A method and device for adaptive steady-state signal acquisition

Abstract

The present invention discloses an adaptive steady-state signal acquisition method and device, wherein the method comprises the following steps: setting signal acquisition parameters; receiving samples of signal acquisition; for signal data, calculating the total signal level of each signal slice and the average value of the total signal level of all signal slices, and comparing the total signal level of each slice with the average value of the total signal level of all signal slices in turn; obtaining a ratio, if the ratio exceeds a threshold range, determining that the current signal slice has no noise, saving the current signal slice and the corresponding total signal level; if the ratio is within the threshold range, determining that the current signal slice contains noise, calculating and discarding the slice signal; for the saved current signal slice, performing self-power spectrum calculation to obtain the self-power spectrum; outputting the saved current signal slice and the obtained self-power spectrum. The technical solution provided by the present invention has high utilization rate of signal acquisition, stronger real-time performance, and better integrity of signal preservation.

Description

Technical Field

[0001] The present invention belongs to the technical field of steady-state signal processing, and in particular relates to an adaptive steady-state signal acquisition method and device. Background Art

[0002] The steady-state signals obtained in actual production will inevitably be mixed with interference from noise signals during the collection and transmission process. Especially when the noise pollution is serious, it will affect the subsequent analysis and processing work. Therefore, in the process of steady-state signal acquisition, the interference of noise should be reduced as much as possible. When the above-mentioned noise interference occurs in the traditional steady-state signal acquisition process, the following three solutions are usually used: The first is to abandon the current data and re-measure when it can be determined that the steady-state signal to be collected can last for a long time or the scene can be reproduced; the second is when the steady-state signal to be collected cannot be collected repeatedly, it will be chosen to manually intercept part of the signal that can be used through experience; the third is to add filtering when conditioning the steady-state signal. However, the above three solutions have the following disadvantages:

[0003] (1) The first solution has poor timeliness and low utilization. The method of discarding the noisy signal and re-collecting the steady-state signal consumes more manpower and material resources, and requires the steady-state signal to be measured to last for a long time;

[0004] (2) The second solution has poor accuracy and redundant operations. It is difficult to determine the boundaries of data interception when selecting data, which may result in a reduction in valid data or failure to completely delete redundant data. In addition, the manual operation steps are cumbersome.

[0005] (3) The third option involves relatively large data changes. The filter function calculation is complex and the data range that needs to be changed is relatively wide, which may filter out the characteristics of the signal itself.

[0006] Based on the above, it is necessary to improve the traditional steady-state signal acquisition method. Summary of the invention

[0007] The object of the present invention is to provide an adaptive steady-state signal acquisition method and device to improve the utilization, real-time performance and integrity of steady-state signal acquisition.

[0008] To achieve the purpose of the present invention, the technical solution provided by the present invention is as follows:

[0009] First aspect

[0010] The present invention provides an adaptive steady-state signal acquisition method, comprising the following steps:

[0011] Step S1: Setting signal acquisition parameters; the signal acquisition parameters include sampling frequency , frequency resolution , average rate , Time window type , Collection duration ;

[0012] Step S2: Receive the samples of the signal collected at time intervals , Slice length The signal is sliced ​​sequentially until the number of samples reaches the preset , and the length is The total number of signal slices is signal data; where , , ;

[0013] Step S3: For a total number of signal slices signal data, calculating the total signal level of each signal slice and the average value of the total signal levels of all signal slices, and comparing the total signal level of each signal slice with the average value of the total signal level of all signal slices in turn;

[0014] Step S4: Get the ratio ,like Exceeds the preset threshold range , then execute step S5; if If it is within the threshold range, then execute step S6;

[0015] Step S5: Determine that the current signal slice has no noise, and save the current signal slice and the corresponding signal level;

[0016] Step S6: Determine whether the current signal slice contains noise, and perform the following calculation: Determine whether the length of the current signal slice is less than or equal to the specified discard length ; If yes, the current signal slice is discarded; if no, the current signal slice is evenly divided into two sub-signal slices, the total signal level of the two sub-signal slices is calculated, and the total signal level is compared with the average value of the total signal level of all signal slices again, and step S4 is executed;

[0017] Step S7: Calculate the auto power spectrum for the current signal slice saved in step S5 to obtain the auto power spectrum;

[0018] Step S8: Output the current signal slice saved in step S5 and the auto-power spectrum obtained in step S7.

