A method and system for continuous pressure tracking transmission

Abstract

The present invention relates to the technical field of pressure tracking transmission, and discloses a method and system for continuous pressure tracking transmission, which includes the following steps: S1: obtaining pressure sensing data and performing data verification on the pressure sensing data to obtain output pressure data; S2: obtaining pressure source input data and performing data verification on the pressure source input data to obtain input pressure data; S3: judging the system state based on the input pressure data; S4: obtaining a pressure control strategy based on the system state; S5: regulating the output pressure based on the pressure control strategy and the output pressure data and the input pressure data. The present invention improves the accuracy and stability of pressure tracking transmission, and enhances the flexibility and intelligence level of the pneumatic pressure system.

Description

Technical Field

[0001] The present invention relates to the technical field of pressure tracking transmission, and in particular to a method and system for continuous pressure tracking transmission. Background Art

[0002] The core of the pneumatic system is to accurately control the pressure and flow of the gas to meet various process requirements. As a key control component of the pneumatic system, the electronic pressure tracking valve is widely used in situations where the output pressure needs to be accurately adjusted. This type of valve can automatically adjust the output pressure according to the changes in the input signal to keep the output pressure consistent with the set value. With the development of Internet of Things technology, modern pneumatic systems with electronic pressure tracking valves as control elements can not only achieve remote monitoring and control, but also analyze and predict by collecting a large amount of operating data, thereby improving the stability and reliability of the system. Although the existing electronic pressure tracking valves can realize automatic tracking and transmission of pressure to a certain extent, there are still some shortcomings.

[0003] Traditional pressure tracking transmission often uses fixed PID parameters, which may not achieve the optimal control effect when facing different working conditions. Especially when the pressure of the pressure source changes rapidly, fixed PID parameters are difficult to adapt to the needs of dynamic changes. For different working environments and application scenarios, existing electronic pressure tracking valves may require customized solutions to achieve the best control effect, which limits their versatility and scope of application. In some application scenarios, such as rapid inflation and deflation processes, the control system needs to be able to respond quickly to pressure changes. However, traditional control strategies often have a slow response speed, making it difficult for the system to adjust the output pressure in a timely manner. Existing electronic pressure tracking valves usually require regular manual parameter adjustments, which increases maintenance costs and may cause production efficiency problems due to operational errors.

[0004] For example, a Chinese patent with the authorization announcement number CN103233946B discloses a backstepping control method for a pneumatic position servo system, which is specifically implemented according to the following steps: Step 1, establish a model of the controlled pneumatic position servo system, and the above-mentioned various variable parameters are respectively detected in real time by respective detection instruments; ignore friction, and obtain a third-order linear model of the pneumatic system, and the control target is to make the model output track the required expected output; Step 2, establish a backstepping controller model for the pneumatic position servo system; Step 3, estimate the unknown parameter values ​​of the pneumatic position servo system, and input the estimated values ​​into a computer for real-time updating of the parameters of the backstepping controller model, and the computer controls the signal output of the amplifier to adjust the displacement of the piston in real time. The invention method does not require the addition of pressure detection hardware or algorithms, and can obtain better tracking effects and higher control accuracy.

[0005] For example, the patent application with publication number CN108897214A discloses a pressure control method and a pneumatic gravity compensation system for a pneumatic gravity compensation system, the method comprising: using an anti-disturbance control controller to construct a closed-loop control loop; designing a tracking differentiator, an extended state observer and nonlinear feedback in the anti-disturbance control controller; measuring the pressure differential in the system, and the extended state observer estimates the total disturbance of the system according to the pressure differential; compensating the initial control amount according to the total disturbance, and inputting the actual control amount obtained after compensation into the controlled gravity compensation system. The application proposes a high-precision pressure control algorithm based on anti-disturbance technology, suppressing the dual disturbances of the environment and the model, and realizing high-precision dynamic gravity compensation; it has strong robustness to changes in air source pressure and sudden changes in load.

[0006] The above patents all have the problem raised by this background technology: they may not be able to achieve the optimal control effect when facing different working conditions.

[0007] The information disclosed in this background technology section is only intended to enhance the understanding of the overall background of the invention and should not be regarded as an acknowledgement or any form of suggestion that the information constitutes the prior art already known to ordinary technicians in this field. Summary of the invention

[0008] The technical problem to be solved by the present invention is to overcome the defects of the prior art, provide a method and system for continuous pressure tracking transmission, improve the accuracy and stability of pressure tracking transmission, and enhance the flexibility and intelligence level of the pneumatic pressure system.

[0009] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0010] In one aspect, the present invention provides a method for continuous pressure tracking transmission, comprising the following steps:

[0011] S1: Acquire pressure sensing data and perform data verification on the pressure sensing data to obtain output pressure data;

[0012] S2: Obtaining input data of the pressure source and performing data verification on the input data of the pressure source to obtain input pressure data;

[0013] S3: determining a system state based on the input pressure data;

[0014] S4: Based on the system state, obtaining a pressure control strategy;

[0015] S5: Regulating the output pressure based on the pressure control strategy and the output pressure data and the input pressure data.

[0016] As a preferred solution of the pressure continuous follow-up transmission method of the present invention, wherein: the pressure sensing data includes output pressure sensing data and input pressure sensing data; wherein the input pressure sensing data is the input pressure value of the pressure source measured by the sensor, and the output pressure sensing data is the output pressure value of the system measured by the sensor;

[0017] The method for performing data verification on any type of pressure sensor data is as follows: continuously collect pressure sensor data and perform data cleaning; collect pressure sensor data once in each sampling period, and form a time series of length N with the pressure sensor data of the previous N-1 sampling periods; perform volatility detection and mutation detection on the pressure sensor data based on the time series, if the pressure sensor data passes the volatility detection and mutation detection, the pressure sensor data passes the data verification; otherwise, the pressure sensor data verification is abnormal;

[0018] The output pressure sensing data and the input pressure sensing data are respectively subjected to data verification; if the output pressure sensing data passes the data verification, the output pressure sensing data in the time series of the output pressure sensing data is extracted as the output pressure data.

[0019] As a preferred solution of the pressure continuous follow-up transmission method of the present invention, the method of performing fluctuation detection and mutation detection on the pressure sensing data is as follows:

[0020] Calculate the volatility index of the time series as follows:

[0021] ;

[0022] in, represents said volatility index; represents the i-th pressure sensor data in the time series, and the value range of i is 1, 2, ..., N; Represents the mean of N pressure sensor data in the time series;

[0023] If the volatility index of the time series is less than the preset volatility threshold, the pressure sensor data passes the volatility test; otherwise, the pressure sensor data volatility test is abnormal;

[0024] The mutation index of each pressure sensing data in the time series is calculated using the following formula:

[0025] ;

[0026] in, Represents the mutation index of the i-th pressure sensor data in the time series; if the mutation index of all pressure sensor data in the time series is less than the preset mutation threshold, the pressure sensor data passes the mutation detection; otherwise, the pressure sensor data mutation detection is abnormal.

[0027] As a preferred solution of the pressure continuous follow-up transmission method of the present invention, the method of verifying the pressure source input data is as follows:

[0028] The input pressure sensor data of the last M sampling cycles are read as reference pressure data; the reference pressure data is the input pressure sensor data that has passed data verification; the M pressure source input data corresponding to the sampling cycles of the reference pressure data are read, and if at least m of the M pressure source input data exceed the preset input threshold range, the pressure source input data is abnormal; otherwise, the cumulative input deviation is calculated, and the formula is as follows:

[0029] ;

[0030] in, Indicates the cumulative input deviation; represents the input data of the jth pressure source, and the value range of j is 1, 2, ..., M; represents the jth reference pressure data;

[0031] If the accumulated input deviation is less than the preset input deviation threshold, the pressure source input data passes the data verification; otherwise, the pressure source input data is abnormal;

[0032] If the pressure source input data passes the data verification, the pressure source input data is extracted as the input pressure data; if the pressure source input data is abnormal, the input pressure sensor data in the reference pressure data is extracted as the input pressure data.

[0033] As a preferred solution of the pressure continuous follow-up transmission method of the present invention, the method for judging the system status is as follows:

[0034] Acquire input pressure data and organize them into a pressure input sequence in chronological order; the pressure input sequence includes the last n data-verified pressure values ​​input by the pressure source;

[0035] The pressure change rate of the pressure input sequence is calculated as follows:

[0036] ;

[0037] in, Represents the pressure change rate of the pressure input sequence; represents the hth pressure value in the pressure input sequence, Represents the h-1th pressure value in the pressure input sequence;

[0038] If the pressure change rate of the pressure input sequence is less than the first change threshold, the system state is a stable state;

[0039] If the pressure change rate of the pressure input sequence is not less than the first change threshold and less than the second change threshold, the system state is a transition state;

[0040] If the pressure change rate of the pressure input sequence is not less than the second change threshold, the system state is a fast-changing state.

[0041] As a preferred solution of the pressure continuous follow-up transmission method of the present invention, the pressure control strategy includes a first pressure control strategy, a second pressure control strategy, and a third pressure control strategy; if the system state is a stable state, the first pressure control strategy is obtained and executed; if the system state is a transitional state, the second pressure control strategy is obtained and executed; if the system state is a rapidly changing state, the third pressure control strategy is obtained and executed;

[0042] The pressure control strategy is a PID control strategy. The content of any pressure control strategy includes the proportional coefficient, integral coefficient, and differential coefficient of the PID controller. The method for formulating any pressure control strategy is as follows: a simulation experiment of pressure follow-up transmission is performed based on PID control, and the proportional coefficient, integral coefficient, and differential coefficient of the PID controller are determined through a genetic algorithm.

