CN111476207A - Target frequency band signal accurate extraction method based on proportional interpolation method - Google Patents

Target frequency band signal accurate extraction method based on proportional interpolation method Download PDF

Info

Publication number
CN111476207A
CN111476207A CN202010383628.XA CN202010383628A CN111476207A CN 111476207 A CN111476207 A CN 111476207A CN 202010383628 A CN202010383628 A CN 202010383628A CN 111476207 A CN111476207 A CN 111476207A
Authority
CN
China
Prior art keywords
frequency band
target frequency
signal
target
original vibration
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202010383628.XA
Other languages
Chinese (zh)
Other versions
CN111476207B (en
Inventor
王琇峰
李睿
金帅普
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xian Jiaotong University
Original Assignee
Xian Jiaotong University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Xian Jiaotong University filed Critical Xian Jiaotong University
Priority to CN202010383628.XA priority Critical patent/CN111476207B/en
Publication of CN111476207A publication Critical patent/CN111476207A/en
Application granted granted Critical
Publication of CN111476207B publication Critical patent/CN111476207B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/12—Classification; Matching
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/02—Preprocessing

Abstract

A target frequency band signal accurate extraction method based on a proportional interpolation method comprises the steps of filtering a target frequency band to obtain an original vibration signal target frequency band signal component; setting an amplitude threshold value for the full-band frequency spectrum of the original vibration signal, solving a frequency and a vibration amplitude value corresponding to a maximum value point of which the amplitude is greater than the threshold value in the frequency spectrum; calculating the average number and the median number of frequency amplitudes corresponding to the maximum value points, screening out frequencies with amplitudes larger than or corresponding to the frequency amplitudes, carrying out proportional interpolation spectrum correction on each component in a full frequency band, and reconstructing components positioned in a target frequency band and out of the target frequency band; calculating the frequency spectrum leakage amount of the reconstructed frequency components, compensating the filtering result of the original vibration signal, and performing vector operation on the original vibration signal by using the frequency spectrum leakage amount inside and outside a target frequency band to obtain a target frequency band signal without the influence of an end point effect; the invention can effectively inhibit the endpoint effect after filtering.

