Method for intelligently adjusting and controlling power of screw air compressor

Abstract

The invention relates to the technical field of equipment or system regulation and control, in particular to an intelligent regulation and control method for the power of a screw air compressor. The method comprises the steps of obtaining a current deviation window, obtaining a current deviation fluctuation intensity characterization value at a current regulation and control moment according to deviation in the current deviation window, and obtaining a historical deviation fluctuation intensity characterization value at a regulation and control moment adjacent to the current regulation and control moment, according to the difference between the historical deviation fluctuation intensity characterization value and the current deviation fluctuation intensity characterization value and the standard deviation of the current deviation window, a differential parameter adjustment factor is obtained; adjusting the differential item parameter at the adjacent regulation and control moment of the current regulation and control moment by using the differential item parameter adjustment factor to obtain a differential item parameter at the current regulation and control moment; and regulating and controlling the power of the screw air compressor at the current regulation and control moment by utilizing the differential item parameters at the current regulation and control moment. And the control stability of the exhaust pressure of the screw air compressor can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment or system regulation and control, and particularly relates to a method for intelligently regulating and controlling the power of a screw air compressor. Background Art

[0002] Currently, in order to achieve energy consumption optimization, extend the equipment life, reduce the maintenance cost, and ensure the stability of the production process, it is usually necessary to maintain the discharge pressure of the screw air compressor at a set value. And currently, the discharge pressure of the screw air compressor is usually controlled by regulating the power of the screw air compressor, that is, currently, the discharge pressure of the screw air compressor is usually maintained at the set value by regulating the power of the screw air compressor. Therefore, regulating the power of the screw air compressor is crucial for the control stability of the discharge pressure of the screw air compressor. In the prior art, a PID controller is usually used to regulate the power of the screw air compressor. However, when using the PID controller to regulate the power of the screw air compressor currently, a fixed differential term parameter is usually used to regulate the power of the screw air compressor. However, this way of regulating the power of the screw air compressor with a fixed differential term parameter will result in poor control stability of the discharge pressure of the screw air compressor. That is, this way of regulating the power of the screw air compressor with a fixed differential term parameter will cause the discharge pressure of the screw air compressor to have a continuous small-amplitude oscillation phenomenon of repeated overshoot and fall. And this continuous small-amplitude oscillation phenomenon of repeated overshoot and fall will have a negative impact on multiple aspects such as the equipment life and the stability of the production process. Therefore, how to regulate the power of the screw air compressor to improve the control stability of the discharge pressure of the screw air compressor has become an urgent problem to be solved. Summary of the Invention

[0003] In order to solve the above problems, the present invention provides a method for intelligently regulating and controlling the power of a screw air compressor, and the specific technical solution adopted is as follows: An embodiment of the present invention provides a method for intelligently regulating and controlling the power of a screw air compressor, including the following steps: Obtain the actual pressure signal at the current regulation moment, where the actual pressure signal is composed of actual pressure data points, the abscissa of the actual pressure data point is time, and the ordinate is the actual pressure data of the screw air compressor; Perform EMD decomposition on the actual pressure signal to obtain the IMM component, and obtain the current actual pressure data window at the current regulation moment according to the energy and period value of the IMM component; The current deviation window corresponding to the current actual pressure data window is obtained based on the difference between the target set pressure value and the actual pressure data in the current actual pressure data window, and the current deviation fluctuation intensity characterization value at the current regulation moment is obtained based on the deviation in the current deviation window; the historical deviation fluctuation intensity characterization value at the adjacent regulation moment of the current regulation moment is obtained, and based on the difference between the historical deviation fluctuation intensity characterization value and the current deviation fluctuation intensity characterization value and the standard deviation of the current deviation window, a differential term parameter adjustment factor is obtained, and the differential term parameter at the adjacent regulation moment of the current regulation moment is adjusted by using the differential term parameter adjustment factor to obtain the differential term parameter at the current regulation moment; The power of the screw air compressor at the current regulation moment is regulated by using the differential term parameter at the current regulation moment.

[0004] Beneficial effects: The present invention first obtains the actual pressure signal at the current regulation moment; then performs EMD decomposition on the actual pressure signal to obtain the IMM component, and obtains the current actual pressure data window at the current regulation moment based on the energy and period value of the IMM component; then the current deviation window corresponding to the current actual pressure data window is obtained based on the difference between the target set pressure value and the actual pressure data in the current actual pressure data window, and the current deviation fluctuation intensity characterization value at the current regulation moment is obtained based on the deviation in the current deviation window; the historical deviation fluctuation intensity characterization value at the adjacent regulation moment of the current regulation moment is obtained, and based on the difference between the historical deviation fluctuation intensity characterization value and the current deviation fluctuation intensity characterization value and the standard deviation of the current deviation window, a differential term parameter adjustment factor is obtained, and the differential term parameter at the adjacent regulation moment of the current regulation moment is adjusted by using the differential term parameter adjustment factor to obtain the differential term parameter at the current regulation moment; finally, the power of the screw air compressor at the current regulation moment is regulated by using the differential term parameter at the current regulation moment. And the present invention can reduce the occurrence of continuous small-amplitude oscillation phenomena of repeated overshoot and fall of the exhaust pressure of the screw air compressor by dynamically adjusting the differential term parameter of the PID controller and regulating the power of the screw air compressor based on the parameters of the dynamically adjusted PID controller, thereby improving the control stability of the exhaust pressure of the screw air compressor, that is, improving the control stability of the screw air compressor system. Description of the Drawings

[0005] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required to be used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0006] Figure 1 This is a flow chart of a method for intelligent power regulation and control of a screw air compressor according to the present invention. DETAILED DESCRIPTION

[0007] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field fall within the scope of protection of the embodiments of the present invention.

[0008] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0009] This embodiment provides a method for intelligently regulating and controlling the power of a screw air compressor, which is described in detail as follows: like Figure 1 As shown, the screw air compressor power intelligent regulation control method includes the following steps: Step S001: Acquire the actual pressure signal at the current control moment.

[0010] This embodiment mainly improves the control stability of the exhaust pressure of the screw air compressor by adaptively adjusting the differential parameter of the PID controller used when regulating the power of the screw air compressor. That is, this embodiment mainly avoids the occurrence of repeated small fluctuations in the exhaust pressure of the screw air compressor, such as repeated overshoot and fall, or avoids the occurrence of small fluctuations in the exhaust pressure of the screw air compressor around the set value, by adaptively adjusting the differential parameter of the PID controller used when regulating the power of the screw air compressor. In addition, the screw air compressor is usually a core component, which together with other auxiliary equipment constitutes a screw air compressor system, thereby providing stable compressed air pressure for production lines, pneumatic equipment, etc. The purpose of regulating the power of the screw air compressor is also to control the exhaust pressure of the screw air compressor system. Therefore, the control input is pressure data, which is then output by the PID controller as an inverter frequency control instruction. That is, the purpose of regulating the power of the screw air compressor is to control the exhaust pressure of the screw air compressor.

[0011] In the following, the regulation process of the power of any screw air compressor will be taken as an example for description, that is, the screw air compressor appearing subsequently in this embodiment is the same screw air compressor. Since the purpose of regulating the power of the screw air compressor is to control the exhaust pressure of the screw air compressor, when adaptively adjusting the differential term parameter of the PID controller used for regulating the power of the screw air compressor subsequently, the exhaust pressure needs to be referred to. Therefore, in the following of this embodiment, it is necessary to first obtain the actual pressure signal at the current regulation moment. The actual pressure signal at the current regulation moment is the basis for obtaining the differential term parameter at the current regulation moment subsequently. Then the specific process of the actual pressure signal at the current regulation moment is as follows: At each acquisition moment within the time period from the start of operation of the screw air compressor to the current regulation moment, obtain the exhaust pressure data of the screw air compressor collected by the industrial pressure sensor. Then use the filtering algorithm to denoise the exhaust pressure data collected within the time period from the start of operation of the screw air compressor to the current regulation moment, and record the denoised data as the actual pressure data of the screw air compressor at the corresponding acquisition moment. That is, for any acquisition moment, the actual pressure data of the screw air compressor at this acquisition moment is the data obtained after denoising the exhaust pressure data of the screw air compressor collected by the industrial pressure sensor at this acquisition moment; then construct a two-dimensional space, where the horizontal axis of the two-dimensional space represents time and the vertical axis represents the actual pressure data. Then map all the actual pressure data of the screw air compressor and the acquisition time corresponding to the actual pressure data obtained within the time period from the start of operation of the screw air compressor to the current regulation moment into the two-dimensional space to obtain the actual pressure data points in the two-dimensional space. Then connect all the actual pressure data points in the two-dimensional space in the order of the acquisition time, and record the signal curve obtained after the connection as the actual pressure signal at the current regulation moment; and if the abscissa value of any actual pressure data point is t0, then the ordinate value of this actual pressure data point is the actual pressure data of the screw air compressor at the acquisition moment t0.

[0012] In this embodiment, the frequency of collecting exhaust pressure data by the industrial pressure sensor is set according to experience. Generally, the collection frequency of the industrial pressure sensor is set between 5 Hz and 10 Hz. And if it is intelligent frequency conversion, the collection frequency is usually set between 10 Hz and 20 Hz. However, it is required that the collection moment of the exhaust pressure data of the screw air compressor be synchronized with the power adjustment moment of the screw air compressor. In addition, since the original output signal of the industrial pressure sensor is not essentially a pressure unit, but an original coded value linearly corresponding to the pressure, the exhaust pressure data of the screw air compressor collected in this embodiment are data after range conversion. And when the industrial pressure sensor collects the exhaust pressure of the screw air compressor, a limiting process operation will be performed. The limiting process and range conversion of the sensor in this embodiment are both well-known. In this embodiment, the implementer can select a filtering algorithm according to the actual situation to denoise the collected exhaust pressure data. For example, a low-pass filter can be selected in this embodiment.

[0013] Therefore, through the above process, the actual pressure signal at the current regulation moment is obtained in this embodiment.

[0014] Step S002: Perform EMD decomposition on the actual pressure signal to obtain IMM components, and obtain the current actual pressure data window at the current regulation moment according to the energy and period values of the IMM components.

[0015] Currently, when using the PID algorithm to regulate the power of the screw air compressor, a fixed derivative parameter is usually used to regulate the power of the screw air compressor. However, this method of regulating the power of the screw air compressor with a fixed derivative parameter will result in poor control stability of the exhaust pressure of the screw air compressor. That is, this method of regulating the power of the screw air compressor with a fixed derivative parameter will cause continuous small-amplitude oscillations of the exhaust pressure of the screw air compressor, such as repeated overshoots and falls. For example, if the fixed derivative parameter is relatively small, the ability to suppress deviation changes will be insufficient, resulting in continuous overshoots. If the fixed derivative parameter is relatively large, the adjustment amount will be overly offset, causing the exhaust pressure of the screw air compressor to oscillate repeatedly near the set value and be difficult to maintain at the set value. And this continuous small-amplitude oscillation phenomenon of repeated overshoots and falls will have a negative impact on multiple aspects such as equipment life and production process stability, such as accelerating equipment wear and failure risk, causing energy efficiency degradation and energy waste, and damaging the stability of the production process.

[0016] In order to improve the control stability of the exhaust pressure of the screw air compressor, that is, in order to avoid the occurrence of repeated small oscillations of the exhaust pressure of the screw air compressor as much as possible, the present embodiment will subsequently adjust the differential parameters adaptively according to the analysis of the deviation fluctuations, and then adjust the power of the screw air compressor based on the differential parameters obtained by the adaptive adjustment, so as to achieve the purpose of controlling the exhaust pressure of the screw air compressor. However, since the exhaust pressure data has the characteristics of nonlinearity, hysteresis and time-varying, the subsequent analysis cannot be based on a single data, but multiple data must be selected. However, in order to make the deviation fluctuations analyzed later more realistic, In order to be practical and effective, this embodiment requires that the selected actual pressure data length can include a complete overshoot to fallback process as much as possible. The complete overshoot to fallback process refers to a complete response from an overshoot to a fallback to the set value. Therefore, this embodiment needs to analyze the periodic characteristics of the actual pressure signal at the current control moment, and then determine the data length used for subsequent adjustment of the differential item parameters based on the obtained periodic characteristics. That is to say, the current actual pressure data window corresponding to the current control moment is determined based on the obtained periodic characteristics. However, due to the nonlinearity, hysteresis and disturbance characteristics of the screw air compressor system, the actual pressure data obtained is often in a non-stationary state. Therefore, directly analyzing the actual pressure signal is not a good choice. It is difficult to extract the true periodic characteristics of the pressure signal. In order to ensure the reliability of the periodic characteristics of the actual pressure signal being analyzed, this embodiment will first perform EMD decomposition on the actual pressure signal at the current control moment, output all the IMM components obtained by decomposition, and then calculate the energy and periodic value of each IMM component. The energy of any IMM component is the sum of the squares of the ordinate values of all sampling points on the IMM component, and the time of the abscissa value of any sampling point on the IMM component is the acquisition moment. EMD can decompose the signal into IMF components with local characteristics. There are relatively regular periodic changes in the IMF components. In addition, the periodic value of any IMM component refers to the intersection of the IMM component and the zero line. The zero line refers to the horizontal axis in the two-dimensional space, which is also the time axis. That is, for any IMM component, first obtain the intersection of the IMM component and the zero line, and arrange all the intersections of the IMM component and the zero line in chronological order to obtain the intersection sequence corresponding to the IMM component, obtain the average value of the time intervals between all adjacent intersections in the intersection sequence, and record it as the period value of the IMM component. The calculation method of the period value of the above-mentioned IMM component belongs to the average period method. As other implementation methods, other well-known methods can also be used to obtain the period value of the IMM component. For example, the implementer can choose to use the energy spectrum density-period analysis method to calculate the period of the IMM component.

[0017] After obtaining the energy and period values of each IMM component, the current actual pressure data window at the current regulation moment is obtained based on the energy and period values of each IMM component. The specific process is as follows: First, all the IMM components obtained by decomposition are sorted according to the energy size, and the sequence obtained by sorting is denoted as the IMM component sequence. Then, the sequence to be analyzed is obtained based on the positions and energies of the IMM components in the IMM component sequence. The process of obtaining the sequence to be analyzed is as follows: Obtain the cumulative sum of the energies of all the IMM components in the IMM component sequence and denote it as the first total energy. Determine whether the ratio of the cumulative sum of the energies of the first N IMM components in the IMM component sequence to the first total energy is greater than the preset proportion threshold, and whether the ratio of the cumulative sum of the energies of the first N - 1 IMM components in the IMM component sequence to the first total energy is not greater than the preset proportion threshold. If both are satisfied, the new sequence composed of the first N IMM components in the IMM component sequence is denoted as the sequence to be analyzed. That is, when the ratio of the cumulative sum of the energies of the first N IMM components in the IMM component sequence to the first total energy is greater than the preset proportion threshold, and at the same time, the ratio of the cumulative sum of the energies of the first N - 1 IMM components in the IMM component sequence to the first total energy is not greater than the preset proportion threshold, the new sequence composed of the first N IMM components in the IMM component sequence is the sequence to be analyzed, where N is greater than 1. And in specific applications, the implementer needs to set the preset proportion threshold according to the actual situation or relevant experience. For example, in this embodiment, the preset proportion threshold can be set to 0.8, but it is required not to be too small or too large. If it is too small, key medium and low-frequency components will be missed, and the signal will not be completely characterized. If it is too large, the redundancy of high-order IMFs will be introduced. In addition, the purpose of obtaining the sequence to be analyzed based on the preset proportion threshold in this embodiment is to improve the reliability of the target period value obtained subsequently, and to make the obtained target period value closer to the energy concentration part of the actual pressure signal at the current regulation moment.

[0018] After obtaining the sequence to be analyzed, the weight factors of each IMM component in the sequence to be analyzed are obtained. For any IMM component in the sequence to be analyzed, in this embodiment, the ratio of the energy of this IMM component to the second total energy is used as the weight factor of this IMM component. The second total energy is the sum of the energies of all IMM components in the sequence to be analyzed. And because in the EMD decomposition process, as the IMF order increases, the proportion of noise and short-term perturbations in the component composition is larger. Therefore, the reference value of the period value of the IMM component with a higher IMF order is smaller. So in this embodiment, the larger the energy of the IMM component, the larger the weight factor, that is, the larger the contribution of the period value of the IMM component with a larger energy to determining the target period value at the current regulation moment. Therefore, after obtaining the weight factors of each IMM component in the sequence to be analyzed, this embodiment calculates the product of the weight factor of each IMM component in the sequence to be analyzed and the period value of the corresponding IMM component, and takes it as the weighted period value of the corresponding IMM component, calculates the sum of the weighted period values of all IMM components in the sequence to be analyzed, and records it as the target period value at the current regulation moment. And the specific calculation formula of the target period value at the current regulation moment is , where N is the total number of IMM components in the sequence to be analyzed, is the weight factor of the nth IMM component in the sequence to be analyzed, is the period value of the nth IMM component in the sequence to be analyzed, and the target period value at the current regulation moment is the length of the current actual pressure data window corresponding to the current regulation moment; then all actual pressure data with the acquisition time in the interval [T - L, T] are obtained, and the window constructed by all actual pressure data with the acquisition time in the interval [T - L, T] is used as the current actual pressure data window at the current regulation moment, T is the current regulation moment, and L is the target period value at the current regulation moment; and this dynamic way of obtaining the current actual pressure data window in this embodiment can provide a reliable basis for the subsequent analysis of the current oscillation trend.

[0019] Therefore, through the above process, this embodiment obtains the current actual pressure data window corresponding to the current regulation moment.

[0020] Step S003: Obtain the current deviation window corresponding to the current actual pressure data window based on the difference between the target set pressure value and the actual pressure data in the current actual pressure data window, and obtain the current deviation fluctuation intensity characterization value at the current regulation moment according to the deviation in the current deviation window; obtain the historical deviation fluctuation intensity characterization value at the adjacent regulation moment of the current regulation moment, and obtain the differential parameter adjustment factor according to the difference between the historical deviation fluctuation intensity characterization value and the current deviation fluctuation intensity characterization value and the standard deviation of the current deviation window, and use the differential parameter adjustment factor to adjust the differential parameter at the adjacent regulation moment of the current regulation moment to obtain the differential parameter at the current regulation moment.

[0021] In the following, this embodiment will determine the differential parameter at the current regulation moment based on the above-obtained data window. The specific process is as follows: First, obtain the set pressure value of the screw air compressor and denote it as the target set pressure value. The set pressure value of the screw air compressor refers to the target exhaust pressure pre-configured by the user on the screw air compressor control system. Then, obtain the current deviation window corresponding to the current actual pressure data window according to the difference between the target set pressure value and the actual pressure data in the current actual pressure data window. The current deviation window is the key to obtaining the differential parameter adjustment direction characterization value and the differential parameter adjustment amplitude subsequently. And the a-th deviation in the current deviation window corresponding to the current actual pressure data window is the result of subtracting the a-th actual pressure data in the current actual pressure data window from the target set pressure value, that is, the a-th deviation in the current deviation window is the deviation of the a-th actual pressure data in the current actual pressure data window. The calculation process of the deviation of the actual pressure data in this embodiment is well-known.

[0022] After obtaining the current deviation window corresponding to the current actual pressure data window at the current regulation moment, obtain the adjacent regulation moment of the current regulation moment. The adjacent regulation moment of the current regulation moment refers to the regulation moment adjacent to the current regulation moment and preceding the current regulation moment in time. Then, obtain the historical actual pressure data window of the adjacent regulation moment of the current regulation moment, and obtain the historical deviation window corresponding to the historical actual pressure data window of the adjacent regulation moment of the current regulation moment according to the difference between the target set pressure value and the actual pressure data in the historical actual pressure data window of the adjacent regulation moment of the current regulation moment. And the obtaining methods of the historical actual pressure data window of the adjacent regulation moment of the current regulation moment and the historical deviation window corresponding to the historical actual pressure data window of the adjacent regulation moment of the current regulation moment are the same as those of the current actual pressure data window at the current regulation moment and the current deviation window corresponding to the current actual pressure data window at the current regulation moment, so no detailed description will be given here.

[0023] After obtaining the current deviation window corresponding to the current actual pressure data window at the current regulation moment and the historical deviation window corresponding to the historical actual pressure data window at the adjacent regulation moment of the current regulation moment, the current deviation fluctuation intensity characterization value at the current regulation moment is obtained according to the deviation in the current deviation window corresponding to the current actual pressure data window at the current regulation moment, and the historical deviation fluctuation intensity characterization value at the adjacent regulation moment of the current regulation moment is obtained according to the deviation in the historical deviation window corresponding to the historical actual pressure data window at the adjacent regulation moment of the current regulation moment. Moreover, the deviation fluctuation intensity characterization value at any regulation moment is either to characterize the deviation fluctuation of the actual pressure data in the actual pressure data window corresponding to the corresponding regulation moment or to characterize the deviation fluctuation in the deviation window corresponding to the actual pressure data window corresponding to the corresponding regulation moment.

[0024] Also, since the obtaining method of the deviation fluctuation intensity characterization value at any regulation moment is the same, that is, the obtaining method of the current deviation fluctuation intensity characterization value at the current regulation moment is the same as the obtaining method of the historical deviation fluctuation intensity characterization value at the adjacent regulation moment of the current regulation moment. Then, for the sake of easy understanding, the following will describe the obtaining process of the current deviation fluctuation intensity characterization value at the current regulation moment as an example. And the specific obtaining process of the current deviation fluctuation intensity characterization value at the current regulation moment is as follows: First, obtain the sum of the absolute values of all deviations in the current deviation window and denote it as the comprehensive deviation. Then, calculate the ratio of the absolute value of each deviation in the current deviation window to the comprehensive deviation and denote it as the weight factor of the corresponding deviation. Then, obtain the squared value of each deviation in the current deviation window. And since a larger deviation can better characterize the situation of the increased fluctuation or unstable response of the screw air compressor, therefore, in order to better reflect the severity of the deviation fluctuation in this embodiment, when calculating the deviation fluctuation intensity at the regulation moment, the larger the deviation, the more it can dominate the final result. That is, when calculating the deviation fluctuation intensity at the regulation moment, in order to make the calculated result better reflect the deviation fluctuation intensity at the corresponding regulation moment, not only the square of the deviation is used to amplify the influence of the larger deviation on the result, but also the participation degree or the contribution degree of the larger deviation to the result is greater. Then, based on the above analysis, according to the squared value of each deviation and the weight factor of the corresponding deviation in the current deviation window, the weighted deviation of each deviation in the current deviation window is obtained. Then, calculate the sum of the weighted deviations of all deviations in the current deviation window and use it as the current deviation fluctuation intensity characterization value corresponding to the current regulation moment. And for any deviation in the current deviation window, the weighted deviation of this deviation refers to the product of the squared value of this deviation and the weight factor of this deviation.

[0025] After obtaining the current deviation fluctuation intensity characterization value at the current regulation moment and the historical deviation fluctuation intensity characterization value at the adjacent regulation moment of the current regulation moment, the differential parameter adjustment factor at the current regulation moment is obtained according to the difference between the historical deviation fluctuation intensity characterization value at the adjacent regulation moment of the current regulation moment and the current deviation fluctuation intensity characterization value, and the standard deviation of the current deviation window. And the differential parameter adjustment factor is the key to determining the differential parameter at the current regulation moment. Then the specific process of obtaining the differential parameter adjustment factor at the current regulation moment is as follows: First, calculate the result of subtracting the historical deviation fluctuation intensity characterization value from the current deviation fluctuation intensity characterization value, and denote it as the deviation fluctuation change characterization value at the current regulation moment. Then, determine whether the deviation fluctuation change characterization value at the current regulation moment is equal to the preset judgment threshold. If it is equal, it indicates that the deviation fluctuation intensity trend at the current regulation moment is stable. At this time, the differential parameter of the PID controller does not need to be adjusted, and the control stability of the exhaust pressure of the screw air compressor can also be ensured. Therefore, when the deviation fluctuation change characterization value is equal to the preset judgment threshold, there is no need to calculate the differential parameter adjustment factor at the current regulation moment, and the constant 1 can be directly used as the differential parameter adjustment factor at the current regulation moment. That is, when the deviation fluctuation change characterization value is equal to the preset judgment threshold, there is no need to calculate the differential parameter adjustment direction characterization value and the differential parameter adjustment amplitude.

[0026] However, when it is determined that the deviation fluctuation change characterization value at the current regulation moment is not equal to the preset judgment threshold, it indicates that there is an increasing or decreasing trend in the deviation fluctuation intensity at the previous regulation moment. At this time, the differential parameter of the PID controller needs to be adjusted to ensure the control stability of the exhaust pressure of the screw air compressor. Therefore, when it is determined that the deviation fluctuation change characterization value at the current regulation moment is not equal to the preset judgment threshold, first, according to the deviation fluctuation change characterization value and the preset judgment threshold, the differential parameter adjustment direction characterization value at the current regulation moment is obtained. The differential parameter adjustment direction characterization value can control the adjustment direction, that is, the differential parameter adjustment direction characterization value can control whether to increase or decrease. Then, according to the absolute value of the deviation fluctuation change characterization value and the standard deviation of the current deviation window, the differential parameter adjustment amplitude at the current regulation moment is obtained. Finally, according to the differential parameter adjustment direction characterization value and the differential parameter adjustment amplitude at the current regulation moment, the differential parameter adjustment factor at the current regulation moment is obtained. In addition, since the change of data at one moment relative to another moment is usually judged based on 0, the preset judgment threshold is set to 0 in this embodiment.

[0027] In this embodiment, the specific process of obtaining the differential parameter adjustment direction characterization value at the current regulation moment according to the deviation fluctuation change characterization value and the preset judgment threshold at the current regulation moment is as follows: Judge whether the deviation fluctuation change characterization value is greater than the preset judgment threshold. If so, it indicates that the current regulation moment is relative to the adjacent regulation moment of the current regulation moment, that is, the current regulation moment is relative to the previous regulation moment of the current regulation moment, and the deviation fluctuation intensity at the current regulation moment has an increasing trend. It also shows that the screw air compressor system is in a drastic adjustment stage. At this time, if the derivative term parameter of the PID controller is relatively small, it will cause the controller to be insensitive to this change, then it may not be able to suppress the upcoming overshoot or rebound in time, thereby exacerbating the oscillation. Therefore, the derivative term parameter should be increased to enhance its inhibitory effect. That is, at this time, in order to make the screw air compressor system more sensitive to capture the deviation change trend, the derivative term parameter of the PID controller should be increased to strengthen the response to the deviation change. Therefore, when the deviation fluctuation change characterization value is greater than the preset judgment threshold, the constant 1 is used as the derivative term parameter adjustment direction characterization value at the current regulation moment; if it is judged that the deviation fluctuation change characterization value is less than the preset judgment threshold, it indicates that the deviation fluctuation intensity at the current regulation moment has a decreasing trend relative to the previous regulation moment of the current regulation moment. Then, the derivative term parameter of the PID controller should be decreased to prevent the controller from overreacting to ensure that the screw air compressor system maintains a stable working state. That is, when the deviation fluctuation weakens, it means that the screw air compressor system is tending to be stable. At this time, a relatively large derivative term parameter of the PID controller may cause a solitary reaction, which will lead to frequent adjustment and oscillation of the system. The derivative term parameter should be decreased. Therefore, when the deviation fluctuation change characterization value is less than the preset judgment threshold, the negative 1 is used as the derivative term parameter adjustment direction characterization value at the current regulation moment.

[0028] In this embodiment, the specific process of obtaining the derivative term parameter adjustment amplitude at the current regulation moment according to the absolute value of the deviation fluctuation change characterization value and the standard deviation of the current deviation window is as follows: First, use the hyperbolic tangent function to normalize the absolute value of the deviation fluctuation change characterization value, and record the normalization result as the normalized deviation fluctuation change characterization value. Obtain the standard deviation of the current deviation window, and use the hyperbolic tangent function to normalize the standard deviation of the current deviation window. Record the normalization result as the normalized deviation standard deviation. Calculate the mean value of the normalized deviation fluctuation change characterization value and the normalized deviation standard deviation, and use it as the derivative term parameter adjustment amplitude at the current regulation moment. And the specific formula for calculating the derivative term parameter adjustment amplitude at the current regulation moment is:

[0029] where, W is the derivative term parameter adjustment amplitude at the current regulation moment, tanh() is the hyperbolic tangent function, D is the deviation fluctuation change characterization value, Is the standard deviation of the current deviation window; and the greater the absolute value of the deviation fluctuation characterization value, it indicates that the screw air compressor system at the current control moment is in a rapid change period, or the current control moment is relative to the previous control moment of the current control moment. The greater the degree of change in the exhaust pressure of the screw air compressor at the current control moment, then in order to improve the control stability of the exhaust pressure of the screw air compressor, the PID controller needs to respond more actively to this change, that is, the differential parameter of the PID controller should be adjusted more significantly at this time; and the larger the standard deviation of the current deviation window, the less concentrated the deviation distribution in the current deviation window, the more severe the deviation fluctuation, and the smaller the deviation in the window. The greater the degree of difference dispersion, the greater the probability that the screw air compressor system is affected by the superposition of load changes or control output delays, and the more unstable the screw air compressor system is, then the differential parameters of the PID controller should be adjusted more significantly to suppress overshoot and continuous oscillation; it can be seen that when the absolute value of the deviation fluctuation change characterization value is larger and the standard deviation of the current deviation window is larger, that is, the larger the adjustment range of the differential parameters at the current control moment, it indicates that relative to the differential parameters of the PID controller at the previous control moment, the adjustment range of the differential parameters of the PID controller is larger at this time, and vice versa.

[0030] In this embodiment, according to the differential parameter adjustment direction representation value at the current control moment and the differential parameter adjustment amplitude at the previous control moment, the specific formula for obtaining the differential parameter adjustment factor at the current control moment is:

[0031] Among them, Q is the differential parameter adjustment factor at the current regulation moment, c is the preset adjustment control coefficient, F is the characterization value of the differential parameter adjustment direction at the current regulation moment, and W is the adjustment amplitude of the differential parameter at the current regulation moment. And when the value of F is 1 and the value of W is larger, it indicates that the increase degree of the differential parameter at the previous regulation moment of the current regulation moment is more. The previous regulation moment of the current regulation moment is the adjacent regulation moment of the current regulation moment. When the value of F is 1 and the value of W is smaller, it indicates that the increase degree of the differential parameter at the previous regulation moment of the current regulation moment is less. When the value of F is -1 and the value of W is larger, it indicates that the decrease degree of the differential parameter at the previous regulation moment of the current regulation moment is more. When the value of F is -1 and the value of W is smaller, it indicates that the decrease degree of the differential parameter at the previous regulation moment of the current regulation moment is less. In addition, in this embodiment, the implementer needs to set the preset adjustment control coefficient according to the maximum increase or decrease degree of the differential parameter. For example, this embodiment requires that the maximum increase or decrease degree of the differential parameter does not exceed the value of the differential parameter at the previous regulation moment of the current regulation moment. Therefore, this embodiment sets the preset adjustment control coefficient to 1.

[0032] After obtaining the differential parameter adjustment factor at the current regulation moment, the differential parameter at the adjacent regulation moment of the current regulation moment is obtained, that is, the differential parameter of the PID controller at the previous regulation moment of the current regulation moment. Then, the differential parameter at the adjacent regulation moment of the current regulation moment is adjusted by using the differential parameter adjustment factor at the current regulation moment, and the adjusted differential parameter is used as the differential parameter at the current regulation moment. And the differential parameter at the previous regulation moment is the product of the differential parameter at the adjacent regulation moment of the current regulation moment and the differential parameter adjustment factor at the current regulation moment, that is, the differential parameter at the current regulation moment is , where is the differential parameter at the adjacent regulation moment of the current regulation moment.

[0033] Therefore, through the above process, this embodiment obtains the differential parameter at the current regulation moment.

[0034] Step S004, regulating the power of the screw air compressor at the current regulation moment by using the differential parameter at the current regulation moment.

[0035] Since usually when adjusting the derivative term parameters, it is also necessary to synchronously adjust the proportional term parameters and the integral term parameters. Therefore, it is necessary to synchronously adjust the proportional term parameters and the integral term parameters at the adjacent control moment of the current control moment based on the proportional term parameters, integral term parameters, derivative term parameters at the adjacent control moment of the current control moment and the derivative term parameters at the current control moment, so as to obtain the proportional term parameters and integral term parameters at the current control moment. And when adjusting the derivative term parameters, the process of synchronously adjusting the proportional term parameters and the integral term parameters is well-known. That is, when adjusting the derivative term parameters, usually the integral term parameters at the current control moment are obtained according to the requirements of engineering experience. For example, if the engineering experience requires that the integral term parameters are between 4 times and 8 times the derivative term parameters, then the integral term parameters at the current control moment are between 4×Td and 8×Td, where Td is the derivative term parameter at the current control moment. When adjusting the derivative term parameters, generally the result calculated according to the formula is used as the proportional term parameter at the current control moment. And when calculating the proportional term parameter at the current control moment, in the formula is the proportional term parameter at the adjacent control moment of the current control moment, is the derivative term parameter at the adjacent control moment of the current control moment, is the derivative term parameter at the current control moment obtained, is the empirical buffer coefficient, which is generally set between 0.8 and 0.9; the proportional term parameter, integral term parameter, and derivative term parameter in this embodiment are the three parameters of the PID controller.

[0036] After obtaining the derivative term parameter, proportional term parameter, and integral term parameter of the PID controller at the current control moment, the power of the screw air compressor at the current control moment is regulated based on the derivative term parameter, proportional term parameter, and integral term parameter of the PID controller at the current control moment; and on the premise of knowing the three parameters of the PID controller, the specific process of regulating the power of the screw air compressor is a well-known technology. In this embodiment, by dynamically adjusting the derivative term parameter of the PID controller and regulating the power of the screw air compressor based on the parameters of the dynamically adjusted PID controller, it is possible to reduce or suppress the continuous small-amplitude oscillation phenomenon of the repeated overshoot and fall of the exhaust pressure of the screw air compressor caused by the inverter regulation delay, the delay accumulation effect after gas compression, etc., thereby improving the control stability of the exhaust pressure of the screw air compressor.

[0037] In summary, in this embodiment, the actual pressure signal at the current regulation moment is first obtained; then the actual pressure signal is decomposed by EMD to obtain the IMM component, and the current actual pressure data window at the current regulation moment is obtained according to the energy and period value of the IMM component; then, according to the difference between the target set pressure value and the actual pressure data in the current actual pressure data window, the current deviation window corresponding to the current actual pressure data window is obtained, and the current deviation fluctuation intensity characterization value at the current regulation moment is obtained according to the deviation in the current deviation window; the historical deviation fluctuation intensity characterization value at the adjacent regulation moment of the current regulation moment is obtained, and according to the difference between the historical deviation fluctuation intensity characterization value and the current deviation fluctuation intensity characterization value and the standard deviation of the current deviation window, the differential parameter adjustment factor is obtained, and the differential parameter at the adjacent regulation moment of the current regulation moment is adjusted by using the differential parameter adjustment factor to obtain the differential parameter at the current regulation moment; finally, the power of the screw air compressor at the current regulation moment is regulated by using the differential parameter at the current regulation moment. And in this embodiment, by dynamically adjusting the differential parameter of the PID controller and regulating the power of the screw air compressor based on the parameters of the dynamically adjusted PID controller, the occurrence of the continuous small-amplitude oscillation phenomenon of the repeated overshoot and fall of the exhaust pressure of the screw air compressor can be reduced, thereby improving the control stability of the exhaust pressure of the screw air compressor, that is, improving the control stability of the screw air compressor system.

[0038] The above-described embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for intelligent power adjustment control of a screw air compressor, characterized in that, The method includes the following steps: Obtain the actual pressure signal at the current regulation moment, where the actual pressure signal is composed of actual pressure data points, the abscissa of the actual pressure data points is time, and the ordinate is the actual pressure data of the screw air compressor; Perform EMD decomposition on the actual pressure signal to obtain IMM components, and obtain the current actual pressure data window at the current regulation moment according to the energy and period values of the IMM components; Obtain the current deviation window corresponding to the current actual pressure data window according to the difference between the target set pressure value and the actual pressure data in the current actual pressure data window, and obtain the current deviation fluctuation intensity characterization value at the current regulation moment according to the deviation in the current deviation window; Obtain the historical deviation fluctuation intensity characterization value at the adjacent regulation moment of the current regulation moment, obtain the differential parameter adjustment factor according to the difference between the historical deviation fluctuation intensity characterization value and the current deviation fluctuation intensity characterization value and the standard deviation of the current deviation window, and use the differential parameter adjustment factor to adjust the differential parameter at the adjacent regulation moment of the current regulation moment to obtain the differential parameter at the current regulation moment; Use the differential parameter at the current regulation moment to regulate the power of the screw air compressor at the current regulation moment.

2. The intelligent power adjustment control method for a screw air compressor according to claim 1, characterized in that, The method for obtaining the current actual pressure data window at the current regulation moment includes: Sort all IMM components according to energy size to obtain an IMM component sequence, and obtain a sequence to be analyzed according to the positions and energies of the IMM components in the IMM component sequence; Denote the ratio of the energy of each IMM component in the sequence to be analyzed to the sum of the energies of all IMM components in the sequence to be analyzed as the weight factor of the corresponding IMM component; Calculate the period value of each IMM component in the sequence to be analyzed, and take the product of the weight factor of each IMM component in the sequence to be analyzed and the corresponding IMM component's period value as the weighted period value of the corresponding IMM component, calculate the sum of the weighted period values of all IMM components in the sequence to be analyzed, and denote it as the target period value at the current regulation moment; Take the window constructed by all actual pressure data whose acquisition time is within the interval [T - L, T] as the current actual pressure data window at the current regulation moment, where T is the current regulation moment and L is the target period value at the current regulation moment.

3. The intelligent adjustment control method for the power of a screw air compressor according to claim 1, characterized in that, The method for obtaining the sequence to be analyzed includes: Denote the sum of the energies of all IMM components in the IMM component sequence as the first total energy. If the ratio of the sum of the energies of the first N IMM components in the IMM component sequence to the first total energy is greater than the preset proportion threshold, and the ratio of the sum of the energies of the first N - 1 IMM components in the IMM component sequence to the first total energy is not greater than the preset proportion threshold, then denote the new sequence composed of the first N IMM components in the IMM component sequence as the sequence to be analyzed.

4. A power intelligent adjustment control method for a screw air compressor according to claim 1, characterized in that, The a-th deviation in the current deviation window is the result of subtracting the a-th actual pressure data in the current actual pressure data window from the target set pressure value.

5. The intelligent power adjustment control method of a screw air compressor according to claim 1, characterized in that, The method for obtaining the characterization value of the current deviation fluctuation intensity includes: Denote the ratio of each absolute deviation in the current deviation window to the sum of all absolute deviations in the current deviation window as the weight factor of the corresponding deviation, calculate the product of the square value of each deviation in the current deviation window and the weight factor of the corresponding deviation, and denote it as the weighted deviation of the corresponding deviation. Take the sum of the weighted deviations of all deviations in the current deviation window as the characterization value of the current deviation fluctuation intensity at the current regulation moment.

6. The intelligent power adjustment control method of a screw air compressor according to claim 1, characterized in that, The method for obtaining the characterization value of the historical deviation fluctuation intensity is the same as the method for obtaining the characterization value of the current deviation fluctuation intensity.

7. A method for intelligent power adjustment control of a screw air compressor according to claim 1, characterized in that The method for obtaining the adjustment factor of the differential term parameter includes: Obtain the result of subtracting the characterization value of the historical deviation fluctuation intensity from the characterization value of the current deviation fluctuation intensity, and denote it as the characterization value of the deviation fluctuation change. Judge whether the characterization value of the deviation fluctuation change is equal to the preset judgment threshold. If so, take the constant 1 as the adjustment factor of the differential term parameter at the current regulation moment. Otherwise, obtain the characterization value of the adjustment direction of the differential term parameter at the current regulation moment according to the characterization value of the deviation fluctuation change and the preset judgment threshold, obtain the adjustment amplitude of the differential term parameter at the current regulation moment according to the absolute value of the characterization value of the deviation fluctuation change and the standard deviation of the current deviation window, and denote the sum of the product of the characterization value of the adjustment direction of the differential term parameter and the adjustment amplitude of the differential term parameter and the preset adjustment control coefficient as the adjustment factor of the differential term parameter at the current regulation moment.

8. A method for intelligent power adjustment control of a screw air compressor according to claim 7, characterized in that, The method for obtaining the characterization value of the adjustment direction of the differential term parameter at the current regulation moment includes: If the characterization value of the deviation fluctuation change is greater than the preset judgment threshold, take the constant 1 as the characterization value of the adjustment direction of the differential term parameter at the current regulation moment. If the characterization value of the deviation fluctuation change is less than the preset judgment threshold, take -1 as the characterization value of the adjustment direction of the differential term parameter at the current regulation moment.

9. The intelligent power adjustment control method for a screw air compressor according to claim 7, characterized in that, The method for obtaining the adjustment amplitude of the differential term parameter at the current regulation moment includes: Normalize the absolute value of the characterization value of the deviation fluctuation change to obtain the normalized characterization value of the deviation fluctuation change, normalize the standard deviation of the current deviation window to obtain the normalized deviation standard deviation, and calculate the mean of the normalized characterization value of the deviation fluctuation change and the normalized deviation standard deviation as the adjustment amplitude of the differential term parameter at the current regulation moment.

10. A power intelligent adjustment control method for a screw air compressor according to claim 1, characterized in that, The differential term parameter at the current regulation moment is the product of the differential term parameter at the adjacent regulation moment of the current regulation moment and the adjustment factor of the differential term parameter at the current regulation moment.

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