CN106485073A - A kind of grinding machine method for diagnosing faults - Google Patents

A kind of grinding machine method for diagnosing faults Download PDF

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Publication number
CN106485073A
CN106485073A CN201610887712.9A CN201610887712A CN106485073A CN 106485073 A CN106485073 A CN 106485073A CN 201610887712 A CN201610887712 A CN 201610887712A CN 106485073 A CN106485073 A CN 106485073A
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signal
generalized
transform
grinding machine
frequency
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陈换过
陈特
易永余
沈建洋
钱嘉诚
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Zhejiang Sci Tech University ZSTU
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Zhejiang Sci Tech University ZSTU
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B24—GRINDING; POLISHING
    • B24B—MACHINES, DEVICES, OR PROCESSES FOR GRINDING OR POLISHING; DRESSING OR CONDITIONING OF ABRADING SURFACES; FEEDING OF GRINDING, POLISHING, OR LAPPING AGENTS
    • B24B49/00—Measuring or gauging equipment for controlling the feed movement of the grinding tool or work; Arrangements of indicating or measuring equipment, e.g. for indicating the start of the grinding operation
    • B24B49/10—Measuring or gauging equipment for controlling the feed movement of the grinding tool or work; Arrangements of indicating or measuring equipment, e.g. for indicating the start of the grinding operation involving electrical means
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00—Subject matter not provided for in other main groups of this subclass
    • 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
    • G06F2218/04—Denoising

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  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Investigating Or Analyzing Materials By The Use Of Ultrasonic Waves (AREA)

Abstract

The invention provides a kind of grinding machine method for diagnosing faults, to overcome prior art easily to produce spurious signal and the defect of alias in failure diagnostic process.A kind of grinding machine method for diagnosing faults, comprises the following steps：A, using acquisition module, the vibration signal of grinding machine is acquired, obtains vibration acceleration signal x (t)；B, wavelet de-noising is carried out to signal x (t), obtain the acceleration signal x after noise reduction1(t)；C, to the acceleration signal x after noise reduction1T () carries out generalized S-transform, obtain time-frequency spectrum；D, generalized S-transform time-frequency spectrum is analyzed, generalized S-transform time-frequency spectrum obtains failure-frequency.When grinding machine has fault, its vibration signal has two features：1st, fault-signal is fainter, is easily flooded by other signals.2nd, grinding machine signal signal amplitude when there is tremor can dramatically increase, and energy quantitative change is big.For the above-mentioned two feature of fault-signal, method for diagnosing faults applies wavelet noise and generalized S-transform to solve the problems, such as two above respectively.

Description

A kind of grinding machine method for diagnosing faults
Technical field
The present invention relates to mechanical engineering technical field, particularly to the grinding machine fault diagnosis side based on generalized S-transform Method.
Background technology
Grinding is a kind of indispensable manufacturing procedure during machine-building, is workpiece accuracy, surface roughness Guarantee Deng important parameter.With the development of high speed, high-rate grinding, it is merely not only precision machined main method, also Become one kind than wide, efficient processing method.
In actual production, lathe can produce vibration, produces tremor, this is due to the self-excited vibration between cutter and workpiece Cause.Tremor can reduce the crudy of finished surface, accelerate lathe to destroy.Substantial amounts of research shows, grinding process is never sent out Raw grinding trembling occurs all to experienced one section of transition grinding process to tremor, contains abundant mill in the signal of this transient process Cut status information, for grinding trembling detection, there is important value.But the output signal right and wrong of grinding trembling transient process Stationary signal, the frequency of signal and amplitude all change over, and signal characteristic reproducibility is poor.Accordingly, it would be desirable to seek one kind Effectively signal characteristic extracting methods, separate the characteristic information of grinding machine tremor from lengthy and tedious original vibration information, obtain To accurate characteristic quantity, realize the monitoring to grinding machine tremor.
Conventional Time-Frequency Analysis Method has Short Time Fourier Transform, Gabor transformation and wavelet transformation etc., and time frequency resolution is Weigh the good and bad important indicator with time-frequency locality energy of these methods.What Short Time Fourier Transform and Gabor transformation used is all Fixed-size sliding window is it is impossible to accurately decompose the big low frequency signal of period ratio time window, and the time frequency resolution of high frequency Poor.Though wavelet transformation can adaptively reflect low frequency and radio-frequency component, wavelet basis function, once selecting, analyzes all numbers According to this wavelet function all must be used, will result in the leakage of signal energy, produce more falseness harmonic wave.
Content of the invention
The invention provides a kind of grinding machine method for diagnosing faults, to overcome prior art easily to produce in failure diagnostic process Raw spurious signal and the defect of alias.
In order to solve above technical problem, the present invention is achieved through the following technical solutions, a kind of grinding machine method for diagnosing faults, Comprise the following steps：
A, using acquisition module, the vibration signal of grinding machine is acquired, obtains vibration acceleration signal x (t)；
B, wavelet de-noising is carried out to signal x (t), obtain the acceleration signal x after noise reduction1(t)；
C, to the acceleration signal x after noise reduction1T () carries out generalized S-transform, obtain time-frequency spectrum；
D, generalized S-transform time-frequency spectrum is analyzed, generalized S-transform time-frequency spectrum obtains failure-frequency.
Further, described acquisition module includes piezoelectric acceleration transducer, data acquisition card and controller box, signal Capture card is connected using wire with sensor, and data acquisition card is plugged on grinding machine by connecting-disconnecting interface.
Further, grinding wheel spindle is equipped with piezoelectric acceleration transducer in X-direction, Y-direction and Z-direction；Motor exists It is equipped with piezoelectric acceleration transducer in X-direction and Y-direction；Column is being equipped with piezoelectricity in X-direction, Y-direction and Z-direction Formula acceleration transducer.It is easy to accurately gather signal.
Further, in step C, to signal x1T () carries out generalized S-transform, comprise the following steps that：
A, set function h (t) ∈ L2(R), L2(R) represent limit power function space, then the one-dimensional S-transformation of signal h (t) is fixed Justice is as formula (1)：
In formula (1)：H (t) express time sequence, τ represents time shift method, and σ represents scale factor, t express time, and f represents Frequency；
Wherein Gauss function such as formula (2)：
B, the Gauss function to generalized S-transform are transformed, and are introduced directly into regulation parameter k, as formula (3)：
C, improved after generalized S-transform, described expression formula such as formula (4)：
Now, (τ f) is accordingly changed into formula (5) to Gauss function g：
Wherein, (τ, f) for the signal after generalized S-transform for S；H (t) is quadractically integrable function；K is regulatory factor and k takes It is worth for 0～10.When within the specific limits, when regulatory factor k increases, the width of window function outwards can carry out continuation, and accordingly The amplitude of window function diminishes；Conversely, the width of window function is then to contract, the amplitude of corresponding window function becomes big.
D, foundation step c obtain improving generalized S-transform to the acceleration signal x after noise reduction1T () carries out Treatment Analysis, look for Be out of order time-frequency energy spectrogram after signal generalized S-transform, can get failure-frequency.
Further, k value is 6～10.
When grinding machine has fault, its vibration signal has two features：1st, fault-signal is fainter, easily other Signal is flooded.2nd, grinding machine signal signal amplitude when there is tremor can dramatically increase, and energy quantitative change is big.
For the above-mentioned two feature of fault-signal, method for diagnosing faults applies wavelet noise and generalized S-transform solution respectively Certainly two above problem.Original vibration signal is carried out noise reduction by application wavelet noise first.Again the fault-signal after noise reduction is entered Row generalized S-transform, can get the frequency band of energy variation on generalized S-transform time-frequency spectrum, obtains failure-frequency.
Brief description
The invention will be further described below in conjunction with the accompanying drawings：
The flow chart of Fig. 1 present invention；
Fig. 2 is the time domain beamformer of Simulink composite signal；
Fig. 3 is the generalized S-transform spectrogram of composite signal；
Fig. 4 is the generalized S-transform spectrogram partial enlarged drawing of composite signal；
The algorithm flow chart of Fig. 5 generalized S-transform.
Specific embodiment
Refering to Fig. 1, a kind of grinding machine method for diagnosing faults, comprise the following steps：
A, using acquisition module, the vibration signal of grinding machine is acquired, obtains vibration acceleration signal x (t)；
B, wavelet de-noising is carried out to signal x (t), obtain acceleration signal x1 (t) after noise reduction；
C, to the acceleration signal x after noise reduction1T () carries out generalized S-transform, obtain time-frequency spectrum；
D, generalized S-transform time-frequency spectrum is analyzed, generalized S-transform time-frequency spectrum obtains failure-frequency.
Acquisition module includes piezoelectric acceleration transducer, data acquisition card and controller box, data acquisition card and biography Sensor adopts wire to be connected, and data acquisition card is plugged on grinding machine by connecting-disconnecting interface.
Acceleration transducer is arranged in the X of grinding wheel spindle, motor and column, Y, in Z-direction.
Refering to Fig. 5, in step C, to signal x1T () carries out generalized S-transform, comprise the following steps that：
A, set function h (t) ∈ L2(R), L2(R) represent limit power function space, then the one-dimensional S-transformation of signal h (t) is fixed Justice is as formula (1)：
In formula (1)：H (t) express time sequence, τ represents time shift method, and σ represents scale factor, t express time, and f represents Frequency；
Wherein Gauss function such as formula (2)：
B, the Gauss function to generalized S-transform are transformed, and are introduced directly into regulation parameter k, as formula (3)：
C, improved after generalized S-transform, described expression formula such as formula (4)：
Now, (τ f) is accordingly changed into formula (5) to Gauss function g：
Wherein, (τ, f) for the signal after generalized S-transform for S；H (t) is quadractically integrable function；K is regulatory factor and k takes It is worth for 0～10.When within the specific limits, when regulatory factor k increases, the width of window function outwards can carry out continuation, and accordingly The amplitude of window function diminishes；Conversely, the width of window function is then to contract, the amplitude of corresponding window function becomes big, when k value is 6 ～10 best results.
D, foundation step c obtain improving generalized S-transform to the acceleration signal x after noise reduction1T () carries out Treatment Analysis, look for Be out of order time-frequency energy spectrogram after signal generalized S-transform, can get failure-frequency.
This grinding machine method for diagnosing faults is carried out based on produced vibration signal in grinding machine running.Grinding machine is in fortune Regardless of whether there is fault all can have a generation of vibration signal during row, but fault-free and faulty when vibration signal have Different differences.When grinding machine does not have fault, vibration signal is steady.When grinding machine occurs tremor fault, vibration signal amplitude can show Write and become big.
It is time-domain signal by the vibration acceleration signal that acceleration transducer records, Fig. 1 is Simulink composite signal Time domain beamformer.
Vibration signal is to be produced by two sinusoidal signal generators and a white noise generator, first sinusoidal signal Generator produce one by 100rad/s and 200rad/s synthesis frequency, and another sinusoidal signal generator produce one by The frequency of 80rad/s and 180rad/s synthesis, two signal phases differ 45 °.Sinusoidal signal (6), sinusoidal signal (7) and white noise Sound (8) can be expressed as:
X (t)=4sin (100t)+4sin (200t)+1 (6)
c1(t)=0.7rand (2001,1) -0.7c2(t)=rand (2001,1) -0.5 (8)
This tremor occurs system to rely on clock module to calculate current simulation time.When simulation time is less than 1.25s, It is output as the random vibration signal synthesizing, so that the stationary vibration process in simulation grinding process；More than 1.25s and little when the time When 1.5s, time comparator changes, and controlling switch controls the random vibration signal of output synthesis to be multiplied with ramp signal, Obtain a new signal, simulate Vibration Condition under chatter state for the grinding machine；When simulation time is more than 1.25s, time ratio Change compared with device, controlling switch, export initial stochastic signal and be multiplied by the later signal of gain such as formula (9), to simulate grinding The stable chatter state of tremor.
Fig. 3 is the vibration signal of grinding machine itself and the generalized S-transform spectrogram of fault-signal composite signal.
What tracing trouble needs obtained is the frequency values corresponding to vibration signal.For simple signal, as x above T () and y (t), directly carries out the frequency values that Fourier transformation can be obtained by vibration signal, but which frequency cannot judge is Cause tremor fault.Generalized S-transform is carried out to composite signal, obtains time-frequency spectrum.Understand in Fig. 3, generalized S-transform time-frequency spectrum At frequency axiss about 16Hz and 32Hz, obvious energy feature occurs, match with the frequency synthesis of emulation experiment, simulation result Demonstrate the effectiveness for grinding machine vibrating signal feature extraction and analysis for the generalized S-transform time-frequency spectrum.
Fig. 4 is the generalized S-transform spectrogram partial enlarged drawing of composite signal.
As can be known from Fig. 4, in stable grinding process, the signal energy value of (before 1.25s) is less and stable；1.25 After second, the change of in figure energy feature can substantially reflect the energy variation rule in tremor generating process：Signal energy value is obvious Become big, energy value is incremented to 0.98 from initial 0.3；After 1.5 seconds, when grinding machine enters stable chatter state, energy value is steady It is scheduled on 0.98, signal energy value reaches maximum, energy tends towards stability.Therefore, generalized S-transform can effectively reflect vibrating signal Energy conversion process, more intuitively analyzes grinding trembling mechanism.
The embodiment of the present invention advantages below is had based on the grinding machine method for diagnosing faults of generalized S-transform：Adopt in the present invention Method is generalized S-transform, and it is the signal processing proposing on the basis of Short Time Fourier Transform and continuous wavelet transform Method.Generalized S-transform is a kind of reversible Time-Frequency Analysis Method, and it maintains the absolute phase information of signal, and frequency division is distinguished at that time Rate changes with frequency, can automatically regulate the width of window function according to the time-frequency characteristics difference of signal Analysis, with Just reach optimal time frequency resolution, have higher separating capacity to unlike signal component in non-stationary signal.Initially with Wavelet de-noising, carries out noise reduction to primary signal；Which solving generalized S-transform is affected larger shortcoming by noise jamming；Screening For non-stationary signal and noise is less for signal, and interference factor is less, and generalized S-transform is stronger to nonstationary random response ability, energy Process such signal well, and result simple, intuitive, improve signal to noise ratio and capacity of resisting disturbance, strengthen the essence of fault diagnosis Degree.

