CN105424387B - Tooth sector real time remote intelligent monitor system - Google Patents
Tooth sector real time remote intelligent monitor system Download PDFInfo
- Publication number
- CN105424387B CN105424387B CN201510807713.3A CN201510807713A CN105424387B CN 105424387 B CN105424387 B CN 105424387B CN 201510807713 A CN201510807713 A CN 201510807713A CN 105424387 B CN105424387 B CN 105424387B
- Authority
- CN
- China
- Prior art keywords
- tooth sector
- signal
- formula
- tooth
- vibrating sensor
- 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.)
- Expired - Fee Related
Links
- 238000003745 diagnosis Methods 0.000 claims abstract description 19
- 238000012545 processing Methods 0.000 claims abstract description 16
- 238000000034 method Methods 0.000 claims abstract description 5
- 238000000605 extraction Methods 0.000 claims abstract description 4
- 230000036541 health Effects 0.000 claims abstract description 4
- 239000013598 vector Substances 0.000 claims description 28
- 238000000354 decomposition reaction Methods 0.000 claims description 16
- 238000012952 Resampling Methods 0.000 claims description 15
- 230000005540 biological transmission Effects 0.000 claims description 10
- 230000001174 ascending effect Effects 0.000 claims description 9
- 230000008859 change Effects 0.000 claims description 9
- 238000001514 detection method Methods 0.000 claims description 9
- 239000000523 sample Substances 0.000 claims description 9
- 230000004907 flux Effects 0.000 claims description 7
- 238000005070 sampling Methods 0.000 claims description 7
- 230000003321 amplification Effects 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 6
- 230000003750 conditioning effect Effects 0.000 claims description 6
- 238000009434 installation Methods 0.000 claims description 6
- 239000002184 metal Substances 0.000 claims description 6
- 238000003199 nucleic acid amplification method Methods 0.000 claims description 6
- 238000012549 training Methods 0.000 claims description 6
- 238000009826 distribution Methods 0.000 claims description 5
- 230000001133 acceleration Effects 0.000 claims description 3
- 230000015572 biosynthetic process Effects 0.000 claims description 3
- 230000000295 complement effect Effects 0.000 claims description 3
- 230000005352 galvanomagnetic phenomena Effects 0.000 claims description 3
- 230000007257 malfunction Effects 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 3
- 230000008054 signal transmission Effects 0.000 claims description 3
- 238000006243 chemical reaction Methods 0.000 abstract description 3
- 238000012544 monitoring process Methods 0.000 description 11
- 230000005611 electricity Effects 0.000 description 3
- 241000208340 Araliaceae Species 0.000 description 2
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 2
- 235000003140 Panax quinquefolius Nutrition 0.000 description 2
- 206010039203 Road traffic accident Diseases 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000006073 displacement reaction Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 235000008434 ginseng Nutrition 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000010295 mobile communication Methods 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- FHQVHHIBKUMWTI-ZCXUNETKSA-N 1-palmitoyl-2-oleoyl phosphatidylethanolamine Chemical compound CCCCCCCCCCCCCCCC(=O)OCC(COP(O)(=O)OCCN)OC(=O)CCCCCCC\C=C/CCCCCCCC FHQVHHIBKUMWTI-ZCXUNETKSA-N 0.000 description 1
- 241001269238 Data Species 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000009429 distress Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 238000004171 remote diagnosis Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M17/00—Testing of vehicles
- G01M17/007—Wheeled or endless-tracked vehicles
- G01M17/06—Steering behaviour; Rolling behaviour
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The invention discloses a kind of tooth sector real time remote intelligent monitor system.The system is mainly made up of two parts：Tooth sector on-line measuring device and long-distance intelligent diagnostic system.The system is by designing a kind of vibration detecting system for Vehicular turn gear.Vibration detecting system carries out the vibration signal of tooth sector to nurse one's health enhanced processing and analog-to-digital conversion first, and then institute's reduced data information remote is sent on the server of distal end by being wirelessly transferred again；Fault-signal feature of the long-distance intelligent diagnostic system primarily directed to Vehicular turn gear, using the intelligent diagnosing method in knowledge based storehouse, the rapid extraction to the fault characteristic signals of tooth sector is realized, so as to realize the rapid of motor turning Gear Fault Diagnosis, accuracy and intellectuality.
Description
Technical field
The present invention relates to the failure monitoring of automobile and diagnostic field, more particularly to a kind of motor turning gear real time remote
Monitoring and fault diagnosis system.
Background technology
Domestic Automotive Industry develops rapidly in recent years, has become the big automobile production state of the first in the world, and various automobile is also
Through coming into huge numbers of families, the at the same time traffic accident caused by vehicle failure happens occasionally, although the security of automobile and can
Compare over by property and be greatly improved, but automobile operationally breaks down and is difficult to avoid that.The particularly steering system of automobile
Unified denier breaks down, it is most likely that causes serious security incident, so the progress of the necessary tooth sector to automobile
State is monitored in real time, all kinds of failure situations that motor turning gear may occur is analyzed and predict, so as to instruct automobile
User's on-call maintenance or with changing automobile steering system, the traffic accident avoided caused by tooth sector of maximum possible.
At present also the real time and on line monitoring to motor turning gear is realized in various automobile without any device.Due to
The vibration signal of motor turning gear belongs to high-frequency signal, and common monitoring and fault diagnosis system do not have specific aim, Wu Faman
The monitoring of sufficient motor turning gear and the requirement of fault diagnosis.Meanwhile in order to meet the requirement of vehicle telematic movement, it is necessary to
Develop a kind of remote monitoring system that can meet automobile actual use feature.The present invention is precisely in order to solving this problem and carrying
Go out, by a kind of motor turning gear real-time remote monitoring system, gather motor turning gear running state information in real time, and
Far-end server is transferred to, the inline diagnosis to automobile gear failure is realized by intelligent diagnostics algorithm.
The content of the invention
In view of defect present in above-mentioned prior art, the present invention provides a kind of motor turning gear real-time monitoring system,
Collection motor turning gear running state information in real time, and far-end server is transferred to, realized by intelligent diagnostics algorithm to vapour
The inline diagnosis of car gear distress.
According to a kind of tooth sector real time remote intelligent monitor system provided by the invention, including：Tooth sector detection system
System, remote failure diagnosis system；
The tooth sector detecting system, including：Vibrating sensor, collector, industrial computer, wireless transmitter module；
Vibrating sensor, for the vibration acceleration signal of tooth sector to be changed into electric signal transmission to collector；
Collector, for carrying out A/D collections to the electric signal, and the digital data transmission that A/D is collected is to work
Control machine；
Industrial computer, for data signal to be stored in into local formation tooth sector state vibration information；
Wireless transmitter module, for tooth sector state vibration information to be carried out into remote data transmission to remote fault diagnosis
System；
The remote failure diagnosis system, including：Server, data base management system, intelligent diagnostics module, diagnostic message
Distribution platform；
Server, for the tooth sector state vibration information sent by internet real-time reception wireless transmitter module；
Data base management system, for storing the tooth sector state vibration information from server；
Intelligent diagnostics module, for carrying out feature extraction to tooth sector state vibration information, so as to determine steering tooth
The running status of wheel, gives warning in advance to failure；
Diagnostic message distribution platform, for carrying out real-time release to the running status of tooth sector, and provide tooth sector
Running status historical data inquiry service.
Preferably, the vibrating sensor, including non-contact electric eddy shift vibrating sensor, the contactless electricity
Eddy current displacement vibrating sensor includes：Sensor probe, preposition conditioning module；
The sensor probe, for launching current vortex and sensing metal to the metal measured surface of tooth sector installation axle
The magnetic flux of measured surface, flux change is converted to by curent change, and then output current signal according to galvanomagnetic-effect；
The preposition conditioning module, including：Oscillator, detection circuit, amplifier and linear compensation circuit；
Oscillator, the current signal for sensor probe to be exported change into the carrier signal of Frequency And Amplitude Modulation；
Circuit is detected, for extracting low frequency signal from the carrier signal after oscillator Frequency And Amplitude Modulation；
Amplifier, for being exported after being amplified to the low frequency signal for detecting circuit output as amplification output signal；
Linear compensation circuit, for the amplification output signal feedback signal back being nursed one's health to obtain to oscillator.
Preferably, the vibrating sensor includes the non-contact electric eddy shift vibrating sensor of two same specifications, should
The non-contact electric eddy shift vibrating sensor of two same specifications is arranged on the both sides of tooth sector in a manner of being distributed symmetrically,
And non-contact electric eddy shift vibrating sensor keeps constant apart from the relative position of tooth sector, so as in tooth sector
Vibration Condition on installation axial direction is monitored to obtain respectively by the two non-contact electric eddy shift vibrating sensors.
Preferably, described intelligent diagnostics module, including following device：
First processing unit, for WAVELET PACKET DECOMPOSITION, specifically, tooth sector state vibration information k (t) is divided
Solution, formula are as follows：
X=<k(t),ψ(t)>
In formula,<·,·>For inner product operation, ψ () is WAVELET PACKET DECOMPOSITION wave filter group, and t is time variable, and x represents to divide
Solve coefficient sequence；
Second processing device, for node resampling, specifically, each wavelet packet bottom is pressed to gained decomposition coefficient sequence x
Node layer carries out resampling, and sampling function is：
X'=G (sort (x, assending), 0.5)
In formula, the coefficient sequence after x ' expression resamplings, G (, 0.5) represents sampling function, and 0.5 attaches most importance to oversampling ratio ginseng
Number, i.e.,：
G (x, 0.5)={ xi},i∈Ωodd
Wherein, { xi},i∈ΩoddExpression takes odd number generic sequence value all in decomposition coefficient sequence x；Sort () is
Ranking functions；Assending is ascending order parameter, and ascending order parametric function represents to carry out ascending order arrangement to list entries；
3rd processing unit, calculated for node entropy, specifically, that seeks the coefficient sequence x ' after resampling is used as entropy
Quadratic sum, formula is as follows：
S=sum (x ')2=∑ (x ')2
In formula, s represents the result of calculation of entropy；
Using the set composition of vector of the result of calculation of the entropy of the bottom layer node of each WAVELET PACKET DECOMPOSITION as signal characteristic
Vectorial S, it is designated as S={ s }；
Fourth process device, for normalizing, specifically, all signal characteristic vectors for training dataset are tried to achieve
Mean μ and standard variance σ, are normalized, the characteristic vector S ' after being normalized, wherein：
S '={ (s- μ)/σ }
5th processing unit, differentiate for reference range, specifically, by tooth sector failure-free operation in training dataset
Data obtained by characteristic vector as reference vector s0, calculate the characteristic vector S and reference vector s of any input data0Cosine
Euclidean distance sim (s, s0)：
In formula, θ represents characteristic vector S and reference vector s0Between complementary chord angle；
If the cosine Euclidean distance of gained is less than threshold value 0.1, then it is assumed that tooth sector is in malfunction.
Compared with prior art, the present invention has the advantages that：
1st, the present invention can realize the on-line monitoring of the real-time running state of motor turning gear, turn so as to analyze automobile
To the failure and working condition that may be present of system, maintenance to automobile and accident is avoided to provide reliably technological guidance.
2nd, by being widely applied, may be led in motor turning design of gears that can be to different batches of the invention and processing
The accident defect of cause is analyzed, so as to reach the batch control box quality management of product.
3rd, because the present invention realizes the network transmission function of car data by the way of based on wireless mobile communications, so
Development to car networking technology has impetus.
Brief description of the drawings
By reading the detailed description with reference to the following drawings, other features, objects and advantages of the invention will become more
Substantially：
Fig. 1 is the monitoring system structural representation of the present invention.
Fig. 2 is the Data Link Map of the present invention.
Fig. 3 is non-contact current vortex displacement vibrating sensor measurement structural representation.
In figure：
1- pops one's head in
2- testees
3- magnetic fluxs
4- is vortexed
Embodiment：
Design, concrete structure and the caused technique effect of the present invention are further described below with reference to accompanying drawing,
To be fully understood by the purpose of the present invention, feature and effect.
Shown in Fig. 1, a kind of motor turning gear real-time remote monitoring system provided by the present invention, including：Motor turning
Gear detector and motor turning Gear Fault Diagnosis system.When it is implemented, vibrating sensor is arranged on motor turning tooth
The connecting portion of wheel shaft and bearing, when motor turning working gear, the vibration of gear can be passed along power transmission shaft by vibration
Sensor is perceived, and vibration signal is converted into electric signal；High-frequency vibration signal is carried out by modulus using 2M/s high speed acquisition device
Conversion, and be transferred to by usb bus on the industrial computer on automobile, industrial computer carries out pre- to these vibration datas first
Processing, then control wireless transmitter module that these data are passed through into 3G/4G network transmissions to far-end server.Positioned at Surveillance center
Server terminal after the detection terminal data are received, be stored in towards in the data system of fault diagnosis feature, then
Current all data are analyzed and processed by intelligent diagnostics algorithm, so as to draw the running status of motor turning gear and energy
Enough find potential equipment fault.
In the specific embodiment of the invention, the tooth sector detection means installed in each automobile has unified data to compile
Number, and mobile communication signal is converted digital signals into by wireless transmitter module, the company of being transferred directly under the transfer of base station
Connect in ethernet networks on the server with fixed ip address.As shown in Figure 2.
In the specific embodiment of the invention, motor turning gear detector can be supplied directly by the battery on automobile
Electricity.The power supply of sensor, collector and wireless transmitter module can solve by the builtin voltage conversion circuit of industrial computer,
And by various interface be its power supply, the input voltage 24V direct currents of industrial computer, the battery on automobile can power 24V direct currents
Electricity, it is possible to directly powered with automobile storage battery for whole detection means.
In the specific embodiment of the invention, the processing side of resampling Wavelet Packet Entropy is used in remote diagnosis system to vibration signal
Formula, wavelet packet specifically use vanishing moment to be decomposed for the biorthogonal wavelet of 3 ranks, and gained decomposition coefficient presses each wavelet packet bottom
Node carries out resampling, specifically carries out resampling by statistical function G (sort (x, assending, 1/2)), and after sampling is
Number seeks its square of entropy, to obtain describing the feature of signal.By it is normal when vibration signal provide reference characteristic.In failure,
Its feature can produce deviation, now departure degree be tried to achieve using normalized Euclidean distance function to new signal characteristic, with this
Criterion as fault diagnosis.
The present invention on each automobile by installing tooth sector detection means, the running state information of motor turning gear
Real-time Transmission is in the intelligent diagnosis system of distal end, while detection means is powered using automobile storage battery, without extra power supply source.
More specifically, according to a kind of tooth sector real time remote intelligent monitor system provided by the invention, including：Turn to
Gear testing system, remote failure diagnosis system；
The tooth sector detecting system, including：Vibrating sensor, collector, industrial computer, wireless transmitter module；
Vibrating sensor, for the vibration acceleration signal of tooth sector to be changed into electric signal transmission to collector；
Collector, for carrying out A/D collections to the electric signal, and the digital data transmission that A/D is collected is to work
Control machine；
Industrial computer, for data signal to be stored in into local formation tooth sector state vibration information；
Wireless transmitter module, for tooth sector state vibration information to be carried out into remote data transmission to remote fault diagnosis
System；
The remote failure diagnosis system, including：Server, data base management system, intelligent diagnostics module, diagnostic message
Distribution platform；
Server, for the tooth sector state vibration information sent by internet real-time reception wireless transmitter module；
Data base management system, for storing the tooth sector state vibration information from server；
Intelligent diagnostics module, for carrying out feature extraction to tooth sector state vibration information, so as to determine steering tooth
The running status of wheel, gives warning in advance to failure；
Diagnostic message distribution platform, for carrying out real-time release to the running status of tooth sector, and provide tooth sector
Running status historical data inquiry service.
The vibrating sensor, including non-contact electric eddy shift vibrating sensor, the non-contact electric eddy position
Moving vibrating sensor includes：Sensor probe, preposition conditioning module；
The sensor probe, for launching current vortex and sensing metal to the metal measured surface of tooth sector installation axle
The magnetic flux of measured surface, flux change is converted to by curent change, and then output current signal according to galvanomagnetic-effect；
The preposition conditioning module, including：Oscillator, detection circuit, amplifier and linear compensation circuit；
Oscillator, the current signal for sensor probe to be exported change into the carrier signal of Frequency And Amplitude Modulation；
Circuit is detected, for extracting low frequency signal from the carrier signal after oscillator Frequency And Amplitude Modulation；
Amplifier, for being exported after being amplified to the low frequency signal for detecting circuit output as amplification output signal；
Linear compensation circuit, for the amplification output signal feedback signal back being nursed one's health to obtain to oscillator.
Preferably, the vibrating sensor includes the non-contact electric eddy shift vibrating sensor of two same specifications, should
The non-contact electric eddy shift vibrating sensor of two same specifications is arranged on the both sides of tooth sector in a manner of being distributed symmetrically,
And non-contact electric eddy shift vibrating sensor keeps constant apart from the relative position of tooth sector, so as in tooth sector
Vibration Condition on installation axial direction is monitored to obtain respectively by the two non-contact electric eddy shift vibrating sensors.
Described intelligent diagnostics module, including following device：
First processing unit, for WAVELET PACKET DECOMPOSITION, specifically, tooth sector state vibration information k (t) is divided
Solution, formula are as follows：
X=<k(t),ψ(t)>
In formula,<·,·>For inner product operation, ψ () is WAVELET PACKET DECOMPOSITION wave filter group, and t is time variable, and x represents to divide
Solve coefficient sequence；
Second processing device, for node resampling, specifically, each wavelet packet bottom is pressed to gained decomposition coefficient sequence x
Node layer carries out resampling, and sampling function is：
X'=G (sort (x, assending), 0.5)
In formula, the coefficient sequence after x ' expression resamplings, G (, 0.5) represents sampling function, and 0.5 attaches most importance to oversampling ratio ginseng
Number, i.e.,：
G (x, 0.5)={ xi},i∈Ωodd
Wherein, { xi},i∈ΩoddExpression takes odd number generic sequence value all in decomposition coefficient sequence x；Sort () is
Ranking functions；Assending is ascending order parameter, and ascending order parametric function represents to carry out ascending order arrangement to list entries；
3rd processing unit, calculated for node entropy, specifically, that seeks the coefficient sequence x ' after resampling is used as entropy
Quadratic sum, formula is as follows：
S=sum (x ')2=∑ (x ')2
In formula, s represents the result of calculation of entropy；
Using the set composition of vector of the result of calculation of the entropy of the bottom layer node of each WAVELET PACKET DECOMPOSITION as signal characteristic
Vectorial S, it is designated as S={ s }；
Fourth process device, for normalizing, specifically, all signal characteristic vectors for training dataset are tried to achieve
Mean μ and standard variance σ, are normalized, the characteristic vector S ' after being normalized, wherein：
S '={ (s- μ)/σ }
5th processing unit, differentiate for reference range, specifically, by tooth sector failure-free operation in training dataset
Data obtained by characteristic vector as reference vector s0, calculate the characteristic vector S and reference vector s of any input data0Cosine
Euclidean distance sim (s, s0)：
In formula, θ represents characteristic vector S and reference vector s0Between complementary chord angle；
If the cosine Euclidean distance of gained is less than threshold value 0.1, then it is assumed that tooth sector is in malfunction.
Above content is to combine specific preferred embodiment to be described in further detail to the present invention, so can not incite somebody to action
The present invention is confined in these above-mentioned explanations.For general technical staff of the technical field of the invention, in the present invention
Concept on the deduction done and replacement be regarded as belonging to protection scope of the present invention.
Claims (3)
- A kind of 1. tooth sector real time remote intelligent monitor system, it is characterised in that including：It is tooth sector detecting system, long-range Fault diagnosis system；The tooth sector detecting system, including：Vibrating sensor, collector, industrial computer, wireless transmitter module；Vibrating sensor, for the vibration acceleration signal of tooth sector to be changed into electric signal transmission to collector；Collector, for carrying out A/D collections to the electric signal, and the digital data transmission that A/D is collected is to industrial computer；Industrial computer, for data signal to be stored in into local formation tooth sector state vibration information；Wireless transmitter module, for giving tooth sector state vibration information progress remote data transmission to remote fault diagnosis system System；The remote failure diagnosis system, including：Server, data base management system, intelligent diagnostics module, diagnostic message issue Platform；Server, for the tooth sector state vibration information sent by internet real-time reception wireless transmitter module；Data base management system, for storing the tooth sector state vibration information from server；Intelligent diagnostics module, for carrying out feature extraction to tooth sector state vibration information, so as to determine tooth sector Running status, failure is given warning in advance；Diagnostic message distribution platform, for carrying out real-time release to the running status of tooth sector, and provide the fortune of tooth sector The inquiry service of the historical data of row state；Described intelligent diagnostics module, including following device：First processing unit, for WAVELET PACKET DECOMPOSITION, specifically, tooth sector state vibration information k (t) is decomposed, it is public Formula is as follows：X=<k(t),ψ(t)>In formula,<·,·>For inner product operation, ψ () is WAVELET PACKET DECOMPOSITION wave filter group, and t is time variable, and x represents resolving system Number Sequence；Second processing device, for node resampling, specifically, each wavelet packet bottom section is pressed to gained decomposition coefficient sequence x Point carries out resampling, and sampling function is：X'=G (sort (x, assending), 0.5)In formula, the coefficient sequence after x ' expression resamplings, G (, 0.5) represents sampling function, and 0.5 attaches most importance to oversampling ratio parameter, I.e.：G (x, 0.5)={ xi},i∈ΩoddWherein, { xi},i∈ΩoddExpression takes odd number generic sequence value all in decomposition coefficient sequence x；Sort () is sequence Function；Assending is ascending order parameter, and ascending order parametric function represents to carry out ascending order arrangement to list entries；3rd processing unit, calculated for node entropy, specifically, ask the putting down as entropy of the coefficient sequence x ' after resampling Fang He, formula are as follows：S=sum (x ')2=∑ (x ')2In formula, s represents the result of calculation of entropy；Using the set composition of vector of the result of calculation of the entropy of the bottom layer node of each WAVELET PACKET DECOMPOSITION as signal characteristic vector S, it is designated as S={ s }；Fourth process device, for normalizing, specifically, average is tried to achieve to all signal characteristic vectors for training dataset μ and standard variance σ, is normalized, the characteristic vector S ' after being normalized, wherein：S '={ (s- μ)/σ }5th processing unit, differentiate for reference range, specifically, by the number of tooth sector failure-free operation in training dataset According to gained characteristic vector as reference vector s0, calculate the characteristic vector S and reference vector s of any input data0Cosine it is European Distance sim (s, s0)：In formula, θ represents characteristic vector S and reference vector s0Between complementary chord angle.If the cosine Euclidean distance of gained is less than threshold value 0.1, then it is assumed that tooth sector is in malfunction；
- 2. tooth sector real time remote intelligent monitor system according to claim 1, it is characterised in that the vibrating sensing Device, including non-contact electric eddy shift vibrating sensor, the non-contact electric eddy shift vibrating sensor include：Sensing Device probe, preposition conditioning module；The sensor probe, it is tested for launching current vortex to the metal measured surface of tooth sector installation axle and sensing metal The magnetic flux on surface, flux change is converted to by curent change, and then output current signal according to galvanomagnetic-effect；The preposition conditioning module, including：Oscillator, detection circuit, amplifier and linear compensation circuit；Oscillator, the current signal for sensor probe to be exported change into the carrier signal of Frequency And Amplitude Modulation；Circuit is detected, for extracting low frequency signal from the carrier signal after oscillator Frequency And Amplitude Modulation；Amplifier, for being exported after being amplified to the low frequency signal for detecting circuit output as amplification output signal；Linear compensation circuit, for the amplification output signal feedback signal back being nursed one's health to obtain to oscillator.
- 3. tooth sector real time remote intelligent monitor system according to claim 2, it is characterised in that the vibrating sensing Device includes the non-contact electric eddy shift vibrating sensor of two same specifications, the non-contact electric eddy position of two same specifications The both sides that vibrating sensor is arranged on tooth sector in a manner of being distributed symmetrically are moved, and non-contact electric eddy shift vibration passes Sensor keeps constant apart from the relative position of tooth sector, so as to which the Vibration Condition on tooth sector installation axial direction is by this Two non-contact electric eddy shift vibrating sensors monitor to obtain respectively.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510807713.3A CN105424387B (en) | 2015-11-19 | 2015-11-19 | Tooth sector real time remote intelligent monitor system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510807713.3A CN105424387B (en) | 2015-11-19 | 2015-11-19 | Tooth sector real time remote intelligent monitor system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105424387A CN105424387A (en) | 2016-03-23 |
| CN105424387B true CN105424387B (en) | 2017-12-15 |
Family
ID=55502741
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510807713.3A Expired - Fee Related CN105424387B (en) | 2015-11-19 | 2015-11-19 | Tooth sector real time remote intelligent monitor system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105424387B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106347578B (en) * | 2016-10-27 | 2018-01-30 | 江苏科技大学 | A kind of marine propulsion shafting bear vibration fault monitoring method |
| CN106959686A (en) * | 2017-04-05 | 2017-07-18 | 黄河水利职业技术学院 | A kind of intelligent remote diagnostic system and method |
| CN107631875B (en) * | 2017-08-01 | 2019-08-02 | 河南同心传动股份有限公司 | Truck drive shaft monitoring running state device and the method for detecting transmission shaft failure |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201417174Y (en) * | 2009-06-19 | 2010-03-03 | 武汉钢铁(集团)公司 | Monitoring system of electro-mechanic equipment |
| CN102053016A (en) * | 2010-11-08 | 2011-05-11 | 江苏大学 | System for monitoring vibration of rotating machinery rolling bearing in wireless mode |
| CN202614531U (en) * | 2012-04-28 | 2012-12-19 | 长安大学 | Motor fault diagnosis apparatus |
| CN104764487A (en) * | 2015-03-05 | 2015-07-08 | 浙江大学 | GPRS-based wind power gear box remote monitoring and diagnosis method |
-
2015
- 2015-11-19 CN CN201510807713.3A patent/CN105424387B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201417174Y (en) * | 2009-06-19 | 2010-03-03 | 武汉钢铁(集团)公司 | Monitoring system of electro-mechanic equipment |
| CN102053016A (en) * | 2010-11-08 | 2011-05-11 | 江苏大学 | System for monitoring vibration of rotating machinery rolling bearing in wireless mode |
| CN202614531U (en) * | 2012-04-28 | 2012-12-19 | 长安大学 | Motor fault diagnosis apparatus |
| CN104764487A (en) * | 2015-03-05 | 2015-07-08 | 浙江大学 | GPRS-based wind power gear box remote monitoring and diagnosis method |
Non-Patent Citations (2)
| Title |
|---|
| "汽车远程诊断信息管理系统的研发";李享;《中国优秀硕士学位论文全文数据库 信息科技辑》;20150715(第7期);第I138-134页 * |
| "电动汽车远程数据管理平台研究";杜刚;《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》;20150315(第4期);第C035-265页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105424387A (en) | 2016-03-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN203101070U (en) | High-speed train running gear fault diagnosis and remote-monitoring system based on Internet of things | |
| CN106394606B (en) | A kind of railway car wheel loses circle detection method and detection device | |
| CN102139700B (en) | Vehicle working condition online monitoring system for rail transit | |
| CN103852271B (en) | High-speed train running gear fault diagnosis and remote monitoring system based on Internet of Things | |
| CN201575927U (en) | Bogie condition monitoring device | |
| CN104386449B (en) | On-line checking intelligent protection device is taken turns end to end for mining belt conveyer | |
| CN105424387B (en) | Tooth sector real time remote intelligent monitor system | |
| CN111260822B (en) | Rail transit vehicle health state analysis method and terminal based on big data | |
| CN109238735B (en) | The malfunction monitoring diagnostic system of the electronic AGV of port cargo | |
| CN102706572A (en) | Fault diagnosis and rehabilitation center for train wheel sets | |
| CN104331066A (en) | Remote vehicle fault diagnosis method | |
| CN206132406U (en) | High -speed rail train health condition monitoring devices | |
| CN111332338A (en) | Track disease detection system | |
| CN212539258U (en) | 350 kilometer EMUs vibration integrated monitoring device | |
| CN110225856A (en) | Logistics/diagnostic monitoring self-power supply device for rolling stock | |
| CN107423692A (en) | A kind of rail corrugation fault detection method based on wavelet-packet energy entropy | |
| CN111401661B (en) | Predictive maintenance method and maintenance system for mechanical equipment | |
| CN108111583B (en) | Bogie rotating part safety monitoring system based on wireless sensor network | |
| CN105988460B (en) | Vehicle runway dynamic testing method, device and system | |
| CN102798413B (en) | A kind of railway dynamic detection system | |
| CN105235715A (en) | Online detecting integrated switch machine and monitoring method | |
| CN212903311U (en) | ZD27 EMUs bogie vibration acceleration monitoring devices | |
| CN210591925U (en) | Axle box vibrating wheel diameter difference detection system | |
| CN106289781B (en) | Rail vehicle bearing fault on-line detection device and method | |
| CN212320653U (en) | Intelligent detection system for subway vehicle faults |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20171215 |