Overflow type fluid pulsation active control method, device and system based on mean value self-adaption

Abstract

The invention provides an overflow type fluid pulsation active control method, device and system based on mean value self-adaption. The method comprises the steps that the construction module extracts the pulsation frequency in an original pressure signal, sinusoidal signals which are mutually orthogonal under the frequency are generated and serve as reference signals to be input into the wave trap, the processing module obtains nonlinear characteristic suppression parameters and generates control signals, and the signals are output to the control valve to complete the active control process. And the mean value estimation module updates the mean value component of the reference control error by using the error signal at the previous moment, and the target control error of the fluid pulsation is used for weight coefficient iteration of the wave trap. The device comprises a control valve, a pressure sensor and an active controller. One end of the control valve is connected with a pipeline, the other end of the control valve is connected with an oil tank, and the control valve overflows pipeline flow according to control signals to cause pipeline flow change to realize pulsation control. According to the method and the device, pulsation suppression can be carried out on the variable pressure fluid system, the pressure change of the system is identified and tracked, and the fluid pulsation suppression effect is improved.

Description

Technical Field

[0001] The present invention relates to the field of hydraulic control technology, and in particular to an overflow type fluid pulsation active control method, device and system based on mean value adaptation. Background Art

[0002] In the fluid pulsation active control scheme based on the bypass overflow principle, a bypass branch can be set on the main line between the hydraulic pump and the actuator, and a control valve can be installed on the bypass branch. The control valve is then controlled to generate a secondary pulsation wave, so that the secondary pulsation wave and the original pressure wave in the main line can be offset against each other, thereby reducing the fluid pulsation in the main line and achieving the purpose of fluid pulsation suppression.

[0003] In the related technology, the pulsation frequency of the fluid can be obtained, a reference signal can be constructed according to the pulsation frequency of the fluid, and then the control signal of the control valve can be determined according to the reference signal and the identification excitation signal, and then the control signal of the control valve can be used to control the control valve to generate a secondary pulsation wave. However, the pulsation suppression effect and control stability of the existing control method still have a lot of room for improvement. Summary of the invention

[0004] According to one aspect of the present disclosure, a method for active control of fluid pulsation based on mean value adaptation is provided, comprising:

[0005] Acquire a first reference signal and a second reference signal based on a target frequency of fluid pulsation, wherein the first reference signal and the second reference signal are orthogonal;

[0006] determining a fluid pulsation active control signal based on the first reference signal and the second reference signal;

[0007] Obtaining a target control error of the fluid pulsation based on the fluid pulsation active control signal and a mean component parameter of a reference control error;

[0008] Inputting the first reference signal and the second reference signal into the secondary channel estimation model to obtain a reference signal filtered by the secondary channel estimation model;

[0009] Based on the target control error of the fluid pulsation and the reference signal filtered by the secondary channel estimation model, the first weight coefficient of the notch filter and the second weight coefficient of the notch filter are updated.

[0010] According to another aspect of the present disclosure, there is provided a fluid pulsation active control device, comprising:

[0011] A construction module is used to obtain a first reference signal and a second reference signal based on a target frequency of fluid pulsation, wherein the first reference signal and the second reference signal are orthogonal;

[0012] a notch filter, for determining a fluid pulsation active control signal based on the first reference signal and the second reference signal;

[0013] A processing module is used to input the first reference signal and the second reference signal into the secondary channel estimation model to obtain the reference signal filtered by the secondary channel estimation model, and update the first weight coefficient of the notch filter and the second weight coefficient of the notch filter based on the target control error of the fluid pulsation and the reference signal filtered by the secondary channel estimation model.

[0014] According to another aspect of the present disclosure, there is provided a fluid pulsation active control system, including: a control valve, a pressure sensor and an active controller, wherein a first end of the control valve is connected to a pipeline, a second end of the control valve is connected to a fuel tank, the pressure sensor and the control valve are both communicatively connected to the active controller, and the active controller is used to execute the method described in this exemplary embodiment.

[0015] According to another aspect of the present disclosure, there is provided an electronic device, comprising:

[0016] processor; and,

[0017] Memory for storing programs,

[0018] The program includes instructions, which, when executed by the processor, cause the processor to perform the method according to the exemplary embodiment of the present disclosure.

[0019] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause the computer to execute the method according to the exemplary embodiments of the present disclosure.

[0020] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the method described in the exemplary embodiments of the present disclosure is implemented.

[0021] One or more technical solutions provided in the exemplary embodiments of the present disclosure can determine the fluid pulsation active control signal based on the first reference signal and the second reference signal, and then introduce the mean component parameter introduced by the reference control error into the reference control correction of the fluid pulsation, thereby obtaining the target control error of the fluid pulsation. In this case, the target control error of the fluid pulsation can exclude the interference of the mean component, so based on the target control error of the fluid pulsation and the reference signal filtered by the secondary channel estimation model, the first weight coefficient of the notch filter and the second weight coefficient of the notch filter are updated, which can ensure the stability of the fluid pulsation active control signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Further details, features and advantages of the present disclosure are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0023] Figure 1 An example schematic diagram showing an active fluid pulsation control system based on a bypass overflow principle;

[0024] Figure 2 A schematic flow chart of a method for actively controlling fluid pulsation according to an exemplary embodiment of the present disclosure is shown;

[0025] Figure 3 A schematic diagram showing an active fluid pulsation control system according to an exemplary embodiment of the present disclosure is shown;

[0026] Figure 4 A time-pressure relationship diagram of an exemplary embodiment of the present disclosure before and after active oil pulsation control is shown;

[0027] Figure 5 A frequency-amplitude relationship diagram before active oil pulsation control is performed in an exemplary embodiment of the present disclosure is shown;

[0028] Figure 6 A frequency-amplitude relationship diagram after active oil pulsation control is performed in an exemplary embodiment of the present disclosure is shown;

[0029] Figure 7 An example schematic diagram showing another fluid pulsation active control system based on the bypass overflow principle;

[0030] Figure 8 A schematic block diagram of functional modules of a fluid pulsation active control device according to an exemplary embodiment of the present disclosure is shown;

[0031] Fig. 9 A schematic block diagram of a chip according to an exemplary embodiment of the present disclosure is shown;

[0032] Fig.10 A structural block diagram of an exemplary electronic device that can be used to implement the embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0033] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0034] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0035] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0036] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0037] Figure 1 An example schematic diagram of a fluid pulsation active control system based on a bypass overflow principle is shown. Figure 1 As shown, the fluid pulsation active control system 100 may include an oil tank 101, a plunger pump 102, a motor 103, a relief valve 104, a control valve 105, a throttle valve 106, a pressure sensor 107, and a controller 108. The motor 103 is connected to the plunger pump 102, the outlet of the oil tank 101 is connected to the inlet of the plunger pump 102, the outlet of the plunger pump 102 is connected to the inlet of the relief valve 104 and the inlet of the control valve 105 respectively, and the outlet of the control valve 105 is connected to the inlet of the oil tank 101 through the throttle valve 106. Here, the outlet of the plunger pump 102 can be connected to the overflow pipeline and the hydraulic pipeline respectively, the overflow valve 104 is arranged on the overflow pipeline, and the control valve 105 and the throttle valve 106 are arranged on the hydraulic pipeline. The pressure sensor 107 can be arranged in the hydraulic pipeline between the control valve 105 and the throttle valve 106. The outlet of the control valve 105 is also connected to the bypass pipeline, and the bypass pipeline is connected to the inlet of the oil tank 101. The controller 108 is electrically connected to the pressure sensor 107 and the control valve 105 respectively.

[0038] When implementing it, Figure 1As shown, driven by the motor 103, the plunger pump 102 rotates, so that the plunger pump 102 draws low-pressure oil from the oil tank 101 and sends the low-pressure oil into the hydraulic pipeline, and the low-pressure oil returns to the oil tank 101 through the throttle valve 106; the overflow valve 104 can control the pressure in the hydraulic pipeline not to exceed the set pressure, thereby playing a safety protection role; the controller 108 can obtain the pressure signal of the position through the pressure sensor 107, and use it as the control error of the fluid pulsation, and update the parameters required in the active control process of the fluid pulsation, so that when the fluid pulsation active control signal controls the control valve 105, the control valve 105 can be used as an active control actuator to control the oil flow of the bypass pipeline.

[0039] The above-mentioned control valve can be a piezoelectric ceramic control valve or other control valves. Taking the piezoelectric ceramic control valve as an example, the pulsation frequency of the oil can be obtained, and a reference signal can be constructed according to the pulsation frequency of the oil. Then, based on the reference signal and the identification excitation signal, the control signal of the piezoelectric ceramic control valve can be determined, and then the control signal of the piezoelectric ceramic control valve can be used to control the piezoelectric ceramic control valve to generate a secondary pulsation wave.

[0040] The inventors discovered that the pressure signal of the fluid pulsation collected by the pressure sensor is actually the reference control error of the fluid pulsation, which contains a mean component. When the weight coefficients of the notch filter, namely the first weight coefficient and the second weight coefficient, are updated based on the reference control error of the fluid pulsation, the mean component will cause the jitter of the weight coefficient of the notch filter to intensify, thereby affecting the fluid pulsation suppression effect. In response to the above problems, an exemplary embodiment of the present disclosure provides a method for active control of fluid pulsation, which can be executed by a controller or a chip of the controller. The method reduces the possibility of blocking the active control signal of the fluid pulsation by introducing the nonlinear characteristic suppression parameter of the secondary channel, thereby improving the pulsation suppression effect and the pulsation control stability.

[0041] Figure 2 FIG. 2 is a flow chart showing a method for actively controlling fluid pulsation according to an exemplary embodiment of the present disclosure. Figure 2 As shown, the fluid pulsation active control method provided by the exemplary embodiment of the present disclosure may include:

[0042] Step 201: Acquire a first reference signal and a second reference signal based on a target frequency of fluid pulsation, wherein the first reference signal and the second reference signal are orthogonal.

[0043] In practical applications, the exemplary embodiment of the present disclosure can obtain pressure signals of multiple sampling points of fluid pulsation in a non-suppressed state within a preset time period, and then determine the amplitude-frequency spectrum of the fluid pulsation based on the pressure signals of multiple sampling points of the fluid pulsation in the non-suppressed state, and determine the target frequency of the fluid pulsation based on the amplitude-frequency spectrum of the fluid pulsation, which is the fluid pulsation frequency corresponding to the maximum fluid pulsation amplitude in the amplitude-frequency spectrum of the fluid pulsation.

[0044] Exemplarily, when the fluid pulsation is in a non-suppressed state, the control valve does not control the fluid pulsation. In this case, the pressure sensor is used to obtain pressure signals of multiple sampling points (such as 4096) in a preset period of time, and then the multiple historical signals are subjected to Fast Fourier Transform (FFT) to obtain the amplitude-spectrum diagram of the fluid pulsation. The amplitude-spectrum diagram of the fluid pulsation can actually represent the corresponding relationship between the fluid pulsation amplitude and the fluid pulsation frequency. Therefore, the amplitude-spectrum diagram of the fluid pulsation can be obtained by analyzing the amplitude-spectrum diagram of the fluid pulsation, and the fluid pulsation frequency corresponding to the maximum fluid pulsation amplitude can be obtained.

[0045] When the target frequency of fluid pulsation is the fluid pulsation frequency corresponding to the maximum fluid pulsation amplitude, the fluid pulsation active control signal determined based on the target frequency of fluid pulsation can actively control the fluid pulsation better, thereby improving the fluid pulsation control effect.

[0046] When the target frequency of fluid pulsation is f, the first reference signal x1(n) of the nth fluid pulsation sampling point is cos(2πfnΔt), and the second reference signal x2(n) of the nth fluid pulsation sampling point is sin(2πfnΔt), where n represents the fluid pulsation.

[0047] The dynamic sampling number, Δt represents the sampling period.

[0048] Step 202: Determine the fluid pulsation active control signal based on the first reference signal and the second reference signal. Here, the first weighted signal can be determined based on the first weight coefficient of the notch filter and the first reference signal, the second weighted signal can be determined based on the second weight coefficient of the notch filter and the second reference signal, and then the fluid pulsation active control signal can be determined based on the first weighted signal and the second weighted signal. This is essentially a process of weighted summing the first reference signal and the second reference signal using the first weight coefficient and the second weight coefficient.

[0049] The inventors found that in the active suppression of fluid pulsation based on the overflow principle, the secondary channel actually contains nonlinear characteristics. This means that when the fluid pulsation active control signal is less than 0, the fluid pulsation active control signal output signal will be blocked. Therefore, the nonlinear characteristics of the secondary channel affect the pulsation suppression effect on the one hand, and the pulsation control stability on the other hand. Based on this, the embodiment of the present application determines the fluid pulsation active control signal based on the first reference signal and the second reference signal, including:

[0050] Based on the first weight coefficient of the notch filter and the first reference signal, a first weighted signal is determined, based on the second weight coefficient of the notch filter and the second reference signal, a second weighted signal is determined, and based on the first weighted signal, the second weighted signal and the nonlinear characteristic suppression parameter of the secondary channel, the fluid pulsation active control signal is determined. In this case, the nonlinear characteristic suppression parameter of the secondary channel can weaken the influence of the nonlinear characteristic of the secondary channel on the fluid pulsation active control signal. Therefore, the exemplary embodiment of the present disclosure utilizes the fluid pulsation active control signal to not only suppress the fluid pulsation relatively well, but also ensure the stability of the fluid pulsation suppression.

[0051] When the control valve is controlled by the fluid pulsation active control signal, the opening parameter of the control valve can be controlled to achieve the purpose of adjusting the flow of the control valve. The nonlinear characteristic suppression parameter of the secondary channel can be determined by the first weight coefficient and the second weight coefficient of the notch filter. For example, the nonlinear characteristic suppression parameter w(n) of the secondary channel satisfies: w1(n) represents the first weight coefficient of the trap at the nth fluid pulsation sampling point, w2(n) represents the second weight coefficient of the trap at the nth fluid pulsation sampling point, and n represents the fluid pulsation sampling sequence number. For example, the fluid pulsation active control signal y(n) at the nth fluid pulsation sampling point can be expressed as formula 1:

[0052]

[0053] According to formula 2, formula 1 is transformed as follows:

[0054]

[0055] In formula 2, The phase of the sinusoidal signal determined by the first two terms of the control signal representing fluid pulsation, and w represents the angular frequency of fluid pulsation. Therefore, formula 1 satisfies formula 3:

[0056]

[0057] It can be seen that when the fluid pulsation active control signal y(n) ≥ 0 in the exemplary embodiment of the present disclosure, using the fluid pulsation active control signal to control the control valve can not only suppress the fluid pulsation relatively well, but also ensure the stability of the fluid pulsation suppression.

[0058] Step 203: Obtain a target control error of the fluid pulsation based on the fluid pulsation active control signal and the mean component parameter of the reference control error.

[0059] In practical applications, the fluid pulsation active control signal can be input into the secondary channel to obtain the reference control error of the fluid pulsation. However, since the reference control error contains a mean component, the mean component mainly comes from the mean component of the original pressure signal in the reference control error. The existence of this mean component will lead to the aggravation of the jitter of the notch filter weight coefficient. Therefore, the reference control error of the fluid pulsation can be corrected by using the mean component parameter of the reference control error to obtain the target control error of the fluid pulsation, thereby ensuring that the target control error of the fluid pulsation obtained can exclude the interference of the mean component and ensure the stability of the active control signal of the fluid pulsation.

[0060] Exemplarily, the mean component of the reference control error may be determined based on the mean component parameter of the reference control error, and then the mean component of the reference control error may be subtracted from the reference control error of the fluid pulsation to obtain the target control error of the fluid pulsation.

[0061] For example: the fluid pulsation active control signal y(n) of the nth fluid pulsation sampling point is input into the secondary channel to obtain the response signal y'(n) of the secondary channel of the nth fluid pulsation sampling point. Based on the response signal y'(n) of the secondary channel of the nth fluid pulsation sampling point and the original pressure signal d(n) of the fluid pulsation at the nth fluid pulsation sampling point, the reference control error e(n) of the fluid pulsation at the nth fluid pulsation sampling point is determined, where e(n) = d(n) - y'(n). Finally, based on the reference control error e(n) of the fluid pulsation at the nth fluid pulsation sampling point and the mean component parameter of the reference control error of the nth fluid pulsation sampling point, Determine the target control error g(n) of the fluid pulsation at the nth fluid pulsation sampling point, where

[0062]

[0063] Taking into account that when the original pressure signal of the fluid pulsation changes, the mean component parameters of the reference control error will also change. Therefore, the mean component parameters of the reference control error in the embodiment of the present application can be iteratively updated. For example, the mean component parameters of the reference control error can be updated based on the active control signal of the fluid pulsation at the previous sampling point and the mean component parameters of the reference control error at the previous sampling point, so that the mean component parameters of the reference control error can be adaptively adjusted.

[0064] Exemplarily, the exemplary embodiments of the present disclosure may also introduce a mean estimator to update the mean component parameters of the reference control error. The mean estimator may be an adaptive filter, which may use an adaptive law to update the mean component parameters of the reference control error. The adaptive law may be expressed as Formula 4:

[0065]

[0066] in, represents the mean component parameter of the reference control error at the nth fluid pulsation sampling point, represents the mean component parameter of the reference control error at the n+1th fluid pulsation sampling point, and μ1 represents the first step length factor.

[0067] Step 204: input the first reference signal and the second reference signal into a secondary channel estimation model to obtain a reference signal filtered by the secondary channel estimation model.

[0068] In practical applications, the reference signal filtered by the secondary channel estimation model may include a first reference signal filtered by the secondary channel estimation model and a second reference signal filtered by the secondary channel estimation model. For example, the first reference signal may be input into the secondary channel estimation model to obtain the first reference signal filtered by the secondary channel estimation model, and the second reference signal may be input into the secondary channel estimation model to obtain the second reference signal filtered by the secondary channel estimation model.

[0069] Step 205: Based on the target control error of the fluid pulsation and the reference signal filtered by the secondary channel estimation model, update the first weight coefficient of the notch filter and the second weight coefficient of the notch filter.

[0070] The exemplary embodiment of the present disclosure may adopt an adaptive filter algorithm to update the first weight coefficient of the notch filter and the second weight coefficient of the notch filter. In this case, the first weight coefficient of the notch filter can be expressed as Formula 5, and the second weight coefficient of the notch filter can be expressed as Formula 6:

[0071]

[0072] Wherein, w1(n) represents the first weight coefficient of the notch filter at the nth fluid pulsation sampling point, w1(n+1) represents the first weight coefficient of the notch filter at the n+1th fluid pulsation sampling point, w2(n) represents the second weight coefficient of the notch filter at the nth fluid pulsation sampling point, w2(n+1) represents the second weight coefficient of the notch filter at the n+1th fluid pulsation sampling point, μ2 represents the second step factor, represents the first reference signal of the nth fluid pulsation sampling point after filtering by the secondary channel estimation model, The second reference signal representing the nth fluid pulsation sampling point after being filtered by the secondary channel estimation model.

[0073] When the target control error of the fluid pulsation is used to update the first weight coefficient of the notch filter and the second weight coefficient of the notch filter, it can be ensured that the output fluid pulsation active control signal can control the fluid pulsation more accurately.

[0074] Figure 3 FIG. 1 is a schematic diagram showing the principle of active fluid pulsation control according to an exemplary embodiment of the present disclosure. Figure 3 As shown, the weight coefficients of the notch filter include the first weight coefficient w1 of the notch filter and the second weight coefficient w2 of the notch filter. The weight coefficients of the notch filter corresponding to the nth fluid pulsation sampling point include the first weight coefficient w1(n) of the notch filter at the nth fluid pulsation sampling point and the second weight coefficient w2(n) of the notch filter at the nth fluid pulsation sampling point.

[0075] After constructing a first reference signal x1(n) of the nth fluid pulsation sampling point and a second reference signal x2(n) of the nth fluid pulsation sampling point using the target frequency of the nth fluid pulsation sampling point, the first reference signal x1(n) of the nth fluid pulsation sampling point can be weighted using the first weight coefficient w1(n) of the nth fluid pulsation sampling point by the notch filter to obtain the first weighted signal of the nth fluid pulsation sampling point, and the second reference signal x2(n) of the nth fluid pulsation sampling point can be weighted using the second weight coefficient w2(n) of the nth fluid pulsation sampling point by the notch filter to obtain the second weighted signal of the nth fluid pulsation sampling point, and then the first weighted signal of the nth fluid pulsation sampling point, the second weighted signal of the nth fluid pulsation sampling point and the nonlinear characteristic suppression parameter of the secondary channel of the nth fluid pulsation sampling point are used. Determine the fluid pulsation active control signal y(n) of the nth fluid pulsation sampling point.

[0076] According to an exemplary embodiment of the present disclosure, the fluid pulsation active control signal y(n) of the nth fluid pulsation sampling point can be input into the secondary channel S(n) to obtain the response signal y'(n) of the secondary channel of the nth fluid pulsation sampling point, and the reference control error e(n) of the fluid pulsation of the nth fluid pulsation sampling point can be determined based on the response signal y'(n) of the secondary channel of the nth fluid pulsation sampling point and the original pressure signal d(n) of the fluid pulsation of the nth fluid pulsation sampling point, where e(n)=d(n)-y'(n), and finally the reference control error e(n) of the fluid pulsation of the nth fluid pulsation sampling point and the mean component parameter of the reference control error signal of the nth fluid pulsation sampling point can be obtained. Determine the target control error g(n) of the fluid pulsation at the nth fluid pulsation sampling point.

[0077] The exemplary embodiment of the present disclosure can update the weight coefficient of the notch filter through the first adaptive filter, for example: the first reference signal x1(n) of the nth fluid pulsation sampling point and the second reference signal x2(n) of the nth fluid pulsation sampling point can be input into the secondary channel estimation model Obtain the first estimated signal of the secondary channel at the nth fluid pulsation sampling point and the second estimated signal of the secondary channel at the nth fluid pulsation sampling point Then the first adaptive filter is based on the first estimated signal of the secondary channel of the nth fluid pulsation sampling point The first weight coefficient w1(n) of the nth fluid pulsation sampling point and the target control error g(n) of the fluid pulsation at the nth fluid pulsation sampling point are used to determine the first weight coefficient w1(n) of the n+1th fluid pulsation sampling point. At the same time, the first adaptive filter is based on the second estimation signal of the secondary channel of the nth fluid pulsation sampling point. The second weight coefficient w2(n) of the nth fluid pulsation sampling point and the target control error g(n) of the fluid pulsation of the nth fluid pulsation sampling point are used to determine the second weight coefficient w2(n) of the n+1th fluid pulsation sampling point. In this case, the weight coefficient of the trap corresponding to the n+1th fluid pulsation sampling point is obtained by using the first weight coefficient w1(n) of the n+1th fluid pulsation sampling point and the second weight coefficient of the n+1th fluid pulsation sampling point.

[0078] The exemplary embodiment of the present disclosure can update the mean component parameter of the reference control error estimated by the mean estimator through the second adaptive filter. For example, the second adaptive filter can be based on the target control error g(n) of the fluid pulsation at the nth fluid pulsation sampling point and the mean component parameter of the reference control error at the nth fluid pulsation sampling point. Determine the mean component parameters of the reference control error at the n+1th fluid pulsation sampling point

[0079] exist Figure 1 When the displacement of the plunger pump is 11.6 mL / r, the speed of the plunger pump is 700 rpm, and the system pressure is 5 MPa, the fluid pulsation active control signal generated by the method of the exemplary embodiment of the present disclosure is used to perform active oil pulsation control. Figure 4 FIG. 2 shows a time-pressure relationship diagram of an exemplary embodiment of the present disclosure before and after active control of oil pulsation. Figure 4 As shown, when the main body of oil pulsation control is not performed, the oil pulsation pressure jitter is relatively large, while when the main body of oil pulsation control is performed, the oil pulsation pressure jitter is relatively small.

[0080] Figure 5 FIG. 2 shows a frequency-amplitude relationship diagram before the oil pulsation active control is performed in an exemplary embodiment of the present disclosure. Figure 5 As shown, before the oil pulsation is actively controlled, the frequency of the oil pulsation is 158.4 Hz and its amplitude is 0.141 MPa. Figure 6 FIG. 2 shows a frequency-amplitude relationship diagram after the oil pulsation active control is performed in the exemplary embodiment of the present disclosure. Figure 6 As shown in the figure, before the oil pulsation is actively controlled, the oil pulsation frequency is 158.8Hz and its amplitude is 0.006765MPa. Figure 5 and Figure 6 It can be seen that after active control of oil pulsation, more than 95% amplitude attenuation was achieved at the target frequency point of 158 Hz.

[0081] Figure 7 An example schematic diagram of another fluid pulsation active control system based on the bypass overflow principle is shown. Figure 7 As shown, the fluid pulsation active control system of the exemplary embodiment of the present disclosure may include: a control valve 701, a pressure sensor 702 and an active controller 703, wherein the first end of the control valve 701 is connected to a pipeline 704, the second end of the control valve 701 is connected to an oil tank 705, and the pressure sensor 702 and the control valve 701 are both in communication connection with the active controller 703. It should be understood that the pipeline 704 may be in communication with a hydraulic pump 706.

[0082] like Figure 7 As shown, the active controller 703 of the exemplary embodiment of the present disclosure can be used to execute the method of the exemplary embodiment of the present disclosure to control the control valve 701, thereby causing the flow rate of the pipeline 704 to change and realize the active control of pulsation. The control valve can only reduce the flow rate of the pipeline 704, corresponding to the secondary channel involved in the active control, which is equivalent to the existence of nonlinear characteristics in the secondary channel.

[0083] For example, Figure 7As shown, the active controller 703 of the exemplary embodiment of the present disclosure may include a construction module 7031, a notch filter 7032, a processing module 7033 and a control module 7034. The construction module 7031 has the functions of time domain frequency domain conversion and target frequency identification. The construction module 7031 can obtain the pressure signal in the non-suppressed state collected by the pressure sensor 702, and generate a first reference signal and a second reference signal. The notch filter 7032 can generate a fluid pulsation active control signal based on the first reference signal and the second reference signal, and send the fluid pulsation active control signal to the active controller 703. The active controller can be controlled based on the fluid pulsation active control signal. At the same time, the processing module 7033 can obtain the pressure signal in the suppressed state, and update the nonlinear characteristic suppression parameter and the mean component parameter of the mean estimation module by obtaining the pressure signal in the suppressed state, so as to update the first weight coefficient and the second weight coefficient of the notch filter 7032 by using the nonlinear characteristic suppression parameter and the mean estimation module, so as to ensure that the fluid pulsation active control signal generated by the notch filter can stably control the opening of the control valve 701.

[0084] The above mainly introduces the solution provided by the embodiment of the present disclosure from the perspective of the server. It is understandable that, in order to implement the above functions, the server includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present disclosure.

[0085] The embodiments of the present disclosure may divide the server into functional units according to the above method examples. For example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The above integrated modules may be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiments of the present disclosure is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0086] In the case of dividing each functional module according to each function, an exemplary embodiment of the present disclosure provides a device for determining a fluid pulsation active control signal, and the device for determining a fluid pulsation active control signal may be a server or a chip applied to a server. Figure 8 FIG. 1 is a schematic block diagram showing the functional modules of a device for determining a fluid pulsation active control signal according to an exemplary embodiment of the present disclosure. Figure 8As shown, the device 800 for determining the fluid pulsation active control signal includes:

[0087] A construction module 801 is used to obtain a first reference signal and a second reference signal based on a target frequency of fluid pulsation, wherein the first reference signal and the second reference signal are orthogonal;

[0088] A notch filter 802, configured to determine a fluid pulsation active control signal based on the first reference signal and the second reference signal;

[0089] The processing module 803 is used to input the first reference signal and the second reference signal into the secondary channel estimation model to obtain the reference signal filtered by the secondary channel estimation model, and update the first weight coefficient of the notch filter and the second weight coefficient of the notch filter based on the target control error of the fluid pulsation and the reference signal filtered by the secondary channel estimation model.

[0090] As a possible implementation method, the processing module 803 is used to determine a first weighted signal based on a first weight coefficient of the notch filter and the first reference signal, determine a second weighted signal based on a second weight coefficient of the notch filter and the second reference signal, and determine the fluid pulsation active control signal based on the first weighted signal, the second weighted signal and the nonlinear characteristic suppression parameter of the secondary channel.

[0091] As a possible implementation, the nonlinear characteristic suppression parameter of the secondary channel is determined by the first weight coefficient of the notch filter and the second weight coefficient of the notch filter, and the nonlinear characteristic suppression parameter w(n) of the secondary channel satisfies:

[0092] w1(n) represents the first weight coefficient of the notch filter, w2(n) represents the second weight coefficient of the notch filter, and n represents the target frequency sampling number of the fluid pulsation.

[0093] As a possible implementation, the processing module 803 is further used to update the mean component parameter of the reference control error based on the active control signal of the fluid pulsation at the previous sampling point and the mean component parameter of the reference control error at the previous sampling point.

[0094] As a possible implementation method, the processing module 803 is used to input the fluid pulsation active control signal into the secondary channel to obtain a reference control error of the fluid pulsation, and use the mean component parameter of the reference control error to correct the reference control error of the fluid pulsation to obtain a target control error of the fluid pulsation.

[0095] As a possible implementation method, the processing module 803 is also used to obtain pressure signals of multiple sampling points of fluid pulsation in a non-suppressed state within a preset time period, determine the amplitude-frequency spectrum of the fluid pulsation based on the pressure signals of the multiple sampling points of the fluid pulsation in the non-suppressed state, and determine the target frequency of the fluid pulsation based on the amplitude-frequency spectrum of the fluid pulsation, the target frequency of the fluid pulsation being the fluid pulsation frequency corresponding to the maximum fluid pulsation amplitude in the amplitude-frequency spectrum of the fluid pulsation.

[0096] Fig. 9 Schematic block diagram of a chip according to an exemplary embodiment of the present disclosure is shown. Fig. 9 As shown, the chip 900 includes one or more than two (including two) processors 901 and a communication interface 902. The communication interface 902 can perform the data sending and receiving steps in the above method, and the processor 901 can perform the data processing steps in the above method.

[0097] Optional, such as Fig. 9 As shown, the chip 900 also includes a memory 903, which may include a read-only memory and a random access memory, and provides operation instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory (NVRAM).

[0098] In some embodiments, Fig. 9 As shown, the processor 901 performs corresponding operations by calling the operation instructions stored in the memory (the operation instructions may be stored in the operating system). The processor 901 controls the processing operations of any one of the terminal devices, and the processor may also be called a central processing unit (CPU). The memory 903 may include a read-only memory and a random access memory, and provides instructions and data to the processor 901. A portion of the memory 903 may also include NVRAM. For example, in an application, the memory, the communication interface, and the memory are coupled together through a bus system, wherein the bus system may include a power bus, a control bus, and a status signal bus in addition to a data bus. However, for the sake of clarity, in Fig. 9 Various buses are labeled as bus system 904.

[0099] The method disclosed in the above-mentioned embodiment of the present disclosure can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above-mentioned processor may be a general-purpose processor, a digital signal processor (digital signal processing, DSP), an ASIC, a field-programmable gate array (field-programmable gate array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present disclosure can be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiment of the present disclosure can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware.

[0100] The exemplary embodiment of the present disclosure also provides an electronic device, comprising: at least one processor; and a memory connected to the at least one processor in communication. The memory stores a computer program that can be executed by the at least one processor, and the computer program is used to cause the electronic device to perform the method according to the embodiment of the present disclosure when executed by the at least one processor.

[0101] The exemplary embodiments of the present disclosure also provide a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to perform the method according to the embodiments of the present disclosure.

[0102] The exemplary embodiments of the present disclosure further provide a computer program product, including a computer program, wherein when the computer program is executed by a processor of a computer, the computer is used to enable the computer to perform the method according to the embodiments of the present disclosure.

[0103] refer to Fig.10, a block diagram of an electronic device 1000 that can be used as a server or client of the present disclosure will now be described, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0104] like Fig.10 As shown, the electronic device 1000 includes a computing unit 1001, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1002 or a computer program loaded from a storage unit 1008 into a random access memory (RAM) 1003. In the RAM 1003, various programs and data required for the operation of the device 1000 can also be stored. The computing unit 1001, the ROM 1002, and the RAM 1003 are connected to each other via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0105] like Fig.10 As shown, multiple components in the electronic device 1000 are connected to the I / O interface 1005, including: an input unit 1006, an output unit 1007, a storage unit 1008, and a communication unit 1009. The input unit 1006 can be any type of device that can input information to the electronic device 1000, and the input unit 1006 can receive input digital or character information, and generate key signal input related to the user settings and / or function control of the electronic device. The output unit 1007 can be any type of device that can present information, and can include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 1008 can include but is not limited to a disk, an optical disk. The communication unit 1009 allows the electronic device 1000 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and can include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth TM device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0106] like Fig.10As shown, the computing unit 1001 can be various general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1001 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1001 performs the various methods and processes described above. For example, in some embodiments, the method of the exemplary embodiment of the present disclosure may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 1008. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 1000 via ROM 1002 and / or communication unit 1009. In some embodiments, the computing unit 1001 can be configured to perform the method of the exemplary embodiment of the present disclosure in any other appropriate manner (e.g., by means of firmware).

[0107] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0108] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0109] As used in this disclosure, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and / or device (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0110] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0111] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0112] A computer system may include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship to each other.

[0113] <23P12021CN>

[0114] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instruction is loaded and executed on a computer, the process or function described in the embodiment of the present disclosure is executed in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, a terminal, a user device or other programmable device. The computer program or instruction may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer program or instruction may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server, data center, etc. that integrates one or more available media. The available medium may be a magnetic medium, for example, a floppy disk, a hard disk, a tape; it may also be an optical medium, for example, a digital video disc (DVD); it may also be a semiconductor medium, for example, a solid state drive (SSD).

[0115] Although the present disclosure has been described in conjunction with specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present disclosure. Accordingly, this specification and the drawings are merely exemplary illustrations of the present disclosure as defined by the appended claims, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present disclosure. Obviously, those skilled in the art may make various modifications and variations to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is also intended to include these modifications and variations.

Claims

1. A fluid pulsation active control method based on mean adaptation, characterized in that: include: Acquire a first reference signal and a second reference signal based on a target frequency of fluid pulsation, wherein the first reference signal and the second reference signal are orthogonal; determining a fluid pulsation active control signal based on the first reference signal and the second reference signal; Obtaining a target control error of the fluid pulsation based on the fluid pulsation active control signal and a mean component parameter of a reference control error; Inputting the first reference signal and the second reference signal into a secondary channel estimation model to obtain a reference signal filtered by the secondary channel estimation model; Based on the target control error of the fluid pulsation and the reference signal filtered by the secondary channel estimation model, a first weight coefficient of the notch filter and a second weight coefficient of the notch filter are updated.

2. The method according to claim 1, characterized in that The step of determining the fluid pulsation active control signal based on the first reference signal and the second reference signal comprises: Determine a first weighted signal based on a first weight coefficient of the notch filter and the first reference signal; Determining a second weighted signal based on a second weight coefficient of the notch filter and the second reference signal; The fluid pulsation active control signal is determined based on the first weighted signal, the second weighted signal and a nonlinear characteristic suppression parameter of the secondary channel.

3. The method according to claim 2, characterized in that The nonlinear characteristic suppression parameter of the secondary channel is determined by the first weight coefficient of the notch filter and the second weight coefficient of the notch filter, and the nonlinear characteristic suppression parameter w(n) of the secondary channel satisfies: w1(n) represents the first weight coefficient of the notch filter, w2(n) represents the second weight coefficient of the notch filter, and n represents the fluid pulsation sampling sequence number.

4. The method according to claim 2, characterized in that: The method further comprises: Based on the active control signal of the fluid pulsation at the last sampling point and the mean component parameter of the reference control error at the last sampling point, the mean component parameter of the reference control error is updated.

5. The method according to claim 1, characterized in that: The step of obtaining a target control error of fluid pulsation based on the fluid pulsation active control signal and the mean component parameter of the reference control error comprises: Inputting the fluid pulsation active control signal into the secondary channel to obtain a reference control error of the fluid pulsation; The reference control error of the fluid pulsation is corrected using the mean component parameter of the reference control error to obtain a target control error of the fluid pulsation.

6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: Acquiring pressure signals of multiple sampling points of fluid pulsation in a non-suppressed state within a preset time period; Determining an amplitude-frequency spectrum of the fluid pulsation based on pressure signals of a plurality of sampling points of the fluid pulsation in a non-suppressed state; Based on the amplitude-frequency spectrum diagram of the fluid pulsation, a target frequency of the fluid pulsation is determined, wherein the target frequency of the fluid pulsation is the fluid pulsation frequency corresponding to the maximum fluid pulsation amplitude in the amplitude-frequency spectrum diagram of the fluid pulsation.

7. A fluid pulsation active control device, characterized in that: include: A construction module is used to obtain a first reference signal and a second reference signal based on a target frequency of fluid pulsation, wherein the first reference signal and the second reference signal are orthogonal; a notch filter, for determining a fluid pulsation active control signal based on the first reference signal and the second reference signal; A processing module is used to input the first reference signal and the second reference signal into a secondary channel estimation model to obtain a reference signal filtered by the secondary channel estimation model, and update a first weight coefficient of a notch filter and a second weight coefficient of the notch filter based on a target control error of the fluid pulsation and the reference signal filtered by the secondary channel estimation model.

8. A fluid pulsation active control system, characterized in that: include: A control valve, a pressure sensor and an active controller, wherein the first end of the control valve is connected to a pipeline, the second end of the control valve is connected to an oil tank, the pressure sensor and the control valve are both communicatively connected to the active controller, and the active controller is used to execute the method described in any one of claims 1 to 6.

9. An electronic device, characterized in that: include: processor; as well as, A memory for storing programs; The program includes instructions, which, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 6.

10. A non-transitory computer-readable storage medium, characterized in that The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 6.

Images