Automatic control method and system for electrical system assembly

Abstract

The invention relates to the technical field of automatic control, in particular to an automatic control method and system for an electrical system component, and the method comprises the steps: obtaining PID control data and a flow monitoring signal; determining a time delay value between the flow monitoring signals according to the correlation between the two flow monitoring signals; a signal fluctuation factor is determined according to the amplitude distribution of a flow monitoring signal of a monitoring point in a short-time window and the amplitude distribution of a flow monitoring signal of a next monitoring point after time delay in the short-time window, and the interference probability is determined by combining the amplitude difference and phase difference of the flow monitoring signals contained in all the short-time windows in a frequency domain. Screening out interference frequency; obtaining a nonlinear error probability according to the distribution of all interference frequencies; and adjusting the proportional gain in the PID control data according to the nonlinear error probability to complete the automatic control of the adjusting type electric valve. The control precision of the adjusting type electric valve during automatic control is improved by supplementing non-linear errors.

Description

Technical Field

[0001] The present application relates to the field of automatic control technology, and in particular to an automatic control method and system for electrical system components. Background Art

[0002] Control valves are commonly used in various equipment and subsystems in electrical systems, such as boilers, generators, etc. In steam turbines, valves can be used to adjust the amount and pressure of steam to ensure the normal operation of the steam turbine; control valves can adjust the flow, pressure or flow rate of the medium to ensure the stability of power generation equipment under different working conditions. Therefore, power station valves play an important role in ensuring the safe and stable operation of electrical systems.

[0003] In electrical systems, PID control systems are often used to achieve automatic control of control valves by online monitoring of their status data. However, the flow state of liquids and gases flowing through valves will change under different conditions. These changes will affect the sensors arranged around the control valves when collecting status data, such as bubbles and liquid diversion in the liquid. As a result, the status data cannot accurately reflect the working state of the valve, causing system errors and deviations in the automatic control of the control valves, and even affecting the normal operation of the electrical system. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide an automatic control method and system for electrical system components. The technical solutions adopted are as follows: In a first aspect, an embodiment of the present application provides an automatic control method for an electrical system component, the method comprising the following steps: Obtaining PID control data of the regulating electric valve and flow monitoring signals at each monitoring point of the regulating electric valve; According to the correlation between the flow monitoring signals at the two monitoring points, the time delay value between the flow monitoring signals at the two monitoring points is determined; according to the amplitude distribution of the flow monitoring signal at the monitoring point in the short-time window and the amplitude distribution of the flow monitoring signal at the next monitoring point after the time delay in the short-time window, the signal fluctuation factor of the monitoring point in each short-time window is determined; According to the amplitude difference, phase difference and signal fluctuation factor of the flow monitoring signals in the frequency domain contained in all short-time windows of adjacent monitoring points, the interference probability of the flow monitoring signals at each frequency of the monitoring point is determined; the interference frequency is obtained according to the interference probability of the flow monitoring signals at all frequencies of the monitoring point; The nonlinear error probability is obtained according to the distribution of interference frequencies at all adjacent monitoring points; the proportional gain in the PID control data is adjusted according to the nonlinear error probability to complete the automatic control of the regulating electric valve.

[0005] Preferably, determining the time delay value between the flow monitoring signals of two monitoring points includes: Preset the initial value of the time delay between the flow monitoring signals of two monitoring points and the iteration step size; The cross-correlation function is constructed by using the signal values ​​of the flow monitoring signals of the two monitoring points at different sampling times and the time delay values ​​between the flow monitoring signals of the two monitoring points; The function value of the cross-correlation function after each iteration of the delay value iteration process is calculated, and the delay value corresponding to the maximum value of all the function values ​​is used as the delay value between the flow monitoring signals of the two monitoring points.

[0006] Preferably, the determining of the signal fluctuation factor of the monitoring point in each short-time window includes: Acquire several short-time windows of flow monitoring signals; The similarity measurement result between the amplitude distribution of the flow monitoring signal of each monitoring point and the next monitoring point adjacent to each monitoring point in the short-time window of the same order is used as the signal fluctuation factor of each monitoring point in the short-time window of the same order.