Description

Target frequency band signal accurate extraction method based on proportional interpolation method
Technical Field
The invention belongs to the field of mechanical equipment diagnosis, and particularly relates to a target frequency band signal accurate extraction method based on a proportional interpolation method.
Background
In the field of fault diagnosis of mechanical equipment, vibration signals are often used for evaluating the operating state of the equipment. Due to differences in device structures, fault components and types, and different frequency bands of fault features of different devices, a specific frequency band of a vibration signal is often extracted and analyzed according to actual analysis conditions. Filtering is a more common target frequency band extraction method, however, if the leakage problem of the target frequency band is ignored, filtering processing is directly performed on the target frequency band, which easily causes endpoint effect of the filtered signal time domain signal, distortion of time domain characteristics, and misjudgment. Therefore, the method for compensating the spectral leakage of the target frequency band is important for accurately extracting the time domain characteristics of the signal target frequency band.
The frequency spectrum leakage is caused by the fact that the signal interception duration does not meet the whole period of a signal, so that deviation is generated when the time domain of the signal is extended, signal energy dispersion is shown in the result of signal frequency spectrum analysis, and the frequency, amplitude and phase information of the corresponding signal are deviated. Because the frequency components in the actual measurement signal are complex, the sampling duration of the signal often cannot satisfy the periods of all the signal components at the same time, and therefore the frequency components with frequency spectrum leakage inevitably exist in the actual measurement signal. If the signal in the target frequency band is directly extracted through filtering, the extracted signal component is necessarily influenced by the frequency spectrum leakage inside and outside the target frequency band, and the end point effect occurs in the time domain characteristic of the signal.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, an object of the present invention is to provide a method for accurately extracting a target frequency band signal based on a proportional interpolation method, wherein main frequency components causing an end-point effect are screened in the entire frequency band of a measured signal, frequency spectrum correction and reconstruction are performed on the frequency components, a frequency spectrum leakage amount of the frequency components is calculated, and a result of filtering the measured signal is compensated by the leakage amount, so as to effectively suppress the end-point effect after filtering.
In order to achieve the purpose, the invention adopts the technical scheme that:
a target frequency band signal accurate extraction method based on a proportional interpolation method comprises the following steps:
1) acquiring an original vibration signal of equipment, carrying out spectrum analysis on the original vibration signal, and filtering a target frequency band to obtain an original vibration signalSignal component of target frequency band, denoted as fori；
2) Setting an amplitude threshold a for the full-band frequency spectrum of the original vibration signal, marking the maximum value points of which the amplitudes are greater than the threshold a in the frequency spectrum as frequency components with larger leakage amount in the original vibration signal, and solving the frequencies and the vibration amplitudes corresponding to the maximum value points;
3) calculating the average number a of the frequency amplitude values corresponding to the maximum value points in the step 2)aveAnd a median amidScreening out amplitude value greater than aaveOr amidCorresponding frequency, denoted as fiWhere i is 1,2,3, … i0(ii) a For each f in the full frequency bandiThe components are subjected to proportional interpolation spectrum correction, and according to the spectrum correction results, f in the target frequency band and f out of the target frequency band are respectively correctediThe components are reconstructed, and the frequency components obtained by reconstruction are recorded as
Figure BDA0002483026590000021
Wherein k is 1,2,3, …, k0，p＝1,2,3,…,p0And satisfy k0+p0＝i0；
4) Calculating the frequency spectrum leakage amount of the reconstructed frequency component, and solving the reconstructed signal in the target frequency band by using cut-off filtering
Figure BDA0002483026590000022
Spectral leakage amount outside target frequency band and signal reconstructed outside target frequency band
Figure BDA0002483026590000023
The amounts of leakage into the target band are respectively referred to as
Figure BDA0002483026590000024
5) Compensating the filtering result of the original vibration signal, and calculating the frequency spectrum leakage quantity inside and outside the target frequency band by using the step 4)
Figure BDA0002483026590000031
Cutting off and filtering the target frequency band of the original vibration signal in the step 1)To get foriAnd carrying out vector operation to obtain a target frequency band signal without the influence of the endpoint effect, wherein the calculation formula is as follows:
Figure BDA0002483026590000032
wherein f isaimRepresenting vibration signals in the target frequency band without influence of end-point effects, foriDirectly filters the intercepted target frequency band signal representing the original signal,
Figure BDA0002483026590000033
representing the amount of spectral leakage of signals in the target frequency band outside the target frequency band,
Figure BDA0002483026590000034
representing the amount of spectral leakage of signals outside the target frequency band into the target frequency band.
The amplitude threshold value a in the step 2) is 0.01.
The invention has the beneficial effects that:
the invention eliminates the end effect generated when the target signal is cut off and filtered, and accurately calculates the frequency spectrum leakage amount introduced in the filtering and extracting process of the target frequency band signal by a proportional interpolation method in frequency spectrum correction, thereby compensating and eliminating the end effect generated by the signal target frequency band filtering.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is a time domain diagram and a frequency domain diagram of an original vibration signal according to an embodiment.
FIG. 3 is a time domain diagram and a frequency domain diagram of signal components in a target frequency band of an original vibration signal according to an embodiment.
Fig. 4 is a time domain diagram of the amount of leakage of signal components in the target frequency band to the spectrum outside the target frequency band and a partially enlarged diagram thereof according to the embodiment.
FIG. 5 is a time domain diagram of the amount of spectral leakage of signal components outside the target frequency band into the target frequency band and a partially enlarged view thereof according to an embodiment.
FIG. 6 is a time domain diagram and a frequency domain diagram of the components in the target frequency band of the vibration signal after the end-point effect is removed according to the embodiment.
Detailed Description
The present invention will be described in further detail with reference to the following drawings and examples.
As shown in fig. 1, a method for accurately extracting a target frequency band signal based on a scale interpolation method includes the following steps:
step 1: the original vibration signal of the equipment is collected through the vibration acceleration sensor, the sampling frequency is 20000Hz, the time domain graph and the frequency domain graph of the collected original vibration signal are shown in figure 2, and the frequency spectrum graph of figure 2 shows that the vibration amplitude of the equipment at 100Hz is higher, so the selected target frequency band is 99.5Hz to 101 Hz. Filtering out the frequency components in the target frequency band of the original vibration signal by cut-off filtering, and recording the frequency components as foriThe time domain graph and the frequency domain graph of the signal in the intercepted target frequency band are shown in fig. 3, and it can be seen from the time domain graph in fig. 3 that the end point effect is caused by performing the cut-off filtering on the target frequency band of the original vibration signal, and the time domain signal obtained by the cut-off filtering has the obvious amplitude distortion phenomenon at the two ends of the time domain graph;
step 2: setting an amplitude threshold value a of 0.01 for the original vibration signal in a full frequency band, screening all maximum value points of which the amplitudes are greater than the threshold value a in a frequency spectrum, marking the maximum value points as frequency components with larger leakage amount in the original vibration signal, and solving the frequency and the vibration amplitude corresponding to the maximum value points;
and step 3: calculating the average number a of the frequency amplitude values corresponding to the maximum point in the step 2aveAnd a median amidScreening out amplitude value greater than aaveOr amidCorresponding frequency, denoted as fiWhere i is 1,2,3, … i0(ii) a For each f in the full frequency bandiThe components are subjected to proportional interpolation spectrum correction, and according to the spectrum correction results, f in the target frequency band and f out of the target frequency band are respectively correctediThe components are reconstructed, and the frequency components obtained by reconstruction are recorded as
Figure BDA0002483026590000051
Wherein k is 1,2,3, …, k0，p＝1,2,3,…,p0And satisfy k0+p0＝i0；
And 4, step 4: calculating the frequency spectrum leakage amount of the reconstructed frequency component, and solving the reconstructed signal in the target frequency band by using cut-off filtering
Figure BDA0002483026590000052
Spectral leakage amount outside target frequency band and signal reconstructed outside target frequency band
Figure BDA0002483026590000053
The amounts of leakage into the target band are respectively referred to as
Figure BDA0002483026590000054
As shown in fig. 4 and 5, it can be seen from fig. 4 and 5 that vibration signal components inside and outside the target frequency band have obvious spectrum leakage characteristics, and appear as amplitude distortions at both ends of the time domain diagram of the signal components in the time domain;
step 6: compensating the result of the cut-off filtering of the original vibration signal, and calculating the frequency spectrum leakage quantity inside and outside the target frequency band by using the step 4)
Figure BDA0002483026590000055
F obtained by cutting and filtering the target frequency band of the original vibration signal in the step 1)oriAnd carrying out vector operation to obtain a target frequency band signal without the influence of the endpoint effect, wherein the calculation formula is as follows:
Figure BDA0002483026590000056
wherein f isaimRepresenting the target band signal without the influence of the end-point effect, foriDirectly filters the intercepted target frequency band signal representing the original signal,
Figure BDA0002483026590000057
representing the amount of spectral leakage of signals in the target frequency band outside the target frequency band,
Figure BDA0002483026590000058
representing spectral leakage of signals outside the target frequency band into the target frequency bandAn amount;
the time domain diagram and the frequency domain diagram of the obtained signal are shown in fig. 6, and it can be seen from fig. 6 that after the original vibration signal is compensated by the cut-off filtering, the amplitude distortion phenomenon does not exist at the two ends of the time domain diagram of the obtained vibration signal of the target frequency band, and the end effect caused by the cut-off filtering of the vibration signal is eliminated.

Claims (2)

1. A target frequency band signal accurate extraction method based on a proportional interpolation method is characterized by comprising the following steps:
1) acquiring an original vibration acceleration signal of equipment, performing spectrum analysis on the original vibration signal, performing cut-off filtering on a target frequency band to obtain a target frequency band signal component of the original vibration signal, and recording the target frequency band signal component as fori；
2) Setting an amplitude threshold a for the full-band frequency spectrum of the original vibration signal, marking the maximum value points of which the amplitudes are greater than the threshold a in the frequency spectrum as frequency components with larger leakage amount in the original vibration signal, and solving the frequencies and the vibration amplitudes corresponding to the maximum value points;
3) calculating the average number a of the frequency amplitude values corresponding to the maximum value points in the step 2)aveAnd a median amidScreening out amplitude value greater than aaveOr amidCorresponding frequency, denoted as fiWhere i is 1,2,3, … i0(ii) a For each f in the full frequency bandiThe components are subjected to proportional interpolation spectrum correction, and according to the spectrum correction results, f in the target frequency band and f out of the target frequency band are respectively correctediThe components are reconstructed, and the frequency components obtained by reconstruction are recorded as
Figure FDA0002483026580000011
Wherein k is 1,2,3, …, k0，p＝1,2,3,…,p0And satisfy k0+p0＝i0；
4) Calculating the frequency spectrum leakage amount of the reconstructed frequency component, and solving the reconstructed signal in the target frequency band by using cut-off filtering
Figure FDA0002483026580000012
Spectral leakage amount outside target frequency band and signal reconstructed outside target frequency band
Figure FDA0002483026580000013
The amounts of leakage into the target band are respectively referred to as
Figure FDA0002483026580000014
5) Compensating the result of the cut-off filtering of the original vibration signal, and calculating the frequency spectrum leakage quantity inside and outside the target frequency band by using the step 4)
Figure FDA0002483026580000015
F obtained by cutting and filtering the target frequency band of the original vibration signal in the step 1)oriAnd carrying out vector operation to obtain a target frequency band signal without the influence of the endpoint effect, wherein the calculation formula is as follows:
Figure FDA0002483026580000021
wherein f isaimRepresenting the target band signal without the influence of the end-point effect, foriDirectly filters the intercepted target frequency band signal representing the original signal,
Figure FDA0002483026580000022
representing the amount of spectral leakage of signals in the target frequency band outside the target frequency band,
Figure FDA0002483026580000023
representing the amount of spectral leakage of signals outside the target frequency band into the target frequency band.
2. The method for accurately extracting the target frequency band signal based on the scale interpolation method as claimed in claim 1, wherein: the amplitude threshold value a in the step 2) is 0.01.
CN202010383628.XA 2020-05-08 2020-05-08 Target frequency band signal accurate extraction method based on proportional interpolation method Active CN111476207B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010383628.XA CN111476207B (en) 2020-05-08 2020-05-08 Target frequency band signal accurate extraction method based on proportional interpolation method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010383628.XA CN111476207B (en) 2020-05-08 2020-05-08 Target frequency band signal accurate extraction method based on proportional interpolation method

Publications (2)

Publication Number Publication Date
CN111476207A true CN111476207A (en) 2020-07-31
CN111476207B CN111476207B (en) 2022-08-05

Family

ID=71763003

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010383628.XA Active CN111476207B (en) 2020-05-08 2020-05-08 Target frequency band signal accurate extraction method based on proportional interpolation method

Country Status (1)

Country Link
CN (1) CN111476207B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115265691A (en) * 2022-09-26 2022-11-01 中国空气动力研究与发展中心设备设计与测试技术研究所 Coriolis flowmeter vibration frequency tracking method and system

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150180689A1 (en) * 2013-12-20 2015-06-25 King Fahd University Of Petroleum And Minerals Cognitive radio spectrum sensing with improved edge detection of frequency bands
CN108764073A (en) * 2018-05-14 2018-11-06 华南理工大学 A kind of acceleration filter of combination spectrum energy form fitting is made an uproar and integration method
CN109030001A (en) * 2018-10-08 2018-12-18 电子科技大学 A kind of Fault Diagnosis of Roller Bearings based on improvement HHT
CN109856455A (en) * 2018-12-15 2019-06-07 中国人民解放军陆军勤务学院 A kind of reality answers change type deamplification method for parameter estimation

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150180689A1 (en) * 2013-12-20 2015-06-25 King Fahd University Of Petroleum And Minerals Cognitive radio spectrum sensing with improved edge detection of frequency bands
CN108764073A (en) * 2018-05-14 2018-11-06 华南理工大学 A kind of acceleration filter of combination spectrum energy form fitting is made an uproar and integration method
CN109030001A (en) * 2018-10-08 2018-12-18 电子科技大学 A kind of Fault Diagnosis of Roller Bearings based on improvement HHT
CN109856455A (en) * 2018-12-15 2019-06-07 中国人民解放军陆军勤务学院 A kind of reality answers change type deamplification method for parameter estimation

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
ZHIQIANG LIAO，AND ETC: "A Vibration Signal Filtering Method Based on KL Divergence Genetic Algorithm – with Application to Low Speed Bearing Fault Diagnosis", 《2018 IEEE 23RD INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP)》 *
张建伟等: "一种适用于泄流结构振动分析的信号降噪方法", 《振动与冲击》 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115265691A (en) * 2022-09-26 2022-11-01 中国空气动力研究与发展中心设备设计与测试技术研究所 Coriolis flowmeter vibration frequency tracking method and system

Also Published As

Publication number Publication date
CN111476207B (en) 2022-08-05

Similar Documents

Publication Publication Date Title
CN107505135B (en) Rolling bearing composite fault extraction method and system
RU2514061C2 (en) Method to determine vibration events with resonant frequency in assembly of rotary blades
EP3166239B1 (en) Method and system for scoring human sound voice quality
US20110301882A1 (en) System and method for passive acoustic monitoring of fluids and solids in pipe flow
CN108805059A (en) The Fault Diagnosis of Gear Case method that sparse regularization filtering is decomposed with adaptive sparse
CN102840907B (en) Rolling bearing vibration signal characteristic extracting and analyzing method under early fault state
CN108764073B (en) Acceleration noise filtering and integrating method combined with spectrum energy form fitting
CN105323018B (en) Method for performing joint jitter and amplitude noise analysis on a real-time oscilloscope
CN111476207B (en) Target frequency band signal accurate extraction method based on proportional interpolation method
CN111769810B (en) Fluid mechanical modulation frequency extraction method based on energy kurtosis spectrum
CN110617982A (en) Rotating machinery equipment fault identification method based on voiceprint signals
CN108287073B (en) Resonance band selection method based on singular value component frequency domain spectrum
CN104359685A (en) Diesel engine fault identification method
CN109596354B (en) Band-pass filtering method based on self-adaptive resonance frequency band identification
CN107941511A (en) A kind of implementation method of the frequency based on signal Time-frequency Decomposition-kurtosis figure
CN113406386B (en) Signal frequency accurate estimation method based on digital down-conversion
CN115884121A (en) Signal processing method and device based on wireless sensing technology
CN111198348B (en) Calibration method for noise test system of magnetic sensor
CN114285505A (en) Automatic noise floor calculation method and system
CN114624520A (en) Self-adaptive pulse signal detection and extraction method
CN114199365A (en) Vibration signal processing method
CN107582068A (en) A kind of distortion product otoacoustic emissions detecting strategy based on the cycle from relevant principle
CN112464855A (en) While-drilling mud positive pulse signal processing method and device based on EEMD
CN110263711B (en) Coupling signal impact feature extraction method based on improved spectral kurtosis
CN110470396B (en) Processing method for smoothing and denoising spectrum

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant