Control method for improving precision qualification rate of belt conveyor operation

Abstract

This invention provides a control method for improving the accuracy and pass rate of belt conveyor operation, belonging to the field of precision control technology. It involves constructing a monitoring system for real-time acquisition of belt conveyor operating status parameters; establishing a nonlinear factor correlation model based on the acquired operating status parameters; and constructing a dynamic optimization control strategy for belt conveyor speed based on the nonlinear factor correlation model. The real-time adjustment speed of the rollers is used as a control command and output to the belt conveyor's frequency converter, which adjusts the drive motor speed according to the control command. By constructing a dynamic correlation model between load fluctuations, belt elastic deformation, and speed control, dynamic optimization control of the belt conveyor's operating speed is achieved, effectively suppressing speed fluctuations, avoiding sudden speed changes during heavy and light load transitions, improving speed control accuracy and material conveying accuracy, thereby enhancing the accuracy and pass rate of belt conveyor operation and meeting high-precision conveying requirements.

Description

Technical Field

[0001] This invention belongs to the field of precision control technology, specifically relating to a control method for improving the accuracy and pass rate of belt conveyor operation. Background Technology

[0002] Belt conveyors, also known as belt conveyors, are a type of continuous conveying equipment. They are widely used in various industrial fields such as mining, ports, metallurgy, chemicals, and food processing due to their advantages of large conveying capacity, long conveying distance, low operating costs, and strong adaptability. They are a crucial piece of equipment in continuous material conveying systems. The operational precision of belt conveyors, especially the stability and accuracy of speed control, directly determines the accuracy of material conveying, production efficiency, and the quality of subsequent processes. The pass rate of operational precision is also one of the important indicators for measuring the operational performance and production reliability of belt conveyors.

[0003] In industrial production, the requirements for the accuracy of material conveying are constantly increasing. Especially in scenarios such as precision chemical, electronic component conveying and quantitative batching conveying, extremely high requirements are placed on the speed control accuracy and operational stability of belt conveyors. Once the speed fluctuates greatly or changes abruptly, it will not only lead to excessive, insufficient or deviated material conveying, affecting product quality, but may also cause problems such as material accumulation, spillage and accelerated equipment wear. In severe cases, it may even lead to production interruption and cause huge economic losses.

[0004] Currently, the speed control methods for existing belt conveyors mainly employ open-loop control or simple closed-loop control. These control methods are simple in structure and low in cost, and can meet basic usage requirements in some extensive production scenarios where conveying accuracy requirements are not high. However, in high-precision conveying scenarios, they have many shortcomings: they do not fully consider the nonlinear interference factors during belt conveyor operation, and the control strategy lacks dynamic optimization capabilities. During actual operation, belt conveyors are affected by a combination of nonlinear factors, the most important of which are load fluctuations and belt elastic deformation. Load fluctuations are a normal occurrence during belt conveyor operation. Due to factors such as the conveying volume, material density, and uneven material distribution, the load on the belt conveyor can vary significantly. Frequent switching between low and heavy loads, often random and sudden, is common in conveyor belts. As flexible components, belts possess inherent elasticity, undergoing stretching or contraction deformation under varying loads and drum speeds. This deformation causes a deviation between the actual belt speed and the theoretical drum speed, with the degree of deformation dynamically changing with load size, operating time, and belt aging. Existing open-loop control methods completely ignore these nonlinear factors, controlling drum speed solely based on preset speed commands, resulting in a fixed speed control deviation. While simple closed-loop control introduces speed feedback, it only adjusts drum speed, failing to account for load fluctuations and belt speed variations. Incorporating nonlinear factors such as elastic deformation into the control logic makes dynamic optimization impossible, and it's difficult to counteract the impact of these factors on speed control. The large speed fluctuation range makes it difficult to meet high-precision conveying requirements. Because nonlinear factors are not dynamically optimized, the speed regulation of existing control methods suffers from lag and limitations. When the load on the belt conveyor changes, especially during rapid switching between heavy and light loads, the output torque of the rollers does not match the load demand, leading to sudden increases or decreases in belt speed and large speed fluctuations. These large speed fluctuations directly cause instability in material conveying speed, deviations in material residence time and conveying distance on the belt, and consequently affect the accuracy of material conveying, reducing conveying speed. The accuracy of conveying is qualified; sudden speed changes are prone to occur when switching between heavy and light loads, which aggravates equipment wear and reduces conveying safety. When switching from heavy to light load, the output torque of the rollers fails to adjust in time to keep up with the decrease in load, resulting in the driving force obtained by the belt being greater than the load resistance, causing a sudden increase in speed. This not only causes material spillage but also aggravates the wear between the belt and the rollers, and may even cause the belt to slip. When switching from light to heavy load, the output torque of the rollers fails to increase in time, resulting in insufficient driving force and a sudden drop in speed. Material accumulates on the belt, increasing the operating load of the belt. Long-term operation will lead to equipment failures such as belt fatigue damage and roller bearing wear. It will also affect the normal connection of subsequent processes and reduce production efficiency.Low control precision makes it difficult to improve the accuracy and pass rate of conveying. Existing control methods lack dynamic compensation and optimization for nonlinear factors, resulting in large steady-state errors in speed control and slow dynamic response. They cannot quickly adapt to changes such as load fluctuations and belt elastic deformation, making it difficult to guarantee the accuracy of material conveying. In actual production, belt conveyors using existing control methods have low material conveying accuracy and pass rates, failing to meet the needs of high-precision production scenarios and limiting their application in high-end industrial fields.

