CN117490834A - Vibration spectrum peak value capturing method - Google Patents
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Abstract
The invention relates to a vibration spectrum peak capturing method, which comprises the steps of performing fast Fourier transform on time domain data acquired by a sensor to obtain frequency domain data, acquiring a change trend and an extreme point of a curve through first-order difference for an input spectrum data sequence, finding an inflection point of a smooth curve through second-order difference, searching data representing the inflection point in normalized second-order difference to obtain the position of the inflection point, and determining the peak value in original sampling data through local neighborhood search. By adopting the normalized second-order difference and sequencing algorithm, more accurate vibration spectrum peak value capture can be realized, complex curve fitting is not needed, and the peak value drift problem caused by smoothing and fitting is solved; the method can be used in weak peak identification environments, has strong universality and provides basis for state monitoring and subsequent vibration analysis; the threshold value required to be set is few, and the peak value capturing result is accurate. The peak value capturing algorithm greatly reduces the pressure of a transmission link and effectively reduces the power consumption of wireless transmission.
Description
Technical Field
The invention relates to a signal processing technology, in particular to a vibration spectrum peak value capturing method.
Background
Peak capture has a wide range of applications in signal processing, edge detection, digital image processing, object recognition, automatic control, and the like. In the vibration field, the peak value of vibration noise is an important index. The first derivative of the peak at the peak point is zero, which is also the local maximum point, and many ineffective interference peaks appear on the frequency spectrum due to various noise interference in actual measurement.
At present, the method for capturing the peak value at home and abroad mainly comprises the following steps:
1. peak capture algorithm based on smooth and piecewise curve fitting;
2. a peak capture algorithm based on a full-time relative threshold;
3. a peak value capturing algorithm based on filtering denoising;
the method comprises the steps of smoothing data firstly, performing segmentation curve fitting on the data based on a peak value capturing algorithm of smoothing and segmentation curve fitting, and optimizing a search algorithm by setting a series of threshold values such as an amplitude threshold value.
The peak value capturing algorithm based on the full-time state relative threshold value utilizes time information to determine the number of peak values, utilizes the relative threshold value method to remove interference fluctuation, and further improves judgment accuracy through the pulse width range and the peak-to-peak interval.
And selecting characteristic points to obtain data with obvious characteristics based on a filtering and iterative peak capturing algorithm, removing noise through the filtering and iterative algorithm, and capturing peak coordinates to two sides of a peak.
However, the above methods for peak capture have drawbacks, mainly including the following:
(1) Too many interference peaks and poor curve fitting effect, proper window selection for data is needed to carry out smoothing pretreatment, and the smoothing treatment and fitting can lead to wave crest drift.
(2) A series of tedious steps for determining various thresholds are required, the algorithm is complex, and the universality is not high.
(3) Filtering and iteration introduce errors in peak position, height, width.
Disclosure of Invention
Aiming at the problem that the precision of the curve fitting search spectrum peak value is not high, the vibration spectrum peak value capturing method is provided, complex curve fitting and threshold value determination are not needed, and meanwhile, the problem of peak value drift caused by smoothing processing and fitting is solved.
The technical scheme of the invention is as follows: a vibration spectrum peak capturing method includes the steps that fast Fourier transformation is conducted on time domain data collected by a sensor to obtain frequency domain data, variation trend and extreme points of a curve are obtained through first-order difference for an input spectrum data sequence, inflection points of a smooth curve are found through second-order difference, data representing the inflection points in normalized second-order difference are searched for, the position of the inflection points is obtained, and then the peak value in original sampling data is determined through local neighborhood search.
Further, the vibration spectrum peak value capturing method specifically comprises the following steps:
performing fast fourier transform on time domain data { T0, & gt, T i, & gt, T n } acquired by a sensor to obtain frequency domain data { S0, & gt, S i, & gt, S n ] };
step two, carrying out normalization first-order difference processing on an input frequency spectrum data sequence { S [0],. The S [ n ] }, wherein a normalization first-order difference formula is as follows:
diff [ i ] = sign (S [ i+1] -S [ i ]), sign (·) is a sign function;
step three, performing differential processing again on the normalized first-order differential sequence { Diff [0],. The first-order differential sequence, & gt, diff [ i ], & gt, diff [ n-1] }: diff2[ i ] =Diff [ i+1] -Diff [ i ], obtain the correspondent second order difference value Diff2[ i ], through comparing Diff2[ i ] =Diff [ i+1] -Diff [ i ], when the correspondent value of Diff2[ i ] is-2, namely demonstrate that has caught a peak value;
step four, setting parameters, determining the search neighborhood length h, and indexing index at the kth peak point k Correcting the position of the true peak value in the interval of the front and rear h/2 of the range, and maximizing the position in the adjacent rangeThe value is taken as the true peak point: index k=k, S [ k ]]＝max{S[k-h/2],S[k+h/]}；
Step five: an amplitude threshold is set, noise interference is eliminated, effective peaks are identified,
traversing the whole sequence, finally capturing indexes and values of all effective peaks.
Further, in the second step
The expression of the sign function is:
by comparing the values of S [ i+1] and S [ i ], if S [ i+1] is greater than S [ i ], the corresponding differential value Diff [ i ] is set to 1; if S [ i+1] is equal to S [ i ], setting the corresponding differential value Diff [ i ] to 0; if the value of S [ i+1] is smaller than S [ i ], the corresponding difference value of Diff [ i ] is set to-1, wherein Diff [ i ] represents the gradient between S [ i+1] and S [ i ], and 1, 0 and-1 are used for replacing the gradient in the rising, unchanged and descending trends of the gradient respectively.
Further, the index is indexed at the kth peak point k The position of the true peak is corrected in the interval of the front and rear h/2: and searching the maximum value in a small range before and after the peak coordinate according to the captured peak coordinate as the center, wherein the searching range can be set according to the signal sampling frequency, and the possible drift is corrected by utilizing local neighborhood searching.
A vibration spectrum peak value capturing device for wireless communication comprises an MEMS vibration accelerometer, an analog signal conditioning circuit, an MCU main control module and a wireless transmission module;
and after the acceleration signals are collected by the MEMS vibration accelerometer and are sent to the analog signal conditioning circuit for processing, the acceleration signals are sent to the MCU main control module, spectrum calculation and peak value capturing are completed in the MCU main control module according to a vibration spectrum peak value capturing method, and the captured peak value is sent to the outside through the wireless sending module.
Preferably, the analog signal conditioning circuit comprises a signal filtering and amplifying circuit and an AD conversion circuit, wherein the signal filtering and amplifying circuit isolates the interference of a low-frequency signal on an acceleration signal in an RC filtering mode, and then performs gain adjustment on the analog signal through an operational amplifier so as to reach the full range of the AD chip and improve the dynamic range of monitoring the whole vibration signal;
the AD conversion circuit selects an ADC chip of AD7606-4, and the AD7606-4 is a 16-bit synchronous sampling analog-digital conversion data acquisition system of 4 channels.
The invention has the beneficial effects that: according to the vibration spectrum peak value capturing method, a normalization second-order difference and sequencing-based algorithm is adopted, so that more accurate vibration spectrum peak value capturing can be realized, complex curve fitting is not needed, and the peak value drift problem caused by smoothing and fitting is solved; the method has the advantages of high peak capture precision, high recognition capability and recognition accuracy for weak peaks, high universality and basis for state monitoring and subsequent vibration analysis, and can be used in weak peak recognition environments; the processing flow of the core algorithm is simple, the threshold value to be set is few, programming is convenient to realize, and the peak value capturing result is accurate. The structure is simple, the robustness is strong, and the cost is lower; the pressure of a transmission link is greatly reduced through a peak value capturing algorithm, the power consumption of wireless transmission is effectively reduced, and the stability and the service life of the whole device are improved.
Drawings
FIG. 1 is a schematic diagram of a vibration spectrum peak capturing method of the present invention;
FIG. 2 is a chart of a fast Fourier transformed spectrum of an embodiment of the present invention;
FIG. 3 is a graph of a normalized second order difference spectrum of an embodiment of the present invention;
FIG. 4 is a graph of peak capture results for an embodiment of the present invention;
FIG. 5 is a block diagram of analog signal acquisition in accordance with an embodiment of the present invention;
FIG. 6 is a functional block diagram of a peak capture device according to an embodiment of the present invention.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
The method for capturing the peak value of the vibration spectrum, as shown in fig. 1, specifically comprises the following steps:
step one, performing fast Fourier transform on time domain data { T0, & gt, T i, & gt, T n } acquired by the sensor, frequency domain data { S [0],., S [ i ],., S [ n ] }, and the frequency domain signal after the fast fourier transform is shown in fig. 2.
Step two, carrying out normalization first-order difference processing on an input frequency spectrum data sequence { S [0],. The S [ n ] }, wherein a normalization first-order difference formula is as follows:
diff [ i ] = sign (S [ i+1] -S [ i ]), sign (·) is a sign function;
step three, performing differential processing again on the normalized first-order differential sequence { Diff [0],. The first-order differential sequence, & gt, diff [ i ], & gt, diff [ n-1] }: diff2[ i ] = Diff [ i+1] -Diff [ i ], a corresponding second-order differential value Diff2[ i ] is obtained, and when the corresponding value of Diff2[ i ] is-2, a peak value is captured by comparing Diff2[ i ] = Diff [ i+1] -Diff [ i ]. The normalized second order differential spectral data is shown in fig. 3.
Step four, setting parameters, determining the search neighborhood length h, and indexing index at the kth peak point k Correcting the position of a real peak value in the interval of the front h/2 and the rear h/2, and taking the maximum value in the neighborhood as a real peak value point: index k=k, S [ k ]]＝max{S[k-h/2],S[k+h/]}；
Step five: setting an amplitude threshold: ordering all captured peak points, customizing threshold value used as effective peak value identification threshold value according to actual physical meaning reflected by spectrum data,
the entire sequence is traversed and eventually the index and value of all valid peaks are captured, as shown in fig. 4.
And for an input spectrum data sequence, acquiring the change trend and the extreme point of the curve through the first-order difference, finding the inflection point of the smooth curve through the second-order difference, searching the data representing the inflection point in the normalized second-order difference to obtain the position of the inflection point, and determining the peak value in the original sampling data through local neighborhood search.
The purpose of normalization is to remove other features than the trend of spectral slope change to simplify processing logic. The principle of the normalized forward first order difference is to conduct difference on vibration spectrum data to obtain corresponding first order difference values, take a sign function on a difference vector, and replace slopes in the rising, unchanged and descending trends of the slopes with 1, 0 and-1 respectively.
The expression of the sign function is
By comparing the values of S [ i+1] and S [ i ], if S [ i+1] is greater than S [ i ], the corresponding differential value Diff [ i ] is set to 1; if S [ i+1] is equal to S [ i ], setting the corresponding differential value Diff [ i ] to 0; if S [ i+1] is less than S [ i ], the corresponding differential value Diff [ i ] is set to-1. Diff [ i ] represents the gradient between S [ i+1] and S [ i ].
The principle of the normalized second-order difference is to conduct difference on the data after the first-order difference to obtain a corresponding second-order difference value Diff2[ i ]. By comparing Diff2[ i ] =diff [ i+1] -Diff [ i ], when the corresponding value of Diff2[ i ] is-2, it is indicated that a peak is captured.
And correcting possible drift by utilizing local neighborhood search, searching for the maximum value in a small range before and after the peak coordinate according to the captured peak coordinate as the center, wherein the searching range can be set according to the signal sampling frequency, and taking the maximum value in the neighborhood as a real peak point.
To exclude noise interference, an amplitude threshold may be set according to a ranking algorithm, and the captured peaks may be compared to the threshold. When the peak value is greater than or equal to the threshold value, determining the peak value as a valid peak value; when the peak value is less than the threshold value, it is determined as an invalid peak value and discarded.
The normalization method is combined with the second-order differential algorithm, the change trend and inflection point of the spectrum data are acquired first, the peak point can be effectively captured, and the problem that the model precision is not high due to filtering and fitting is solved; and then, a local neighborhood search algorithm and an amplitude threshold method are used, so that the method has the advantages of low computational complexity, strong robustness, simplicity in implementation and the like.
The peak value capturing algorithm can extract a large amount of acquired spectrum data into a small amount of required peak value points through peak value searching, so that the pressure of data transmission and sending is greatly reduced, and the method is particularly suitable for small-sized, low-power consumption or a series of wireless communication equipment. Therefore, the vibration spectrum peak value capturing device for wireless communication is designed. The device comprises an MEMS vibration accelerometer, an analog signal conditioning circuit, a power management module, an MCU main control module and a wireless transmission module.
The analog signal conditioning circuit mainly comprises a signal filtering and amplifying circuit and an AD conversion circuit, wherein the filtering and amplifying circuit mainly aims at an acceleration signal, the acceleration signal is required to be isolated from interference of low-frequency signals in an RC filtering mode, and then gain adjustment is carried out on the analog signal through an operational amplifier so as to reach the full range of the AD chip and improve the dynamic range of monitoring the whole vibration signal. A block diagram of analog signal acquisition is shown in fig. 5.
And integrating acquisition requirements of triaxial vibration signals, and selecting an ADC chip of AD 7606-4. AD7606-4 is a 16-bit synchronous sampling analog-digital conversion data acquisition system with 4 channels. The module comprises an analog input clamping protection, a second-order anti-aliasing analog filter, a sample-and-hold amplifier, a 16-bit charge redistribution successive approximation analog-to-digital converter (ADC), a flexible digital filter, a 2.5V reference voltage source, a reference buffer region and a high-speed serial and parallel interface.
The main power supply of the device is provided by a battery, 5V power supply is converted into 3.3V digital power supply and 3V analog power supply through a DC-DC power management chip, an LDO power supply management chip and the like, and the digital power supply and the analog power supply are respectively provided with power supply for a digital device and an analog device, so that the influence of pulse interference voltage on a digital circuit on analog signals in the analog circuit can be avoided. The power supply circuit is added with a power supply filtering and overvoltage protection design, so that the power supply noise interference can be reduced, and the damage to the circuit caused by overvoltage and overcurrent is prevented.
In the device, voltage signals acquired by the MEMS accelerometer are input into the AD7606 through a signal conditioning circuit, spectrum calculation and the first 20 peak values are captured in the MCU main control module, and the captured peak values are transmitted to the outside through the wireless module. The overall function of the peak capture device is shown in fig. 6.
The above examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (6)
1. A vibration spectrum peak capturing method is characterized in that time domain data acquired by a sensor are subjected to fast Fourier transform to obtain frequency domain data, for an input spectrum data sequence, a change trend and an extreme point of a curve are acquired through first-order difference, a second-order difference finds out an inflection point of a smooth curve, data representing the inflection point in normalized second-order difference is searched for to obtain the position of the inflection point, and then a peak value in original sampling data is determined through local neighborhood search.
