CN111071300B - High-speed train rail transit fault safety monitoring and early warning system and signal processing method - Google Patents
High-speed train rail transit fault safety monitoring and early warning system and signal processing method Download PDFInfo
- Publication number
- CN111071300B CN111071300B CN202010087853.9A CN202010087853A CN111071300B CN 111071300 B CN111071300 B CN 111071300B CN 202010087853 A CN202010087853 A CN 202010087853A CN 111071300 B CN111071300 B CN 111071300B
- Authority
- CN
- China
- Prior art keywords
- train
- vibration
- rail
- monitoring
- optical
- 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
- 238000012544 monitoring process Methods 0.000 title claims abstract description 74
- 238000003672 processing method Methods 0.000 title claims abstract description 16
- 230000003287 optical effect Effects 0.000 claims abstract description 81
- 238000001514 detection method Methods 0.000 claims abstract description 43
- 239000013307 optical fiber Substances 0.000 claims abstract description 37
- 239000013598 vector Substances 0.000 claims abstract description 24
- 230000001427 coherent effect Effects 0.000 claims abstract description 18
- 238000000034 method Methods 0.000 claims abstract description 15
- 238000004458 analytical method Methods 0.000 claims abstract description 11
- 238000001228 spectrum Methods 0.000 claims abstract description 6
- 238000010183 spectrum analysis Methods 0.000 claims abstract description 6
- 230000036541 health Effects 0.000 claims description 39
- 230000008878 coupling Effects 0.000 claims description 37
- 238000010168 coupling process Methods 0.000 claims description 37
- 238000005859 coupling reaction Methods 0.000 claims description 37
- 238000004891 communication Methods 0.000 claims description 24
- 238000004422 calculation algorithm Methods 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 12
- 238000000605 extraction Methods 0.000 claims description 8
- 230000001360 synchronised effect Effects 0.000 claims description 6
- 238000012935 Averaging Methods 0.000 claims description 4
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 230000009467 reduction Effects 0.000 claims description 4
- 238000012549 training Methods 0.000 claims description 4
- 238000010276 construction Methods 0.000 claims description 3
- 238000003909 pattern recognition Methods 0.000 claims description 3
- 238000012567 pattern recognition method Methods 0.000 claims description 3
- 238000005259 measurement Methods 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000002708 enhancing effect Effects 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000004643 material aging Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000000725 suspension Substances 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
- B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
- B61L23/042—Track changes detection
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L15/00—Indicators provided on the vehicle or train for signalling purposes
- B61L15/009—On-board display devices
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
- B61L27/70—Details of trackside communication
Landscapes
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Train Traffic Observation, Control, And Security (AREA)
Abstract
The invention discloses a train track traffic fault safety monitoring and early warning system and a signal processing method, wherein a vibration sensing system based on Sagnac interference and a phase sensitive optical time domain reflection vibration detection system based on coherent detection are combined to monitor damage to a bogie and a rail. Monitoring the vibration of the bogie through a Sagnac interferometer, deploying a distributed optical fiber at the outer side of the rail, and monitoring the vibration of the rail by using a phase-sensitive optical time domain reflection vibration detection system; and performing time-frequency analysis by using short-time Fourier transform, establishing a frequency spectrum characteristic database for performing frequency spectrum analysis, establishing a vibration characteristic vector, and performing vibration mode identification by using a related vector product to realize monitoring and early warning on the running state of the train and the safe and healthy damage of the track. The method has the advantages of being safe in nature, high in signal measurement precision, capable of directly reducing signal phase information, high in reliability, good in real-time performance, long in sensing distance, capable of obtaining early warning information of rail transit hazards of the train in advance and the like.
Description
Technical Field
The invention relates to the technical field of distributed optical fiber sensing and the field of train track detection, in particular to a high-speed train track traffic fault safety monitoring and early warning system and a signal processing method.
Background
At present, many rail transit projects at home and abroad have potential safety hazards in different degrees. Health monitoring of trains and tracks plays a crucial role in the safety of people's life and property. With the increase of the operation time of the rail transit engineering and the long-time running of the train, due to the influence of adverse factors such as the action of environmental load, fatigue effect, corrosion and material aging, the bogie which is positioned at the bottom layer of the train and is used for supporting the whole train body and the rail structure in the rail transit inevitably generate damage accumulation and resistance attenuation. If the damage is not discovered and treated in time, the damage can be rapidly expanded, and once the damage of the key structural components is accumulated to a certain degree, the damage of the whole structure can be caused, so that the irretrievable tragedy is caused. Therefore, it is necessary to monitor and warn the bottom bogie and track of the train for fault safety and health.
Traditional rail detecting system is expensive, mostly is point type electricity sensor, lays and maintains the difficulty, and the real-time is poor, and the limitation is great, so urgently needed one kind can carry out full distributed on-line monitoring, carry out the system that the fault safety health detected the early warning to train bottom bearing structure and rail structure to the rail. At present, all the structural safety monitoring on the train bogie is an electrical point type sensor, and information cannot be acquired at the first time if the structure is damaged; the most popular phase-sensitive optical time domain reflection system based on direct detection at present can only realize simple positioning of vibration due to the principle limitation, cannot directly restore the phase information of the vibration, and has short sensing distance and poor signal-to-noise ratio. In addition, the existing layout scheme of the phase-sensitive optical time domain vibration sensing system is to collect signals by using the existing communication optical cable laid in the railway system, and because the communication optical cable does not directly contact with a rail and a roadbed, the efficiency of vibration coupling to the optical fiber is low, the sensitivity of the system to vibration detection is influenced, and therefore high-precision real-time health and safety detection on damage to a train bogie and the rail is influenced.
Disclosure of Invention
The invention provides a rail transit fault safety monitoring and early warning system and a signal processing method for a high-speed train, aiming at carrying out safety early warning and monitoring on a plurality of bogies at the bottom layer of the train and the damage health state of a rail respectively by using two technologies through combining a vibration detection system based on the Sagnac interference principle and a vibration detection system based on the coherent light time domain reflection technology; in the signal processing method of the remote monitoring center, short-time Fourier transform is used for time-frequency analysis, data are fused for frequency spectrum analysis, frequency spectrum feature libraries are respectively established, corresponding vibration feature vectors are further established, a relevant vector machine mode recognition model is trained and feature extraction is carried out, and finally a mode recognition scheme is established, so that intelligent recognition and detection of train running states and track safety and health damage are achieved, and the monitoring and early warning effects are achieved.
The technical scheme provided by the invention is a rail transit fault safety monitoring and early warning system for a high-speed train, distributed optical fibers are laid on two sides of a framework plane of a plurality of bogies at the bottom layer of the train and are coupled and fixed, so that the direct detection of the vibration of two sides of the framework of the bogie is realized, and the framework is connected to a dual-optical switch module, so that the synchronous detection and monitoring of the plurality of bogies are realized; optical cables are directly distributed on the outer sides of the two tracks and are in strong coupling fixation with the rails, and meanwhile, the other ends of the optical cables are connected with the optical switches, so that synchronous monitoring of the multiple rails is realized; the system comprises:
train bogie structural damage health monitoring subsystem deploys in train digital monitoring room, includes: the system comprises a Sagnac interferometer, a double-optical switch module, a high-speed data acquisition module, a first data display device, a first network communication port, a train bogie frame, a vibration detection optical fiber ring at the first side of the train bogie frame and a vibration detection optical fiber ring at the second side of the train bogie frame; the Sagnac interferometer is connected with the double-optical switch module and the data high-speed acquisition module, and the data high-speed acquisition module is sequentially connected with the first data display device and the first network communication port; the train bogie frame first side vibration detection optical fiber ring and the train bogie frame second side vibration detection optical fiber ring are respectively and fixedly arranged on two sides of the train bogie frame and are respectively connected with the double-optical switch module;
the system comprises a data high-speed acquisition module, a remote monitoring center, a data processing module, a data transmission module and a data transmission module, wherein the Sagnac interferometer is connected with a dual-optical switch module and used for detecting multiple paths of optical fibers laid on a bogie;
the track structure damage health monitoring subsystem is deployed in the railway track monitoring machine room along the railway, and comprises: the first data display device, the first network communication port, the optical switch, the coherent optical time domain reflectometer, the first outside coupling optical cable of the first track of the circuit, the second outside coupling optical cable of the first track of the circuit, the first outside coupling optical cable of the second track of the circuit, and the second outside coupling optical cable of the second track of the circuit; the coherent optical time domain reflectometer is connected with the optical switch and the second data display device, the second network communication port is connected with the second data display device, and the first outer side coupling optical cable of the first track, the second outer side coupling optical cable of the first track, the first outer side coupling optical cable of the second track and the second outer side coupling optical cable of the second track are respectively fixedly arranged at the outer sides of the corresponding tracks in a coupling way and are respectively connected with the optical switch;
the coherent optical time domain reflectometer is used for carrying out multi-path switching and real-time monitoring on the health damage states of the plurality of rails through the optical switch, the second data display device is connected with the coherent optical time domain reflectometer and is connected with the second network communication port, and the acquired data are displayed and transmitted to the remote monitoring center for signal processing.
In addition, the invention provides a processing method of a high-speed train and rail transit fault safety monitoring and early warning signal, which is used for carrying out signal analysis and processing on the data signal sent to a remote monitoring center by the high-speed train and rail transit fault safety monitoring and early warning system in the technical scheme, and comprises the following processing steps:
the method comprises the following steps: the remote monitoring center respectively receives vibration data from the train bogie structure health monitoring subsystem and the rail safety health monitoring subsystem;
step two: dividing the time domain signal by setting a window function and parameters;
step three: performing time-frequency conversion on the time domain signals through Fourier transform to obtain a plurality of short-time frequency signals;
step four: noise reduction and signal extraction are carried out through an accumulative averaging and peak searching algorithm, and finally a long-time frequency domain signal of bogie and rail vibration is obtained;
step five: respectively establishing a vibration frequency spectrum characteristic library of the bogie and the track according to the long-time frequency domain signal;
step six: fusing each parameter and the two vibration feature libraries to perform spectrum analysis, and establishing corresponding vibration feature vectors;
step seven: carrying out model training and feature extraction on the correlation vector machine mode identification algorithm, determining parameters such as weight and correlation vector of the algorithm, and completing construction of a correlation vector machine mode identification scheme;
step eight: and short-time Fourier transform time-frequency analysis and a related vector machine are fused for pattern recognition, a train and track fault damage pattern recognition method model is established, and intelligent monitoring and early warning of the train running state and the track safety and health damage state are realized.
The invention discloses a high-speed train and rail transit fault safety monitoring and early warning system and a signal processing method, which have the following advantages and prominent innovation points:
the method comprises the steps that firstly, a train bogie structure damage health monitoring subsystem is designed and deployed on a train by combining the advantages of a Sagnac interference principle and a coherent detection phase sensitive optical time domain reflection technology, and a track structure damage health monitoring subsystem is designed and deployed in a railway track monitoring machine room along a railway;
designing a signal processing method of a high-speed train and rail transit fault safety monitoring and early warning system, fusing a short-time Fourier transform time-frequency analysis method to carry out high-precision restoration on frequency signals, and carrying out classification and identification on various vibration modes by a machine learning algorithm-related vector machine, and finally realizing intelligent monitoring and early warning on the health damage states of train bogies and rail structures;
three, two sensor layout modes: arranging and fixedly mounting Sagnac vibration detection optical fiber rings on two sides of a framework plane of a train bogie to realize monitoring of the health state of the bogie; and (3) laying and fixing distributed optical fibers at the peripheries of two sides of the rail, performing strong coupling, enhancing the efficiency of coupling rail vibration to the optical fibers, and realizing monitoring of the damage state of the rail.
Drawings
Fig. 1 is a schematic structural diagram of a train bogie structural damage health monitoring subsystem of a high-speed train rail transit fault safety monitoring and early warning system provided by the invention.
Fig. 2 is a schematic structural diagram of a track structure damage health monitoring subsystem of the rail transit fault safety monitoring and early warning system for the high-speed train provided by the invention.
Fig. 3 is a schematic flow chart of a method for processing a rail transit fault safety monitoring and early warning signal of a high-speed train provided by the invention.
In the figure, 1, sagnac interferometer; 2. a dual-optical switch module; 3. a data high-speed acquisition module; 4. a first data display device; 5. a first network communication port; 6. a train bogie frame; 7. a vibration detection optical fiber ring is arranged on the first side of the train bogie frame; 8. a vibration detection optical fiber ring is arranged on the second side of the train bogie frame; 9. a second data display device; 10. a second network communication port; 11. an optical switch; 12. a coherent optical time domain reflectometer; 13. a first outer side coupling optical cable of a track of the line; 14. a second outside coupling optical cable of the first track of the circuit; 15. a first outer side coupling optical cable of a second track of the line; 16. and the second track of the circuit is coupled with the optical cable at the second outer side.
Detailed Description
The technical solution of the present invention will be further described in more detail with reference to the following embodiments. It is to be understood that the described embodiments are merely a few embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The working principle and the specific working process of the high-speed train and rail transit fault safety monitoring and early warning system of the invention are further described with reference to the attached drawings 1, 2 and 3:
as shown in fig. 1 and 2, the invention provides a rail transit fault safety monitoring and early warning system for a high-speed train. The bogie at the bottom of the train mainly comprises a framework, a wheel set, an axle box, a suspension device driving device and a foundation braking device, wherein the framework is used as an installation framework and a supporting foundation of the bogie, and the structural health state of the framework influences the safe operation of the whole bogie, so that distributed optical fiber vibration detection rings are laid on two sides of the framework plane of a plurality of bogies at the bottom of the train and are coupled and fixed to realize the direct detection of the vibration of the two sides of the bogie framework, and the optical fiber rings are connected with a dual-optical switch module to realize the synchronous detection and monitoring of the plurality of bogies; optical cables are directly distributed on the outer sides of the two tracks and are in strong coupling fixation with the rails, and meanwhile, the other ends of the optical cables are connected with the optical switches, so that synchronous monitoring of the multiple rails is realized; the system comprises:
train bogie structural damage health monitoring subsystem deploys in train digital monitoring room, includes: the system comprises a Sagnac interferometer 1, a double-optical switch module 2, a high-speed data acquisition module 3, a first data display device 4, a first network communication port 5, a train bogie frame 6, a train bogie frame first side vibration detection optical fiber ring 7 and a train bogie frame second side vibration detection optical fiber ring 8; the Sagnac interferometer 1 is connected with the double-optical switch module 2 and the data high-speed acquisition module 3, and the data high-speed acquisition module 3 is sequentially connected with the first data display device 4 and the first network communication port 5; the vibration detection optical fiber ring 7 at the first side of the train bogie frame and the vibration detection optical fiber ring 8 at the second side of the train bogie frame are respectively and fixedly arranged at two sides of the train bogie frame 6 and are respectively connected with the double-light switch module 2;
the system comprises a Sagnac interferometer 1, a double-optical switch module 2, a data high-speed acquisition module 3, a first data display device 4, a remote monitoring center and a signal processing method, wherein the Sagnac interferometer 1 is connected with the double-optical switch module 2 and used for detecting multiple paths of optical fibers laid on a bogie;
the track structure harms health monitoring subsystem and deploys the computer lab along the railway, includes: a second data display device 9, a second network communication port 10, an optical switch 11, a coherent optical time domain reflectometer 12, a line-one-rail first outside coupled optical cable 13, a line-one-rail second outside coupled optical cable 14, a line-two-rail first outside coupled optical cable 15, a line-two-rail second outside coupled optical cable 16; the coherent optical time domain reflectometer 12 is connected with the optical switch 11 and the second data display device 9, the second network communication port 10 is connected with the second data display device 9, and the first outside coupling optical cable 13 of the first track, the second outside coupling optical cable 14 of the first track, the first outside coupling optical cable 15 of the second track and the second outside coupling optical cable 16 of the second track are respectively fixedly coupled at the outer sides of the corresponding tracks and are respectively connected with the optical switch 11;
the coherent optical time domain reflector 12 performs multi-path switching through the optical switch 11 to monitor the health damage state of the plurality of rails in real time, the second data display device 9 is connected with the coherent optical time domain reflector 12 and the second network communication port 10, displays the acquired data and transmits the data to the remote monitoring center for signal processing.
Two vibration detection optical fiber rings, namely a vibration detection optical fiber ring 7 at the first side of the train bogie frame and a vibration detection optical fiber ring 8 at the second side of the train bogie frame, are respectively fixed at two sides of a bogie frame 6 at the bottom layer of the train according to the attached diagram 1, and are strongly coupled to be completely attached and fixed on the frame. In the running process of a train, vibration information of a bogie is transmitted to a double-optical switch module 2 through a detection optical fiber, and then transmitted to a sagnac interferometer 1 through the double-optical switch module 2 to demodulate a vibration signal, further, the sagnac interferometer 1 transmits the demodulated vibration signal to a first data display device 4 through a data high-speed acquisition module 3, and finally the first data display device 4 is connected with a first network communication port 5, and the acquired vibration signal is transmitted to a remote digital monitoring center through the equipment to be further processed.
Distributed optical fibers are respectively arranged on the outer sides of the rails of the track system according to the diagram shown in fig. 2, namely, a first outer side coupling optical cable 13 of a first rail of a line, a second outer side coupling optical cable 14 of the first rail of the line, a first outer side coupling optical cable 15 of a second rail of the line and a second outer side coupling optical cable 16 of the second rail of the line are respectively fixedly coupled and arranged on the outer sides of the corresponding rails, then the optical cables extend into a track monitoring machine room of the railway along the railway and are connected with an optical switch 11, the optical switch 11 is connected with a coherent optical time domain reflectometer 12 to perform preliminary demodulation on data, after the data acquisition is completed, a preliminary demodulation result of a vibration signal is transmitted to a second data display device 9, and the data preliminarily demodulated by a demodulator is transmitted to a remote monitoring center through a second network communication port 10 for further data processing.
Fig. 3 shows a signal processing method of a high-speed train and rail transit fault safety monitoring and early warning system. The method comprises the following steps:
the method comprises the following steps: the remote monitoring center respectively receives vibration data from the train bogie structure health monitoring subsystem and the rail safety health monitoring subsystem;
step two: dividing the time domain signal by setting a window function and parameters;
step three: performing time-frequency conversion on the time domain signals through Fourier transform to obtain a plurality of short-time frequency signals;
step four: noise reduction and signal extraction are carried out through an accumulative averaging and peak searching algorithm, and finally a long-time frequency domain signal of bogie and rail vibration is obtained;
step five: respectively establishing a vibration frequency spectrum characteristic library of the bogie and the track according to the long-time frequency domain signal;
step six: fusing each parameter and the two vibration feature libraries to perform spectrum analysis, and establishing corresponding vibration feature vectors;
step seven: carrying out model training and feature extraction on the correlation vector machine mode identification algorithm, determining parameters such as weight and correlation vector of the algorithm, and completing construction of a correlation vector machine mode identification scheme;
step eight: and short-time Fourier transform time-frequency analysis and a related vector machine are fused for pattern recognition, a train and track fault damage pattern recognition method model is established, and intelligent monitoring and early warning of the train running state and the track safety and health damage state are realized.
The method integrates a time-frequency analysis method of short-time Fourier transform and a correlation vector product mode identification method, and is used for signal analysis and processing of a remote monitoring center. In the processing method, firstly, vibration data from a train bogie structure health monitoring subsystem and a rail safety health monitoring subsystem are respectively received, and time domain signals are segmented through setting of window functions and parameters; then, performing time-frequency conversion on the time domain signals through Fourier transform to obtain a plurality of short-time frequency spectrum signals; and then noise reduction and signal extraction are carried out through an accumulative averaging and peak searching algorithm, and finally a long-time frequency domain signal of bogie and track vibration is obtained. And then according to multi-data fusion spectrum analysis, vibration frequency characteristics of the bogie and the rail in various modes such as strong vibration of the impact rail under various position states of the train in a tunnel, a tunnel portal, a mountainous area, a plain area and the like are obtained, corresponding vibration characteristic vectors are established for training and identifying a relevant vector machine mode identification algorithm, and finally a train and rail fault damage state mode identification method model is established, so that early warning monitoring of the train running state and the rail safety and health damage state is realized.
The existing distribution scheme of the phase sensitive optical time domain vibration sensing system is to collect signals by using the existing communication optical cable laid in the railway system, and because the communication optical cable does not directly contact with a rail and a roadbed, the efficiency of vibration coupling to the optical fiber is very low, and the detection sensitivity of the system is seriously influenced. In addition, the existing train bogie detection device is a point type electrical sensor, and structural health damage detection cannot be realized.
Different from the prior art, the novel high-speed train and rail transit fault safety monitoring and early warning system, the implementation method and the signal processing method thereof have the following advantages and prominent innovation points:
the method comprises the steps that firstly, a train bogie structure damage health monitoring subsystem is designed and deployed on a train by combining the advantages of a Sagnac interference principle and a coherent detection phase sensitive optical time domain reflection technology, and a track structure damage health monitoring subsystem is designed and deployed in a railway track monitoring machine room along a railway;
designing a signal processing method of a high-speed train and rail transit fault safety monitoring and early warning system, fusing a short-time Fourier transform time-frequency analysis method to carry out high-precision restoration on frequency signals, and identifying various vibration modes by a machine learning algorithm-related vector machine, and finally realizing intelligent monitoring and early warning on the health damage states of train bogie and rail structures;
three, two sensor layout modes: arranging and fixedly mounting Sagnac vibration detection optical fiber rings on two sides of a framework plane of a train bogie to realize monitoring of the health state of the bogie; and (3) laying and fixing distributed optical fibers at the peripheries of two sides of the rail, performing strong coupling, enhancing the efficiency of coupling rail vibration to the optical fibers, and realizing monitoring of the damage state of the rail.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (2)
1. A high-speed train rail transit fault safety monitoring and early warning system is characterized in that distributed optical fiber vibration detection optical fiber rings are laid on two sides of a framework plane of a plurality of bogies at the bottom layer of a train and are coupled and fixed, so that the direct detection of the vibration of two sides of the framework of the bogie is realized, and the bogie is connected to a double-optical switch module, so that the synchronous detection and monitoring of the plurality of bogies are realized; optical cables are directly distributed on the outer sides of the two tracks and are in strong coupling fixation with the rails, and meanwhile, the other ends of the optical cables are connected with the optical switches, so that synchronous monitoring of the multiple rails is realized; characterized in that the system comprises: train bogie structural damage health monitoring subsystem deploys in train digital monitoring room, includes: the system comprises a Sagnac interferometer (1), a double-optical switch module (2), a high-speed data acquisition module (3), a first data display device (4), a first network communication port (5), a train bogie framework (6), a vibration detection optical fiber ring (7) at the first side of the train bogie framework and a vibration detection optical fiber ring (8) at the second side of the train bogie framework; the Sagnac interferometer (1) is connected with the double-optical switch module (2) and the data high-speed acquisition module (3), and the data high-speed acquisition module (3) is sequentially connected with the first data display device (4) and the first network communication port (5); a vibration detection optical fiber ring (7) at the first side of the train bogie frame and a vibration detection optical fiber ring (8) at the second side of the train bogie frame are respectively and fixedly arranged at the two sides of the train bogie frame (6) and are respectively connected with the double-light switch module (2); the system comprises a Sagnac interferometer (1), a double-optical switch module (2), a data high-speed acquisition module (3), a first data display device (4), a remote monitoring center and a signal processing method, wherein the Sagnac interferometer (1) is connected with the double-optical switch module (2) and used for detecting multi-path optical fibers laid on a bogie, the data high-speed acquisition module is used for transmitting data acquired by the Sagnac interferometer (1) to the first data display device (4) for display, and meanwhile, the data is transmitted to the remote monitoring center through a first network communication port (5) for data processing and display; the track structure damage health monitoring subsystem is deployed in the railway track monitoring machine room along the railway, and comprises: a second data display device (9), a second network communication port (10), an optical switch (11), a coherent optical time domain reflectometer (12), a line-first rail first outside coupling optical cable (13), a line-first rail second outside coupling optical cable (14), a line-second rail first outside coupling optical cable (15), a line-second rail second outside coupling optical cable (16); the coherent light time domain reflectometer (12) is connected with the optical switch (11) and the second data display device (9), the second network communication port (10) is connected with the second data display device (9), and the first outer side coupling optical cable (13) of the first track, the second outer side coupling optical cable (14) of the first track, the first outer side coupling optical cable (15) of the second track and the second outer side coupling optical cable (16) of the second track are respectively fixedly coupled at the outer sides of the corresponding tracks and are respectively connected with the optical switch (11); the coherent optical time domain reflectometer (12) carries out multi-path switching through the optical switch (11) to monitor the health damage states of the plurality of rails in real time, the second data display device (9) is connected with the coherent optical time domain reflectometer (12) and is connected with the second network communication port (10), and the acquired data are displayed and transmitted to the remote monitoring center for signal processing.
2. A processing method of a high-speed train rail transit fault safety monitoring and early warning signal is used for carrying out signal analysis and processing on a data signal which is sent to a remote monitoring center by the high-speed train and rail transit fault safety monitoring and early warning system in claim 1, and is characterized by comprising the following processing steps: the method comprises the following steps: the remote monitoring center respectively receives vibration data from the train bogie structure health monitoring subsystem and the rail safety health monitoring subsystem; step two: dividing the time domain signal by setting a window function and parameters; step three: performing time-frequency conversion on the time domain signals through Fourier transform to obtain a plurality of short-time frequency signals; step four: noise reduction and signal extraction are carried out through an accumulative averaging and peak searching algorithm, and finally a long-time frequency domain signal of bogie and rail vibration is obtained; step five: respectively establishing a vibration frequency spectrum characteristic library of the bogie and the track according to the long-time frequency domain signal; step six: fusing each parameter and the two vibration feature libraries to perform spectrum analysis, and establishing corresponding vibration feature vectors; step seven: carrying out model training and feature extraction on the correlation vector machine mode identification algorithm, determining parameters such as weight and correlation vector of the algorithm, and completing construction of a correlation vector machine mode identification scheme; step eight: and short-time Fourier transform time-frequency analysis and a related vector machine are fused for pattern recognition, a train and track fault damage pattern recognition method model is established, and intelligent monitoring and early warning of the train running state and the track safety and health damage state are realized.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010087853.9A CN111071300B (en) | 2020-02-12 | 2020-02-12 | High-speed train rail transit fault safety monitoring and early warning system and signal processing method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010087853.9A CN111071300B (en) | 2020-02-12 | 2020-02-12 | High-speed train rail transit fault safety monitoring and early warning system and signal processing method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111071300A CN111071300A (en) | 2020-04-28 |
| CN111071300B true CN111071300B (en) | 2021-12-14 |
Family
ID=70324224
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010087853.9A Active CN111071300B (en) | 2020-02-12 | 2020-02-12 | High-speed train rail transit fault safety monitoring and early warning system and signal processing method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111071300B (en) |
Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111537056A (en) * | 2020-07-08 | 2020-08-14 | 浙江浙能天然气运行有限公司 | Pipeline along-line third-party construction dynamic early warning method based on SVM and time-frequency domain characteristics |
| CN111845843A (en) * | 2020-07-13 | 2020-10-30 | 南京大学 | High-speed rail safe operation detection method based on optical fiber distributed vibration monitoring |
| CN111884709B (en) * | 2020-07-20 | 2021-09-14 | 中铁第四勘察设计院集团有限公司 | Railway communication optical cable on-line monitoring system and method |
| CN112033674B (en) * | 2020-08-07 | 2022-03-15 | 太原理工大学 | Train fault online detection system and method |
| CN112225024A (en) * | 2020-10-28 | 2021-01-15 | 中建七局第一建筑有限公司 | Traction type elevator fault analysis method |
| CN113418590A (en) * | 2021-07-19 | 2021-09-21 | 安徽徽一通讯科技有限公司 | Method for monitoring railway signal by optical fiber sensing |
| CN114544206B (en) * | 2022-01-20 | 2023-07-07 | 清华大学 | Polygonal fault detection method and device for wheel set of rail transit locomotive |
| CN114684217B (en) * | 2022-03-16 | 2024-03-01 | 武汉理工大学 | Rail transit health monitoring system and method |
| CN114633774A (en) * | 2022-03-30 | 2022-06-17 | 东莞理工学院 | Rail transit fault detection system based on artificial intelligence |
| CN115406490A (en) * | 2022-11-02 | 2022-11-29 | 高勘(广州)技术有限公司 | Optical cable pipeline monitoring method, device, equipment and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1676389A (en) * | 2004-03-29 | 2005-10-05 | 香港理工大学 | System and process for monitoring railway tracks |
| CN101487723A (en) * | 2009-03-02 | 2009-07-22 | 北京航空航天大学 | Optical fiber distributed perturbation sensor based on Sagnac interferometer |
| CN103175849A (en) * | 2013-04-17 | 2013-06-26 | 黑龙江大学 | Optical fiber on-line vehicle bearing fault detection device |
| CN203376168U (en) * | 2013-04-23 | 2014-01-01 | 南车青岛四方机车车辆股份有限公司 | High-speed train bogie system state real-time monitoring apparatus |
| CN106323442A (en) * | 2016-08-18 | 2017-01-11 | 南京发艾博光电科技有限公司 | Railway health monitoring method based on distributed optical fiber vibration sensing system |
| CN106394612A (en) * | 2016-10-24 | 2017-02-15 | 南京派光信息技术有限公司 | Crossing train approaching real-time pre-warning system and method based on distributed optical fibers |
| EP3531078A1 (en) * | 2018-02-21 | 2019-08-28 | Frauscher Sensortechnik GmbH | Evaluation unit, tracking system and method for evaluating a digital signal |
-
2020
- 2020-02-12 CN CN202010087853.9A patent/CN111071300B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1676389A (en) * | 2004-03-29 | 2005-10-05 | 香港理工大学 | System and process for monitoring railway tracks |
| CN101487723A (en) * | 2009-03-02 | 2009-07-22 | 北京航空航天大学 | Optical fiber distributed perturbation sensor based on Sagnac interferometer |
| CN103175849A (en) * | 2013-04-17 | 2013-06-26 | 黑龙江大学 | Optical fiber on-line vehicle bearing fault detection device |
| CN203376168U (en) * | 2013-04-23 | 2014-01-01 | 南车青岛四方机车车辆股份有限公司 | High-speed train bogie system state real-time monitoring apparatus |
| CN106323442A (en) * | 2016-08-18 | 2017-01-11 | 南京发艾博光电科技有限公司 | Railway health monitoring method based on distributed optical fiber vibration sensing system |
| CN106394612A (en) * | 2016-10-24 | 2017-02-15 | 南京派光信息技术有限公司 | Crossing train approaching real-time pre-warning system and method based on distributed optical fibers |
| EP3531078A1 (en) * | 2018-02-21 | 2019-08-28 | Frauscher Sensortechnik GmbH | Evaluation unit, tracking system and method for evaluating a digital signal |
Non-Patent Citations (1)
| Title |
|---|
| 光纤传感器在轨道交通领域的应用前景概述;王飞等;《计算机与数字工程》;20150531;第43卷(第05期);正文第4.1节 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111071300A (en) | 2020-04-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111071300B (en) | High-speed train rail transit fault safety monitoring and early warning system and signal processing method | |
| Wei et al. | A fiber Bragg grating sensor system for train axle counting | |
| US8985523B2 (en) | Railway system using acoustic monitoring | |
| Boffi et al. | Optical fiber sensors to measure collector performance in the pantograph-catenary interaction | |
| CN106828543A (en) | A kind of optical fiber distributed type train monitoring system | |
| CN104401360A (en) | Multi-means fusion-based safety real-time monitoring method and multi-means fusion-based safety real-time monitoring system for railway track system | |
| CN104374465A (en) | Subway low-frequency vibration test device and method based on fiber bragg grating sensors | |
| CN111442788A (en) | Health monitoring method and system for overhead transmission line | |
| Nedoma et al. | Non-destructive fiber-optic sensor system for the measurement of speed in road traffic | |
| CN110281984A (en) | High-speed maglev train positioning system and localization method based on optical frequency domain reflection technology | |
| CN105806637A (en) | General testing system of railway vehicles | |
| CN110631681A (en) | High-speed rail safe operation detection method based on optical fiber distributed vibration monitoring | |
| Boffi | Sensing applications in deployed telecommunication fiber infrastructures | |
| CN210284245U (en) | Track shunting failure monitoring system based on optical fiber sensing | |
| CN113715873B (en) | phi-OTDR dynamic nano-strain real-time positioning system of urban rail transit train | |
| Espinosa et al. | Detector of electrical discontinuity of rails in double-track railway lines: electronic system and measurement methodology | |
| CN204214542U (en) | Based on fiber-optic grating sensor subway low-frequency vibration testing apparatus | |
| CN109959847B (en) | Optical fiber passive pollution flashover monitoring system | |
| US11733070B2 (en) | Street light operating status monitoring using distributed optical fiber sensing | |
| CN117451163A (en) | Power optical cable monitoring system based on double-flow convolutional neural network algorithm | |
| US12078528B2 (en) | Fiber sensing using supervisory path of submarine cables | |
| CN107976610A (en) | A kind of bow net pulls out value calculating method and its device | |
| CN114084198A (en) | Train state identification and warning system and method based on distributed sound wave sensing | |
| CN113067650A (en) | BTM signal and interference analysis processing apparatus | |
| WO2020116031A1 (en) | Railroad monitoring system, railroad monitoring device, railroad monitoring method, and non-transitory computer-readable medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |