Real-time processing method of vibration sensor signal, computing device and storage medium

Abstract

The invention provides a real-time processing method of a vibration sensor signal, computing equipment and a computer readable storage medium. The method comprises the following steps: acquiring a vibration sensor signal, wherein the vibration sensor signal comprises a vibration acceleration signal or an angular velocity signal; performing discrete time integration on the vibration sensor signal to obtain a sensor integration signal; carrying out tap delay on the sensor integral signal based on a preset tap number to obtain an integral signal array at a sampling moment; performing linear fitting on the integral signal array at the sampling moment to obtain a trend term linear fitting parameter at the sampling moment; and determining the trend term of the vibration sensor signal at the sampling moment based on the trend term linear fitting parameter at the sampling moment and the preset tap number.

Description

Technical Field

[0001] The present invention generally relates to the field of control, and more specifically, to a real-time processing method for vibration sensor signals, a computing device, and a computer-readable storage medium. Background Art

[0002] The suspension system is an important part of the vehicle, which plays the role of elastically supporting the vehicle body, alleviating and attenuating the vibration of the vehicle body caused by uneven road surface when the vehicle is driving, so as to ensure the smooth driving of the vehicle. In theory, the vehicle suspension is a system composed of springs and shock absorbers, which determines the handling stability and ride comfort of the vehicle.

[0003] At present, magnetorheological shock absorbers have been widely used in vehicle suspension systems. Magnetorheological shock absorbers use electromagnetic reactions to monitor the movement of the vehicle body and wheels in real time. The sensors transmit data to the system for analysis, thereby making a quick response to road conditions and driving environment. When the vehicle vibrates, the control system analyzes and processes the signals collected by the sensor, and combines the vibration reduction requirements with a pre-designed control strategy to provide the corresponding current value. By controlling the current size, the magnetic field strength generated by the shock absorber's conductive coil is controlled, thereby achieving precise adjustment of the state of the magnetorheological fluid in the shock absorber and achieving the purpose of precise and controllable damping.

[0004] However, the signal collected by the sensor usually contains a trend item. The trend item refers to the deviation of the sensor signal from the baseline, which may be caused by the acquisition system or the signal itself. For example, the vibration signal collected in the vibration test often deviates from the baseline due to the zero drift of the amplifier caused by temperature changes, the instability of the low-frequency performance outside the sensor frequency range, and the environmental interference around the sensor. The deviation from the baseline usually changes with time. For example, for the acceleration sensor on the vehicle, assuming that its baseline direction is perpendicular to the ground and a zero-frequency sensor is used, the standard zero-frequency signal of the acceleration signal collected should be a gravity acceleration (i.e. 9.8m / s^2). However, since the baseline of the sensor cannot be constantly perpendicular to the ground in practice, the trend item value of the acceleration signal actually collected usually floats below the gravity acceleration, such as 9.6m / s^2, 9.7m / s^2, etc.

[0005] In the process of vibration control, such as vehicle vibration control, the measured sensor signals are usually signals such as acceleration signals or angular velocity signals, and the signals required for control are the integral signals of these signals, that is, velocity signals or angle signals. Therefore, it is necessary to filter, remove trend terms, integrate, etc. for the measured sensor signals. Common methods for removing trend terms can use finite impulse response (FIR) filters, infinite impulse response (IIR) filters, Kalman filters, etc. However, these filters are causal filters. Limited by the algorithm principle, these methods will cause time delays to the signals, resulting in an increase in the overall response time of the system, thereby affecting the real-time control effect. For example, when the program main frequency is several hundred hertz and the low-pass filter cutoff frequency is a few hertz, the filter processing delay will be more than 8ms. If the total response time of the entire system is expected to be less than 10ms to achieve real-time control, a filter processing delay greater than 8ms is unacceptable. Summary of the invention

[0006] In response to at least one of the above problems, the present invention provides a method for processing a vibration sensor signal, which can obtain a sensor integrated signal without a trend term without delay by first integrating the detected vibration sensor signal and then fitting a trend term to remove the trend term from the signal.

[0007] According to one aspect of the present invention, a real-time processing method for a vibration sensor signal is provided. The method comprises: acquiring the vibration sensor signal, the vibration sensor signal comprising a vehicle acceleration signal or an angular velocity signal; performing discrete time integration on the vibration sensor signal to obtain a sensor integral signal; performing tap delay on the sensor integral signal based on a predetermined number of taps to obtain an integral signal array at a sampling moment; performing linear fitting on the integral signal array at the sampling moment to obtain a linear fitting parameter of a trend item at the sampling moment; and determining a trend item of the sensor integral signal at the sampling moment based on the linear fitting parameter of the trend item at the sampling moment and the predetermined number of taps.

[0008] In some implementations, the method further includes: performing detrending processing on the sensor integrated signal at the sampling moment based on the trend term of the sensor integrated signal at the sampling moment.

[0009] In some implementations, performing discrete-time integration on the vibration sensor signal to obtain a sensor integrated signal includes: performing discrete-time integration on the vibration sensor signal using a reverse Euler algorithm to obtain the sensor integrated signal.

[0010] In some implementations, the sensor integrated signal is represented by: i =a i-1 +K*t*xi , where K is the preset input gain value, t is the minimum time step of the vibration sensor signal, and x i is the sensor signal at sampling time i.

[0011] In some implementations, performing a tap delay on the sensor integrated signal based on a predetermined number of taps to obtain an integrated signal array at a sampling moment includes: determining the integrated signal array at the sampling moment as a sequence of sensor integrated signals at the sampling moment and N-1 sampling moments before the sampling moment; or determining the integrated signal array at the sampling moment as a sequence of sensor integrated signals at N-1 sampling moments before the sampling moment, where N is the predetermined number of taps.

[0012] In some implementations, the trend term linear fitting parameters include a slope parameter and an intercept parameter.

[0013] In some implementations, the slope parameter at the sampling time is expressed as:

[0014]

[0015] The intercept parameter at the sampling time is expressed as:

[0016]

[0017] where k i represents the slope parameter at sampling time i, b i represents the intercept parameter at sampling time i, {y ij |j=1,…,N} represents the integrated signal array at sampling time i, and N represents the predetermined number of taps.

[0018] In some implementations, the method further includes: determining whether the slope parameter is less than a first threshold; if the slope parameter is less than the first threshold, determining the slope parameter as the first threshold; if the slope parameter is not less than the first threshold, determining whether the slope parameter is greater than a second threshold; if the slope parameter is greater than the second threshold, determining the slope parameter as the second threshold, wherein the second threshold is greater than the first threshold.

[0019] According to another aspect of the present invention, a computing device is provided. The computing device includes: at least one processor; and at least one memory, the at least one memory is coupled to the at least one processor and stores instructions for execution by the at least one processor, and when the instructions are executed by the at least one processor, the computing device executes the steps according to the above method.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, on which a computer program code is stored. When the computer program code is executed, the method described above is executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The present invention will be better understood and other objects, details, features and advantages of the present invention will become more apparent through the following description of specific embodiments of the present invention given with reference to the accompanying drawings.

[0022] Figure 1 A schematic diagram of a vehicle vibration reduction system 100 according to some embodiments of the present invention is shown.

[0023] Figure 2 An exemplary flow chart of a method for real-time processing of vibration sensor signals according to an embodiment of the present invention is shown.

[0024] Figure 3 FIG. 4 is a flow chart showing a process of processing the determined slope parameter according to an embodiment of the present invention.

[0025] Figure 4 A block diagram of a computing device suitable for implementing embodiments of the present disclosure is shown.

[0026] FIG. 5A to FIG. 5C A schematic diagram of a simulation of a vibration sensor signal processing result according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0027] The preferred embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present invention more thorough and complete, and to fully convey the scope of the present invention to those skilled in the art.

