CN115294709A - Optical fiber vibration monitoring model, precaution system, electronic equipment and storage medium - Google Patents
Optical fiber vibration monitoring model, precaution system, electronic equipment and storage medium Download PDFInfo
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- CN115294709A CN115294709A CN202210919853.XA CN202210919853A CN115294709A CN 115294709 A CN115294709 A CN 115294709A CN 202210919853 A CN202210919853 A CN 202210919853A CN 115294709 A CN115294709 A CN 115294709A
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- G08B13/00—Burglar, theft or intruder alarms
- G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
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- G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
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Abstract
The invention provides an optical fiber vibration monitoring model, which is used for sending signals, receiving return signals, processing and analyzing the return signals and monitoring perimeter safety in real time, wherein the monitoring model comprises a physical layer, a monitoring module and a monitoring module, wherein the physical layer is positioned at the bottommost layer of the monitoring model and is used for constructing and reusing an optical fiber sensing communication platform; the realization layer is used for acquiring and processing information through basic equipment to realize micro-vibration sensing, signal mediation and signal positioning; the algorithm layer is used for receiving and analyzing the information processed by the implementation layer, and realizing neural network identification, time sequence analysis, support vector machine and event discrimination and analysis; the application layer is used for displaying the analysis result of the algorithm layer and performing man-machine interaction, and intelligent alarming, GIS positioning marking, informatization application integration and self-adaptive learning are achieved. Based on the optical fiber vibration monitoring model, the invention also provides a long-distance perimeter safety precaution system which is used for monitoring and identifying the invasion events occurring on the defense deployment perimeter in real time and sending out corresponding alarm and positioning.
Description
Technical Field
The invention belongs to the technical field of perimeter precaution, and particularly relates to an optical fiber vibration monitoring model, a precaution system, electronic equipment and a storage medium.
Background
The perimeter precaution means that a visible or invisible protective wall is formed at the boundary of a protective area by utilizing the technologies of microwave, infrared, electronic fence and the like, if a person passes through or wants to pass through, the corresponding detector can send out an alarm signal to an alarm control host of a security duty room or a control center, and simultaneously sends out sound-light alarm and displays the alarm position.
At present, most perimeter precaution systems are designed aiming at short distance and are not suitable for long-distance monitoring, for perimeter precaution systems in environments such as a motor train section, a motor train station, a railway line and the like, the types of intrusion behaviors cannot be accurately judged, misjudgment is easy to generate, vibration signals generated due to rain and snow environments, winged insects, animals and the like are judged as artificial intrusion, and therefore the workload is increased for security personnel; in addition, most of the existing perimeter precaution systems are independent systems, do not have a segmented management function, and are not beneficial to long-distance monitoring.
Disclosure of Invention
In view of the above problems in the prior art, it is an object of the present invention to provide an optical fiber vibration monitoring model, a countermeasure system, an electronic device, and a storage medium:
a fiber optic vibration monitoring model comprising: the monitoring model comprises a physical layer, an implementation layer, an algorithm layer and an application layer which are sequentially connected;
the physical layer is positioned at the bottommost layer of the monitoring model and comprises basic equipment used for constructing and reusing an optical fiber sensing communication platform;
the realization layer is used for acquiring and processing information through basic equipment to realize micro-vibration sensing, signal mediation, signal positioning and signal noise reduction enhancement;
the algorithm layer is used for receiving and analyzing the information processed by the implementation layer, and realizing neural network identification, time sequence analysis, support vector machine and event discrimination and analysis;
the application layer is used for displaying the analysis result of the algorithm layer and performing man-machine interaction, and intelligent alarming, GIS positioning marking, informatization application integration and self-adaptive learning are achieved.
