeline in real time when the conveying pipeline is conveying materials; The gas data analysis module is used to analyze the transport gas data in the transport pipeline to obtain a real-time airflow stability index and a real-time comprehensive airflow resistance index of the transport gas in the transport pipeline; The gas data anomaly monitoring module is used to perform an anomaly analysis on the real-time airflow stability index and the real-time comprehensive airflow resistance index of the gas transported in the transport pipeline based on a preset index judgment rule; The gas adjustment module is used to analyze the gas flow rate adjustment value and the compressed air flow adjustment value of the gas conveyed in the conveying pipeline when the real-time airflow stability index and the real-time comprehensive airflow resistance index of the gas conveyed in the conveying pipeline are abnormal, and to control and adjust the gas conveyed in the conveying pipeline; The transported gas data includes real-time gas density value, real-time gas flow rate value, and real-time gas dynamic viscosity value; The specific steps for obtaining the real-time airflow stability index of the conveying gas in the conveying pipeline are as follows: Obtain the equivalent spherical diameter value of the particle surface area and the actual diameter value of the particles in the conveyed material, and conduct a comprehensive analysis to obtain the particle shape factor and average particle diameter value in the conveyed material; The material humidity value in the conveying material is obtained, and a comprehensive analysis is performed based on the particle shape factor, average particle diameter value, real-time gas density value, real-time gas flow rate value, and real-time gas dynamic viscosity value of the conveying gas in the conveying pipeline to obtain the real-time airflow stability index of the conveying gas in the conveying pipeline.

2. The pneumatic material intelligent conveying control system according to claim 1 is characterized in that: The specific formula for calculating the real-time airflow stability index of the conveying gas in the conveying pipeline is as follows: ； in, is the real-time air flow stability index of the gas transported in the transport pipeline, It is the real-time density value of the gas transported in the pipeline. is the real-time flow rate of the gas transported in the transport pipeline, is the particle shape factor of the conveying material, is the average diameter of particles in the conveyed material, It is the real-time dynamic viscosity value of the gas transported in the pipeline. is the humidity correction factor stored in the database, It is the material humidity value in the conveyed material.

3. The pneumatic material intelligent conveying control system according to claim 2 is characterized in that: The specific steps for obtaining the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline are as follows: Obtain the pipe length and pipe diameter of the transmission pipeline; The real-time gas density value, real-time gas flow rate value, and average particle diameter value of the conveyed gas in the conveying pipeline are comprehensively analyzed in combination with the pipeline length value and pipeline diameter value of the conveying pipeline to obtain the real-time comprehensive airflow resistance index of the conveyed gas in the conveying pipeline.

4. The pneumatic material intelligent conveying control system according to claim 3 is characterized in that: The specific formula for calculating the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline is as follows: ； in, It is the real-time comprehensive air flow resistance index of the gas transported in the transport pipeline. is the friction coefficient stored in the database, is the length of the transmission pipeline, is the pipe diameter value of the transmission pipeline, It is the real-time density value of the gas transported in the pipeline. is the real-time flow rate of the gas transported in the transport pipeline, is the average diameter of particles in the conveyed material, is the particle impact factor stored in the database.

5. The pneumatic material intelligent conveying control system according to claim 4 is characterized in that: The specific steps for abnormal analysis of the real-time airflow stability index and the real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline are as follows: Compare and analyze the real-time airflow stability index and the real-time comprehensive airflow resistance index of the gas transported in the transport pipeline with the preset airflow stability threshold and airflow resistance threshold respectively; When the real-time airflow stability index of the transported gas in the transport pipeline is higher than a preset airflow stability threshold, the real-time airflow stability index of the transported gas in the transport pipeline is regarded as an abnormal airflow stability; When the real-time comprehensive airflow resistance index of the transported gas in the transport pipeline is higher than a preset airflow resistance threshold, the real-time comprehensive airflow resistance index of the transported gas in the transport pipeline is regarded as abnormal airflow resistance.

6. The pneumatic material intelligent conveying control system according to claim 5, characterized in that: The specific steps for analyzing the gas flow rate adjustment value of the conveying gas in the conveying pipeline are as follows: Reading the real-time airflow stability index of the conveying gas in the conveying pipeline, the preset airflow stability threshold, and the real-time gas flow rate value of the conveying gas in the conveying pipeline, and performing comprehensive analysis to obtain the gas flow rate adjustment value of the conveying gas in the conveying pipeline; The specific formula for calculating the gas flow rate adjustment value of the conveying gas in the conveying pipeline is as follows: ； in, is the gas flow rate adjustment value of the gas transported in the transport pipeline, is the flow rate adjustment coefficient stored in the database, is the real-time air flow stability index of the gas transported in the transport pipeline, is the preset airflow stability threshold, It is the real-time flow rate of the gas transported in the transport pipeline.

7. The pneumatic material intelligent conveying control system according to claim 6, characterized in that: The specific steps for analyzing the compressed air flow adjustment value of the conveying gas in the conveying pipeline are: Obtain the compressed air flow rate of the conveying gas in the conveying pipeline; The real-time comprehensive airflow resistance index of the conveying gas in the conveying pipeline, the preset airflow resistance threshold, and the compressed air flow rate of the conveying gas in the conveying pipeline are comprehensively analyzed to obtain the compressed air flow adjustment value of the conveying gas in the conveying pipeline.

8. The pneumatic material intelligent conveying control system according to claim 7, characterized in that: The specific formula for calculating the compressed air flow adjustment value of the conveying gas in the conveying pipeline is as follows: ； in, It is the compressed air flow adjustment value of the gas transported in the transport pipeline. is the flow adjustment coefficient stored in the database, It is the real-time comprehensive air flow resistance index of the gas transported in the transport pipeline. is the preset airflow resistance threshold, It is the compressed air flow rate that transports gas in the delivery pipeline.

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