[0007] Preferably, the method for acquiring the short-time window is: performing short-time Fourier transform on each flow monitoring signal respectively to obtain a plurality of short-time windows of each flow monitoring signal.

[0008] Preferably, the determining of the interference probability of the flow monitoring signal of the monitoring point at each frequency includes: For any two adjacent monitoring points, each short-time window of the flow monitoring signal of the previous monitoring point of the two monitoring points plus the window after the delay value is added is used as the delay window of each short-time window; Counting all the overlapping sampling moments in all short-time windows of the flow monitoring signal of the latter monitoring point of the two monitoring points and in each of the time delay windows, and combining the windows formed by the short-time windows where all the overlapping sampling moments are located as the combined window of each short-time window of the flow monitoring signal of the previous monitoring point; Determine the fluctuation recovery coefficient of each frequency in each short-time window based on the amplitude and phase of each short-time window of the flow monitoring signal of the previous monitoring point and the same frequency in the combined window; The ratio of the signal fluctuation factor of each short-time window of the flow monitoring signal of the previous monitoring point to the recovery coefficient of the fluctuation situation is recorded as the parameter ratio, and the average of the difference between the constant parameter and the normalized result of the parameter ratio is accumulated over all short-time windows as the interference probability of each frequency in each short-time window.

[0009] Preferably, determining the fluctuation recovery coefficient of each frequency in each short-time window includes: The ratio of the amplitudes at the same frequency in each short-time window and the combination window of each short-time window is taken as the amplitude variation; The ratio of the phases at the same frequency in each short-time window and the combination window of each short-time window is taken as the phase variation; The fluctuation recovery coefficient of each frequency in each short-time window of the flow monitoring signal of the previous monitoring point is composed of two parts: amplitude change and phase change; wherein the fluctuation recovery coefficient is positively correlated with the amplitude change and the phase change, respectively.

[0010] Preferably, obtaining the interference frequency according to the interference probability of the flow monitoring signal at all frequencies of the monitoring point specifically includes: The interference probability of each frequency in all short-time windows of the flow monitoring signal of each monitoring point is calculated respectively, and the frequency whose interference probability is greater than a preset threshold is taken as the interference frequency.

[0011] Preferably, obtaining the nonlinear error probability according to the distribution of interference frequencies at all adjacent monitoring points specifically includes: Obtain all interference frequencies of the flow monitoring signal of each monitoring point respectively; obtain the intersection of all interference frequencies of the flow monitoring signals of all monitoring points, and use the interference frequency in the intersection as the characteristic frequency; The mean of the distribution variance of the signal amplitude of each monitoring point and the next monitoring point of each monitoring point at all characteristic frequencies is taken as the nonlinear error caused by the interference of the flow monitoring signal of each monitoring point; Based on the nonlinear errors generated by the interference of the flow monitoring signals of all monitoring points, all the nonlinear errors are normalized, and the normalized processing result of each nonlinear error is used as a nonlinear error probability.

[0012] Preferably, the adjusting the proportional gain in the PID control data according to the nonlinear error probability to complete the automatic control of the regulating electric valve includes: The product of the sum of the nonlinear error probability and the constant parameter of each monitoring point and the proportional gain of the PID controller at the historical adjustment time is taken as the proportional gain of each monitoring point at the adjustment time; The average of the proportional gains of all monitoring points at the adjustment time is used as the actual proportional gain of the PID controller at the adjustment time. The PID controller is used to generate a control signal based on the actual proportional gain, and the control signal is used to complete the automatic control of the opening of the regulating electric valve.

[0013] In a second aspect, an embodiment of the present application further provides an automatic control system for an electrical system component, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of an automatic control method for an electrical system component as described above are implemented.

[0014] This application has at least the following beneficial effects: The present application analyzes the nonlinear error problem caused by turbulence, bubbles and other phenomena in the flow monitoring signal of the water supply process in the regulating electric valve connecting pipeline due to the change of water supply flow rate in the process of driving the steam turbine to generate electricity by boiler heating, and calculates the delay value of the flow monitoring signal by analyzing the flow monitoring signals of adjacent monitoring points; secondly, the synchronous fluctuation of the flow monitoring signals of adjacent monitoring points when the fluid flows is analyzed to obtain the signal fluctuation factor, which indicates the possibility that the flow monitoring signal fluctuates due to the change of fluid flow rate at the monitoring point; further, on the basis of processing the flow monitoring signal by short-time Fourier transform, the frequency domain change of the flow monitoring signal is analyzed, and the delay window and the combination window of each short-time window are obtained according to the delay value, and the amplitude difference and phase difference of the flow monitoring signals of adjacent monitoring points in the frequency domain are analyzed. Combined with the signal fluctuation factor, the interference probability of each frequency is obtained, and then all frequencies that may have interference are screened out to obtain the nonlinear error probability, and then the PID gain component is adjusted according to the expectation of the occurrence of nonlinear error, so that the PID controller can effectively compensate for the nonlinear error that may be caused by bubbles at the regulating electric valve, thereby improving the control accuracy of the regulating electric valve. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 A flowchart of a method for automatically controlling an electrical system component is provided for one embodiment of the present application. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0018] 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 application belongs.

[0019] The following is a detailed description of a specific scheme of an automatic control method and system for electrical system components provided by the present application in conjunction with the accompanying drawings.

[0020] See also Figure 1 , which shows a flowchart of a method for automatically controlling an electrical system component provided by an embodiment of the present application, the method comprising the following steps: S1, obtaining PID control data of the regulating electric valve and flow monitoring signals at each monitoring point of the regulating electric valve.

[0021] When the regulating electric valve is in operation in the electrical system, it can be used for different media. For example, the opening of the electric valve is controlled to adjust the water supply of the boiler, or the steam flow is adjusted to realize the control of the rotor rotation to generate electricity, etc. In one embodiment of the present application, the subsequent automatic control process of the regulating electric valve is described by controlling the water supply by the opening of the regulating electric valve when the boiler burns to heat the water supply. Sensors are arranged around the regulating electric valve to obtain monitoring signals. The arrangement positions include but are not limited to the pipes connecting the electric valve and the electric valve itself. The purpose is to obtain monitoring signals at different monitoring points. The specific number of monitoring points is set by the implementer according to the actual scenario, and this application does not impose any restrictions.

[0022] Specifically, an embodiment of the present application uses an electromagnetic flowmeter to obtain the flow monitoring signal of the regulating electric valve at M monitoring points with the same sampling frequency. In this embodiment, M is set to 5 and the sampling frequency is set to 500HZ. Secondly, for each collected flow monitoring signal, a data filtering algorithm is used, including but not limited to mean filtering, Gaussian filtering, and median filtering. Data filtering is a well-known technology in the field of data processing, and the specific process will not be repeated. Preferably, an embodiment of the present application uses mean filtering to process the flow monitoring signal at each monitoring point respectively.

[0023] Furthermore, the control parameters of the regulating electric valve when automatically controlling each historical adjustment moment in the historical time period are obtained from the log data of the electrical system, wherein the control parameters include the preset component gain of the PID control module in the PID controller, including the proportional gain , integral gain , differential gain .

[0024] S2, according to the correlation between the flow monitoring signals at the two monitoring points, determine the time delay value between the flow monitoring signals of the two monitoring points; according to the amplitude distribution of the flow monitoring signal of the monitoring point in the short-time window and the amplitude distribution of the flow monitoring signal of the next monitoring point after the delay in the short-time window, determine the signal fluctuation factor of the monitoring point in each short-time window.

[0025] The greater the flow rate and pipe diameter when supplying water in the pipe connected to the regulating electric valve, the more likely it is to generate bubbles and more complex flow conditions; too fast a flow rate can easily cause local turbulence and oscillation at the regulating electric valve, thereby causing bubbles to form, changing the flow characteristics and making the flow measurement results more complicated; this is manifested in the electromagnetic flowmeter collecting flow monitoring signals as small nonlinear fluctuations in the trend of the flow signal.

[0026] Specifically, when collecting flow monitoring signals at different monitoring points, local turbulence and oscillation caused by excessive flow velocity will cause the flow monitoring signals at some collection moments to have different time delays at different monitoring points; in order to obtain the time delay between flow monitoring signals at adjacent positions during the fluid flow process, the time delay value between the two positions is obtained based on the correlation between the flow monitoring signals at the two monitoring points.

[0027] Specifically, the cross-correlation function between the flow monitoring signals at two monitoring points is first calculated: ; Where N represents the number of sampling moments of the flow monitoring signal, Represents the value of the flow monitoring signal at the first monitoring point at the tth moment, Represents the flow monitoring signal of the second monitoring point The value of the moment, is the time delay between two monitoring points.

[0028] It should be noted that when When iterating, set the step size to , initial value , the iterative process is T, , 2T…, The maximum iteration value is set to 1s, and the value of T is taken as the empirical value of 0.1s. The function value of the correlation function after each iteration is calculated in sequence, and the function value corresponding to the maximum value of the cross-correlation function F is calculated. As the delay value between two monitoring points.

[0029] The cross-correlation function is the largest, which means that the previous flow monitoring signal is The latter flow monitoring signal after the time delay has the maximum correlation, which is consistent with the flow characteristics of the fluid.

[0030] Furthermore, bubbles are formed by air mixed in during the water supply process. When bubbles exist, the internal resistance of the fluid is large, and the speed is slower than that of the fluid without bubbles. However, the bubbles will rise and gather in the fluid in the pipe. Therefore, the bubbles inside the water flow should gradually decrease with the flow, and the fluctuations in the signal trend item caused by the bubbles will gradually disappear; and after the bubbles are reduced, the flow rate of the fluid will tend to be normal and stable.

[0031] Specifically, in order to analyze the flow monitoring signal, firstly, each flow monitoring signal is subjected to short-time Fourier transform, and the short-time window length is set to L, and the value range of L is 0.1s to 1s. In this embodiment, the size of L is set to the empirical value of 0.1s, and several short-time windows of each flow monitoring signal are obtained. Among them, short-time Fourier transform is a well-known technology in the field of data processing, and the specific process will not be repeated.

[0032] Furthermore, if the flow rate of water in the pipeline connected to the regulating electric valve is normal, the amplitude distribution of the flow monitoring signal at the first monitoring point in the short-time window should be relatively close to the amplitude distribution of the flow monitoring signal at the second monitoring point after a time delay in the short-time window.

[0033] Therefore, for short-time windows of any order, taking the pth short-time window as an example, the similarity measurement result between the amplitude distribution of the flow monitoring signal of the first monitoring point in the pth short-time window and the amplitude distribution of the flow monitoring signal of the second monitoring point in the pth short-time window is used as the signal fluctuation factor of the flow monitoring signal of the first monitoring point in the pth short-time window. The signal fluctuation factor reflects whether the flow monitoring signal of the first monitoring point in the short-time window of the same order has the characteristic of a smooth delay to the flow monitoring signal of the second monitoring point. The larger the signal fluctuation factor, the smoother the water supply between the first monitoring point and the second monitoring point.

[0034] It should be noted that the similarity metric is used to measure the similarity between the amplitude distributions in two short-time windows. Therefore, when the purpose of similarity measurement can be achieved, the similarity measurement method includes but is not limited to value variance, Pearson correlation coefficient, and cosine similarity. This application does not impose any special restrictions on the specific method of similarity measurement. As an example, this embodiment calculates the Pearson correlation coefficient between the amplitude distributions in two short-time windows as the similarity measurement result.

[0035] S3, determines the interference probability of the flow monitoring signal of the monitoring point at each frequency according to the amplitude difference, phase difference and signal fluctuation factor of the flow monitoring signal contained in all short-time windows of adjacent monitoring points in the frequency domain; obtains the interference frequency according to the interference probability of the flow monitoring signal of the monitoring point at all frequencies.

[0036] Specifically, when the water flows through the two sensors during the water supply process, the signal components of most frequencies should have the same phase, while the signal amplitude of a few frequencies will increase and the phase will decrease. The signal frequency with this characteristic may be the frequency component corresponding to the bubbles in the fluid.

[0037] Therefore, in order to analyze the amplitude changes of the frequency signal and extract the bubble frequency, the present application first obtains the amplitude spectrum and phase spectrum of the flow monitoring signal contained in the flow monitoring signal of the first monitoring point in each short-time window; the amplitude spectrum represents the instantaneous flow of different frequency signals, and the phase represents the time offset of different frequency signals.

[0038] Specifically, taking the first monitoring point as an example, based on the correlation between the delayed flow monitoring signal of the second monitoring point and all amplitude spectra and phase spectra in each short-time window in the flow monitoring signal of the first monitoring point, the frequency component corresponding to the signal fluctuation generated by the influence is extracted. First, for each monitoring point except the last monitoring point, the window after each short-time window in the flow monitoring signal of the monitoring point is obtained by adding the delay value, which is recorded as the delay window of each short-time window. The delay window of the flow monitoring signal of the first monitoring point corresponds to the window composed of all overlapping short-time windows in the flow monitoring signal of the second monitoring point, which is recorded as the combined window.

[0039] Specifically, taking the first monitoring point and the second monitoring point as an example, the flow monitoring signal of the first monitoring point is calculated at each moment in each short-time window. The corresponding sampling time in the flow monitoring signal at the second monitoring point, that is, the vth sampling time corresponds to the Sampling time; all sampling times in the first short-term window a1 of the flow monitoring signal at the first monitoring point are added with the delay value The time window determined later is the time delay window ab1 of a1. ab1 involves two short-time windows b1 and b2 in the flow monitoring signal at the second monitoring point. The combination of the two short-time windows is called the combined window of a1.

[0040] Furthermore, the two amplitude spectra and two phase spectra within the short-time window and its combined window are aligned at the same frequency; if a certain frequency within the short-time window has no value at the same frequency position in the amplitude spectrum and phase spectrum within the combined window, it is replaced by a constant 1. For each monitoring point except the last monitoring point, the fluctuation recovery coefficient of the flow monitoring signal contained in each short-time window of the monitoring point at each frequency is obtained based on the difference in amplitude spectrum and phase spectrum of the flow monitoring signal contained in each short-time window in the flow monitoring signal of the monitoring point and its combined window in the flow monitoring signal of the next monitoring point, which is used to reflect the situation in which the data fluctuation of the flow monitoring signal at the previous monitoring point in the water supply process is restored to normal in the flow monitoring signal at the next monitoring point. The calculation formula for the fluctuation recovery coefficient of the flow monitoring signal at the i-th frequency in the p-th short-time window at the first monitoring point is: in, Represents the recovery coefficient of the fluctuation of the flow monitoring signal of the first monitoring point at the i-th frequency in the p-th short-time window; , Respectively represent the amplitude and phase of the i-th frequency in the amplitude spectrum and phase spectrum of the flow monitoring signal of the first monitoring point in the p-th short-time window, , They respectively represent the amplitude and phase of the i-th frequency in the amplitude spectrum and phase spectrum of the flow monitoring signal of the p-th short-time window at the second monitoring point in the combined window.

[0041] when , When both are larger, it means that the i-th frequency has experienced an amplitude rebound and phase reduction between the flow monitoring signal at the previous monitoring point and the flow monitoring signal at the next monitoring point; there are bubbles when the fluid passes through the previous monitoring point, and the fluid containing bubbles has a greater resistance, and the flow rate is slower than the normal fluid, and there is a delay at the previous monitoring point; and when the fluid moves from the previous monitoring point to the next monitoring point, the bubbles float up and gradually decrease, the flow rate returns to normal, and the delay disappears.

[0042] Secondly, according to the recovery coefficient and signal fluctuation factor of the flow monitoring signal at the monitoring point in all short-time windows, the interference probability of the flow monitoring signal at each frequency at the monitoring point is obtained, which is used to reflect the probability that the flow monitoring signal collected at each monitoring point in the water supply process is affected by turbulence, bubbles and other phenomena caused by flow velocity changes. The calculation formula for the interference probability of the flow monitoring signal at the first monitoring point at the i-th frequency is: in, represents the interference probability of the flow monitoring signal of the first monitoring point at the i-th frequency, n is the number of short-time windows corresponding to the flow monitoring signal of the first monitoring point, is the signal fluctuation factor of the flow monitoring signal at the first monitoring point in the pth short-time window, Represents the recovery coefficient of the fluctuation of the flow monitoring signal of the first monitoring point at the i-th frequency in the p-th short-time window.

[0043] It should be noted that the more serious the signal fluctuation of the flow monitoring signal at the first monitoring point in the pth short-time window, the greater the possibility that the signal fluctuation of the flow monitoring signal at the second monitoring point will return to normal at the i-th frequency in the combination window corresponding to the pth short-time window, and the greater the parameter ratio The smaller the value of is, the higher the probability that the component of the flow monitoring signal at the ith frequency at the first monitoring point is interfered with.

[0044] Furthermore, the interference probability of the flow monitoring signal of the first monitoring point at each frequency is calculated respectively and compared with a preset threshold. In this embodiment, the preset threshold is set to 0.6, and the frequency with an interference probability greater than the threshold is taken as the interference frequency of the flow monitoring signal caused by turbulence, bubbles and other phenomena caused by changes in flow velocity near the connecting pipe of the regulating electric valve during the water supply process, resulting in data fluctuations.

[0045] S4, obtaining the nonlinear error probability according to the distribution of the interference frequencies at all adjacent monitoring points; adjusting the proportional gain in the PID control data according to the nonlinear error probability, and completing the automatic control of the regulating electric valve.

[0046] Nonlinear error means that during the water supply process, when water flows in the connecting pipe before reaching the regulating electric valve, it may cause error fluctuations in the fluid flow rate due to turbulence, bubbles, etc. This nonlinear error may cause the sensor at the regulating electric valve to obtain incorrect flow measurement results, thereby causing valve control deviation. The three gain components of the PID controller are proportional gain, To compensate for the real-time error, in order to eliminate the deviation, the present application calculates the nonlinear error according to the bubble interference frequency and adjusts the proportional gain of the three gain components of the PID controller.

[0047] Specifically, firstly, according to the above process, all interference frequencies of the flow monitoring signal of each monitoring point are obtained respectively; secondly, the intersection of all interference frequencies of the flow monitoring signals of all monitoring points is obtained, and the interference frequency in the intersection is used as the characteristic frequency.

[0048] Furthermore, the distribution variances of the signal amplitudes of the flow monitoring signals at the first monitoring point and the second monitoring point at all the characteristic frequencies are calculated respectively, and the mean of the two distribution variances is taken as the nonlinear error caused by the interference to the flow monitoring signal at the first monitoring point during the water supply process.

[0049] When the regulating electric valve is automatically controlled, the flow rate change in the water supply process is real-time, so it is necessary to supplement it based on the nonlinear error and the proportional gain of the PID controller to eliminate the impact of the error.

[0050] Specifically, based on the nonlinear error caused by the interference of the flow monitoring signals of all monitoring points, the nonlinear error caused by the interference of the flow monitoring signals of each monitoring point is normalized, and the normalized result of each nonlinear error is used as a nonlinear error probability, and the proportional gain at the adjustment time is determined in combination with the proportional gain. The specific calculation formula of the proportional gain of the first monitoring point at the adjustment time is: In the formula, is the proportional gain of the first monitoring point at the adjustment time, is the proportional gain of the PID controller controlling the regulating electric valve at the historical moment, is the nonlinear error probability of the first monitoring point.

[0051] Since multiple sensors are arranged around the regulating electric valve, in order to avoid the influence of the sensor accuracy on the monitoring result of a single monitoring point, the average of the proportional gain of all monitoring points at the same adjustment time is calculated as the actual proportional gain of the PID controller at the adjustment time. Among them, the adjustment time can be based on the preset fixed time interval of the last sampling time, and the time interval can be 5 minutes or 10 minutes, which is set by the implementer according to the specific situation. For example, the proportional gain of the PID-controlled regulating electric valve in the water supply process is adjusted every 10 minutes, so that the PID controller can effectively compensate for the nonlinear error generated when the regulating electric valve is automatically controlled according to the flow monitoring signal.

[0052] Specifically, the integral gain , differential gain , the actual proportional gain at the time of adjustment is used as the input of the PID controller, and the PID outputs a control signal, which is received by the positioner and converted into the specific opening position of the valve. For example, if the control signal requires the valve to be opened by 50%, the positioner will ensure that the valve opening is exactly 50%. Receive the actuator valve position signal fed back by the actuator valve position sensor, convert the signal into a digital signal through the A / D converter and calibrate it; according to the calibrated actuator valve position signal, decode the corresponding commutation control logic of the brushless DC motor winding. Subsequently, a pulse width modulation (PWM) sequence is generated based on the calibrated actuator valve position signal and the target opening signal provided by the actuator valve control system. According to the PWM sequence and the winding commutation control logic, the winding current of the brushless DC motor is controlled, and the opening of the actuator valve is adjusted through the brushless DC motor and the gear system.

[0053] Based on the same inventive concept as the above method, an embodiment of the present application also provides an automatic control system for electrical system components, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps in the above-mentioned automatic control method for electrical system components are implemented.

[0054] Through the above description of the implementation method in combination with the accompanying drawings, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0055] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. An automatic control method for an electrical system component, characterized in that: The method comprises the following steps: Obtaining PID control data of the regulating electric valve and flow monitoring signals at each monitoring point of the regulating electric valve; According to the correlation between the flow monitoring signals at the two monitoring points, the time delay value between the flow monitoring signals at the two monitoring points is determined; according to the amplitude distribution of the flow monitoring signal at the monitoring point in the short-time window and the amplitude distribution of the flow monitoring signal at the next monitoring point after the time delay in the short-time window, the signal fluctuation factor of the monitoring point in each short-time window is determined; According to the amplitude difference, phase difference and signal fluctuation factor of the flow monitoring signals in the frequency domain contained in all short-time windows of adjacent monitoring points, the interference probability of the flow monitoring signals at each frequency of the monitoring point is determined; the interference frequency is obtained according to the interference probability of the flow monitoring signals at all frequencies of the monitoring point; The nonlinear error probability is obtained according to the distribution of interference frequencies at all adjacent monitoring points; the proportional gain in the PID control data is adjusted according to the nonlinear error probability to complete the automatic control of the regulating electric valve.

2. An automatic control method for an electrical system component as claimed in claim 1, characterized in that: Determining the time delay value between the flow monitoring signals of two monitoring points includes: Preset the initial value of the time delay between the flow monitoring signals of two monitoring points and the iteration step size; The cross-correlation function is constructed by using the signal values ​​of the flow monitoring signals of the two monitoring points at different sampling times and the time delay values ​​between the flow monitoring signals of the two monitoring points; The function value of the cross-correlation function after each iteration of the delay value iteration process is calculated, and the delay value corresponding to the maximum value of all the function values ​​is used as the delay value between the flow monitoring signals of the two monitoring points.

3. An automatic control method for an electrical system component as claimed in claim 1, characterized in that: The determining of the signal fluctuation factor of the monitoring point in each short-time window includes: Acquire several short-time windows of flow monitoring signals; The similarity measurement result between the amplitude distribution of the flow monitoring signal of each monitoring point and the next monitoring point adjacent to each monitoring point in the short-time window of the same order is used as the signal fluctuation factor of each monitoring point in the short-time window of the same order.

4. An automatic control method for an electrical system component as claimed in claim 3, characterized in that: The method for acquiring the short-time window is: performing short-time Fourier transform on each flow monitoring signal respectively to obtain a plurality of short-time windows of each flow monitoring signal.

5. An automatic control method for an electrical system component as claimed in claim 1, characterized in that: The determining of the interference probability of the flow monitoring signal of the monitoring point at each frequency includes: For any two adjacent monitoring points, each short-time window of the flow monitoring signal of the previous monitoring point of the two monitoring points plus the window after the delay value is added is used as the delay window of each short-time window; Counting all the overlapping sampling moments in all short-time windows of the flow monitoring signal of the latter monitoring point of the two monitoring points and in each of the time delay windows, and combining the windows formed by the short-time windows where all the overlapping sampling moments are located as the combined window of each short-time window of the flow monitoring signal of the previous monitoring point; Determine the fluctuation recovery coefficient of each frequency in each short-time window based on the amplitude and phase of each short-time window of the flow monitoring signal of the previous monitoring point and the same frequency in the combined window; The ratio of the signal fluctuation factor of each short-time window of the flow monitoring signal of the previous monitoring point to the recovery coefficient of the fluctuation situation is recorded as the parameter ratio, and the average of the difference between the constant parameter and the normalized result of the parameter ratio is accumulated over all short-time windows as the interference probability of each frequency in each short-time window.

6. An automatic control method for an electrical system component as claimed in claim 5, characterized in that: Determining the recovery coefficient of the fluctuation of each frequency in each short-time window includes: The ratio of the amplitudes at the same frequency in each short-time window and the combination window of each short-time window is taken as the amplitude variation; The ratio of the phases at the same frequency in each short-time window and the combination window of each short-time window is taken as the phase variation; The fluctuation recovery coefficient of each frequency in each short-time window of the flow monitoring signal of the previous monitoring point is composed of two parts: amplitude change and phase change; wherein the fluctuation recovery coefficient is positively correlated with the amplitude change and phase change, respectively.

7. An automatic control method for an electrical system component as claimed in claim 1, characterized in that: The obtaining of the interference frequency according to the interference probability of the flow monitoring signal at all frequencies of the monitoring point specifically includes: The interference probability of each frequency in all short-time windows of the flow monitoring signal of each monitoring point is calculated respectively, and the frequency whose interference probability is greater than a preset threshold is taken as the interference frequency.

8. An automatic control method for an electrical system component as claimed in claim 1, characterized in that: The nonlinear error probability is obtained according to the distribution of interference frequencies at all adjacent monitoring points, specifically including: Obtain all interference frequencies of the flow monitoring signal of each monitoring point respectively; obtain the intersection of all interference frequencies of the flow monitoring signals of all monitoring points, and use the interference frequency in the intersection as the characteristic frequency; The mean of the distribution variance of the signal amplitude of each monitoring point and the next monitoring point of each monitoring point at all characteristic frequencies is taken as the nonlinear error caused by the interference of the flow monitoring signal of each monitoring point; Based on the nonlinear errors generated by the interference of the flow monitoring signals of all monitoring points, all the nonlinear errors are normalized, and the normalized processing result of each nonlinear error is used as a nonlinear error probability.

9. An automatic control method for an electrical system component as claimed in claim 1, characterized in that: The method of adjusting the proportional gain in the PID control data according to the nonlinear error probability to complete the automatic control of the regulating electric valve includes: The product of the sum of the nonlinear error probability and the constant parameter of each monitoring point and the proportional gain of the PID controller at the historical adjustment time is taken as the proportional gain of each monitoring point at the adjustment time; The average of the proportional gains of all monitoring points at the adjustment time is used as the actual proportional gain of the PID controller at the adjustment time. The PID controller is used to generate a control signal based on the actual proportional gain, and the control signal is used to complete the automatic control of the opening of the regulating electric valve.

10. An automatic control system for an electrical system component, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the automatic control method for an electrical system component as claimed in any one of claims 1 to 9 are implemented.

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