CN108334685B - Frequency spectrum refining method for vibration signal of engineering vehicle - Google Patents
Frequency spectrum refining method for vibration signal of engineering vehicle Download PDFInfo
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Abstract
The invention relates to a frequency spectrum refining method of an engineering vehicle vibration signal, which comprises the following steps: the method comprises the steps of collecting vibration signals of the engineering vehicle, amplifying the vibration signals of the engineering vehicle, filtering the amplified vibration signals, carrying out rectification processing on data obtained through filtering, calculating the frequency of the rectified data to obtain effective peak frequency, calculating the frequency difference value of the effective peak value to judge whether frequency spectrum thinning processing is needed or not, carrying out thinning processing on the signals needing processing, and repeating the processing until all sensors finish processing. By the method, the defect of poor vibration control effect of the engineering vehicle can be overcome, and the vibration of the engineering vehicle is reduced.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a frequency spectrum refining method for a vibration signal of an engineering vehicle.
Background
When the engineering vehicle runs and works, random excitation influenced by road unevenness and excitation of vehicle-mounted equipment during running are suffered, the excitation causes the vibration of the whole vehicle through the transmission of tires and suspensions, and the safety of vehicle structures and workers is damaged by overlarge vibration, so that effective control is needed. The key step of the vibration control is to carry out frequency spectrum analysis on the vehicle vibration response signal to extract frequency and phase information, so that active control or passive control measures are taken in a targeted manner, and the vibration of the engineering vehicle is reduced.
The traditional spectrum feature extraction analysis generally adopts Fast Fourier Transform (FFT) to obtain a panoramic spectrum of the whole frequency range, however, the working condition of the engineering vehicle is often in an unsteady and variable working condition, and the vibration response signal has the characteristic of dense spectrum, so that the dense narrow-band spectrum interval needs to be screened and subjected to fine analysis. By adopting an artificial processing method, uncertain factors such as artificial errors exist, which can cause omission of a frequency spectrum peak value, and further the vibration control effect of the engineering vehicle is greatly reduced.
Disclosure of Invention
In view of the above analysis, the present invention aims to provide a method for refining a spectrum of a vibration signal of an engineering vehicle, so as to solve the problem that the vibration control effect of the engineering vehicle is greatly reduced due to missing of a spectrum peak caused by manually refining data in the prior art.
The purpose of the invention is mainly realized by the following technical scheme:
a method for refining the frequency spectrum of a vibration signal of an engineering vehicle is characterized by comprising the following steps:
installing a plurality of acceleration sensors in the engineering vehicle to acquire vibration signals;
preprocessing the acquired vibration signals, including signal amplification processing and filtering processing on the amplified acceleration sensor signals;
carrying out data regularization processing on the data signals filtered by each acceleration sensor to form regularized data;
calculating the frequency spectrum of each line of data according to the serial number of the column-direction dimension of the normalized data to obtain the effective peak frequency of the line of data;
calculating the frequency difference value of adjacent effective peaks in the data frequency spectrum, judging whether frequency spectrum refinement processing is needed, if so, extracting the initial frequency and the end frequency of the frequency band needing refinement processing, performing linear frequency modulation Z conversion, and storing the result to obtain a refined frequency spectrum of the corresponding frequency band; otherwise, directly storing the frequency spectrum result.
Traversing each line of data, processing to obtain CZT of the frequency spectrum refining frequency band, and storing a result; and finishing the spectrum thinning processing until all frequency bands needing thinning are finished.
The invention has the following beneficial effects: the method utilizes a frequency spectrum refining method of the vibration signals of the engineering vehicle to process the acquired data in batches, thereby greatly improving the data processing efficiency and improving the vibration control effect.
On the basis of the scheme, the invention is further improved as follows:
further, the acceleration sensors are respectively arranged on the left side of an axle of the engineering vehicle, the front center position of the frame and the center position of a cab floor.
The beneficial effect of adopting the further scheme is that: the acceleration sensors which respectively collect a plurality of different positions can contain vibration changes of all main vibration sources, so that data collection is more complete, and the obtained data is more effective.
Further, the signal preprocessing comprises:
the acquired vibration signals are amplified, and primary amplification, high-pass filtering and secondary amplification are sequentially carried out;
and removing noise from the amplified signal by using a low-pass filter.
The beneficial effect of adopting the further scheme is that: after the signal is amplified by the needed multiple, a plurality of high-frequency noises are superposed, and the high-frequency noises can be filtered out by adopting a low-pass filtering mode, so that the influence of the noises on data is reduced; the first-stage amplifying circuit obtains zero-position output voltage of a superposition sensor in an output signal, and a high-pass filter circuit is required to be added in front of a second-stage amplifier to isolate the signal in order to eliminate the influence of the zero-position output voltage on subsequent target amplification.