In order to realize micro-vibration sensing through a sensing optical fiber, the basic equipment comprises a sensing controller, a signal processing module and a sensing module, wherein the sensing controller comprises a laser, a demodulator, an amplifier, a filter, a coupler and a photoelectric detector which are sequentially connected, the coupler is also coupled with the sensing module, and the photoelectric detector is connected with the signal processing module;
the sensing module comprises a sensing optical fiber and a light source, wherein the sensing optical fiber is used for receiving the detection light emitted by the coupler and transmitting the scattered light to the coupler;
the signal processing module comprises a digital-to-analog converter and a signal processing module which are connected with each other, the digital-to-analog converter is electrically connected with the photoelectric detector, the digital-to-analog converter is used for performing digital-to-analog conversion on signals transmitted by the photoelectric detector, and the signal processor is used for performing signal preprocessing, signal identification classification and event analysis on the signals subjected to digital-to-analog conversion to generate a classification result of an event, responding the classification result through an early warning application program and learning the increment of the classifier.
For processing the received signal by a signal processor, the signal pre-processing includes bandpass filtering, down-sampling and wavelet de-noising; the signal identification classification comprises segment segmentation, feature extraction and signal classification; the event analysis comprises intensity calculation, reliability calculation and positioning value correction; the early warning application program comprises early warning rules, man-machine interaction and new event recording; the classifier incremental learning includes new event training and classifier optimization.
The signal processor comprises a first-stage classifier based on a neural network and a second-stage classifier based on a voting mechanism, and the process of signal identification and classification is carried out by the signal processor, and the method specifically comprises the following steps:
s1, a first-stage classifier receives single segment characteristics of a signal and outputs a segment type of the signal after recognizing the segment characteristics based on a neural recognition network;
s2, the second-stage classifier receives the segment types of the signals and outputs event types through the segment types of the signals based on a voting mechanism;
s3, judging whether the event type is correct or not, storing correct data into a database, and storing wrong data into the database after manual revision and counting;
s4, triggering the classifier increment learning module to automatically operate when the accumulated number of error data of event classification reaches a threshold value;
and S5, the classifier increment learning module retrains the neural network of the first-stage classifier and updates the neural network parameters of the first-stage classifier.
Based on the optical fiber vibration monitoring model, the invention also provides a long-distance perimeter safety and protection system, which is used for monitoring and identifying the invasion event occurring on the defense perimeter in real time and sending out corresponding alarm and positioning, the safety and protection system is connected with an external system, the safety and protection system comprises,
the control center platform is used for monitoring the intrusion behavior, calculating and positioning the marked intrusion position, sending a corresponding alarm instruction and calling the visual tracking equipment to record the intrusion behavior; the control center platform comprises a first-level control center platform and at least one second-level control center platform which are in communication coupling with each other, and the second-level control center platform comprises a signal processor and is used for carrying out optical fiber vibration monitoring intrusion behavior and early warning;
a field device communicatively coupled to the control center platform, the field device comprising,
the front-end detection equipment is used for deploying perimeter intrusion behavior detection and returning detection data; the front-end detection equipment comprises a sensing optical fiber, an electronic fence and laser correlation;
the visual tracking equipment is used for receiving the alarm information sent by the control center platform, processing the alarm information to obtain specific alarm content, and calling the video monitoring terminal at the corresponding position to record video;
the sound and light alarm equipment is used for receiving an alarm instruction sent by the control center platform and sending an alarm signal;
the external system comprises a railway time synchronization system and a railway comprehensive video monitoring system, the railway comprehensive video monitoring system comprises at least one video monitoring terminal, and the video monitoring terminal is used for receiving signals of the visual tracking equipment and recording intrusion behaviors.
In order to realize the linkage of the long-distance perimeter safety precaution system and an external system, the first-level control center platform is in communication coupling with a railway time synchronization system, the second-level control center platform is in communication coupling with a railway comprehensive video monitoring system, the first-level control center platform and the second-level control center platform respectively comprise a user terminal, a management terminal, an application server and a database server, and the second-level control center platform further comprises an interface server.
An electronic device, the electronic device comprising:
a memory for storing executable instructions;
and the processor is used for realizing the long-distance perimeter safety precaution system when the executable instructions stored in the memory are executed.
A computer readable storage medium storing executable instructions that when executed by a processor implement the long-distance perimeter security system described above.
The invention has the beneficial effects that: the invention provides an optical fiber vibration monitoring model,
1. a distributed and reusable optical fiber sensing communication platform is constructed through infrastructure of a physical layer, so that functions of micro-vibration sensing, signal processing and signal analysis are realized, and the event type can be judged according to a vibration signal monitored by a sensing optical fiber and an application layer response is triggered;
2. the accuracy of classification results can be effectively improved by processing and analyzing signals through an algorithm layer and performing secondary classification through a two-stage classifier according to different rules; furthermore, a signal processor records new events and accumulates error information, and the result feedback is realized by means of classifier increment learning and the first-stage classifier is retrained, so that the accuracy of the classification result is further improved, and false alarm is avoided.
The invention provides a long-distance perimeter security system,
1. the system is characterized in that a first-stage control center platform is connected with a railway time synchronization system for general control, a second-stage control center platform is connected with a railway comprehensive video monitoring system and field equipment for real-time monitoring, segmented monitoring and management are realized by arranging a plurality of second-stage control center platforms, and long-distance monitoring can be segmented into short-distance monitoring and general control can be realized;
2. furthermore, the response efficiency of the precaution system can be improved through segmented monitoring, and when the vibration signal is monitored and the event is judged to be an invasion event, the video recording can be conveniently and quickly started by the video monitoring terminal at the corresponding position.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of the hierarchy of the monitoring model of the present invention;
FIG. 2 is a flow chart of the micro-vibration process of the present invention;
FIG. 3 is a flow chart of the digital to analog conversion of the present invention;
FIG. 4 is a signal processing flow diagram of the present invention;
FIG. 5 is a flow chart of the signal identification classification of the present invention;
fig. 6 is a schematic diagram of the monitoring system of the present invention.
Detailed Description
Example one
An optical fiber vibration monitoring model is used for sending signals, receiving return signals, processing and analyzing the return signals and monitoring perimeter safety in real time.
As shown in fig. 1, the monitoring model includes a physical layer, which is located at the lowest layer of the monitoring model and includes a basic device for constructing a reusable optical fiber sensing communication platform.
As shown in fig. 2, the basic device includes a sensing controller, a signal processing module and a sensing module, the sensing controller includes a laser, a demodulator, an amplifier, a filter, a coupler and a photodetector connected in sequence, the coupler is further coupled with the sensing module, the photodetector is connected with the signal processing module, the laser is used for emitting laser, the demodulator, the amplifier and the filter are used for processing the laser emitted by the sensor, and the coupler is used for dividing the processed laser into detection light and reference light, transmitting the detection light to the sensing module, receiving scattered light generated by the sensing module, and performing coherent reception processing with the reference light to transmit to the photodetector.
As shown in fig. 2, the sensing module includes a sensing fiber for receiving the probe light emitted from the coupler and transmitting the scattered light to the coupler.
As shown in fig. 2, the signal processing module includes a digital-to-analog converter and a signal processing module connected to each other, the digital-to-analog converter is electrically connected to the photodetector, the digital-to-analog converter is configured to perform digital-to-analog conversion on a signal transmitted by the photodetector, and the signal processor is configured to perform signal preprocessing, signal recognition and classification and event analysis on the signal after the digital-to-analog conversion to generate a classification result of an event, respond to the classification result through an early warning application program, and learn the classifier increment.
As shown in fig. 4, the signal pre-processing includes band-pass filtering, down-sampling and wavelet de-noising; the signal identification classification comprises segment segmentation, feature extraction and signal classification; the event analysis comprises intensity calculation, reliability calculation and positioning value correction; the early warning application program comprises early warning rules, man-machine interaction and new event recording; the classifier incremental learning includes new event training and classifier optimization.
As shown in fig. 5, the signal processor includes a first-stage classifier based on a neural network and a second-stage classifier based on a voting mechanism, and the process of signal recognition and classification by the signal processor specifically includes the following steps:
s1, a first-stage classifier receives single segment characteristics of a signal and outputs a segment type of the signal after recognizing the segment characteristics based on a neural recognition network;
s2, the second-stage classifier receives the segment types of the signals and outputs event types through the segment types of the signals based on a voting mechanism;
s3, judging whether the event type is correct or not, storing correct data into a database, and storing wrong data into the database after manual revision and counting;
s4, triggering the classifier increment learning module to automatically operate when the accumulated number of error data of event classification reaches a threshold value;
and S5, the classifier increment learning module retrains the neural network of the first-stage classifier and updates the neural network parameters of the first-stage classifier.
As shown in fig. 3, the digital-to-analog conversion process includes low noise signal amplification, automatic gain control, anti-aliasing filtering, AD sampling, digital demodulation, and delay calculation.
As shown in fig. 1, the monitoring model includes an implementation layer, and the implementation layer is used for acquiring and processing information through a base device, and implementing micro-vibration sensing, signal mediation, signal positioning and signal noise reduction enhancement;
as shown in fig. 1, the monitoring model includes an algorithm layer, and the algorithm layer is configured to receive and analyze information processed by the implementation layer, and implement neural network identification, time series analysis, support vector machine, and event discrimination and analysis;
as shown in fig. 1, the monitoring model further includes an application layer, and the application layer is used for displaying the analysis result of the algorithm layer and performing human-computer interaction, thereby realizing intelligent alarm, GIS positioning mark, informatization application integration and adaptive learning.
As shown in fig. 6, based on the optical fiber vibration monitoring model, the invention further provides a long-distance perimeter security system, which is used for monitoring and identifying intrusion events occurring on the deployment perimeter in real time and sending out corresponding alarms and positioning, and is connected with an external system, wherein the security system comprises a control center platform, and is used for monitoring intrusion behaviors, calculating and positioning a marked intrusion position, sending out corresponding alarm instructions, and calling a visual tracking device to record the intrusion behaviors; the control center platform comprises a first-level control center platform and at least one second-level control center platform which are in communication coupling with each other, and the second-level control center platform comprises a signal processor and is used for carrying out optical fiber vibration monitoring intrusion behavior and early warning.
As shown in fig. 6, a first-level control center platform is communicatively coupled with a railway time synchronization system, a second-level control center platform is communicatively coupled with a railway integrated video monitoring system, the first-level control center platform and the second-level control center platform both include a user terminal, a management terminal, an application server and a database server, and the second-level control center platform further includes an interface server.
As shown in fig. 6, the security system includes a field device communicatively coupled to the control center platform, the field device including a front-end detection device for detecting and returning detection data of the deployment perimeter intrusion behavior, the front-end detection device including a sensing fiber, an electronic fence, and a laser correlation; the field device comprises a visual tracking device which is used for receiving the alarm information sent by the control center platform, processing the alarm information to obtain specific alarm content and calling the video monitoring terminal at the corresponding position to record video; the field device comprises sound-light alarm equipment for receiving an alarm instruction sent by the control center platform and sending an alarm signal;
as shown in fig. 6, the external system includes a railway time synchronization system and a railway integrated video monitoring system, the railway integrated video monitoring system includes at least one video monitoring terminal, and the video monitoring terminal is configured to receive a signal from the visual tracking device and record an intrusion behavior. The railway integrated video monitoring system comprises at least one area node, wherein the area node is in communication coupling with a video monitoring terminal, and the area node is in communication coupling with a video gathering point.
An electronic device, the electronic device comprising:
a memory for storing executable instructions;
and the processor is used for realizing the long-distance perimeter safety precaution system when the executable instructions stored in the memory are executed.
A computer readable storage medium storing executable instructions that when executed by a processor implement the long-distance perimeter security system described above.
The working process of the long-distance perimeter safety precaution system comprises intrusion detection, signal processing, alarm linkage and mode learning, wherein:
1. intrusion detection: acquiring alarm information through an electronic fence, laser correlation, a sensing optical fiber and the like of front-end detection equipment, and transmitting the information to a second-level control center platform for processing;
2. signal processing: in the second-stage control center platform,
the signal processor sends the optical fiber sensing signal transmitted by the front-end equipment to the interface server after digital-to-analog conversion and signal analysis;
the interface server receives the alarm information, sends instructions to the visual tracking equipment and the acousto-optic alarm equipment, and triggers visual and acousto-optic alarm linkage response;
the database server records corresponding alarm information and video information to form important information reports such as alarm types, alarm sources, perimeter names, alarm positions, site areas, alarm time and the like and alarm videos;
the application server transmits alarm information to a client interface through a software platform, displays alarm GIS superposition information through the client interface, outputs an alarm prompt tone through the software interface, and displays an intrusion position video picture in a linkage manner;
in addition, if other external systems exist, information linkage between the systems can be realized.
3. And (3) alarm linkage:
the acousto-optic alarm equipment receives the instruction of the interface server and then sends acousto-optic alarm information;
after receiving the instruction of the interface server, the visual tracking equipment calls a video monitoring terminal to perform image positioning on the perimeter intrusion area, and synchronously transmits video data back to the database server for storage;
and displaying alarm information on a client software interface.
4. Pattern learning: when a certain area of the perimeter generates the same non-human intrusion behavior for many times, the system can record and learn according to the waveform generated by the intrusion behavior, and when the same intrusion behavior occurs again after the learning frequency reaches a threshold value, the system can filter the intrusion alarm, so that the false alarm is reduced.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. An optical fiber vibration monitoring model is used for sending out signals, receiving return signals, processing and analyzing the return signals and monitoring perimeter safety in real time, and is characterized in that the monitoring model comprises a physical layer, an implementation layer, an algorithm layer and an application layer which are sequentially connected;
the physical layer is positioned at the bottommost layer of the monitoring model and comprises basic equipment used for constructing and reusing an optical fiber sensing communication platform;
the realization layer is used for acquiring and processing information through basic equipment to realize micro-vibration sensing, signal mediation, signal positioning and signal noise reduction enhancement;
the algorithm layer is used for receiving and analyzing the information processed by the implementation layer, and realizing neural network identification, time sequence analysis, support vector machine and event discrimination and analysis;
the application layer is used for displaying the analysis result of the algorithm layer and performing man-machine interaction, and intelligent alarming, GIS positioning marking, informatization application integration and self-adaptive learning are achieved.
2. The optical fiber vibration monitoring model according to claim 1, wherein the base device comprises a sensing controller, a signal processing module and a sensing module, the sensing controller comprises a laser, a demodulator, an amplifier, a filter, a coupler and a photodetector which are connected in sequence, the coupler is further coupled with the sensing module, and the photodetector is connected with the signal processing module;
the sensing module comprises a sensing optical fiber and a light source, wherein the sensing optical fiber is used for receiving the detection light emitted by the coupler and transmitting the scattered light to the coupler;
the signal processing module comprises a digital-to-analog converter and a signal processing module which are connected with each other, the digital-to-analog converter is electrically connected with the photoelectric detector, the digital-to-analog converter is used for performing digital-to-analog conversion on signals transmitted by the photoelectric detector, and the signal processor is used for performing signal preprocessing, signal identification classification and event analysis on the signals subjected to digital-to-analog conversion to generate a classification result of an event, responding the classification result through an early warning application program and learning the increment of the classifier.
3. The fiber optic vibration monitoring model of claim 2, wherein the signal pre-processing includes band-pass filtering, down-sampling, and wavelet de-noising; the signal identification classification comprises segment segmentation, feature extraction and signal classification; the event analysis comprises intensity calculation, reliability calculation and positioning value correction; the early warning application program comprises early warning rules, man-machine interaction and new event recording; the classifier incremental learning includes new event training and classifier optimization.
4. The fiber vibration monitoring model according to claim 2, wherein the signal processor comprises a first-stage classifier based on a neural network and a second-stage classifier based on a voting mechanism, and the signal processor performs a signal identification classification process, specifically comprising the following steps:
s1, a first-stage classifier receives single segment characteristics of a signal and outputs a segment type of the signal after recognizing the segment characteristics based on a neural recognition network;
s2, the second-stage classifier receives the segment types of the signals and outputs event types through the segment types of the signals based on a voting mechanism;
s3, judging whether the event type is correct or not, storing correct data into a database, and storing wrong data into the database after manual revision and counting;
s4, triggering the classifier increment learning module to automatically operate when the accumulated number of error data of event classification reaches a threshold value;
and S5, the classifier increment learning module retrains the neural network of the first-stage classifier and updates the neural network parameters of the first-stage classifier.
5. A long-distance perimeter security system comprising the fiber vibration monitoring model of claims 1-4 for real-time monitoring, identification of intrusion events occurring on a deployment perimeter and corresponding alerting and locating, wherein the security system is connected to an external system, the security system comprising,
the control center platform is used for monitoring the intrusion behavior, calculating and positioning the marked intrusion position, sending a corresponding alarm instruction and calling the visual tracking equipment to record the intrusion behavior; the control center platform comprises a first-level control center platform and at least one second-level control center platform which are in communication coupling with each other, and the second-level control center platform comprises a signal processor and is used for carrying out optical fiber vibration monitoring intrusion behavior and early warning;
a field device communicatively coupled to the control center platform, the field device comprising,
the front-end detection equipment is used for deploying perimeter intrusion behavior detection and returning detection data; the front-end detection equipment comprises a sensing optical fiber, an electronic fence and laser correlation;
the visual tracking equipment is used for receiving the alarm information sent by the control center platform, processing the alarm information to obtain specific alarm content, and calling the video monitoring terminal at the corresponding position to record video;
the sound and light alarm equipment is used for receiving the alarm instruction sent by the control center platform and sending an alarm signal;
the external system comprises a railway time synchronization system and a railway comprehensive video monitoring system, the railway comprehensive video monitoring system comprises at least one video monitoring terminal, and the video monitoring terminal is used for receiving signals of the visual tracking equipment and recording intrusion behaviors.
6. The long-distance perimeter security system of claim 5, wherein the first level control center platform is communicatively coupled to a railway time synchronization system, the second level control center platform is communicatively coupled to a railway integrated video surveillance system, the first level control center platform and the second level control center platform each comprise a user terminal, a management terminal, an application server and a database server, the second level control center platform further comprising an interface server.
7. An electronic device, characterized in that the electronic device comprises:
a memory for storing executable instructions;
a processor configured to implement the long-range perimeter security system of claim 5 when executing the executable instructions stored by the memory.
8. A computer readable storage medium storing executable instructions that when executed by a processor implement the long-distance perimeter security system of claim 5.
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| CN115773812A (en) * | 2022-12-13 | 2023-03-10 | 杭州巨骐信息科技股份有限公司 | Cable protection detection method based on optical fiber vibration measurement technology |
| CN116915329A (en) * | 2023-09-13 | 2023-10-20 | 高勘(广州)技术有限公司 | Terminal automatic access method, terminal, base station, communication system and storage medium |
| CN116915329B (en) * | 2023-09-13 | 2023-12-08 | 高勘(广州)技术有限公司 | Terminal automatic access method, terminal, base station, communication system and storage medium |
| CN117351623A (en) * | 2023-09-22 | 2024-01-05 | 奇点新源国际技术开发(北京)有限公司 | A perimeter intrusion detection method and system |
| CN117409520A (en) * | 2023-10-25 | 2024-01-16 | 中国铁路成都局集团有限公司 | A railway perimeter intrusion monitoring method and system based on light-vision fusion and deep learning |
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