2. The method for capturing peaks of vibration spectrum according to claim 1, comprising the steps of:
performing fast fourier transform on time domain data { T0, & gt, T i, & gt, T n } acquired by a sensor to obtain frequency domain data { S0, & gt, S i, & gt, S n ] };
step two, carrying out normalization first-order difference processing on an input frequency spectrum data sequence { S [0],. The S [ n ] }, wherein a normalization first-order difference formula is as follows:
diff [ i ] = sign (S [ i+1] -S [ i ]), sign (·) is a sign function;
step three, performing differential processing again on the normalized first-order differential sequence { Diff [0],. The first-order differential sequence, & gt, diff [ i ], & gt, diff [ n-1] }: diff2[ i ] =Diff [ i+1] -Diff [ i ], obtain the correspondent second order difference value Diff2[ i ], through comparing Diff2[ i ] =Diff [ i+1] -Diff [ i ], when the correspondent value of Diff2[ i ] is-2, namely demonstrate that has caught a peak value;
step four, setting parameters, determining the search neighborhood length h, and indexing index at the kth peak point k Correcting the position of a real peak value in the interval of the front h/2 and the rear h/2, and taking the maximum value in the neighborhood as a real peak value point: index k=k, S [ k ]]＝max{S[k-h/2],S[k+h/]}；
Step five: an amplitude threshold is set, noise interference is eliminated, effective peaks are identified,
traversing the whole sequence, finally capturing indexes and values of all effective peaks.
3. The method of claim 2, wherein the sign function in the second step has the expression:
by comparing the values of S [ i+1] and S [ i ], if S [ i+1] is greater than S [ i ], the corresponding differential value Diff [ i ] is set to 1; if S [ i+1] is equal to S [ i ], setting the corresponding differential value Diff [ i ] to 0; if the value of S [ i+1] is smaller than S [ i ], the corresponding difference value of Diff [ i ] is set to-1, wherein Diff [ i ] represents the gradient between S [ i+1] and S [ i ], and 1, 0 and-1 are used for replacing the gradient in the rising, unchanged and descending trends of the gradient respectively.
4. The method of claim 2, wherein index is indexed at a kth peak point k The position of the true peak is corrected in the interval of the front and rear h/2: according to the captured peak coordinatesAnd (3) searching the maximum value in a small range before and after the peak coordinate, wherein the searching range can be set according to the signal sampling frequency, and the local neighborhood search is utilized to correct the possible drift.
5. The vibration spectrum peak value capturing device for wireless communication is characterized by comprising an MEMS vibration accelerometer, an analog signal conditioning circuit, an MCU main control module and a wireless transmission module;
and after the acceleration signals are collected by the MEMS vibration accelerometer and are sent to the analog signal conditioning circuit for processing, the acceleration signals are sent to the MCU main control module, spectrum calculation and peak value capturing are completed in the MCU main control module according to a vibration spectrum peak value capturing method, and the captured peak value is sent to the outside through the wireless sending module.
6. The vibration spectrum peak capturing device of wireless communication according to claim 5, wherein the analog signal conditioning circuit comprises a signal filtering and amplifying circuit and an AD conversion circuit, the signal filtering and amplifying circuit isolates the interference of the low-frequency signal to the acceleration signal by an RC filtering mode, and then performs gain adjustment to the analog signal by an operational amplifier so as to reach the full range of the AD chip and improve the dynamic range of monitoring the whole vibration signal;
the AD conversion circuit selects an ADC chip of AD7606-4, and the AD7606-4 is a 16-bit synchronous sampling analog-digital conversion data acquisition system of 4 channels.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN118009914A (en) * | 2024-04-08 | 2024-05-10 | 上海中医药大学附属岳阳中西医结合医院 | Infrared spectrum-based intelligent moxibustion robot part temperature deformation monitoring method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN118314673A (en) * | 2024-04-07 | 2024-07-09 | 河南唐都科技有限公司 | Intelligent fire disaster early warning method and system based on internet data |
| CN118009914A (en) * | 2024-04-08 | 2024-05-10 | 上海中医药大学附属岳阳中西医结合医院 | Infrared spectrum-based intelligent moxibustion robot part temperature deformation monitoring method |
| CN118009914B (en) * | 2024-04-08 | 2024-06-11 | 上海中医药大学附属岳阳中西医结合医院 | Infrared spectrum-based intelligent moxibustion robot part temperature deformation monitoring method |
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