[0005] Therefore, developing a control method that can fully consider nonlinear factors such as load fluctuations and belt elastic deformation, achieve dynamic optimization control, effectively suppress speed fluctuations and sudden speed changes, and improve the operating accuracy and conveying accuracy qualification rate of belt conveyors has become a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] The purpose of this section is to outline some aspects of the embodiments of the present invention and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section, as well as in the abstract and title of the present application, to avoid obscuring the purpose of this section, the abstract and title of the invention. Such simplifications or omissions shall not be used to limit the scope of the present invention.

[0007] In view of the aforementioned existing problems, the present invention is proposed.

[0008] To solve the above-mentioned technical problems, the present invention provides the following technical solution: This invention provides a control method for improving the accuracy and pass rate of belt conveyor operation, comprising: Establish a monitoring system for real-time acquisition of operating status parameters of belt conveyors; The PLC controller establishes a nonlinear factor correlation model based on the collected operating status parameters of the belt conveyor; The PLC controller constructs a dynamic optimization control strategy for the belt conveyor speed based on a nonlinear factor correlation model. The PLC controller adjusts the rotation speed of the drum in real time. As a control command, the output is sent to the frequency converter of the belt conveyor, and the frequency converter adjusts the speed of the drive motor according to the control command.

[0009] Furthermore, the operating status parameters of the belt conveyor include the drum speed, belt load, belt tension, and ambient temperature. The drum speed is collected by a speed sensor installed on the shaft end of the drum shaft. The belt load is collected by a pressure sensor installed between the idler roller and the frame. The belt tension is collected by a tension sensor installed on the belt tensioning device. The ambient temperature is collected by a temperature sensor located in the environment where the belt conveyor is located. The speed sensor, pressure sensor, tension sensor, and temperature sensor are all connected to the PLC controller to form a monitoring system. The real-time collected operating status parameters of the belt conveyor are transmitted to the PLC controller.

[0010] Furthermore, methods for establishing nonlinear factor correlation models specifically include: First, calculate the theoretical linear velocity of the roller. The theoretical linear velocity of the drum The result is obtained by applying formula (1): (1); In formula (1), This refers to the real-time rotational speed of the drum. The radius of the roller; Secondly, according to Hooke's Law, the elastic deformation of the belt... Belt tension Elastic modulus Cross-sectional area and effective conveying length The relationship represented by formula (2) is satisfied as follows: (2); Define the speed correction caused by the elastic deformation of the belt as Its relationship with elastic deformation Effective conveying length of the belt and the theoretical linear velocity of the roller The correlation is shown in formula (3): (3).

[0011] Furthermore, methods for establishing nonlinear factor correlation models also include: Substituting formula (2) into formula (3), we obtain the velocity correction caused by elastic deformation as represented by formula (4): (4); Then define the speed correction caused by load fluctuations as: Its relationship with belt load and belt tension The correlation is shown in formula (5): (5); Therefore, the actual running speed of the belt With respect to the theoretical linear velocity of the drum Velocity correction due to elastic deformation Speed ​​correction due to load fluctuations The relationship between them is shown in formula (7): (7).

[0012] Furthermore, the elastic modulus of the belt is obtained by correcting it using formula (6). : (6); In formula (6), The elastic modulus of the belt at real-time ambient temperature; Standard temperature The elastic modulus of the belt below; The temperature coefficient of elastic modulus of the belt; This represents the real-time ambient temperature.

[0013] Furthermore, methods for establishing nonlinear factor correlation models also include: Substituting formulas (1), (4), and (5) into formula (7), we obtain the actual running speed of the belt as shown in formula (8). The complete expression, i.e., the nonlinear factor correlation model of the belt conveyor: (8).

[0014] Furthermore, the dynamic optimization control strategy for belt conveyor speed specifically includes: First, set the preset target speed of the belt conveyor. The actual running speed of the belt is calculated using formula (9). With the preset target speed speed deviation : (9); Based on speed deviation Load fluctuation rate and the rate of change of elastic deformation of the belt Construct dynamic optimization adjustment quantity Among them, the rate of change of load fluctuation The ratio of the difference in belt load between two consecutive data collections to the sampling period is given by formula (10): (10); In formula (10), For the first The belt load collected in this second sampling. For the first The belt load collected in this second sampling. The sampling period; elastic deformation rate of belt The ratio of the difference in elastic deformation of the belt between two consecutive measurements to the sampling period is given by formula (11): (11); In formula (11), For the first The elastic deformation of the belt was obtained in this second measurement. For the first -1 elastic deformation of the belt obtained; Next, the dynamic optimization adjustment amount is obtained, and the dynamic optimization adjustment amount is calculated using formula (12). : (12); In formula (12), , The coefficient of friction between the roller and the belt; Based on dynamic optimization adjustment amount The real-time adjustable speed of the drum is obtained by applying formula (13). : (13).

[0015] Furthermore, the dynamic optimization control strategy for belt conveyor speed also includes: applying formula (14) to adjust the rotational speed of the drum in real time. Set upper and lower limit constraints: (14); In formula (14), The minimum safe rotation speed of the drum is set. The set maximum safe rotational speed of the drum; like < Then take = ;like > Then take = ;like Within the range of upper and lower limit constraints, then directly use As a real-time adjustment of the drum speed.

[0016] Furthermore, the methods by which the frequency converter adjusts the speed of the drive motor according to control commands include: The frequency converter adjusts the speed of the drive motor according to the control command to adjust the speed of the drum in real time.

[0017] Furthermore, control methods to improve the accuracy and pass rate of belt conveyor operation also include: the PLC controller also calculates the accuracy and pass rate of belt conveyor operation in real time, and the calculation method is as follows: Set the allowable speed deviation range [ , [Statistics on the actual operating speed of the belt obtained per unit time before the current moment.] With the preset target speed speed deviation Within the allowable range of speed deviation [ , The deviation between the quantity within and the speed obtained per unit time. The ratio of the total number of belt conveyors is the accuracy pass rate of belt conveyor operation. , The calculation formula is formula (15): (15); In formula (15), The actual running speed of the belt obtained per unit time With the preset target speed speed deviation Within the allowable range of speed deviation [ , The quantity within ] The speed deviation obtained per unit time The total quantity; Then, the PLC controller displays the accuracy pass rate in real time on the connected display screen. ,when < At that time, the PLC controller controls the buzzer connected to it to automatically emit a warning buzzer signal. The set pass rate threshold.

[0018] The beneficial effects of the present invention are as follows, compared with the prior art: This invention fully considers nonlinear interference factors, significantly improving control accuracy. By establishing a comprehensive operational status monitoring system, it collects relevant parameters of nonlinear factors such as load fluctuations, belt elastic deformation, and ambient temperature in real time. A nonlinear correlation model is established between load fluctuations, belt elastic deformation, and the actual belt speed, comprehensively incorporating nonlinear factors into the control process. This achieves dynamic compensation for speed deviations and effectively suppresses the impact of nonlinear factors on speed control. Compared with existing control methods, the speed control accuracy of this invention is significantly improved, and speed fluctuations can be controlled within a reasonable range, meeting the requirements of high-precision conveying. This invention also achieves dynamic optimization and predictive control, avoiding sudden speed changes. The dynamic optimization control strategy constructed in this invention not only adjusts based on the current speed deviation but also achieves predictive compensation through the rate of change of load fluctuations and the rate of change of belt elastic deformation. It adjusts the drum speed in advance, avoiding sudden speed increases or decreases due to adjustment lag during heavy and light load switching, reducing material spillage, equipment wear, and other problems, thus improving the stability and safety of the belt conveyor operation. The accuracy qualification rate is significantly improved. This invention, through real-time optimized control, ensures that the actual operating speed of the belt remains stable within the preset target speed range. Combined with a real-time statistics and early warning mechanism for accuracy pass rate, it can promptly detect and handle equipment anomalies, ensuring the belt conveyor operates at high precision for extended periods, significantly improving the accuracy of material conveying and production reliability. This invention reduces equipment wear and operating costs. By avoiding sudden speed changes, it reduces wear between the belt and rollers, belt fatigue damage, roller bearing wear, and other equipment failures, extending the belt conveyor's service life. Simultaneously, the dynamic optimization adjustment strategy ensures precise matching of the drive motor's output torque to load requirements, reducing motor energy consumption and further decreasing the belt conveyor's operating and maintenance costs. This invention is easy to operate and highly intelligent. Through a PLC controller, it achieves fully automated control of the entire process of data acquisition, analysis, calculation, adjustment, and feedback. Speed ​​adjustment can be completed without manual intervention, while real-time display of accuracy pass rate and automatic issuance of early warning signals facilitate timely troubleshooting by staff, reducing manual labor intensity and enhancing the intelligence level of belt conveyor operation. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is an overall flowchart of the control method for improving the accuracy and pass rate of belt conveyor operation as described in this invention. Detailed Implementation

