CN208224838U - A kind of EMU sound fault diagnosis system - Google Patents
A kind of EMU sound fault diagnosis system Download PDFInfo
- Publication number
- CN208224838U CN208224838U CN201820831184.XU CN201820831184U CN208224838U CN 208224838 U CN208224838 U CN 208224838U CN 201820831184 U CN201820831184 U CN 201820831184U CN 208224838 U CN208224838 U CN 208224838U
- Authority
- CN
- China
- Prior art keywords
- emu
- acoustic
- fault diagnosis
- diagnosis system
- sound
- 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.)
- Active
Links
Landscapes
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The utility model discloses a kind of EMU sound fault diagnosis systems, belong to rolling stock fault test set field, including acoustic sensor array, imaging sensor, hardware handles circuit, analysis host, data storage server and display terminal.Acoustic sensor array acquires acoustic information, and imaging sensor acquires image information, and is delivered separately to hardware handles circuit and is pre-processed, and is then communicated to analysis host, and analysis host computer acoustic information carries out auditory localization and fault identification to EMU；Image information is identified simultaneously, the vehicle group number of automatic identification EMU, vehicle number information.Transmitting fault information is stored to data storage server, and simultaneous transmission to display terminal shows fault message.The utility model can integrate time domain field statistical factors, sound intensity size and frequency domain field energy accounting, frequency content analysis, carry out comprehensive judgement to acoustic signal, and the power of failure is indicated with the color of image and brightness.
Description
Technical field
The utility model belongs to rolling stock fault test set field, specifically a kind of EMU sound fault diagnosis system
System.
Background technique
For the comfort for ensuring passenger, while the influence to Along Railway environment is reduced, EMU wants noise limit value
It asks very strict, does not have to running environment when running at high speed, start and stopping according to EMU, formulated different EMU and made an uproar
Sound test and standard limit.Abnormal noise signal not only reduces the comfort of passenger, while can reflect the vehicle event of EMU
Barrier, and then different accident analyses, identification and decision algorithm are established to different faults position.
Abnormal noise mainly includes EMU car internal vibration noise and cooling device noise；
When EMU high-speed cruising (speed reaches 300km/h), the vibration of interaction and its generation between wheel track is made an uproar
Sound is the main source of EMU car internal vibration noise.The cooling device of EMU is to cooling tractive transformer, traction current transformation
Device and traction electric machine etc..The thermal losses generated when its work is taken away by cooling device, guarantees that equipment operates normally, to guarantee
The traffic safety of EMU.The cooling device of independent blower is either used, or using the cold cooling dress for adding forced air cooling of oil
It sets, integrates formula structure for what is be made of oil radiator, air inlet duct, draught fan impeller, air compartment, mast-up, electric connector etc..
During EMU dynamic operation and static state power on, blower run at high speed generation high noisy become cooling device noise master
Want source.
The maintenance to EMU acoustic category failure domestic at present is realized by the means manually monitored mostly, is entered in EMU
It library and once powers in maintenance process, staff monitors EMU sound by human ear, judges whether EMU deposits
In abnormal sound information.Since artificial detection is influenced by subjective factor, there are biggish individual differences, can not be with existing skill
Art standard matches, therefore snoop results have very big contingency and otherness.
Utility model content
The utility model is for existing EMU sound trouble hunting based on manually monitoring, and snoop results are by subjective factor
Influence interference, evaluation result can not quantitative measurement, and with existing technical standard can not be corresponding problem；Propose a kind of EMU
Sound fault diagnosis system.
The EMU sound fault diagnosis system, including acoustic sensor array, imaging sensor, hardware handles electricity
Road, analysis host, data storage server and display terminal.
Acoustic sensor array and imaging sensor are integrated on one piece of pentagonal circuit board；The pentagon circuit board with
Hardware handles circuit and analysis host are separately fixed on intelligent carriage, the inspection by the mobile realization of intelligent carriage to EMU
It surveys, will test result and be stored on data storage server, and pass through display terminal real-time display.
Wherein, acoustic sensor array includes several acoustic sensors, includes A/D modulus of conversion inside each acoustic sensor
Block；By several acoustic sensor average packets, centered on image taking sensor, every group of acoustic sensor is along pentagonal vertex
It is scattered in a clockwise arcuate structure with central point, all acoustic sensors collectively form spiral shape.
Utility model has the advantages that
1) a kind of, EMU sound fault diagnosis system is led to using two-dimentional microphone array for the first time in overhaul of train-set
Two dimensional beam forming technique is crossed to position more sound sources.
2) a kind of, EMU sound fault diagnosis system, can wheel to EMU side to, main transformer fan, traction electricity
The acoustic signals such as machine blower, air-conditioning draught fan, dust bellows carry out positioning and fault identification.
3) a kind of, EMU sound fault diagnosis system can integrate time domain by the sector structure of acoustic sensor array
Field statistical factors, sound intensity size and frequency domain field energy accounting, frequency content analysis, carry out comprehensive judgement to acoustic signal.
4) a kind of, EMU sound fault diagnosis system shows sound source in space in display terminal in the form of ultrasonogram
Distribution, and indicate with the color of image and brightness the power of failure.
Detailed description of the invention
Fig. 1 is a kind of EMU sound fault diagnosis system structural schematic diagram of the utility model；
Fig. 2 is acoustic sensor array and imaging sensor distribution in the utility model EMU sound fault diagnosis system
Figure；
1- EMU；2- air-conditioning draught fan；3- traction convertor cooling device blower；4- dust bellows；5- tractive transformer
Cooling device blower；6- traction electric machine cooling device blower；7- wheel；10- acoustic sensor；101- acoustic sensor array；
102- imaging sensor；103- hardware handles circuit；104- analyzes host；105- data storage server；106- display terminal.
Specific embodiment
The specific implementation method of the utility model is described in detail with reference to the accompanying drawing.
A kind of EMU sound fault diagnosis system, can be realized motor-car by acoustic sensor array and imaging sensor
Sound and Image Acquisition under group motion and standstill two states；And image information to acquisition and acoustic information carry out positioning and
Acoustic image is shown, the image information that imaging sensor acquires is merged to form ultrasonogram with the acoustic information that acoustic sensor acquires；
The power of acoustic information is shown in image information by brightness and color.
As shown in Figure 1, including acoustic sensor array 101, imaging sensor 102, hardware handles circuit 103, analysis master
Machine 104, data storage server 105 and display terminal 106.
Acoustic sensor array 101 and imaging sensor 102 are integrated on one piece of pentagonal circuit board；By the figure of acquisition
As information and acoustic information are positioned and are overlapped, the power of acoustic information is shown in image information by brightness and color；
The circuit board is powered 12V by adapter.The pentagon circuit board and hardware handles circuit 103 and analysis host 104 are solid respectively
It is scheduled on intelligent carriage, the detection by the mobile realization of intelligent carriage to EMU, will test result and be stored in data storage
On server 105, and shown by display terminal 106；106 real-time display EMU 1 of display terminal by when ultrasonogram,
And when there are failure, the ultrasonogram of abort situation can be shown.
As shown in Fig. 2, the imaging sensor 102 uses high speed camera, acquisition EMU side includes air-conditioning draught fan
2, traction convertor cooling device blower 3, dust bellows 4, tractive transformer cooling device blower 5, traction electric machine cooling device
The image information of blower 6, the non-sphering of wheel 7.
Acoustic sensor array 101 includes 30 acoustic sensors 10, and each acoustic sensor 10 selects high-performance, Gao Ji
The digital MEMS microphone of Cheng Du, inside include A/D conversion module, and response frequency is adopted from 35Hz to 10kHz towards EMU 1
Collection EMU side includes air-conditioning draught fan 2, traction convertor cooling device blower 3, dust bellows 4, the cooling dress of tractive transformer
Set the acoustic information of blower 5, traction electric machine cooling device blower 6, the non-sphering of wheel 7；Acoustic information includes: energy accounting, system
Count the factor, sound intensity size, frequency content, historical trend data and arm's length standard acoustic contrast etc..
30 acoustic sensors 10 are divided into five groups, and centered on high speed camera, every group of acoustic sensor 10 is along five
The vertex of side shape and central point are scattered in a clockwise arcuate structure, and all acoustic sensor array 101 are common
Helical structure is constituted, the inscribed circle diameter of pentagon circuit board is 35cm, weight 1.87kg, realizes acoustic sensor array
101 and imaging sensor 102 acquire information flexibility.
For the demand for adapting to the accident analysis of different type EMU sound and identification, acoustic sensor array 101 and image
The height and angle that sensor 102 acquires can be adjusted according to the type of different EMU；The frequency of acquisition acoustic signal passes through
The control software of analysis host 104 is adjusted.
For the safety of safeguard work equipment, the EMU sound fault diagnosis system installment work status indicator lamp,
When equipment is in running order, has alarm function, while acoustic sensor array 101 and imaging sensor 102 are apart from dynamic
Distance >=1m of vehicle group 1.
Acoustic information and image information are transferred to hardware handles circuit 103 and complete the noise reduction of acoustics and image information, filtering
With amplification etc. pretreatment；Hardware handles circuit 103 includes FPGA processor, 50 channel number word I/O, DRAM and Ethernet；Using
FPGA processor realizes parallel computation, and to realize accident analysis and identification, the video frame rate of ultrasonogram is 25fps.
Host 104 is analyzed by beam forming technique, image information and acoustic information are analyzed, to realize EMU
The accurate positioning of 1 vehicle cab recognition and sound source, analysis host 104 identify the vehicle of motor train unit train, vehicle using image recognition technology
Number information, and EMU is automatically positioned according to vehicle number information and enters institute's cis-position and A, B ends；Using the energy accounting of acoustic information,
The modes such as statistical factors, sound intensity size, frequency content, historical trend data and arm's length standard acoustic contrast, to the EMU 1
Air-conditioning draught fan 2, tractive transformer cooling device blower 5, traction convertor cooling device blower 3, the traction electric machine of side are cooling
Device blower 6, dust bellows 4 and wheel 7 lose round and other acoustic informations and are positioned, analyzed and identified, to realize sound source
Positioning and identification；In 106 real-time display fault message of display terminal in a manner of ultrasonogram.
Display terminal 106 is after analysis host 104 completes the analysis and identification of image information and acoustic information, with ultrasonogram
Form display diagnosis fail result, and image information and acoustic information in real-time display detection process.
Acoustic imaging technology is the measuring technique based on acoustic sensor array 101 and imaging sensor 102, passes through measurement one
Determine the signal phase difference that sound wave in space reaches sensor, determines sound source position according to beam-forming technology, and with ultrasonogram
Mode show sound source in the distribution in space, wherein with the power of the color of image and brightness representative voice.
When EMU 1 passes through, it is cooling that acoustic sensor array 101 acquires the air-conditioning draught fan 2 of EMU, traction convertor
Device blower 3, dust bellows 4, tractive transformer cooling device blower 5, traction electric machine cooling device blower 6 and wheel 7 are non-circular
The acoustic information of change, while imaging sensor 102 acquires the image information of the above-mentioned component of EMU, and by acoustic information and figure
As information passes to hardware handles circuit 103, hardware handles circuit 103 is pre-processed, pretreated acoustic information and figure
Host 104 is analyzed as information is transferred to by Ethernet, analysis host 104 is using acoustic information to the air-conditioning of 1 side of EMU
Blower 2, tractive transformer cooling device blower 5, traction convertor cooling device blower 3, traction electric machine cooling device blower 6,
Dust bellows 4 and wheel 7 lose circle and are positioned, analyzed and identified, to realize auditory localization and fault identification；
Treated that fault message is transferred to by Ethernet for the initial data of acoustics and image and by analysis host 104
Data storage server 105 is stored, and the acoustics and image raw information of every train and accident analysis determine that result is stored in
Data storage server 105；Display terminal 106 is transmitted in a manner of ultrasonogram VGA line simultaneously and shows fault message, sound
The power for learning information is shown in image information by brightness and color.
The EMU sound fault diagnosis system, can acquire moment voice signal or impact sound signal；It can
Analysis and fault identification are carried out to the voice signal of single-point；It simultaneously can be according to vehicle, license number and cis-position information to emphasis acoustics
Information is positioned, analyzed and is identified.To realize data storage and historical trending analysis, data storage server design storage is not
Monitoring data less than 1 month.
Claims (7)
1. a kind of EMU sound fault diagnosis system, which is characterized in that including acoustic sensor array, imaging sensor, hard
Part processing circuit, analysis host, data storage server and display terminal；
Acoustic sensor array and imaging sensor are integrated on one piece of pentagonal circuit board；The pentagon circuit board and hardware
Processing circuit and analysis host are separately fixed on intelligent carriage, the detection by the mobile realization of intelligent carriage to EMU,
It will test result to be stored on data storage server, and pass through display terminal real-time display；
Wherein, acoustic sensor array includes several acoustic sensors, includes A/D conversion module inside each acoustic sensor；
By several acoustic sensor average packets, centered on image taking sensor, every group of acoustic sensor along pentagonal vertex with
Central point is scattered in a clockwise arcuate structure, and all acoustic sensors collectively form spiral shape.
2. a kind of EMU sound fault diagnosis system as described in claim 1, which is characterized in that the hardware handles electricity
Road includes FPGA processor, 50 channel number word I/O, DRAM and Ethernet.
3. a kind of EMU sound fault diagnosis system as described in claim 1, which is characterized in that the pentagon circuit
Plate is powered 12V by adapter.
4. a kind of EMU sound fault diagnosis system as described in claim 1, which is characterized in that the imaging sensor
Using high speed camera, acquiring EMU side includes air-conditioning draught fan, traction convertor cooling device blower, dust bellows, traction
The image information of transformer cooling device blower, traction electric machine cooling device blower and the non-sphering of wheel.
5. a kind of EMU sound fault diagnosis system as described in claim 1, which is characterized in that each acoustics passes
Sensor selects high-performance, the digital MEMS microphone of high integration, and response frequency is from 35Hz to 10kHz.
6. a kind of EMU sound fault diagnosis system as described in claim 1, which is characterized in that the pentagon circuit
The inscribed circle diameter of plate is 35cm, weight 1.87kg.
7. a kind of EMU sound fault diagnosis system as described in claim 1, which is characterized in that the acoustic sensor
The height and angle of array and imaging sensor acquisition can be adjusted according to the type of different EMU；Acquire the frequency of acoustic signal
Rate is adjusted by analyzing the control software of host.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201820831184.XU CN208224838U (en) | 2018-05-31 | 2018-05-31 | A kind of EMU sound fault diagnosis system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201820831184.XU CN208224838U (en) | 2018-05-31 | 2018-05-31 | A kind of EMU sound fault diagnosis system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN208224838U true CN208224838U (en) | 2018-12-11 |
Family
ID=64507525
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201820831184.XU Active CN208224838U (en) | 2018-05-31 | 2018-05-31 | A kind of EMU sound fault diagnosis system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN208224838U (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110672950A (en) * | 2019-10-08 | 2020-01-10 | 深圳海岸语音技术有限公司 | Power equipment fault sound image detection system and method |
| CN111189530A (en) * | 2020-01-20 | 2020-05-22 | 成都铁安科技有限责任公司 | Rail edge acoustic system for detecting train fan fault |
| CN113341251A (en) * | 2021-06-02 | 2021-09-03 | 启晗电力建设集团有限公司 | Power transmission and transformation site construction monitoring system |
| CN115875008A (en) * | 2023-01-06 | 2023-03-31 | 四川省川建勘察设计院有限公司 | Intelligent drilling data acquisition method and system for geological drilling machine and storage medium |
-
2018
- 2018-05-31 CN CN201820831184.XU patent/CN208224838U/en active Active
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110672950A (en) * | 2019-10-08 | 2020-01-10 | 深圳海岸语音技术有限公司 | Power equipment fault sound image detection system and method |
| CN111189530A (en) * | 2020-01-20 | 2020-05-22 | 成都铁安科技有限责任公司 | Rail edge acoustic system for detecting train fan fault |
| CN113341251A (en) * | 2021-06-02 | 2021-09-03 | 启晗电力建设集团有限公司 | Power transmission and transformation site construction monitoring system |
| CN113341251B (en) * | 2021-06-02 | 2024-02-27 | 启晗电力建设集团有限公司 | Power transmission and transformation field construction monitoring system |
| CN115875008A (en) * | 2023-01-06 | 2023-03-31 | 四川省川建勘察设计院有限公司 | Intelligent drilling data acquisition method and system for geological drilling machine and storage medium |
| CN115875008B (en) * | 2023-01-06 | 2023-06-13 | 四川省川建勘察设计院有限公司 | Intelligent drilling data acquisition method, system and storage medium of geological drilling machine |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN208224838U (en) | A kind of EMU sound fault diagnosis system | |
| CN108594795A (en) | A kind of EMU sound fault diagnosis system and diagnostic method | |
| CN204556257U (en) | A kind of rolling stock rolling bearing acoustic diagnostic instrument | |
| CN107458383B (en) | Automatic detection of vehicle faults using audio signals | |
| CN105115605A (en) | Track train infrared detection system and detection method | |
| CN109460007B (en) | Abnormal sound diagnosis and driving decision method for hybrid electric vehicle | |
| CN102998130B (en) | Fault detecting method for train suspension system of data driving based on acceleration measuring | |
| CN108362508A (en) | Auto NVH detection device, method and automobile remaining life appraisal procedure | |
| CN211374073U (en) | Automobile fault remote diagnosis system | |
| CN110379437A (en) | The method and apparatus of runner wagon internal fault | |
| WO2023138581A1 (en) | Method and apparatus for detecting polygonal fault of wheel set of rail transit locomotive | |
| CN209055845U (en) | A kind of high-speed EMUs driving faults monitoring and fault diagnosis system | |
| CN103700220A (en) | Fatigue driving monitoring device | |
| CN110631832A (en) | Subway vehicle bearing fault on-line detection method | |
| CN110726568A (en) | NVH testing device and method for fuel cell vehicle | |
| CN113447270B (en) | Acoustic monitoring system and method for traction motor bearing of railway vehicle | |
| CN114264491B (en) | Rail vehicle wheel set parameter detection system | |
| CN202939486U (en) | Automobile fault remote diagnosis system | |
| CN109019349B (en) | Fault detection method, detector, computer storage medium and crane | |
| CN108111583B (en) | Bogie rotating part safety monitoring system based on wireless sensor network | |
| CN110985424A (en) | Intelligent diagnosis system and method for fan faults of motor train unit | |
| CN208044677U (en) | Vehicle monitoring system | |
| CN110758456A (en) | Wheel rail health state monitoring system and method | |
| CN116331069A (en) | Portable bow net detection track inspection vehicle detection system with power | |
| CN114544205A (en) | Automatic fault diagnosis system for locomotive wheel drive running-in test |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP03 | Change of name, title or address |
Address after: 9th floor, No. 61 Zhichun Road, Haidian District, Beijing, 100190 Patentee after: Beijing Aerospace Shenzhou Intelligent Equipment Technology Co.,Ltd. Patentee after: BEIJING AEROSPACE CTROWELL INFORMATION TECHNOLOGY CO.,LTD. Address before: 100080 No. 61, Haidian District, Beijing, Zhichun Road Patentee before: BEIJING CTROWELL INFRARED TECHNOLOGY Co.,Ltd. Patentee before: BEIJING AEROSPACE CTROWELL INFORMATION TECHNOLOGY CO.,LTD. |
|
| CP03 | Change of name, title or address |