Further, the performing data normalization processing on the data signal filtered by each acceleration sensor to form normalized data includes:
the number of the data collected by the sensors after filtering is M, namely M data vectors with different lengths are contained, and M is the number of the sensors; finding the maximum value of the number of sampling points, namely the maximum value of the length, and recording the maximum value as N;
zero padding is carried out after the rest M-1 data vectors, so that the length of each data vector is N;
the zero-padded vectors are arranged in the first, second, and … th columns to form normalized data.
The beneficial effect of adopting the further scheme is that: and zero padding is carried out on the filtered data with different lengths to form normalized data, and each data can be better subjected to subsequent processing. The maximum value data vector is selected as the length standard, so that the validity of all data is protected, and the waste caused by setting the data length to exceed the fixed value of each data length is prevented.
Further, the calculating the frequency spectrum of each column of data comprises:
performing fast Fourier transform on the column of data;
and taking an absolute value of the transformation result to obtain a frequency spectrum amplitude.
The beneficial effect of adopting the further scheme is that: and calculating the effective frequency spectrum of the data by using fast Fourier transform, storing the effective peak frequency and referring to the subsequent calculated frequency difference value.
Further, the obtaining the effective peak frequency includes:
and taking the maximum value of the frequency spectrum amplitude as a criterion of the effective peak value, judging the effective peak value when the amplitude is higher than a times of the maximum value, extracting a frequency value corresponding to the effective peak value, and storing the frequency value as an effective peak value frequency sequence.
The beneficial effect of adopting the further scheme is that: and the effective peak value condition is set, so that the effective frequency can be saved and the refinement can be continued.
Further, the judging whether the frequency spectrum refining is needed includes sequentially comparing the frequency difference sequence of the effective peak value with the value b times of the original frequency resolution, if the frequency difference values are all larger than or equal to the value b times of the original frequency resolution, the frequency spectrum refining is not needed, and the frequency spectrum result is directly stored;
and if the frequency difference values are all smaller than the value b times of the original frequency resolution, carrying out frequency spectrum refinement.
Wherein, the value range of b is as follows: 3 to 5.
The beneficial effect of adopting the further scheme is that: the frequency difference sequence of the effective peak value is compared with the original frequency to judge whether the frequency spectrum needs to be refined or not, and the process of frequency spectrum refinement which does not need to be refined is avoided. The value range of b is set to be 3-5 as the refining standard, so that the refining requirement is met, and waste caused by excessive refining is avoided.
Further, the determining the starting frequency of the spectrum refinement band comprises:
and when the frequency difference value is smaller than the value b times of the original frequency resolution for the first time, extracting an effective peak frequency point corresponding to the subtracted number from the difference value as the initial frequency of the first section of the frequency spectrum refining frequency band.
The beneficial effect of adopting the further scheme is that: and comparing the frequency difference value with the original b-fold value of the frequency resolution to judge whether the frequency spectrum still needs to be refined. Thereby limiting the initial range of the frequency of the spectrum refinement and reducing the process of spectrum refinement which is not necessarily refined.
Further, the determining the termination frequency of the spectrum refinement band comprises:
if the frequency difference scores are smaller than the value b times the original frequency resolution ratio until the last sequence number of the difference sequence, extracting the last effective peak frequency point as the termination frequency of the section of frequency spectrum refining frequency band; the data only has a segment of frequency band to be subjected to spectrum refinement;
and if the frequency difference score is larger than the value b times the original frequency resolution in the comparison process, extracting an effective peak frequency point corresponding to the subtracted number from the difference value as the termination frequency of the first section of frequency spectrum refining frequency band.
The beneficial effect of adopting the further scheme is that: and when the frequency difference scores are all greater than b times of the original frequency, stopping thinning, and limiting the thinning range so as to avoid unnecessary thinning. And the defect of easy omission of manual judgment is avoided by adopting an automatic judgment method.
Further, performing Chirp Z Transform (CZT) according to the following formula and storing the result;
wherein:
x (n), fs are respectively a list of data and sampling frequency of the normalized working condition;
fmin1,fmax1respectively refining the starting frequency and the ending frequency of the frequency band of the frequency spectrum;
R＝(fmax1-fmin1) The/delta f, the number of points of the frequency band CZT is refined by the frequency spectrum;
r is 0,1, R-1, and the serial number of the frequency spectrum refinement frequency band CZT;
Δ f, is the frequency resolution after spectral refinement.
The beneficial effect of adopting the further scheme is that: and thinning the frequency needing thinning by utilizing a linear Z conversion mode, so that the resolution is reduced, and the purpose of thinning is achieved.
In the invention, the technical schemes can be combined with each other to realize more preferable combination schemes. Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, wherein like reference numerals are used to designate like parts throughout.
FIG. 1 is a system block diagram of a method for refining the frequency spectrum of a vibration signal of an engineering vehicle according to the invention;
FIG. 2 is a diagram illustrating an exemplary efficient peak screening of a list of data in accordance with an embodiment of the present invention;
FIG. 3 is a partial enlarged view of an effective peak screening of a list of data according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating a refined frequency band determination for a list of data according to an embodiment of the present invention;
FIG. 5 is a diagram illustrating a spectrum refinement process for a list of data according to an embodiment of the present invention;
Detailed Description
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate preferred embodiments of the invention and together with the description, serve to explain the principles of the invention and not to limit the scope of the invention.
The invention discloses a method for refining the frequency spectrum of a vibration signal of an engineering vehicle, which specifically comprises the following steps:
Specifically, the signal amplification circuit is composed of a two-stage amplification circuit. And eliminating the influence of the zero output voltage on subsequent target amplification by using a second-order high-pass filter.
And 2, filtering the amplified signal to remove noise.
Specifically, a low-pass filter is used to filter out the high-frequency noise generated after amplification. After the signal is amplified by the required times, a lot of high-frequency noise is superposed, and the high-frequency noise needs to be filtered by adopting a low-pass filtering mode.
And 3, introducing the filtered signals into an MATLAB working area, and carrying out data regularization treatment on the filtered signals.
Preferably, the step 3 comprises the steps of:
step 301, the number of the filtered data collected by the sensors is M, wherein M is the number of the sensors, that is, the data vectors comprise M data vectors with different lengths, and the maximum value of the number of sampling points, that is, the maximum value of the length, is found and is marked as N;
step 302, performing zero padding processing on the rest M-1 data vectors to enable the length of each data vector to be N;
step 303, arranging the zero-padded vectors according to the first column, the second column and the M-th column … to form regularized data.
And zero padding is carried out on the data vectors with different lengths to form normalized data, and each data can be better subjected to subsequent processing. The maximum value data vector is selected as the optimal length standard, so that the validity of all data is protected, and the waste caused by setting the data length as a fixed value is prevented.
Step 4, according to the column dimension serial number of the normalized data, firstly calculating the frequency spectrum of the column data to obtain the effective peak frequency;
preferably, calculating the frequency spectrum of each column of data to obtain the effective peak frequency comprises:
step 401, performing Fast Fourier Transform (FFT) on the data, as shown in fig. 2, wherein fig. 3 is an enlarged view of fig. 2, and thus it can be seen that the frequency at the peak is much higher than the effective peak frequency, so that refinement processing is required;
step 402, taking an absolute value of a result of FFT to obtain a frequency spectrum amplitude;
and step 403, extracting the maximum value of the spectrum amplitude as a criterion of the effective peak value, determining the effective peak value when the amplitude is higher than a times of the maximum value, extracting a frequency value corresponding to the effective peak value, and storing the frequency value as an effective peak value frequency sequence.
Preferably, the value range of a is 0.1-0.2.
By finding the effective peak-to-peak frequency, the frequency is used as a reference value of the frequency spectrum needing to be refined. And reference is made for subsequent calculation of the frequency difference value. By utilizing fast Fourier transform, the effective frequency spectrum of the data is calculated, and the effective peak frequency is stored, so that the waste caused by all thinning can be avoided, and the efficiency is improved.
And 5, judging whether the line of data needs to be subjected to frequency spectrum thinning processing according to the frequency difference value of the adjacent effective peak values.
Specifically, if the result of the determination is that the frequency spectrum refinement processing needs to be performed, extracting the start frequency and the end frequency of the frequency band to be refined, performing the chirp Z transform, and storing the result to obtain a refined frequency spectrum of the corresponding frequency band, where the result is shown in fig. 5; and if the judgment result is that the frequency spectrum thinning processing is not needed, directly storing the frequency spectrum result.
Specifically, the step 5 includes the following steps:
step 501, calculating a frequency difference sequence of the effective peak frequency sequence;
step 502, sequentially comparing the frequency difference sequence of the effective peak value with the value b times of the original frequency resolution, if the frequency difference values are all larger than the value b times of the original frequency resolution, directly storing the frequency spectrum result without carrying out frequency spectrum refinement; otherwise step 503 is entered.
Preferably, b has a value in the range of 3 to 5.
Step 503, determining the starting frequency of the frequency spectrum refining frequency band;
when the frequency difference value is smaller than the value b times the original frequency resolution for the first time, extracting an effective peak frequency point corresponding to the subtracted number from the differential value as the initial frequency of the first section of the frequency spectrum refining frequency band, as shown in fig. 4, judging the differential value of the utilization frequency by the refining frequency band of the data;
step 504, determining the termination frequency of the frequency spectrum refining frequency band;
if the frequency difference scores are smaller than the value b times the original frequency resolution ratio until the last sequence number of the difference sequence, extracting the last effective peak frequency point as the termination frequency of the section of frequency spectrum refining frequency band; the data only has a segment of frequency band to be subjected to spectrum refinement;
if the frequency difference score is larger than the value b times of the original frequency resolution in the comparison process, extracting an effective peak frequency point corresponding to the subtracted number from the difference value as the termination frequency of the first section of frequency spectrum refining frequency band;
step 505, repeating steps 503 and 504, extracting the starting frequency and the terminating frequency of the next section of frequency spectrum refining frequency band until the last sequence number of the difference sequence and the frequency spectrum refining frequency band is judged to be finished;
step 506, aiming at each section of frequency spectrum refinement frequency band of each data in each normalized working condition, calculating the linear frequency modulation Z transformation (CZT) according to the following formula, and storing the result;
wherein:
x (n), fs are respectively a list of data and sampling frequency of the normalized working condition;
fmin1,fmax1respectively refining the starting frequency and the ending frequency of the frequency band of the frequency spectrum;
R＝(fmax1-fmin1) The/delta f, the number of points of the frequency band CZT is refined by the frequency spectrum;
r is 0,1, R-1, and the serial number of the frequency spectrum refinement frequency band CZT;
delta f is the frequency resolution after frequency spectrum refinement, and is generally set to be 10-20 times of the original resolution optionally;
step 507, continuing to step 506, calculating CZT of each section of frequency spectrum refining frequency band of each line of data in each sensor after normalization, and storing the result; and finishing the spectrum thinning processing until all frequency bands needing thinning of each column of data.
In step 5, the frequency difference sequence of the effective peak value is compared with the original frequency to judge whether the frequency spectrum needs to be thinned and limit the starting range and the ending range of the frequency spectrum thinned, so that an unnecessary thinning process is avoided. The frequency spectrum needing to be refined in the second section is refined and judged as the same as the frequency spectrum in the first section, and the automatic judgment method is used, so that the defect that manual judgment is easy to omit is overcome. And thinning the frequency needing thinning by utilizing a linear Z conversion mode, so that the resolution is reduced, and the thinning effect is achieved. And automatically processing the frequency band to be refined in the second section of the first working condition by using an automatic refining batch processing method.
Step 6, traversing each sensor, processing to obtain CZT of the frequency spectrum refining frequency band, and storing the result; and finishing the spectrum thinning processing until all frequency bands needing thinning are finished.
In summary, the embodiment of the invention provides a method for refining a frequency spectrum of a vibration signal of an engineering vehicle, which can solve the defects that the working condition of the engineering vehicle is often unstable and variable, and in the prior art, an artificial processing method is adopted, uncertain factors such as artificial errors exist, so that a frequency spectrum peak value is omitted, and the vibration control effect of the engineering vehicle is greatly reduced. The vibration signal data can be processed in batch and automatically.
Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program, which is stored in a computer readable storage medium, to instruct related hardware. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (6)
1. A method for refining the frequency spectrum of a vibration signal of an engineering vehicle is characterized by comprising the following steps:
installing a plurality of acceleration sensors in the engineering vehicle to acquire vibration signals; the acceleration sensors are respectively arranged on the left side of an axle of the engineering vehicle, the front center of a frame and the center of a cab floor;
preprocessing the acquired vibration signals, including signal amplification processing and filtering processing on the amplified acceleration sensor signals;
carrying out data regularization processing on the data signals filtered by each acceleration sensor to form regularized data;
calculating the frequency spectrum of each line of data according to the serial number of the column-direction dimension of the normalized data to obtain the effective peak frequency of the line of data;
calculating the frequency difference value of adjacent effective peaks in the data frequency spectrum, judging whether frequency spectrum refinement processing is needed, if so, extracting the initial frequency and the end frequency of the frequency band needing refinement processing, performing linear frequency modulation Z conversion, and storing the result to obtain a refined frequency spectrum of the corresponding frequency band; if not, directly storing the frequency spectrum result;
the judgment of whether the frequency spectrum refining is needed or not comprises the steps of sequentially comparing the frequency difference sequence of the effective peak value with the value b times of the original frequency resolution, and if the frequency difference values are all larger than or equal to the value b times of the original frequency resolution, directly storing the frequency spectrum result without frequency spectrum refining;
if the frequency difference values are all smaller than the value b times of the original frequency resolution, frequency spectrum refinement is required;
wherein, the value range of b is as follows: 3-5;
determining the starting frequency of the refinement processing band comprises:
when the frequency difference value is smaller than the value b times of the original frequency resolution for the first time, extracting an effective peak frequency point corresponding to the subtracted number from the difference value as the initial frequency of the first section of frequency spectrum refining frequency band;
determining the termination frequency of the refinement processing band comprises:
if the frequency difference scores are smaller than the value b times the original frequency resolution ratio until the last sequence number of the difference sequence, extracting the last effective peak frequency point as the termination frequency of the section of frequency spectrum refining frequency band; the data only has a segment of frequency band to be subjected to spectrum refinement; if the frequency difference score is larger than the value b times of the original frequency resolution in the comparison process, extracting an effective peak frequency point corresponding to the subtracted number from the difference value as the termination frequency of the first section of frequency spectrum refining frequency band;
traversing each line of data, processing to obtain CZT of the frequency spectrum refining frequency band, and storing a result; and finishing the spectrum thinning processing until all frequency bands needing thinning are finished.
2. The method for refining the frequency spectrum of the vibration signal of the engineering vehicle according to claim 1, wherein the signal preprocessing comprises:
the acquired vibration signals are amplified, and primary amplification, high-pass filtering and secondary amplification are sequentially carried out;
the filtering process removes noise from the amplified signal by using a low-pass filter.
3. The method for refining the frequency spectrum of the vibration signal of the engineering vehicle according to claim 1, wherein the step of performing data regularization processing on the data signal filtered by each acceleration sensor to form regularized data comprises the following steps:
the number of the data collected by the sensors after filtering is M, namely M data vectors with different lengths are contained, and M is the number of the sensors; finding the maximum value of the number of sampling points, namely the maximum value of the length, and recording the maximum value as N;
zero padding is carried out after the rest M-1 data vectors, so that the length of each data vector is N;
the zero-padded vectors are arranged in the first, second, and … th columns to form normalized data.
4. The method for refining the frequency spectrum of the vibration signal of the engineering vehicle according to claim 1, wherein the calculating the frequency spectrum of each column of data comprises:
performing fast Fourier transform on the column of data;
and taking an absolute value of the transformation result to obtain a frequency spectrum amplitude.
5. The method for refining the frequency spectrum of the vibration signal of the engineering vehicle according to claim 4, wherein the obtaining the effective peak frequency comprises:
and taking the maximum value of the frequency spectrum amplitude as a criterion of the effective peak value, judging the effective peak value when the amplitude is higher than a times of the maximum value, extracting a frequency value corresponding to the effective peak value, and storing the frequency value as an effective peak value frequency sequence.
6. The method for refining the frequency spectrum of the vibration signal of the engineering vehicle according to the claim 5, characterized in that, the Chirp Z Transform (CZT) is carried out according to the following formula, and the result is stored;
wherein:
x (n), fs are respectively a list of data and sampling frequency of the normalized working condition;
fmin1,fmax1respectively refining the starting frequency and the ending frequency of the frequency band of the frequency spectrum;
R＝(fmax1-fmin1) The/delta f, the number of points of the frequency band CZT is refined by the frequency spectrum;
r-1, which is the serial number of the frequency spectrum refinement frequency band CZT;
Δ f, is the frequency resolution after spectral refinement.
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| CN101251411A (en) * | 2008-03-14 | 2008-08-27 | 西安交通大学 | Apparatus for measuring impeller blade |
| CN104375111A (en) * | 2014-11-16 | 2015-02-25 | 甘肃省机械科学研究院 | Rapid high-precision refining correction method for intensive frequency spectrum |
| CN105334460A (en) * | 2015-11-27 | 2016-02-17 | 浙江大学城市学院 | Machine running state online monitoring analysis system based on noise and vibration analysis |
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| CN101251411A (en) * | 2008-03-14 | 2008-08-27 | 西安交通大学 | Apparatus for measuring impeller blade |
| CN104375111A (en) * | 2014-11-16 | 2015-02-25 | 甘肃省机械科学研究院 | Rapid high-precision refining correction method for intensive frequency spectrum |
| CN105334460A (en) * | 2015-11-27 | 2016-02-17 | 浙江大学城市学院 | Machine running state online monitoring analysis system based on noise and vibration analysis |
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