[0020] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0021] Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort should fall within the scope of protection of this invention.

[0022] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0023] According to an embodiment of the present invention, in combination Figure 1 The flowchart shown illustrates a control method for improving the accuracy and pass rate of belt conveyor operation according to the present invention, comprising: S1. Establish a monitoring system for real-time acquisition of the belt conveyor's operating status parameters. Note the following in this step: In a preferred embodiment, the operating status parameters of the belt conveyor include the real-time rotational speed of the belt conveyor's drum, belt load, belt tension, and ambient temperature. The drum rotational speed is acquired by a speed sensor installed at the shaft end of the belt conveyor's drum shaft. The belt load is acquired by a pressure sensor installed between the idler roller and the belt. The belt tension is acquired by a tension sensor installed on the belt tensioning device of the belt conveyor. The ambient temperature is acquired by a temperature sensor located in the environment where the belt conveyor is located. The speed sensor, pressure sensor, tension sensor, and temperature sensor are all connected to the PLC controller to form a monitoring system. The real-time acquired operating status parameters of the belt conveyor are all transmitted to the PLC controller.

[0024] It should be noted that the belt conveyor includes a roller and a driven roller that are sleeved on the roller shaft. The roller shaft is connected to the output shaft of the drive motor. The belt is sleeved on the roller and the driven roller. The idler roller fixed on the frame supports the belt. The PLC controller is connected to the drive motor through the frequency converter. The belt and the belt tensioning device are connected.

[0025] Furthermore, the starting time and frequency of the speed sensor, pressure sensor, tension sensor, and temperature sensor are all the same, which enables the synchronous acquisition of the belt conveyor's operating status parameters.

[0026] S2 and the PLC controller, based on the collected operating status parameters of the belt conveyor, establish a nonlinear factor correlation model between load fluctuations, belt elastic deformation, and the actual operating speed of the belt. This model clarifies the influence of each nonlinear factor on the belt conveyor's operating speed, providing a theoretical basis for subsequent dynamic optimization control. Note that the following points should be noted in this step: In a preferred embodiment, the method for establishing a nonlinear factor correlation model between load fluctuation, belt elastic deformation, and actual belt operating speed specifically includes: First, calculate the theoretical linear velocity of the roller. The theoretical linear velocity of the drum The result is obtained by applying formula (1): (1); In formula (1), This refers to the real-time rotational speed of the drum. The radius of the roller; Secondly, consider the influence of belt elastic deformation on speed. That is, the belt will elastically stretch under tension, causing a deviation between the actual belt speed and the theoretical linear speed of the roller. According to Hooke's Law, the elastic deformation of the belt... Belt tension Elastic modulus Cross-sectional area and effective conveying length The relationship represented by formula (2) is satisfied as follows: (2); It should be noted that formula (2) is based on Hooke's Law and accurately reflects the relationship between parameters such as belt tension, elastic modulus, and cross-sectional area and the elastic deformation of the belt, which conforms to the deformation law of the belt as a flexible component; cross-sectional area It refers to the cross-sectional area of ​​the belt.

[0027] Furthermore, the effective conveying length of the belt This is the distance between the axis of the driven drum and the axis of the driven drum.

[0028] Due to the elastic deformation of the belt, the actual operating speed of the belt will change. The speed correction caused by the elastic deformation of the belt is defined as... Its relationship with elastic deformation Effective conveying length of the belt and the theoretical linear velocity of the roller The correlation is shown in formula (3): (3).

[0029] It should be noted that in formula (3), elastic deformation With the effective conveying length of the belt Inversely proportional, the longer the effective conveying length of the belt, the greater the elastic deformation for the same amount of time. The smaller the impact on speed, the better; compared to the theoretical linear speed of the roller. Proportional to the theoretical linear velocity of the roller The faster, the greater the elastic deformation. The speed correction caused by the elastic deformation of the belt due to deformation is This perfectly reflects the deformation per unit length, thereby accurately quantifying the speed deviation; Formula (3) is for the purpose of calculating the actual running speed of the belt in the future. By quantifying the speed deviation caused by elastic deformation, it provides an accurate basis for dynamic optimization control, avoiding inaccurate speed control due to elastic deformation, which is in complete agreement with the key objectives of the present invention to suppress speed fluctuations and improve accuracy.

[0030] In a preferred embodiment, the method for establishing a nonlinear factor correlation model between load fluctuations, belt elastic deformation, and actual belt operating speed further includes: Substituting formula (2) into formula (3), we obtain the velocity correction caused by elastic deformation as represented by formula (4): (4); Then, considering the impact of load fluctuations on speed, load fluctuations in the belt conveyor cause changes in the friction between the belt and the rollers, thus affecting the actual operating speed of the belt. The speed correction caused by load fluctuations is defined as follows: Its relationship with belt load and belt tension The correlation is shown in formula (5): (5); It should be noted that the theoretical linear velocity of the roller... Speed ​​correction due to load fluctuations Positive correlation, speed correction caused by load fluctuations It is inversely proportional to the actual operating speed of the belt; that is, when the belt is loaded... When the torque increases, the friction between the belt and the roller increases. If the output torque of the roller remains unchanged, the actual speed of the belt will decrease. At this time, it is necessary to... The adjustment compensates for the speed reduction deviation, and the two are inversely proportional; when the belt is loaded... When the friction decreases, the actual speed of the belt will increase, and the speed correction caused by load fluctuations will also increase. Similarly, the deviation caused by the increase in speed is compensated by inverse adjustment; belt tension Increased speed correction due to load fluctuations However, the speed decreases, while the actual running speed of the belt increases.

[0031] In a preferred embodiment, ambient temperature affects the elastic modulus of the belt. The change in elastic modulus caused by temperature change can be corrected by formula (6) to obtain the elastic modulus of the belt. : (6); In formula (6), The elastic modulus of the belt at real-time ambient temperature; Standard temperature The elastic modulus of the belt below; This is the temperature coefficient of elastic modulus of the belt, which reflects the degree of influence of temperature on the elastic modulus of the belt. This represents the real-time ambient temperature.

[0032] It should be noted that the standard temperature Typically 25℃; standard temperature The method for obtaining the elastic modulus of the belt can be as follows: under a standard temperature environment of 25℃, it can be determined by material mechanics experiments, that is, a constant tension is applied to the belt sample and its elastic deformation is measured.

[0033] Formula (6) is used to compensate for the effect of ambient temperature on the elastic deformation of the belt, ensuring the speed correction caused by elastic deformation. This ensures high calculation accuracy and avoids control errors caused by temperature changes.

[0034] Based on the above analysis, the actual operating speed of this belt is... With respect to the theoretical linear velocity of the drum Velocity correction due to elastic deformation Speed ​​correction due to load fluctuations The relationship between them is shown in formula (7): (7).

[0035] It should be noted that in formula (7), the velocity correction caused by elastic deformation Let the actual running speed of the belt Increased speed correction due to load fluctuations Let the actual running speed of the belt The value decreases, and the sum of the two, combined with the theoretical linear velocity of the roller, results in a smaller value. This accurately reflects the actual running speed of the belt.

[0036] In a preferred embodiment, the method for establishing a nonlinear factor correlation model between load fluctuations, belt elastic deformation, and actual belt operating speed further includes: Substituting formulas (1), (4), and (5) into formula (7), we obtain the actual running speed of the belt as shown in formula (8). The complete expression, i.e., the nonlinear factor correlation model of the belt conveyor: (8).

[0037] It should be noted that Formula (8) clarifies the dynamic relationship between parameters such as drum speed, load, tension, elastic modulus, and belt cross-sectional area and the actual running speed of the belt. It fully reflects the influence of nonlinear factors such as load fluctuation and belt elastic deformation on the running speed of the belt conveyor, providing key model support for subsequent dynamic optimization control.

[0038] Based on the nonlinear factor correlation model established by S2, the S3 and PLC controllers construct a dynamic optimization control strategy for the belt conveyor speed, mainly by adjusting the real-time rotational speed of the drum. It compensates for speed deviations caused by load fluctuations and belt elastic deformation, thereby achieving the actual operating speed of the belt. With the preset target speed Accurate matching. It is important to note the following in this step: In a preferred embodiment, the dynamic optimization control strategy for the belt conveyor speed specifically includes: First, set the preset target speed of the belt conveyor. The actual running speed of the belt is calculated using formula (9). With the preset target speed speed deviation : (9); Furthermore, when When the speed is >0, it indicates that the actual operating speed of the belt is lower than the preset target speed of the belt conveyor, and the real-time speed of the roller needs to be increased; when When the speed is less than 0, it indicates that the actual operating speed of the belt is higher than the preset target speed of the belt conveyor, and the real-time speed needs to be reduced; when... When the speed is 0, the actual running speed of the belt is consistent with the preset target speed of the belt conveyor, and no speed deviation compensation is required.

[0039] To achieve rapid and accurate compensation for speed deviations and avoid over-adjustment or lag, based on speed deviation... Load fluctuation rate and the rate of change of elastic deformation of the belt Construct dynamic optimization adjustment quantity , Used to adjust the real-time rotational speed of the drum. Among them, the rate of change of load fluctuation The ratio of the difference in belt load between two consecutive data collections to the sampling period is given by formula (10): (10); In formula (10), For the first The belt load collected in this second sampling. For the first The belt load collected in this second sampling. The sampling period; elastic deformation rate of belt The ratio of the difference in elastic deformation of the belt between two consecutive measurements to the sampling period is given by formula (11): (11); In formula (11), For the first The elastic deformation of the belt was obtained in this second measurement. For the first -1 elastic deformation of the belt obtained; Next, the dynamic optimization adjustment amount is obtained, and the dynamic optimization adjustment amount is calculated using formula (12). : (12); In formula (12), , The coefficient of friction between the roller and the belt; It should be noted that in formula (12), the first term on the right side of the equal sign is the speed deviation compensation term, which is used to compensate for the speed deviation. Adjusting the real-time rotational speed of the drum achieves accurate compensation for the current speed deviation; the second term on the right side of the equation is the predictive compensation term for load fluctuations, based on the load fluctuation rate. Adjust the drum speed in advance to avoid sudden speed changes caused by rapid load variations; the third term on the right side of the equation is the anticipatory compensation term for elastic deformation, based on the rate of change of elastic deformation. Adjust the real-time rotation speed of the roller in advance to compensate for the speed deviation caused by the dynamic changes in the elastic deformation of the belt.

[0040] Based on dynamic optimization adjustment amount The real-time adjustable speed of the drum is obtained by applying formula (13). : (13).

[0041] In a preferred embodiment, the dynamic optimization control strategy for the belt conveyor speed further includes: to ensure the safety and stability of the drum speed adjustment and to avoid equipment failure caused by excessively high or low speeds, formula (14) is applied to adjust the drum speed in real time. Set upper and lower limit constraints: (14); In formula (14), The minimum safe rotation speed of the drum is set. The set maximum safe rotational speed of the drum; like < Then take = ;like > Then take = ;like Within the range of upper and lower limit constraints, then directly use As a real-time adjustment of the drum speed.

[0042] It should be noted that the preset target speed of the belt conveyor It is set according to actual production needs and is a constant value; it is the preset target speed of the belt conveyor. This refers to the belt speed set according to actual production needs; the sampling period is the sampling period of the sensor, which can be a speed sensor, pressure sensor, tension sensor, or temperature sensor.

[0043] Furthermore, the minimum safe rotation speed of the drum. and the maximum safe speed of the drum Set according to the production requirements of the belt conveyor.

[0044] S4 and the PLC controller will adjust the real-time rotational speed of the roller calculated by S3. As control commands, the output is sent to the frequency converter of the belt conveyor, and the frequency converter adjusts the speed of the drive motor according to the control commands. It is important to note the following in this step: In a preferred embodiment, the method for adjusting the speed of the drive motor according to the control command by the frequency converter includes: The frequency converter adjusts the speed of the drive motor to the real-time adjustable speed of the drum according to the control command, thereby driving the drum to rotate and realizing the adjustment of the belt conveyor's running speed. At the same time, the monitoring system continuously collects the operating status parameters of the belt conveyor and transmits them to the PLC controller in real time. The controller repeats the S2~S4 process according to the latest collected parameters to achieve dynamic optimization control.

[0045] In a preferred embodiment, the control method for improving the accuracy pass rate of belt conveyor operation further includes: the PLC controller also calculates the accuracy pass rate of belt conveyor operation in real time, and the calculation method is as follows: Set the allowable speed deviation range [ , [Statistics on the actual operating speed of the belt obtained per unit time before the current moment.] With the preset target speed speed deviation Within the allowable range of speed deviation [ , The deviation between the quantity within and the speed obtained per unit time. The ratio of the total number of belt conveyors is the accuracy pass rate of belt conveyor operation. , The calculation formula is formula (15): (15); In formula (15), The actual running speed of the belt obtained per unit time With the preset target speed speed deviation Within the allowable range of speed deviation [ , The quantity within ] The speed deviation obtained per unit time The total quantity; Then, the PLC controller displays the accuracy pass rate in real time on the connected display screen. ,when < At that time, the PLC controller controls the buzzer connected to it to automatically emit a warning buzzer signal. The system automatically issues a warning buzzer signal to remind staff to check the operating status of the belt conveyor based on the set pass rate threshold, ensuring that the belt conveyor is always in a high-precision operating state.

[0046] It should be noted that the allowable speed deviation range is set according to the high-precision conveying requirements, for example, it is [-0.01]. 0.01 The unit of time is usually 1 hour; It is designed according to specific requirements.

[0047] For example, The possible value is 95%.

[0048] The purpose of this invention is to overcome the shortcomings of existing belt conveyor speed control technologies, which fail to consider nonlinear factors such as load fluctuations and belt elastic deformation, resulting in large speed fluctuations, sudden speed changes during heavy and light load transitions, and low conveying accuracy pass rates. This invention provides a control method to improve the accuracy pass rate of belt conveyor operation. This method constructs a dynamic correlation model between load fluctuations, belt elastic deformation, and speed control to achieve dynamic optimization control of the belt conveyor's operating speed. This effectively suppresses speed fluctuations, avoids sudden speed changes during heavy and light load transitions, improves speed control accuracy and material conveying accuracy, and ultimately enhances the accuracy pass rate of belt conveyor operation, meeting the requirements for high-precision conveying.

[0049] It should be recognized that embodiments of the present invention may be implemented or carried out by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable storage medium.

[0050] The method can be implemented using standard programming techniques, including a non-transitory computer-readable storage medium configured with a computer program in the computer program, wherein the storage medium is configured such that the computer operates in a specific and predefined manner.

[0051] Each program can be implemented in a high-level procedural or object-oriented programming language to communicate with the computer system; however, if required, the program can be implemented in assembly or machine language.

[0052] In any case, the language can be either compiled or interpreted.

[0053] Furthermore, for this purpose, the program can run on programmed application-specific integrated circuits.

[0054] The processes described herein (or variations and / or combinations thereof) can be executed under the control of one or more computer systems configured with executable instructions, and can be implemented by hardware or a combination thereof as code (e.g., executable instructions, one or more computer programs, or one or more applications) that commonly executes on one or more processors. The computer program includes a plurality of instructions executable by one or more processors.

[0055] Furthermore, the method can be implemented in any suitable computing platform, including but not limited to personal computers, minicomputers, mainframes, workstations, networked or distributed computing environments, standalone or integrated computer platforms, or in communication with charged particle tools or other imaging devices.

[0056] Various aspects of the present invention can be implemented in machine-readable code stored on a non-transitory storage medium or device, whether portable or integrated into a computing platform, such as a hard disk, optical read and / or write storage medium, RAM, ROM, etc., such that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the processes described herein.

[0057] Furthermore, machine-readable code, or parts thereof, can be transmitted via wired or wireless networks.

[0058] When such media includes instructions or programs that combine with a microprocessor or other data processor to implement the steps described above, the invention described herein includes these and other different types of non-transitory computer-readable storage media.

[0059] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A control method for improving the precision qualification rate of a belt conveyor operation, characterized by, include: Establish a monitoring system for real-time acquisition of operating status parameters of belt conveyors; The PLC controller establishes a nonlinear factor correlation model based on the collected operating status parameters of the belt conveyor; The PLC controller constructs a dynamic optimization control strategy for the belt conveyor speed based on a nonlinear factor correlation model. The PLC controller will adjust the real-time rotating speed of the roller As a control instruction, output to the frequency converter of the belt conveyor, the frequency converter adjusts the rotating speed of the driving motor according to the control instruction; The operating status parameters of the belt conveyor include the drum speed, belt load, belt tension, and ambient temperature. The drum speed is acquired by a speed sensor installed on the shaft end of the drum. The belt load is acquired by a pressure sensor installed between the idler roller and the frame. The belt tension is acquired by a tension sensor installed on the belt tensioning device. The ambient temperature is acquired by a temperature sensor located in the environment where the belt conveyor is located. The speed sensor, pressure sensor, tension sensor, and temperature sensor are all connected to the PLC controller to form a monitoring system. The real-time acquired operating status parameters of the belt conveyor are transmitted to the PLC controller. Methods for establishing nonlinear factor correlation models include: First, calculate the theoretical linear velocity of the roller. The theoretical linear velocity of the drum The result is obtained by applying formula (1): （1）； In formula (1), This refers to the real-time rotational speed of the drum. The radius of the roller; Secondly, according to Hooke's Law, the elastic deformation of the belt... Belt tension Elastic modulus Cross-sectional area and effective conveying length The relationship represented by formula (2) is satisfied as follows: （2）； Define the speed correction caused by the elastic deformation of the belt as Its relationship with elastic deformation Effective conveying length of the belt and the theoretical linear velocity of the roller The correlation is shown in formula (3): （3）； Methods for establishing nonlinear factor correlation models also include: Substituting formula (2) into formula (3), we obtain the velocity correction caused by elastic deformation as represented by formula (4): （4）； Then define the speed correction caused by load fluctuations as: Its relationship with belt load and belt tension The correlation is shown in formula (5): （5）； Therefore, the actual running speed of the belt With respect to the theoretical linear velocity of the drum Velocity correction due to elastic deformation Speed ​​correction due to load fluctuations The relationship between them is shown in formula (7): （7）； The elastic modulus of the belt is obtained by correcting it using formula (6). : （6）； In formula (6), The elastic modulus of the belt at real-time ambient temperature; Standard temperature The elastic modulus of the belt below; The temperature coefficient of elastic modulus of the belt; This refers to the real-time ambient temperature. Methods for establishing nonlinear factor correlation models also include: Substituting formulas (1), (4), and (5) into formula (7), we obtain the actual running speed of the belt as shown in formula (8). The complete expression, i.e., the nonlinear factor correlation model of the belt conveyor: （8）。 2. The control method for improving the accuracy and pass rate of belt conveyor operation according to claim 1, characterized in that, The dynamic optimization control strategy for belt conveyor speed specifically includes: First, set the preset target speed of the belt conveyor. The actual running speed of the belt is calculated using formula (9). With the preset target speed speed deviation : （9）； Based on speed deviation Load fluctuation rate and the rate of change of elastic deformation of the belt Construct dynamic optimization adjustment quantity Among them, the rate of change of load fluctuation The ratio of the difference in belt load between two consecutive data collections to the sampling period is given by formula (10): （10）； In formula (10), For the first The belt load collected in this second sampling. For the first The belt load collected in this second sampling. The sampling period; elastic deformation rate of belt The ratio of the difference in elastic deformation of the belt between two consecutive measurements to the sampling period is given by formula (11): （11）； In formula (11), For the first The elastic deformation of the belt was obtained in this second measurement. For the first The elastic deformation of the belt obtained in this second measurement; Next, the dynamic optimization adjustment amount is obtained, and the dynamic optimization adjustment amount is calculated using formula (12). : （12）； In formula (12), , The coefficient of friction between the roller and the belt; Based on dynamic optimization adjustment amount The real-time adjustable speed of the drum is obtained by applying formula (13). : （13）。 3. The control method for improving the accuracy and pass rate of belt conveyor operation according to claim 2, characterized in that, The dynamic optimization control strategy for belt conveyor speed also includes: applying formula (14) to adjust the rotational speed of the drum in real time. Set upper and lower limit constraints: （14）； In formula (14), The minimum safe rotation speed of the drum is set. The set maximum safe rotational speed of the drum; like < Then take = ;like > Then take = ;like Within the range of upper and lower limit constraints, then directly use As a real-time adjustment of the drum speed.

4. The control method for improving the accuracy and pass rate of belt conveyor operation according to claim 3, characterized in that, The methods by which a frequency converter adjusts the speed of a drive motor according to control commands include: The frequency converter adjusts the speed of the drive motor according to the control command to adjust the speed of the drum in real time.

5. The control method for improving the accuracy and pass rate of belt conveyor operation according to claim 4, characterized in that, Also includes: The PLC controller also calculates the accuracy pass rate of the belt conveyor operation in real time, and the calculation method is as follows: Set the allowable speed deviation range Statistically calculate the actual operating speed of the belt within a unit of time up to the current moment. With the preset target speed speed deviation Within the allowable speed deviation range The deviation between the quantity within and the speed obtained per unit time The ratio of the total number of belt conveyors is the accuracy pass rate of belt conveyor operation. , The calculation formula is formula (15): （15）； In formula (15), The actual running speed of the belt obtained per unit time With the preset target speed speed deviation Within the allowable speed deviation range The number inside, The speed deviation obtained per unit time The total quantity; Then, the PLC controller displays the accuracy pass rate in real time on the connected display screen. ,when < At that time, the PLC controller controls the buzzer connected to it to automatically emit a warning buzzer signal. The set pass rate threshold.

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