CN106525223A - Offline detection method for abnormal noise of gear assembly - Google Patents
Offline detection method for abnormal noise of gear assembly Download PDFInfo
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- CN106525223A CN106525223A CN201610940218.4A CN201610940218A CN106525223A CN 106525223 A CN106525223 A CN 106525223A CN 201610940218 A CN201610940218 A CN 201610940218A CN 106525223 A CN106525223 A CN 106525223A
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- 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
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- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
Abstract
An offline detection method for abnormal noise of a gear assembly is disclosed. Firstly, a minimum entropy deconvolution filtering method is used for carrying out deconvolution of a measured vibration signal to eliminate influences of the propagation path on an abnormal noise feature signal of the gear assembly and enhance the signal-to-noise ratio of the feature signal; then the signal subjected to deconvolution is quantified by a kurtosis index; and finally, by comparing the set threshold with the kurtosis index of the deconvolution signal, the abnormal noise state of the gear assembly is determined. The method is free of influences of environmental noise and the running condition of the gear assembly, is high in detection accuracy and fast in detection speed, and is suitable for the offline detection the abnormal noise of the gear assembly. The method is beneficial for ensuring the out-going quality of the gear assembly product, reducing the risk of returning the gear assembly and helping the enterprise establish a good brand image.
Description
Technical field
The present invention relates to gear drive fault diagnosis technology field, more particularly to a kind of gear drive abnormal sound
Off-line test method.
Background technology
Gear drive is the vitals in machine driven system, is widely used in communications and transportation, engineering machinery etc.
Industry.The quality of its product quality directly affects the normal work of plant equipment.
Gear drive abnormal sound refers to that gear drive is generated during operating and specifies more than technological document
Abnormal sound, belong to mechanical breakdown.Gear drive abnormal sound indicates gear or bearing in gear drive etc.
Main parts size is changed, reflects heterogeneity and different degrees of gear drive failure, is shown which is present and is produced
Quality problem.Therefore, it is necessary to the gear drive that there will be abnormal sound with a kind of method is detected.Current common practice
It is that works engineer is judged to the abnormal sound of gear drive by human ear, but human ear result of determination receives subjective impact
Greatly, ambient noise ambient influnence is easily received, while increased the workload and the risk by noise hazard of workman, it is difficult to meet gear
The off-line test demand of transmission device abnormal sound.
The content of the invention
In order to overcome the shortcoming of above-mentioned prior art, it is an object of the invention to provide a kind of gear drive abnormal sound
Off-line test method, realizes the off-line test of gear drive abnormal sound, it is to avoid substandard product dispatches from the factory.
In order to achieve the above object, the technical scheme taken of the present invention is：
A kind of off-line test method of gear drive abnormal sound, comprises the following steps：
Step one, gear drive is arranged on off-line test testing stand, one is installed above gear drive
Individual acceleration transducer, or a sound transducer is installed around gear drive；
Step 2, the acceleration transducer installed using data acquisition equipment and step one or sound transducer, gather tooth
Vibration signal x of the wheel transmission device under different operating conditions1(t), x2(t) ..., xn(t), wherein, n represents the quantity of operating mode,
T represents the time；
Step 3, using the minimum entropy deconvolution filtering method of Ralph Wiggins to vibration signal x1(t), x2
(t) ..., xnT () carries out deconvolution process respectively, obtain signal y after deconvolution1(t), y2(t) ..., yn(t), minimum entropy uncoiling
That accumulates filtering method realizes that step is as follows：
1. initialize an input signalFilter coefficientArrange
2. calculate input signalToeplitz autocorrelation matrix X0,Wherein, the sampled point that N is included in representing an input signal
Number, L represent Toeplitz autocorrelation matrix X0Line number；
3. calculate output signalComputing formula isWherein,Represent from phase
Close matrix X0Transposed matrix；
4. recalculate input signalFilter coefficientComputing formula is：
5. by alternative manner, iterative calculation 2.～4. step, the condition that iteration terminates is：Double output signal
The difference of kurtosis index is less than 0.01, wherein, the computing formula of kurtosis index is：
Wherein, | | signed magnitude arithmetic(al) is represented,Represent mean value computing；
6. last group of output signal during 5. walk the is designated as the output result of minimum entropy deconvolution filtering method；
Step 4, calculates signal y after deconvolution respectively using kurtosis Index Formula1(t), y2(t) ..., ynThe kurtosis of (t)
Index, respectively obtains kurtosis index K of signal after deconvolution1, K2..., Kn；
Step 5, have no abnormal sound gear drive signal y after the deconvolution that aforementioned four step is obtained1(t), y2
(t) ..., ynT there is no obvious shock characteristic in (), its kurtosis index K1, K2..., KnValue all near 3；And there is abnormal sound tooth
The signal y that wheel transmission device is obtained by aforementioned four step1(t), y2(t) ..., ynAll there is obvious shock characteristic in (t), its
Kurtosis index K1, K2..., KnValue be both greater than 4；Therefore one initial abnormal sound threshold value T=4 is set, if calculated kurtosis
Index K1, K2..., KnIn any one value more than arrange abnormal sound threshold value, then judge that the gear drive quality does not conform to
Lattice；If calculated kurtosis index K1, K2..., KnThe abnormal sound threshold value for both less than arranging, then judge the loading drive gear
Put up-to-standard.
The initial value of described abnormal sound threshold value T is set to 4, subsequently abnormal sound threshold value is revised according to sample accumulation.
Beneficial effects of the present invention：
The present invention is according to the frequency spectrum of gear drive noise reduction with depositing at the intrinsic frequency of gear drive
In the frequency feature with gear mesh frequency as interval, it is contemplated that the vibration signal that sensor is measured is abnormal sound characteristic signal and biography
The result of path convolution is broadcast, the inventive method is not affected by gear drive operating condition, can be in different rotating speeds and difference
Gear drive abnormal sound detection is carried out under load.The method can improve the degree of accuracy of gear drive abnormal sound off-line test
And efficiency, and the risk of human cost and staff by noise hazard is effectively reduced, it is adapted to gear drive abnormal sound
Off-line test, can promote the use of in gear drive manufacturing enterprise, be with a wide range of applications.
Description of the drawings
Implementing procedure figures of the Fig. 1 for the inventive method.
Fig. 2 is the gear drive vibration signal x that has no abnormal sound1The time-domain diagram of (t).
Fig. 3 is abnormal sound gear drive vibration signal x2The time-domain diagram of (t).
Fig. 4 is the gear drive vibration signal x that has no abnormal sound1T signal y that () is obtained Jing after the inventive method process1(t)
Time-domain diagram.
Fig. 5 is abnormal sound gear drive vibration signal x2T signal y that () is obtained Jing after the inventive method process2When (t)
Domain figure.
Specific embodiment
Describe the present invention with case study on implementation below in conjunction with the accompanying drawings.
Part car vehicle bridge (gear drive) assembly of certain gear drive manufactory production is being assembled to car load
Afterwards, user reflects car under some operating modes, and driving axis send irksome Abnormal Sound, badly influences driver and takes advantage of
The comfortableness of visitor.But there is the drive axle of abnormal sound in factory testing, its all kinds of acoustics index meets automobile industry standard
The requirement of defined.For the problem, plant technology department is mainly judged to the abnormal sound of vehicle bridge by human ear, but human ear is sentenced
Determine result big by subjective impact, and easily receive ambient noise ambient influnence, it is difficult to meet the detection of vehicle bridge abnormal sound and require.By the present invention
Method solves the problem.
With reference to Fig. 1, a kind of off-line test method of gear drive abnormal sound is comprised the following steps：
Step one, vehicle bridge is arranged on off-line test testing stand, installs an acceleration and pass above the axle housing of vehicle bridge
Sensor；
Step 2, using data acquisition equipment and the mounted acceleration transducer of step one, gathers normal vehicle bridge respectively
The vibration signal x of (vehicle bridge 1) with abnormal sound vehicle bridge (vehicle bridge 2) under identical operating condition1(t), x2(t), wherein, t represents the time,
As shown in Figures 2 and 3, Fig. 2 and Fig. 3 respectively show the normal and abnormal sound axle vibraqtions time domain plethysmographic signal under identical operating mode；
Step 3, using vibration signal x of the minimum entropy deconvolution filtering method of Ralph Wiggins to collection1(t), x2
T (), carries out deconvolution process respectively, obtain signal y after deconvolution1(t), y2T (), such as Fig. 4 and Fig. 5, Fig. 4 and Fig. 5 show respectively
Normal and abnormal sound axle vibraqtions signal x1(t), x2Signal y after (t) deconvolution1(t), y2The time domain waveform of (t), contrast Fig. 4 and
Fig. 5 can be found that the axle vibraqtions signal that there is abnormal sound occurs in that obvious periodic shock after deconvolution；Minimum entropy uncoiling
That accumulates filtering method realizes that step is as follows：
1. initialize an input signalFilter coefficientArrange
2. calculate input signalToeplitz autocorrelation matrix X0, computing formula is：Wherein, the sampled point number that N is included in representing an input signal, L
Represent Toeplitz autocorrelation matrix X0Line number；
3. calculate output signalComputing formula isWherein,Represent from phase
Close matrix X0Transposed matrix；
4. recalculate input signalFilter coefficientComputing formula is：
5. by alternative manner, iterative calculation 2.～4. step, the condition that iteration terminates is：Double output signal
The difference of kurtosis index is less than 0.01, wherein, the computing formula of kurtosis index is：
Wherein, | | signed magnitude arithmetic(al) is represented,Represent mean value computing；
6. last group of output signal during 5. walk the is designated as the output result of minimum entropy deconvolution filtering method；
Step 4, using kurtosis index computing formula, calculates signal y after deconvolution respectively1(t), y2The kurtosis index of (t),
Obtain kurtosis index K of signal after deconvolution1=3.0, K2=5.2；
Step 5, the vehicle bridge that has no abnormal sound signal y after the deconvolution that aforementioned four step is obtained1(t), y2(t) ..., yn
T there is no obvious shock characteristic in (), its kurtosis index K1, K2..., KnValue be all close to 3；And there is abnormal sound vehicle bridge by upper
State the signal y that four steps are obtained1(t), y2(t) ..., ynT all there is obvious shock characteristic in (), its kurtosis index K1, K2...,
KnValue be both greater than 4；Therefore abnormal sound threshold value T=4, K are set1Less than 4, illustrate that the vehicle bridge 1 is up-to-standard；K2More than 4, this is illustrated
Be present abnormal sound in vehicle bridge 2, be judged to off quality.
Above content is with reference to specific preferred embodiment further description made for the present invention, it is impossible to assert
The specific embodiment of the present invention is only limitted to this, for general technical staff of the technical field of the invention, is not taking off
On the premise of present inventive concept, some simple deduction or replace can also be made, the present invention should be all considered as belonging to by institute
Claims of submission determine the protection domain of patent.
Claims (2)
1. a kind of off-line test method of gear drive abnormal sound, it is characterised in that comprise the following steps：
Step one, gear drive is arranged on off-line test testing stand, installs one and add above gear drive
Velocity sensor, or a sound transducer is installed around gear drive；
Step 2, the acceleration transducer installed using data acquisition equipment and step one or sound transducer, collection gear are passed
Vibration signal x of the dynamic device under different operating conditions1(t), x2(t) ..., xn(t), wherein, n represents the quantity of operating mode, t generations
The table time；
Step 3, using the minimum entropy deconvolution filtering method of Ralph Wiggins to vibration signal x1(t), x2(t) ..., xn
T () carries out deconvolution process respectively, obtain signal y after deconvolution1(t), y2(t) ..., yn(t), minimum entropy deconvolution filtering side
Method realizes that step is as follows：
1. initialize an input signalFilter coefficientArrange
2. calculate input signalToeplitz autocorrelation matrix X0,Wherein, the sampled point number that N is included in representing an input signal,
L represents Toeplitz autocorrelation matrix X0Line number；
3. calculate output signalComputing formula isWherein,Represent auto-correlation square
Battle array X0Transposed matrix；
4. recalculate input signalFilter coefficientComputing formula is：
5. by alternative manner, iterative calculation 2.～4. step, the condition that iteration terminates is：The kurtosis of double output signal
The difference of index is less than 0.01, wherein, the computing formula of kurtosis index is：
Wherein, | | signed magnitude arithmetic(al) is represented,Represent mean value computing；
6. last group of output signal during 5. walk the is designated as the output result of minimum entropy deconvolution filtering method；
Step 4, calculates signal y after deconvolution respectively using kurtosis Index Formula1(t), y2(t) ..., ynThe kurtosis index of (t),
Respectively obtain kurtosis index K of signal after deconvolution1, K2..., Kn；
Step 5, have no abnormal sound gear drive signal y after the deconvolution that aforementioned four step is obtained1(t), y2(t) ...,
ynT there is no obvious shock characteristic in (), its kurtosis index K1, K2..., KnValue all near 3；And there is abnormal sound gear drive
The signal y that device is obtained by aforementioned four step1(t), y2(t) ..., ynT all there is obvious shock characteristic in (), its kurtosis refers to
Mark K1, K2..., KnValue be both greater than 4；Therefore one initial abnormal sound threshold value T=4 is set, if calculated kurtosis index
K1, K2..., KnIn any one value more than arrange abnormal sound threshold value, then judge that the gear drive is off quality；Such as
Really calculated kurtosis index K1, K2..., KnThe abnormal sound threshold value for both less than arranging, then judge the gear drive quality
It is qualified.
2. the off-line test method of a kind of gear drive abnormal sound according to claim 1, it is characterised in that：Described
The initial value of abnormal sound threshold value T is set to 4, subsequently abnormal sound threshold value is revised according to sample accumulation and user feedback.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107271181A (en) * | 2017-06-19 | 2017-10-20 | 苏州微著设备诊断技术有限公司 | A kind of weak impact component extracting method of epicyclic gearbox |
| CN109443525A (en) * | 2018-11-02 | 2019-03-08 | 四川长虹电器股份有限公司 | A kind of equipment abnormal sound detection system and detection method |
| CN110044472A (en) * | 2019-03-22 | 2019-07-23 | 武汉源海博创科技有限公司 | Product abnormal sound abnormal sound intelligent checking system on a kind of line |
| CN112326169A (en) * | 2020-10-28 | 2021-02-05 | 未来振动(北京)测试技术有限公司 | Vibration type abnormal sound and abnormal sound detection system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202092871U (en) * | 2011-05-20 | 2011-12-28 | 万向钱潮（桂林）汽车底盘部件有限公司 | Noise detection device for automobile rear axle main reducer assembly |
| CN105510032A (en) * | 2015-12-11 | 2016-04-20 | 西安交通大学 | Deconvolution method based on harmonic to noise ratio guidance |
| CN105699082A (en) * | 2016-01-25 | 2016-06-22 | 西安交通大学 | Sparse maximum signal-to-noise ratio deconvolution method |
-
2016
- 2016-11-01 CN CN201610940218.4A patent/CN106525223A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202092871U (en) * | 2011-05-20 | 2011-12-28 | 万向钱潮（桂林）汽车底盘部件有限公司 | Noise detection device for automobile rear axle main reducer assembly |
| CN105510032A (en) * | 2015-12-11 | 2016-04-20 | 西安交通大学 | Deconvolution method based on harmonic to noise ratio guidance |
| CN105699082A (en) * | 2016-01-25 | 2016-06-22 | 西安交通大学 | Sparse maximum signal-to-noise ratio deconvolution method |
Non-Patent Citations (2)
| Title |
|---|
| 冷军发 等: "基于最小熵解卷积的齿轮箱早期故障诊断", 《机械科学与技术》 * |
| 江瑞龙: "基于最小熵解卷积的滚动轴承故障诊断研究", 《中国硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107271181A (en) * | 2017-06-19 | 2017-10-20 | 苏州微著设备诊断技术有限公司 | A kind of weak impact component extracting method of epicyclic gearbox |
| CN107271181B (en) * | 2017-06-19 | 2019-03-05 | 苏州微著设备诊断技术有限公司 | A kind of weak impact component extracting method of epicyclic gearbox |
| CN109443525A (en) * | 2018-11-02 | 2019-03-08 | 四川长虹电器股份有限公司 | A kind of equipment abnormal sound detection system and detection method |
| CN110044472A (en) * | 2019-03-22 | 2019-07-23 | 武汉源海博创科技有限公司 | Product abnormal sound abnormal sound intelligent checking system on a kind of line |
| CN110044472B (en) * | 2019-03-22 | 2021-11-16 | 宁波慧声智创科技有限公司 | Intelligent detection system for abnormal sound and abnormal sound of online product |
| CN112326169A (en) * | 2020-10-28 | 2021-02-05 | 未来振动(北京)测试技术有限公司 | Vibration type abnormal sound and abnormal sound detection system |
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Application publication date: 20170322 |