[0028] In the following description, certain specific details are set forth for the purpose of illustrating various embodiments of the invention to provide a thorough understanding of the various embodiments of the invention. However, those skilled in the relevant art will recognize that the embodiments may be practiced without one or more of these specific details. In other cases, well-known devices, structures, and techniques associated with the present application may not be shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

[0029] Unless the context requires otherwise, throughout the specification and claims, the word "comprise" and variations such as "include" and "have" should be construed in an open, inclusive sense, ie, should be interpreted as "including, but not limited to."

[0030] References throughout the specification to "one embodiment" or "some embodiments" indicate that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearance of "in one embodiment" or "some embodiments" in various places throughout the specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any manner in one or more embodiments.

[0031] In addition, the terms "first", "second", "third", etc. used in the specification and claims are only used to distinguish each object for the sake of clarity of description, and do not limit the size or other order of the objects described, unless otherwise specified.

[0032] Figure 1 Schematic diagram of a vehicle vibration reduction system 100 according to some embodiments of the present invention is shown. The vehicle vibration reduction system 100 may include at least one vibration sensor 110 and a controller 120. The vibration sensor 110 may be an acceleration sensor or an angular velocity sensor. The acceleration sensor may be located near the two front wheels 12 of the vehicle 10, forming part of the front shock absorber of the vehicle 10, or may be located near the two rear wheels 16 of the vehicle 10, forming part of the rear shock absorber of the vehicle 10. For example, as a side view, Figure 1 The vibration sensor 110-1 shown is an acceleration sensor located near the left front wheel, and the vibration sensor 110-2 is an acceleration sensor located near the left rear wheel. The two acceleration sensors located near the right front wheel and the right rear wheel are omitted in the figure. In addition, the vibration sensor 110 may also include an angular velocity sensor for measuring angular velocity, such as Figure 1 The vibration sensor 110-3 shown in FIG. Each vibration sensor 110 collects corresponding sensor signals according to its operating frequency, and the controller 120 processes these vibration sensor signals to control the magnetic field strength generated by the conductive coil of the shock absorber, thereby controlling the state of the magnetorheological fluid in the shock absorber to achieve the vibration reduction effect of the vehicle 10. The controller 120 can be, for example, or can be located in an electronic control unit (ECU) of the vehicle 10.

[0033] Note that although the vehicle vibration reduction system 100 is used as an example to illustrate the real-time processing of the vibration sensor signal in this article, those skilled in the art can understand that the processing method described in this article can be easily applied to other systems as long as the system meets the processing conditions described in this article, for example, a vibration sensor 110 (such as a zero-frequency vibration sensor) as described in this article is used, and the movement of the vibration sensor 110 on the non-measurement axis is not significant (that is, only a small offset relative to the baseline is generated), etc.

[0034] Further, the controller 120 may include at least one processor and at least one memory coupled to the at least one processor, the memory storing instructions executable by the at least one processor, and the instructions, when executed by the at least one processor, performing at least a portion of the method described below. The specific structure of the controller 120 may be described below in conjunction with FIG. 5 , for example.

[0035] Figure 2 FIG. 2 shows an exemplary flow chart of a real-time processing method 200 of a vibration sensor signal according to an embodiment of the present invention. The processing method 200 may be Figure 1 The vehicle vibration reduction system 100 , more specifically, is implemented by a controller 120 .

[0036] like Figure 2 As shown in FIG. 1 , in block 210 , the controller 120 may obtain a vibration sensor signal X of the vehicle 10 . The vibration sensor signal may include an acceleration signal (e.g., Figure 1 An acceleration sensor, such as the vibration sensor 110-1 or the vibration sensor 110-2, detects) or an angular velocity signal (for example, Figure 1 Here, the vibration sensor signal X may be a vibration sensor signal x at each sampling moment obtained by one of the vibration sensors 110 according to the sampling frequency of the vibration sensor 110. i (i=1,2,……), that is, X={x i}.

[0037] At block 220, the controller 120 may perform a discrete time integration on the vibration sensor signal X to obtain a sensor integrated signal A={a i Similarly, the sensor integrated signal A can be expressed as a set of sensor integrated signals a arranged according to the sampling time i , that is, A={a i Here, the vibration sensor signal X may be integrated in discrete time using a forward Euler algorithm, a reverse Euler algorithm, or a trapezoidal method.

[0038] For example, when using the reverse Euler algorithm, the sensor integrated signal a at sampling time i is i It can be expressed as:

[0039] a i =a i-1 +K*t*x i

[0040] Wherein, K is the preset input gain value, for example, it can be set to 1, t is the minimum time step of the vibration sensor signal (i.e., the sensor sampling interval, assuming that the sensor sampling interval remains unchanged), xi is the vibration sensor signal at sampling time i.

[0041] By performing discrete time integration on the vibration sensor signal X to obtain the sensor integral signal A, on the one hand, the acceleration signal or angular velocity signal can be converted into the velocity signal or angle signal required for the final vibration reduction control; on the other hand, through discrete time integration, the high-frequency random noise of the vibration sensor signal during the acquisition process can be eliminated.

[0042] In block 230, the controller 120 may perform a tap delay on the sensor integrated signal A based on a predetermined number of taps N to obtain an integrated signal array Y at sampling time i. i For example, the sensor integrated signal A may be tapped and delayed by a tap delay device.

[0043] Depending on the different implementations of the tapped delay, the integrated signal array Y at sampling time i is obtained i In one implementation, the integrated signal array Y obtained at sampling time i is i The sensor integrated signal a at sampling time i can be included i and the sensor integrated signal a at N-1 sampling moments before sampling moment i i-1 、a i-2 , ...a i-(N-1) The sequence of i ={a i-(N-1) ,a i-(N-2) ,…a i-2 ,a i-1 ,a i In another implementation, the integrated signal array Y obtained at sampling time i is i It can only include the sensor integrated signal a at N-1 sampling moments before sampling moment i i-1 、a i-2 , ...a i-(N-1) The sequence of i ={a i-(N-1) ,a i-(N-2) ,…a i-2 ,a i-1}. i ={a i-(N-1) ,a i-(N-2) ,…a i-2 ,a i-1 ,a i} is used as an example for description. For convenience, Y i Represented as {y i1 ,y i2 ,…,y iN}.

[0044] Here, the predetermined number of taps N can be set differently according to different application scenarios. In theory, for a given application scenario, the target component (or useful component) in the vibration sensor signal usually has a given frequency range or frequency component, and the frequency of the trend item will obviously deviate from the frequency range or component (usually far below), so the delay time t of the tap delayer can be selected or set to the minimum value that can effectively distinguish the target component and the trend item, so that the predetermined number of taps N can be set to 1 / t.

[0045] In block 240, the controller 120 may perform a calculation on the integrated signal array Y at sampling time i. i Perform linear fitting to obtain the linear fitting parameters of the trend term at sampling time i.

[0046] In some embodiments, the least square method can be used to calculate the integrated signal array Y i Perform linear fitting. In the case of linear fitting, the fitting parameters at sampling time i may include the slope parameter k i and the intercept parameter b i .

[0047] In some embodiments, the slope parameter k at sampling time i can be obtained by the following formula (1): i , and the intercept parameter b at sampling time i is obtained by the following formula (2): i :

[0048]

[0049]

[0050] Where j=1,……N.

[0051] Next, in block 250 , the controller 120 may determine the trend term of the vibration sensor signal at the sampling time i based on the linear fitting parameter of the trend term at the sampling time i and the predetermined number of taps N.

[0052] In some embodiments, the trend term T of the vibration sensor signal at sampling time i is i It can be expressed as:

[0053] T i =k i *N+b i (3)

[0054] Furthermore, the method 200 may also perform detrending term processing on the vibration sensor signal at the sampling time i based on the trend term at the sampling time i determined in block 250 .

[0055] Specifically, the vibration sensor signal after detrending can be expressed as:

[0056]

[0057] Vibration sensor signal after detrending The controller 120 can further use the signal to perform vehicle vibration reduction control. (and other control signals and control parameters, etc.) generate a control signal to control the magnitude of the generated current value, which is used to control the magnetic field strength of the shock absorber conductive coil, thereby achieving control of the state of the magnetorheological fluid in the shock absorber.

[0058] According to the above formula (1), it can be seen that the slope parameter k at sampling time i is i It can reflect the changing trend of the first N signals at that moment. Therefore, at some moments, the slope parameter may be too large or too small. This usually means that a spike value appears in the sensor measurement signal. In this case, the signal after determining the trend term and the detrending term in the above manner will produce amplitude distortion.

[0059] For this situation, the method 200 may further include a further processing procedure for the slope parameter. Figure 3 FIG. 4 is a flow chart showing a process of processing the determined slope parameter according to an embodiment of the present invention. Figure 3 The process is, for example, Figure 2 Block 240 is shown to determine the slope parameter k at sampling time i i Then execute.

[0060] Specifically, in block 241, the slope parameter k is determined i Is it less than the first threshold th1?

[0061] If the slope parameter k is determined i is less than the first threshold th1, then in block 242, the slope parameter k i Determined as the first threshold th1.

[0062] If the slope parameter k is determined i is not less than the first threshold th1, then in block 243, the slope parameter k is further determined. i Is it greater than the second threshold th2?

[0063] If the slope parameter k is determined i is greater than the second threshold th2, then in block 244, the slope parameter k i Determined as the second threshold th2.

[0064] Here, the second threshold th2 is greater than the first threshold th1.

[0065] If the slope parameter k is determined in block 243 i is not greater than the second threshold value th2, then in box 245, the slope parameter k calculated in box 240 is still used. i .

[0066] In this way, the slope parameter k that is too large or too small can be i Limit to a range near a standard value. For example, when the vibration sensor signal is an acceleration signal, the standard value is 1 gravitational acceleration gt. In this case, the first threshold value can be set to be slightly smaller than the standard value, such as 0.8gt, and the second threshold value can be set to be slightly larger than the standard value, such as 1.2gt.

[0067] Figure 4 A block diagram of a computing device 400 suitable for implementing embodiments of the present disclosure is shown. The computing device 400 may be used to implement the controller 120 as described above.

[0068] As shown, computing device 400 may include processor 410. Processor 410 controls the operation and functionality of computing device 400. For example, in some embodiments, processor 410 may perform various operations with the aid of instructions 430 stored in memory 420 coupled thereto. Memory 420 may be of any suitable type suitable for the local technical environment and may be implemented using any suitable data storage technology, including but not limited to semiconductor-based memory devices, magnetic memory devices and systems, and optical memory devices and systems. Although Figure 4 Only one memory 420 is shown in the figure, but those skilled in the art will appreciate that the computing device 400 may include more physically different memories 620 .

[0069] The processor 410 may be of any suitable type suitable for the local technical environment, and may include, but is not limited to, one or more of a general purpose computer, a special purpose computer, a microprocessor, a digital signal processor (DSP), and a processor-based multi-core processor architecture. The computing device 400 may also include multiple processors 410. The processor 410 is coupled to the transceiver 440, which may enable the reception and transmission of information with the aid of one or more communication components. Figures 1 to 3 All features described with respect to the controller 120 are applicable to the computing device 400 and will not be described in detail herein.

[0070] By utilizing the solution of the present invention, by first integrating the acceleration signal or angular velocity signal collected by the vehicle sensor, and then fitting a trend term to remove the trend term from the collected signal, a velocity signal or angle signal without a trend term can be obtained without delay, thereby helping to improve the response speed of the vehicle vibration reduction system.

[0071] FIG. 5A to FIG. 5C FIG. 1 is a schematic diagram showing a simulation result of a vibration sensor signal processing result according to an embodiment of the present invention. Figure 5A Schematic diagram of the original signal with trend term (i.e., the acquired vibration sensor signal) is shown in FIG. Figure 5B A schematic diagram showing a trend item of a sensor integrated signal at each sampling moment determined according to the method of the present invention is shown; Figure 5C A schematic diagram is shown of a signal (ie, a detrended integrated signal) obtained after detrending the sensor integrated signal at each moment.

[0072] The present invention may be implemented as a method, an apparatus, a system and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing various aspects of the present invention.

[0073] In one or more exemplary designs, the functions described in the present invention may be implemented using hardware, software, firmware, or any combination thereof. For example, if implemented using software, the functions may be stored as one or more instructions or codes on a computer-readable medium, or transmitted as one or more instructions or codes on a computer-readable medium.

[0074] The various units of the apparatus disclosed herein may be implemented using discrete hardware components or may be integrated on a hardware component, such as a processor. For example, the various exemplary logic blocks, modules, and circuits described in conjunction with the present invention may be implemented or executed using a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof for performing the functions described herein.

[0075] Those skilled in the art should also understand that the various illustrative logical blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments of the present invention may be implemented as electronic hardware, computer software, or a combination of the two.

[0076] The above description of the present invention is intended to enable any person of ordinary skill in the art to implement or use the present invention. Various modifications of the present invention are apparent to those of ordinary skill in the art, and the general principles defined herein may also be applied to other variations without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited to the examples and designs described herein, but is consistent with the broadest range of principles and novel features disclosed herein.

Claims

1. A real-time processing method for a vibration sensor signal, comprising: Acquire the vibration sensor signal, where the vibration sensor signal includes an acceleration signal or an angular velocity signal; Performing discrete time integration on the vibration sensor signal to obtain a sensor integrated signal; Performing tap delay on the sensor integrated signal based on a predetermined number of taps to obtain an integrated signal array at a sampling time; Performing linear fitting on the integrated signal array at the sampling moment to obtain linear fitting parameters of the trend item at the sampling moment; as well as The trend term of the sensor integrated signal at the sampling moment is determined based on the linear fitting parameter of the trend term at the sampling moment and the predetermined number of taps.

2. The method of claim 1, further comprising: Detrending term processing is performed on the sensor integrated signal at the sampling moment based on the trend term of the sensor integrated signal at the sampling moment.

3. The method of claim 1 , wherein performing discrete-time integration on the vibration sensor signal to obtain a sensor integrated signal comprises: The vibration sensor signal is integrated in discrete time using a reverse Euler algorithm to obtain the sensor integrated signal.

4. The method of claim 3, wherein the sensor integrated signal is represented by: a i =a i-1 +K*t*x i in, K is the preset input gain value, t is the minimum time step of the vibration sensor signal, x i is the sensor signal at sampling time i.

5. The method of claim 1, wherein performing tap delay on the sensor integrated signal based on a predetermined number of taps to obtain an integrated signal array at a sampling time comprises: Determine the array of integrated signals at the sampling moment as a sequence of sensor integrated signals at the sampling moment and N-1 sampling moments before the sampling moment; or The integrated signal array at the sampling moment is determined as a sequence of sensor integrated signals at N-1 sampling moments before the sampling moment, Wherein N is the predetermined number of taps. The method according to claim 1 , wherein the trend term linear fitting parameters include a slope parameter and an intercept parameter.

7. The method of claim 6, wherein the slope parameter at the sampling moment is expressed as: The intercept parameter at the sampling time is expressed as: where k i represents the slope parameter at sampling time i, b i represents the intercept parameter at sampling time i, {y ij |j=1,…,N} represents the integrated signal array at sampling time i, and N represents the predetermined number of taps.

8. The method of claim 6, further comprising: determining whether the slope parameter is less than a first threshold; If the slope parameter is less than the first threshold, determining the slope parameter as the first threshold; If the slope parameter is not less than the first threshold, determining whether the slope parameter is greater than a second threshold; If the slope parameter is greater than the second threshold, the slope parameter is determined to be the second threshold, wherein the second threshold is greater than the first threshold.

9. A computing device comprising: A memory non-transitorily stores computer executable instructions; a processor configured to execute the computer executable instructions; Wherein, when the computer executable instructions are executed by the processor, the method according to any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium having a computer program code stored thereon, wherein the computer program code executes the method according to any one of claims 1 to 8 when executed.

Images