[0019] Second aspect

[0020] The present invention provides an adaptive steady-state signal acquisition device, comprising the following units: a parameter setting unit, a signal acquisition unit, a signal calculation and comparison unit, a comparison result output unit, a slice storage unit, a slice discarding unit, an auto-power spectrum calculation unit, and a slice output unit;

[0021] The parameter setting unit is used to set signal acquisition parameters; the signal acquisition parameters include sampling frequency , frequency resolution , average rate , Time window type , Collection duration ;

[0022] The signal acquisition unit is used to receive samples of signal acquisition at time intervals , Slice length The signal is sliced ​​sequentially until the number of samples reaches the preset , and the length is The total number of signal slices is signal data; where , , ;

[0023] The signal calculation comparison unit is used for calculating the total number of signal slices. signal data, calculating the total signal level of each signal slice and the average value of the total signal levels of all signal slices, and comparing the total signal level of each signal slice with the average value of the total signal level of all signal slices in turn;

[0024] The comparison result output unit is used to obtain a ratio of ,like Exceeds the preset threshold range , then execute the slice saving unit; if If the value is within the threshold range, the slice discarding unit is executed;

[0025] The slice saving unit is used to determine that the current signal slice has no noise, and save the current signal slice and the corresponding signal total level;

[0026] The slice discarding unit is used to determine whether the current signal slice contains noise and perform the following calculations: determine whether the length of the current signal slice is less than or equal to the specified discarding length ; If yes, the current signal slice is discarded; if no, the current signal slice is evenly divided into two sub-signal slices, the total signal level of the two sub-signal slices is calculated, and the total signal level of all signal slices is compared again, and the comparison result output unit is executed;

[0027] The auto-power spectrum calculation unit is used to perform auto-power spectrum calculation on the saved current signal slice to obtain the auto-power spectrum;

[0028] The slice output unit is used to output the saved current signal slice and the autopower spectrum.

[0029] Compared with the prior art, the technical solution provided by the present invention has the following advantages:

[0030] (1) The technical solution provided by the present invention does not discard the entire segment of data and re-collect it like the traditional method for processing noisy signals, but deletes the shorter abnormal data obtained after multiple segmentation. This solution only changes the local data and has no effect on the overall data, and the utilization rate of the collected signal is high.

[0031] (2) The technical solution provided by the present invention has real-time requirements for signal processing. When the signals to be collected are sometimes random and the scenes cannot be reproduced, data collection is required to have stronger real-time performance. By using the technical solution provided by the present invention, adaptive processing can be achieved when interference signals appear during a collection process without interrupting the collection, which has stronger real-time performance.

[0032] (3) The technical solution provided by the present invention will not affect other undeleted data when deleting abnormal data, and can relatively completely retain the characteristics of signal data, and the integrity of signal preservation is better. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A schematic diagram of the method flow provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] It should be noted that the present invention provides a solution for adaptively processing interference signals that occur during steady-state signal acquisition without interrupting acquisition, which can solve the problem of strong signal interference that occurs during steady-state signal acquisition.

[0036] It should be noted that the steady-state signal acquisition solution provided by the present invention is applicable to the acquisition of signals in various steady-state environments. For example, automobile manufacturers can collect vibration noise signals in real time during the operation of the automobile and perform real-time analysis. Through the analysis of acoustic and vibration signals, they can quickly and accurately diagnose and repair abnormal vehicle noise, thereby improving service efficiency.

[0037] like Figure 1 As shown, this embodiment provides an adaptive steady-state signal acquisition method, comprising the following steps:

[0038] Step S1: Setting signal acquisition parameters; the signal acquisition parameters include sampling frequency , frequency resolution , average rate , Time window type , Collection duration ;

[0039] It should be noted that the sampling frequency refers to the number of samples per second; the frequency resolution refers to the minimum interval that can distinguish two different frequency components in the frequency domain; the average rate refers to the number of slice starting points contained in the sample per second when slicing; the time window type specifies the time period for sampling and processing the signal.

[0040] Step S2: Receive the samples of the signal collected at time intervals , Slice length The signal is sliced ​​sequentially until the number of samples reaches the preset , and the length is The total number of signal slices is signal data; where , , ;

[0041] Step S3: For a total number of signal slices signal data, calculating the total signal level of each signal slice and the average value of the total signal levels of all signal slices, and comparing the total signal level of each signal slice with the average value of the total signal level of all signal slices in turn;

[0042] In step S3, the total signal level is calculated as follows:

[0043] ;

[0044] Among them, OA is the overall signal level, is the total number of samples in the slice interval, The first The amplitude of the samples, For the first The time window weight coefficient corresponding to the samples, is the time window energy compensation coefficient, and By time window type With slice length Sure.

[0045] Wherein, the time window is a Hanning window, Calculated by the following formula:

[0046] .

[0047] Step S4: Get the ratio ,like Exceeds the preset threshold range , then execute step S5; if If it is within the threshold range, then execute step S6;

[0048] Step S5: Determine that the current signal slice has no noise, and save the current signal slice and the corresponding signal level;

[0049] Step S6: Determine whether the current signal slice contains noise, and perform the following calculation: Determine whether the length of the current signal slice is less than or equal to the specified discard length ; If yes, the current signal slice is discarded; if no, the current signal slice is evenly divided into two sub-signal slices, the total signal level of the two sub-signal slices is calculated, and the total signal level is compared with the average value of the total signal level of all signal slices again, and step S4 is executed;

[0050] It should be noted that the signal slices containing noise use the binary method to successively approximate the range interval where the noise is located, and the data in the interval where the noise signal is located is deleted.

[0051] Step S7: Calculate the auto power spectrum for the current signal slice saved in step S5 to obtain the auto power spectrum;

[0052] Wherein, in step S7, the autopower spectrum is calculated in the following manner:

[0053] ;

[0054] in, express The autopower spectrum of the frequency components is After Fourier transformation, The mean value of the frequency components.

[0055] Among them, the The calculation method uses one of the following calculation methods:

[0056] (1) Linear average calculation formula:

[0057] ;

[0058] in, Indicates After Fourier transformation of the slice The complex value of the frequency components;

[0059] (2) The energy average calculation formula is:

[0060] ;

[0061] in, Indicates After Fourier transformation of the slice The complex value of the frequency components.

[0062] Among them, the The calculation method is as follows:

[0063] ;

[0064] in, It is the first The signal value of each sampling point; Indicates the phase relationship between different frequency components.

[0065] Step S8: Output the current signal slice saved in step S5 and the auto-power spectrum obtained in step S7.

[0066] Through experiments, it is found that the technical solution of the present invention has no effect on the signal interval without noise, and only affects the data in the noise interval. And the data processed by the technical solution of the present invention is only slightly affected when performing subsequent calculations (such as amplitude, phase, octave analysis, etc.).

[0067] Corresponding to the above method, this embodiment provides an adaptive steady-state signal acquisition device, including the following units: a parameter setting unit, a signal acquisition unit, a signal calculation and comparison unit, a comparison result output unit, a slice storage unit, a slice discarding unit, an auto-power spectrum calculation unit, and a slice output unit;

[0068] The parameter setting unit is used to set signal acquisition parameters; the signal acquisition parameters include sampling frequency , frequency resolution , average rate , Time window type , Collection duration ;

[0069] The signal acquisition unit is used to receive samples of signal acquisition at time intervals , Slice length The signal is sliced ​​sequentially until the number of samples reaches the preset , and the length is The total number of signal slices is signal data; where , , ;

[0070] The signal calculation comparison unit is used for calculating the total number of signal slices. signal data, calculating the total signal level of each signal slice and the average value of the total signal levels of all signal slices, and comparing the total signal level of each signal slice with the average value of the total signal level of all signal slices in turn;

[0071] The comparison result output unit is used to obtain a ratio of ,like Exceeds the preset threshold range , then execute the slice saving unit; if If the value is within the threshold range, the slice discarding unit is executed;

[0072] The slice saving unit is used to determine that the current signal slice has no noise, and save the current signal slice and the corresponding signal total level;

[0073] The slice discarding unit is used to determine whether the current signal slice contains noise and perform the following calculations: determine whether the length of the current signal slice is less than or equal to the specified discarding length ; If yes, the current signal slice is discarded; if no, the current signal slice is evenly divided into two sub-signal slices, the total signal level of the two sub-signal slices is calculated, and the total signal level of all signal slices is compared again, and the comparison result output unit is executed;

[0074] The auto-power spectrum calculation unit is used to perform auto-power spectrum calculation on the saved current signal slice to obtain the auto-power spectrum;

[0075] The slice output unit is used to output the saved current signal slice and the autopower spectrum.

[0076] The calculation method of the total signal level is as follows:

[0077] ;

[0078] Among them, OA is the overall signal level, is the total number of samples in the slice interval, The first The amplitude of the samples, For the first The time window weight coefficient corresponding to the samples, is the time window energy compensation coefficient, and By time window type With slice length Sure.

[0079] Wherein, the time window is a Hanning window, Calculated by the following formula:

[0080] .

[0081] The autopower spectrum is calculated as follows:

[0082] ;

[0083] in, express The autopower spectrum of the frequency components is After Fourier transformation, The mean value of the frequency components.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate and explain the present invention, and are not intended to limit the present invention to the scope of the described embodiments. In addition, those skilled in the art can understand that the present invention is not limited to the above embodiments, and more variations and modifications can be made according to the teachings of the present invention, and these variations and modifications all fall within the scope of the protection claimed by the present invention.

Claims

1. An adaptive steady-state signal acquisition method, characterized in that: The steps include: Step S1: Setting signal acquisition parameters; the signal acquisition parameters include sampling frequency f s , frequency resolution Δf, average rate R, time window type ψ, acquisition duration T; Step S2: Receive samples of the signal collected at time intervals t step , and slice length N, and slice the signal in sequence until the number of samples reaches the preset L, and obtain signal data with a length of L and a total number of signal slices of S; where L = f s ×T,S=R×T,N=f s / Δf; Step S3: for signal data with a total number of signal slices S, calculate the total signal level of each signal slice and the average value of the total signal levels of all signal slices, and compare the total signal level of each signal slice with the average value of the total signal levels of all signal slices in turn; Step S4: The comparison result is output as a ratio of λ. If λ exceeds a preset threshold range (σ1, σ2), step S5 is executed; if λ is within the threshold range, step S6 is executed; Step S5: Determine that the current signal slice has no noise, and save the current signal slice and the corresponding signal level; Step S6: Determine whether the current signal slice contains noise, and perform the following calculation: Determine whether the length of the current signal slice is less than or equal to the specified discard length l min ; If yes, the current signal slice is discarded; if no, the current signal slice is evenly divided into two sub-signal slices, the total signal level of the two sub-signal slices is calculated, and the total signal level is compared with the average value of the total signal level of all signal slices again, and step S4 is executed; Step S7: Calculate the auto power spectrum for the current signal slice saved in step S5 to obtain the auto power spectrum; Step S8: Output the current signal slice saved in step S5 and the auto-power spectrum obtained in step S7.

2. The adaptive steady-state signal acquisition method according to claim 1, characterized in that: In step S3, the total level of the signal is calculated as follows: Among them, OA is the total signal level, p+1 is the total number of samples in the slice interval, and y m is the amplitude of the mth sample in the slice interval, w m is the time window weight coefficient corresponding to the mth sample in the slice interval, γ e is the time window energy compensation coefficient, w m With γ e Determined by the time window type ψ and the slice length N.

3. The adaptive steady-state signal acquisition method according to claim 2, characterized in that: The time window is a Hanning window, w m Calculated by the following formula: w m =(1-cos(2πm / (N-1))) / 2。 4. The adaptive steady-state signal acquisition method according to claim 3, characterized in that: In step S7, the autopower spectrum is calculated in the following manner: Where autopower[k] represents the autopower spectrum of k frequency components, y avg [k] represents the mean value of k frequency components after Fourier transform.

5. The adaptive steady-state signal acquisition method according to claim 4, characterized in that: The avg [k] is calculated using one of the following calculation methods: (1) Linear average calculation formula: Among them, y fft,i [k] represents the complex value of the k frequency components after Fourier transform of the i-th slice; (2) The energy average calculation formula is: Among them, y fft,i [k] represents the complex value of the k frequency components after Fourier transform of the i-th slice.

6. The adaptive steady-state signal acquisition method according to claim 5, characterized in that: The fft,i [k] is calculated as follows: Where f(n) is the signal value of the nth sampling point in the time domain; Indicates the phase relationship between different frequency components.

7. An adaptive steady-state signal acquisition device, characterized in that: It includes the following units: a parameter setting unit, a signal acquisition unit, a signal calculation and comparison unit, a comparison result output unit, a slice saving unit, a slice discarding unit, an auto-power spectrum calculation unit, and a slice output unit; The parameter setting unit is used to set the signal acquisition parameters; the signal acquisition parameters include the sampling frequency f s , frequency resolution Δf, average rate R, time window type ψ, acquisition duration T; The signal acquisition unit is used to receive samples of signal acquisition at a time interval t step , and slice length N, and slice the signal in sequence until the number of samples reaches the preset L, and obtain signal data with a length of L and a total number of signal slices of S; where L = f s ×T,S=R×T,N=f s / Δf; a signal calculation and comparison unit, for calculating the total signal level of each signal slice and the average value of the total signal levels of all signal slices for signal data having a total signal slice number S, and comparing the total signal level of each signal slice with the average value of the total signal levels of all signal slices in turn; The comparison result output unit is used to obtain a ratio of λ, and if λ exceeds a preset threshold range (σ1, σ2), the slice preservation unit is executed; if λ is within the threshold range, the slice discarding unit is executed; The slice saving unit is used to determine that the current signal slice has no noise, and save the current signal slice and the corresponding signal total level; The slice discarding unit is used to determine whether the current signal slice contains noise and perform the following calculations: determine whether the length of the current signal slice is less than or equal to the specified discarding length l min ; If yes, the current signal slice is discarded; if no, the current signal slice is evenly divided into two sub-signal slices, the total signal level of the two sub-signal slices is calculated, and the total signal level of all signal slices is compared again, and the comparison result output unit is executed; The auto-power spectrum calculation unit is used to perform auto-power spectrum calculation on the saved current signal slice to obtain the auto-power spectrum; The slice output unit is used to output the saved current signal slice and the autopower spectrum.

8. The adaptive steady-state signal acquisition device according to claim 7, characterized in that: The total level of the signal is calculated as follows: Among them, OA is the total signal level, p+1 is the total number of samples in the slice interval, and y m is the amplitude of the mth sample in the slice interval, w m is the time window weight coefficient corresponding to the mth sample in the slice interval, γ e is the time window energy compensation coefficient, w m With γ e Determined by the time window type ψ and the slice length N.

9. The adaptive steady-state signal acquisition device according to claim 8, characterized in that: The time window is a Hanning window, w m Calculated by the following formula: w m =(1-cos(2πm / (N-1))) / 2。 10. The adaptive steady-state signal acquisition device according to claim 9, characterized in that: The autopower spectrum is calculated as follows: Where autopower[k] represents the autopower spectrum of k frequency components, y avg [k] represents the mean value of k frequency components after Fourier transform.

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