Claims (5)

1. a kind of grinding machine method for diagnosing faults, comprises the following steps：
A, using acquisition module, the vibration signal of grinding machine is acquired, obtains vibration acceleration signal x (t)；
B, wavelet de-noising is carried out to signal x (t), obtain the acceleration signal x after noise reduction1(t)；
C, to the acceleration signal x after noise reduction1T () carries out generalized S-transform, obtain time-frequency spectrum；
D, generalized S-transform time-frequency spectrum is analyzed, generalized S-transform time-frequency spectrum obtains failure-frequency.
2. a kind of grinding machine method for diagnosing faults according to claim 1, is characterized in that：Described acquisition module includes piezoelectric type Acceleration transducer, data acquisition card and controller box, data acquisition card is connected using wire with sensor, data acquisition card It is plugged on grinding machine by connecting-disconnecting interface.
3. a kind of grinding machine method for diagnosing faults according to claim 2, is characterized in that：Grinding wheel spindle is in X-direction, Y-direction With piezoelectric acceleration transducer is equipped with Z-direction；Motor is being equipped with piezoelectric type acceleration sensing in X-direction and Y-direction Device；Column is being equipped with piezoelectric acceleration transducer in X-direction, Y-direction and Z-direction.
4. a kind of grinding machine method for diagnosing faults according to claim 1, is characterized in that：In step C, to signal x1T () enters Row generalized S-transform, comprises the following steps that：
A, set function h (t) ∈ L2(R), L2(R) represent limit power function space, then the one-dimensional S-transformation of signal h (t) defines such as Formula (1)：
S ( τ , f , σ ) = ∫ - ∞ + ∞ h ( t ) g ( τ - t ) exp ( - i 2 π f t ) d t = ∫ - ∞ + ∞ h ( t ) 1 σ 2 π exp [ ( τ - t ) 2 2 σ 2 ] exp ( - i 2 π f t ) d t - - - ( 1 )
In formula:H (t) express time sequence, τ represents time shift method, and σ represents scale factor, t express time, and f represents frequency；
Wherein Gauss function such as formula (2)：
g ( t ) = 1 σ 2 π exp [ ( τ - t ) 2 2 σ 2 ] - - - ( 2 )
B, the Gauss function to generalized S-transform are transformed, and are introduced directly into regulation parameter k, as formula (3)：
σ = k f - - - ( 3 )
C, improved after generalized S-transform, described expression formula such as formula (4)：
S ( τ , f ) = ∫ - ∞ + ∞ h ( t ) g ( τ , f ) exp ( - i 2 π f t ) d t = ∫ - ∞ + ∞ h ( t ) | f / k | 2 π exp [ - ( f / k ) 2 ( τ - t ) 2 2 ] exp ( - i 2 π f t ) d t - - - ( 4 )
Now, (τ f) is accordingly changed into formula (5) to Gauss function g：
g ( τ , f ) = | f / k | 2 π exp [ - ( f / k ) 2 ( τ - t ) 2 2 ] - - - ( 5 )
Wherein, (τ, f) for the signal after generalized S-transform for S；H (t) is quadractically integrable function；For regulatory factor and k value is 0 to k ～10.
D, foundation step c obtain improving generalized S-transform to the acceleration signal x after noise reduction1T () carries out Treatment Analysis, find out fault After signal generalized S-transform, time-frequency energy spectrogram, can get failure-frequency.
5. a kind of grinding machine method for diagnosing faults according to claim 4, is characterized in that：K value is 6～10.
CN201610887712.9A 2016-10-12 2016-10-12 A kind of grinding machine method for diagnosing faults Pending CN106485073A (en)

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CN108318169A (en) * 2018-01-12 2018-07-24 西南交通大学 Maximum dynamic force appraisal procedure and steel rail welding line maintenance system at a kind of steel rail welding line
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CN108318169A (en) * 2018-01-12 2018-07-24 西南交通大学 Maximum dynamic force appraisal procedure and steel rail welding line maintenance system at a kind of steel rail welding line
CN117249996A (en) * 2023-11-10 2023-12-19 太原理工大学 Fault diagnosis method for gearbox bearing of mining scraper
CN117249996B (en) * 2023-11-10 2024-02-13 太原理工大学 Fault diagnosis method for gearbox bearing of mining scraper

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Application publication date: 20170308