[0043] As a preferred solution of the pressure continuous follow-up transmission method of the present invention, the formula of the fitness function involved in the genetic algorithm when formulating the first pressure control strategy is as follows:

[0044] ;

[0045] in, Represents the fitness of individuals in the genetic algorithm; Represents steady-state error; V represents output fluctuation amplitude; , All are weight coefficients;

[0046] The calculation formula of the steady-state error is as follows:

[0047] ;

[0048] in, represents the steady-state output value in the simulation experiment of pressure follow-up transmission, Indicates the target pressure value;

[0049] The calculation formula of the output fluctuation amplitude is as follows:

[0050] ;

[0051] in, Indicates the maximum value after the output pressure reaches the steady state. Indicates the minimum value after the output pressure reaches a steady state.

[0052] As a preferred solution of the pressure continuous follow-up transmission method of the present invention, the formula of the fitness function involved in the genetic algorithm when formulating the second pressure control strategy is as follows:

[0053] ;

[0054] in, Represents the fitness of individuals in the genetic algorithm; Indicates the maximum overshoot; represents the rise time; , All are weight coefficients;

[0055] The calculation formula of the maximum overshoot is as follows:

[0056] ;

[0057] in, Indicates the peak value when the output pressure value exceeds the target pressure value for the first time;

[0058] The calculation formula of the rise time is as follows:

[0059] ;

[0060] in, It indicates the time point when the output pressure value rises to 10% of the target pressure value for the first time after the simulation experiment of pressure follow-up transmission starts; Indicates the time point when the output pressure value first rises to 90% of the target pressure value;

[0061] The formula of the fitness function involved in the genetic algorithm when formulating the third pressure control strategy is as follows:

[0062] ;

[0063] in, represents the fitness of individuals in the genetic algorithm when formulating the third pressure control strategy, , are all weight coefficients.

[0064] As a preferred solution of the pressure continuous follow-up transmission method of the present invention, the method for regulating the output pressure is as follows:

[0065] Calculate the output error using the following formula:

[0066] ;

[0067] in, represents the output error of the kth sampling period; Represents the input pressure data of the kth sampling period; Represents the output pressure data of the kth sampling period; Indicates the preset pressure difference;

[0068] Based on the output error, calculating an output signal value;

[0069] Based on the output signal value, output pressure regulation is performed.

[0070] As a preferred solution of the pressure continuous follow-up transmission method of the present invention, if the output error The absolute value of is not less than the preset dead zone width D, then the calculation formula of the output signal value is as follows:

[0071] ;

[0072] in, Represents the output signal value of the kth sampling period; represents the proportionality coefficient; represents the integral coefficient; represents the differential coefficient; Represents the output error of the lth sampling period; represents the output error of the k-1th sampling period; Indicates the period length of any sampling period;

[0073] If the output error If the absolute value of is less than the preset dead zone width D, the calculation formula of the output signal value is as follows:

[0074] ;

[0075] in, Represents the output signal value of the k-1th sampling period.

[0076] In a second aspect, the present invention provides a pressure continuous follow-up transmission system, including a data acquisition module, a data verification module, a state judgment module, a controller module, and a pressure control module;

[0077] The data acquisition module includes a sensor unit for collecting pressure sensing data; and an input unit for receiving pressure source input data;

[0078] The data verification module is used to perform data verification on the pressure sensing data and the pressure source input data to obtain output pressure data and input pressure data;

[0079] The state judgment module is used to judge the system state based on the input pressure data;

[0080] The controller module is used to compare the output pressure data with the input pressure data and generate a pressure control instruction;

[0081] The pressure control module is used to execute the pressure control instruction and perform output pressure regulation.

[0082] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0083] By performing volatility detection and mutation detection on pressure sensor data, abnormal data can be effectively identified, ensuring the quality and reliability of the data. Using sensor data as a verification and backup replacement for pressure source input data enhances the robustness and fault tolerance of the system.

[0084] According to different system states, different PID control strategies are adopted, so that the control system can automatically adjust parameters to adapt to different working conditions, improving the flexibility and intelligence of control. Using genetic algorithms to optimize PID parameters, the best control parameter combination can be found for different working conditions, further improving the control effect. By automatically optimizing PID parameters, the debugging process is simplified, the need for manual intervention is reduced, and work efficiency is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0086] Figure 1 A flow chart of the pressure continuous follow-up transmission method provided by the present invention;

[0087] Figure 2 A schematic diagram of the structure of the pressure continuous follow-up transmission system provided by the present invention;

[0088] Figure 3 A flow chart of a method for verifying pressure sensing data provided by the present invention;

[0089] Figure 4 A flow chart of a method for verifying pressure source input data provided by the present invention. DETAILED DESCRIPTION

[0090] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0091] Example 1

[0092] This embodiment introduces a pressure continuous follow-up transmission method, referring to Figure 1 , the method comprises the following steps:

[0093] S1: Acquire pressure sensing data and perform data verification on the pressure sensing data to obtain output pressure data;

[0094] The pressure sensing data includes output pressure sensing data and input pressure sensing data; wherein the input pressure sensing data is the input pressure value of the pressure source measured by the sensor, and the output pressure sensing data is the output pressure value of the system measured by the sensor;

[0095] like Figure 3 As shown, the method for data verification of any pressure sensing data is as follows:

[0096] Continuously collect pressure sensor data and perform data cleaning; collect pressure sensor data once in each sampling period, and form a time series of length N with the pressure sensor data of the previous N-1 sampling periods, where N is a positive integer; and perform volatility detection on the pressure sensor data, the method is as follows:

[0097] Calculate the volatility index of the time series as follows:

[0098] ;

[0099] in, represents said volatility index; represents the i-th pressure sensor data in the time series, and the value range of i is 1, 2, ..., N; Represents the mean of N pressure sensor data in the time series;

[0100] If the volatility index of the time series is less than the preset volatility threshold, the pressure sensor data passes the volatility test; otherwise, the pressure sensor data volatility test is abnormal;

[0101] Volatility detection can detect whether the random fluctuations of pressure sensor data are beyond the normal range. By calculating the volatility index of the data to measure the stability of the data, it can reflect the overall quality of the data and identify abnormal situations, such as whether the sensor is in a stable environment or whether there is continuous noise interference.

[0102] Perform mutation detection on pressure sensing data as follows:

[0103] The mutation index of each pressure sensing data in the time series is calculated using the following formula:

[0104] ;

[0105] in, Represents the mutation index of the i-th pressure sensor data in the time series; if the mutation index of all pressure sensor data in the time series is less than the preset mutation threshold, the pressure sensor data passes the mutation detection; otherwise, the pressure sensor data mutation detection is abnormal; if the pressure sensor data passes the volatility detection and mutation detection, the pressure sensor data passes the data verification; otherwise, the pressure sensor data verification is abnormal, and the abnormal data and abnormal type are fed back to the management personnel, prompting the management personnel to perform maintenance.

[0106] Mutation detection can detect whether there are sudden and significant changes in pressure sensing data. By calculating the mutation index to identify mutations, abnormal changes in a single data point or a short period of time can be detected, which is very effective for discovering momentary failures or external interference of the sensor.

[0107] The output pressure sensing data and the input pressure sensing data are respectively subjected to data verification; if the output pressure sensing data passes the data verification, the output pressure sensing data in the time series of the output pressure sensing data is extracted as the output pressure data.

[0108] S2: Obtaining input data of the pressure source and performing data verification on the input data of the pressure source to obtain input pressure data;

[0109] Reference Figure 4 , the method for data verification of pressure source input data is as follows:

[0110] The input pressure sensing data of the last M sampling cycles are read as reference pressure data, where M is a positive integer; the reference pressure data is the input pressure sensing data that has passed data verification; a pressure source input data is acquired in each sampling cycle; M pressure source input data corresponding to the sampling cycle of the reference pressure data are read, and if at least m of the M pressure source input data exceed the preset input threshold range, the pressure source input data is abnormal, where m is a positive integer, and the input threshold range is determined by those skilled in the art through a large number of experiments; otherwise, the cumulative input deviation is calculated, and the formula is as follows:

[0111] ;

[0112] in, Indicates the cumulative input deviation; represents the input data of the jth pressure source, and the value range of j is 1, 2, ..., M; represents the jth reference pressure data;

[0113] If the accumulated input deviation is less than the preset input deviation threshold, the pressure source input data passes the data verification; otherwise, the pressure source input data is abnormal;

[0114] If the pressure source input data passes the data verification, the pressure source input data is extracted as the input pressure data; if the pressure source input data is abnormal, the input pressure sensor data in the reference pressure data is extracted as the input pressure data; and an abnormal warning is issued to the management personnel to remind the management personnel to perform data verification and maintenance on the pressure source input.

[0115] The robustness of the system can be improved by collecting input pressure sensing data through sensors as a verification and alternative to the pressure source input data. When the pressure source input data passes the data verification, the pressure source input data is used as the input pressure data to avoid the measurement error of the sensor; when the pressure source input data is abnormal, the pressure sensing data that passes the data verification is used as the input pressure data to ensure that the subsequent pressure regulation can proceed normally.

[0116] S3: Determine the system status based on the input pressure data; the method is as follows:

[0117] Continuously acquire input pressure data and organize them into a pressure input sequence in chronological order; the pressure input sequence includes the last n data-verified pressure values ​​input by the pressure source; n is a positive integer;

[0118] The pressure change rate of the pressure input sequence is calculated as follows:

[0119] ;

[0120] in, Represents the pressure change rate of the pressure input sequence; represents the hth pressure value in the pressure input sequence, Indicates the h-1th pressure value in the pressure input sequence, and the value range of h is 1, 2, ..., n;

[0121] If the pressure change rate of the pressure input sequence is less than the first change threshold, the system state is a stable state;

[0122] If the pressure change rate of the pressure input sequence is not less than the first change threshold and less than the second change threshold, the system state is a transition state;

[0123] If the pressure change rate of the pressure input sequence is not less than the second change threshold, the system state is a fast-changing state.

[0124] The pressure change rate reflects the fluctuation speed of the input pressure. When the pressure change rate is less than the first change threshold, the input pressure fluctuates slightly, there is no obvious overshoot or oscillation, and the system is in a stable state. At this time, unnecessary control actions should be reduced when regulating the output pressure. When the pressure change rate is not less than the first change threshold and less than the second change threshold, oscillation and overshoot occur, and the system is in a transitional state. When regulating the output pressure, the response speed of the output control should be increased to reduce oscillation and overshoot. When the pressure change rate is not less than the second change threshold, the pressure source changes quickly, and the system is in a fast-changing state. When regulating the output pressure, the change of the pressure source should be responded to more quickly to minimize oscillation and overshoot.

[0125] S4: Based on the system state, obtaining a pressure control strategy;

[0126] The pressure control strategy includes a first pressure control strategy, a second pressure control strategy, and a third pressure control strategy; if the system state is a stable state, the first pressure control strategy is obtained and executed; if the system state is a transitional state, the second pressure control strategy is obtained and executed; if the system state is a rapidly changing state, the third pressure control strategy is obtained and executed;

[0127] The pressure control strategy is a PID control strategy. The content of any pressure control strategy includes the proportional coefficient, integral coefficient, and differential coefficient of the PID controller. The formulation method of any pressure control strategy is as follows:

[0128] A simulation experiment of pressure follow-up transmission is carried out based on PID control, and the proportional coefficient, integral coefficient, and differential coefficient of the PID controller are determined by genetic algorithm; the method is as follows:

[0129] S100: Set population size, crossover probability, and mutation probability;

[0130] S200: Generate S individuals and form the initial population, where S is the population size; each individual contains a chromosome, corresponding to a PID control strategy; each chromosome contains 3 genes, corresponding to the proportional coefficient, integral coefficient, and differential coefficient respectively; set the value range of the parameters corresponding to each gene to ensure that the parameters in the initial population are within a reasonable range.

[0131] S300: performing a simulation experiment of pressure follow-up transmission based on the PID control strategy corresponding to each individual, and calculating the fitness of each individual based on the fitness function;

[0132] S400: performing selection operation, crossover operation, and mutation operation in sequence, and generating the next generation population;

[0133] S500: repeat steps S300-S400 until the highest fitness of all individuals in the population converges;

[0134] The individual with the highest fitness in the population is the individual closest to the optimal solution to the problem. The highest fitness convergence means that the highest fitness value in the population no longer changes significantly in one or more iteration cycles. During the iteration process, if the highest fitness converges, it is considered that the genetic algorithm has found the optimal solution, and the iteration can be stopped at this time. During the iteration process, the highest fitness in each generation of the population is recorded and compared with the highest fitness value of the previous generation. Set a change threshold for the highest fitness. If the change in the highest fitness value is less than the change threshold for several consecutive generations, such as 3 consecutive generations, it is considered that the highest fitness converges.

[0135] S600: Obtain the proportional coefficient, integral coefficient, and differential coefficient corresponding to the individual with the highest fitness as a pressure control strategy.

[0136] The simulation experiment of the pressure following transmission can use Simulink or other simulation tools to simulate the PID control process of the pressure following transmission. First, a target pressure value is set, and then the output pressure is regulated based on PID control until the output pressure value stabilizes near a fixed value and no longer fluctuates significantly, that is, a steady state is reached; the fixed value is the steady-state output value.

[0137] When different pressure control strategies are formulated by genetic algorithms, different fitness functions are used. The formula of the fitness function corresponding to the first pressure control strategy is as follows:

[0138] ;

[0139] in, represents the fitness of individuals in the genetic algorithm when formulating the first pressure control strategy; Represents steady-state error; V represents output fluctuation amplitude; , They are all weight coefficients, which are set by technicians in this field based on actual needs;

[0140] The steady-state error is the error between the output pressure value and the target pressure value after the output pressure value reaches the steady state in the simulation experiment of pressure follow-up transmission. The calculation formula is as follows:

[0141] ;

[0142] in, represents the steady-state output value in the simulation experiment of pressure follow-up transmission, Indicates the target pressure value; steady-state output value It is represented by the mean of several output pressure values ​​after reaching steady state;

[0143] The output fluctuation amplitude represents the maximum deviation of the output pressure value after reaching a steady state in the simulation experiment of pressure follow-up transmission. The calculation formula is as follows:

[0144] ;

[0145] in, Indicates the maximum value after the output pressure reaches the steady state. Indicates the minimum value after the output pressure reaches a steady state.

[0146] When the system is in a stable state, taking the steady-state error as part of the fitness function can minimize the steady-state error, ensuring that the PID controller can make the output as close to the set value as possible when the system is stable, thereby improving control accuracy; taking the output fluctuation amplitude as another part of the fitness function can minimize the fluctuation range of the output pressure, ensuring that the system maintains the smoothness and consistency of the output, reducing unnecessary control actions, and reducing energy consumption and equipment wear.

[0147] The formula of the fitness function corresponding to the second pressure control strategy is as follows:

[0148] ;

[0149] in, It represents the fitness of individuals in the genetic algorithm when formulating the second pressure control strategy; Indicates the maximum overshoot; represents the rise time; , They are all weight coefficients, which are set by technicians in this field based on actual needs;

[0150] The maximum overshoot represents the peak error rate when the output pressure value exceeds the target pressure value for the first time in the simulation experiment of pressure follow-up transmission. The calculation formula is as follows:

[0151] ;

[0152] in, It indicates the peak value when the output pressure value exceeds the target pressure value for the first time. After the simulation experiment of pressure follow-up transmission starts, the output pressure value increases with PID control. After it exceeds the target pressure value for the first time, it will gradually decrease under PID control and become less than the target pressure value after several sampling points. The maximum output pressure value among these sampling points is .

[0153] The calculation formula of the rise time is as follows:

[0154] ;

[0155] in, It indicates the time point when the output pressure value rises to 10% of the target pressure value for the first time after the simulation experiment of pressure follow-up transmission starts; Indicates the time point when the output pressure value first rises to 90% of the target pressure value.

[0156] When the system is in a rapidly changing state, minimizing the maximum overshoot through the fitness function can ensure that the system can quickly stabilize when transferring from one state to another, reduce unnecessary oscillations and overshoot, and improve the response speed and stability of the system; minimizing the rise time through the fitness function can ensure that the system can quickly respond to changes in the pressure source and shorten the time to reach a new steady state, thereby improving the dynamic performance of the system.

[0157] The formula of the fitness function corresponding to the third pressure control strategy is as follows:

[0158] ;

[0159] in, represents the fitness of individuals in the genetic algorithm when formulating the third pressure control strategy, , They are all weight coefficients, which are set by technicians in this field based on actual needs;

[0160] When the system is in a rapidly changing state, the main goal of PID control is to minimize the rise time, which can ensure that the system can respond quickly when the pressure source changes rapidly and improve the dynamic response speed of the system; at the same time, it is also necessary to take into account the steady-state error to ensure that the system can maintain a high control accuracy even in a rapidly changing state.

[0161] By designing specialized fitness functions for different system states, it can be ensured that the PID control strategy can automatically adjust parameters to adapt to the changing environment, thereby performing well under various working conditions and achieving more intelligent pressure transmission control.

[0162] S5: Based on the pressure control strategy and the output pressure data and input pressure data, the output pressure is regulated. The specific method is as follows:

[0163] Calculate the output error using the following formula:

[0164] ;

[0165] in, represents the output error of the kth sampling period; Represents the input pressure data of the kth sampling period; Represents the output pressure data of the kth sampling period; Indicates the preset pressure difference;

[0166] Based on the output error, the output signal value is calculated as follows:

[0167] If the output error The absolute value of is not less than the preset dead zone width D, then the calculation formula of the output signal value is as follows:

[0168] ;

[0169] in, Represents the output signal value of the kth sampling period; represents the proportionality coefficient; represents the integral coefficient; represents the differential coefficient; Represents the output error of the lth sampling period; represents the output error of the k-1th sampling period; Indicates the period length of any sampling period;

[0170] If the output error If the absolute value of is less than the preset dead zone width D, the calculation formula of the output signal value is as follows:

[0171] ;

[0172] in, Represents the output signal value of the k-1th sampling period;

[0173] By setting the dead zone width D, when the output error is small, the output signal value will not be changed, thereby reducing unnecessary control actions, helping to improve the stability and efficiency of the system, and reducing unnecessary energy consumption and equipment wear while ensuring the output pressure control effect.

[0174] Based on the output signal value, the output pressure is regulated. The PID control algorithm converts the output signal value It is mapped to the opening of the solenoid valve or electric valve to control the gas flow and thus the output pressure value.

[0175] By repeating steps S1 to S5, the pressure source can be continuously followed up and transmitted, and the PID parameters can be automatically optimized, which can greatly simplify the debugging process, reduce manual intervention, and improve work efficiency.

[0176] Example 2

[0177] This embodiment is the second embodiment of the present invention; it is based on the same inventive concept as embodiment 1, Figure 2,This embodiment introduces a pressure continuous follow-up transmission system, including a data acquisition module, a data verification module, a state judgment module, a controller module, and a pressure control module;

[0178] The data acquisition module includes a sensor unit for collecting pressure sensing data; and an input unit for receiving pressure source input data; the sensor unit converts the actual pressure value detected by the sensor into an electrical signal and sends it to the data verification module.

[0179] The data verification module is used to perform data verification on the pressure sensor data and the pressure source input data to obtain output pressure data and input pressure data; the module is configured with a fluctuation index calculation formula, a fluctuation threshold, a mutation index calculation formula, a mutation threshold, a cumulative input deviation calculation formula, and an input deviation threshold, which are used to determine whether the pressure sensor data and the pressure source input data pass the data verification; the module also includes an abnormal feedback unit, which is used to feedback abnormal information to the management personnel when data abnormalities occur.

[0180] The state judgment module is used to judge the system state based on the input pressure data; the module is configured with a calculation formula for the pressure change rate, a first change threshold, and a second change threshold, and judges the system state based on a comparison of the pressure change rate with the first change threshold and the second change threshold.

[0181] The controller module is used to compare the output pressure data with the input pressure data and generate a pressure control instruction; the module is configured with a first pressure control strategy, a second pressure control strategy, and a third pressure control strategy, and selects to execute the corresponding pressure control strategy based on the system state; through the PID control algorithm, the output signal value is calculated based on the pressure control strategy, and the output signal value is converted into a pressure control instruction.

[0182] The pressure control module is used to execute the pressure control instruction to adjust the output pressure. The module controls the opening of the solenoid valve or the electric valve based on the pressure control instruction, thereby controlling the flow of the gas and further controlling the output pressure value.

[0183] The specific functions of the above modules are realized by referring to the relevant contents of the pressure continuous follow-up transmission method described in Example 1, which will not be elaborated here.

[0184] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0185] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the purpose and scope of protection of the present invention, which are all within the protection of the present invention.

Claims

1. A method for continuously following up and transmitting gas pressure in a pneumatic system, characterized in that: The following steps are involved: S1: Obtaining pressure sensing data and performing data verification on the pressure sensing data to obtain output pressure data; the pressure sensing data includes output pressure sensing data and input pressure sensing data; wherein the input pressure sensing data is the input pressure value of the pressure source measured by the sensor, and the output pressure sensing data is the output pressure value of the system measured by the sensor; S2: Obtaining input data of the pressure source and performing data verification on the input data of the pressure source to obtain input pressure data; S3: judging the system state based on the input pressure data, specifically including: judging the system state based on the change rate of the input pressure data; the system state includes a stable state, a transitional state, and a rapidly changing state; the method for judging the system state is as follows: Acquire input pressure data and organize them into a pressure input sequence in chronological order; the pressure input sequence includes the last n data-verified pressure values ​​input by the pressure source; The pressure change rate of the pressure input sequence is calculated as follows: Among them, P r Represents the pressure change rate of the pressure input sequence; y h represents the hth pressure value in the pressure input sequence, y h-1 Represents the h-1th pressure value in the pressure input sequence; If the pressure change rate of the pressure input sequence is less than the first change threshold, the system state is a stable state; If the pressure change rate of the pressure input sequence is not less than the first change threshold and less than the second change threshold, the system state is a transition state; If the pressure change rate of the pressure input sequence is not less than the second change threshold, the system state is a rapid change state; S4: Based on the system state, obtaining a pressure control strategy; The pressure control strategy includes a first pressure control strategy, a second pressure control strategy, and a third pressure control strategy; if the system state is a stable state, the first pressure control strategy is obtained and executed; if the system state is a transitional state, the second pressure control strategy is obtained and executed; if the system state is a rapidly changing state, the third pressure control strategy is obtained and executed; The pressure control strategy is a PID control strategy, and the content of any pressure control strategy includes the proportional coefficient, integral coefficient, and differential coefficient of the PID controller; the method for formulating any pressure control strategy is as follows: a simulation experiment of pressure follow-up transmission is performed based on PID control, and the proportional coefficient, integral coefficient, and differential coefficient of the PID controller are determined by a genetic algorithm; When determining the proportional coefficient, integral coefficient and differential coefficient of the first pressure control strategy, the fitness of the individual in the genetic algorithm is calculated based on the steady-state error and the output fluctuation amplitude; the steady-state error is the absolute value of the difference between the steady-state output value and the target pressure value in the simulation experiment; the output fluctuation amplitude is the difference between the maximum value and the minimum value after the output pressure value reaches the maximum value after the steady state in the simulation experiment; When determining the proportional coefficient, integral coefficient, and differential coefficient of the second pressure control strategy, the fitness of the individual is calculated based on the maximum overshoot and rise time; the maximum overshoot is the deviation rate between the peak value and the target pressure value when the output pressure value exceeds the target pressure value for the first time in the simulation experiment; the rise time is the time difference between the time point when the output pressure value first rises to 90% of the target pressure value and the time point when the output pressure value first rises to 10% of the target pressure value in the simulation experiment; When determining the proportional coefficient, integral coefficient, and differential coefficient of the third pressure control strategy, the fitness of the individual is calculated based on the rise time and steady-state error; S5: Regulating the output pressure based on the pressure control strategy and the output pressure data and the input pressure data.

2. A method for continuously following up and transmitting gas pressure of a pneumatic system as claimed in claim 1, characterized in that: The method for performing data verification on any type of pressure sensor data is as follows: continuously collect pressure sensor data and perform data cleaning; collect pressure sensor data once in each sampling period, and form a time series of length N with the pressure sensor data of the previous N-1 sampling periods; perform volatility detection and mutation detection on the pressure sensor data based on the time series, if the pressure sensor data passes the volatility detection and mutation detection, the pressure sensor data passes the data verification; otherwise, the pressure sensor data verification is abnormal; Performing data verification on the output pressure sensing data and the input pressure sensing data respectively; If the output pressure sensing data passes the data verification, the output pressure sensing data in the time series of the output pressure sensing data is extracted as the output pressure data.

3. A method for continuously following up and transmitting gas pressure of a pneumatic system as claimed in claim 2, characterized in that: The method for performing fluctuation detection and mutation detection on pressure sensing data is as follows: Calculate the volatility index of the time series as follows: Wherein, δ represents the volatility index; x i represents the i-th pressure sensor data in the time series, and the value range of i is 1, 2, ..., N; μ represents the mean value of N pressure sensor data in the time series; If the volatility index of the time series is less than the preset volatility threshold, the pressure sensor data passes the volatility test; otherwise, the pressure sensor data volatility test is abnormal; The mutation index of each pressure sensing data in the time series is calculated using the following formula: Among them, λ i Represents the mutation index of the i-th pressure sensor data in the time series; if the mutation index of all pressure sensor data in the time series is less than the preset mutation threshold, the pressure sensor data passes the mutation detection; otherwise, the pressure sensor data mutation detection is abnormal.

4. A method for continuously following up and transmitting gas pressure of a pneumatic system as claimed in claim 3, characterized in that: The method for performing data verification on the pressure source input data is as follows: Read the input pressure sensor data of the last M sampling cycles as reference pressure data; the reference pressure data is the input pressure sensor data that has passed data verification; read M pressure source input data corresponding to the sampling cycles of the reference pressure data, and if at least m of the M pressure source input data exceed a preset input threshold range, the pressure source input data is abnormal; Otherwise, calculate the cumulative input deviation as follows: Where σ represents the cumulative input deviation; y j represents the input data of the jth pressure source, and the value range of j is 1, 2, ..., M; y j0 represents the jth reference pressure data; If the accumulated input deviation is less than the preset input deviation threshold, the pressure source input data passes the data verification; otherwise, the pressure source input data is abnormal; If the pressure source input data passes the data verification, the pressure source input data is extracted as the input pressure data; if the pressure source input data is abnormal, the input pressure sensor data in the reference pressure data is extracted as the input pressure data.

5. A method for continuously following up and transmitting gas pressure of a pneumatic system as claimed in claim 4, characterized in that: The formula of the fitness function involved in the genetic algorithm when formulating the first pressure control strategy is as follows: Among them, F s Represents the fitness of individuals in the genetic algorithm; E s represents steady-state error; V represents output fluctuation amplitude; w1 and w2 are weight coefficients; The calculation formula of the steady-state error is as follows: AND s =|and s -and d |; Among them, y s represents the steady-state output value in the simulation experiment of pressure follow-up transmission, y d Indicates the target pressure value; The calculation formula of the output fluctuation amplitude is as follows: V=y smax -and smin ; Among them, y smax Indicates the maximum value after the output pressure reaches the steady state, y smin Indicates the minimum value after the output pressure reaches a steady state.

6. A method for continuously following up and transmitting gas pressure of a pneumatic system as claimed in claim 5, characterized in that: The formula of the fitness function involved in the genetic algorithm when formulating the second pressure control strategy is as follows: Among them, F t Represents the fitness of individuals in the genetic algorithm; M O Indicates the maximum overshoot; T r Indicates rise time; w3 and w4 are weight coefficients; The calculation formula of the maximum overshoot is as follows: Among them, y max Indicates the peak value when the output pressure value exceeds the target pressure value for the first time; The calculation formula of the rise time is as follows: T r =t 90％ -t 10％ ; Among them, t 10％ It indicates the time point when the output pressure value rises to 10% of the target pressure value for the first time after the simulation experiment of pressure follow-up transmission starts; t 90％ Indicates the time point when the output pressure value first rises to 90% of the target pressure value; The formula of the fitness function involved in the genetic algorithm when formulating the third pressure control strategy is as follows: Among them, F f It represents the fitness of individuals in the genetic algorithm when formulating the third pressure control strategy. w5 and w6 are weight coefficients.

7. A method for continuously following up and transmitting gas pressure of a pneumatic system as claimed in claim 6, characterized in that: The method for controlling the output pressure is as follows: Calculate the output error using the following formula: e(k)=z(k0)-α-z(k); Wherein, e(k) represents the output error of the kth sampling period; z(k0) represents the input pressure data of the kth sampling period; z(k) represents the output pressure data of the kth sampling period; α represents the preset pressure difference; Based on the output error, an output signal value is calculated; and based on the output signal value, output pressure is regulated.

8. A gas pressure continuous follow-up transmission system for a pneumatic system, used to implement a gas pressure continuous follow-up transmission method for a pneumatic system according to any one of claims 1 to 7, characterized in that: It includes a data acquisition module, a data verification module, a state judgment module, a controller module, and a pressure control module; The data acquisition module includes a sensor unit for collecting pressure sensing data; and an input unit for receiving pressure source input data; The data verification module is used to perform data verification on the pressure sensing data and the pressure source input data to obtain output pressure data and input pressure data; The state judgment module is used to judge the system state based on the input pressure data; The controller module is used to compare the output pressure data with the input pressure data and generate a pressure control instruction; The pressure control module is used to execute the pressure control instruction and perform output pressure regulation.

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