CN112542046B - Early warning monitoring method for long-distance pipeline heavy vehicle based on DAS - Google Patents
Early warning monitoring method for long-distance pipeline heavy vehicle based on DAS Download PDFInfo
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- CN112542046B CN112542046B CN202011427966.5A CN202011427966A CN112542046B CN 112542046 B CN112542046 B CN 112542046B CN 202011427966 A CN202011427966 A CN 202011427966A CN 112542046 B CN112542046 B CN 112542046B
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/24—Reminder alarms, e.g. anti-loss alarms
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/056—Detecting movement of traffic to be counted or controlled with provision for distinguishing direction of travel
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Abstract
The invention discloses a DAS-based early warning and monitoring method for a long-distance pipeline heavy vehicle, which comprises the following steps that an optical fiber is buried along a pipeline, the starting point of the optical fiber is connected with a vibration detection system, and the vibration detection system receives a signal transmitted by the optical fiber and demodulates the vibration signal; carrying out Fourier transform on the vibration signal to finally obtain three parameters of vibration amplitude, frequency energy and frequency domain energy distribution, and obtaining a heavy vehicle type according to a grading mechanism; after the heavy vehicle signal is obtained, the heavy vehicle signal calculates the running speed and direction of the heavy vehicle within the optical fiber detection range according to the moving track in the track wave crest. The time of the predicted arrival of the heavy vehicle at the concerned position is calculated in real time, the heavy vehicle position is updated by the client and the server, and animation track reminding is carried out at the corresponding geographic position on the GIS, so that the heavy vehicle condition environment of the pipeline early warning system is controlled in real time, and the safety of the pipeline system is improved.
Description
Technical Field
The invention relates to the technical field of optical fiber vibration detection, in particular to a DAS-based long-distance pipeline heavy vehicle early warning and monitoring method.
Background
The safety problem caused by heavy vehicle rolling, which is most concerned by communication pipelines in the current environment, is more and more considered, and the former pipeline detection means and short distance can not give an alarm to process even if the heavy vehicle is detected.
Disclosure of Invention
The invention aims to solve the technical problem of the prior art and provides a pipeline heavy vehicle early warning and monitoring method capable of prejudging the automobile track in advance.
In order to solve the technical problems, the invention adopts the technical scheme that: a DAS-based long-distance pipeline heavy vehicle early warning monitoring method comprises the following steps:
embedding an optical fiber along the pipeline, wherein the starting point of the optical fiber is connected with a vibration detection system, and the vibration detection system receives a signal transmitted by the optical fiber and demodulates the vibration signal;
carrying out Fourier transform on the vibration signal to finally obtain three parameters of vibration amplitude, frequency energy and frequency domain energy distribution;
counting various data when a large number of heavy vehicles pass through the pipeline, counting the probability distribution of the amplitude distribution range of vibration caused by the heavy vehicles, the frequency energy probability distribution and the frequency domain energy distribution average value, and establishing a sample library;
calculating the similarity coefficient r of the detected heavy vehicle data in the operation of the system and the average value of the frequency domain energy distribution in the system sample library through the frequency domain energy distribution of each data
Calculating the product of the similarity coefficient r and the detected vibration frequency domain energy caused by heavy vehicle, and inquiring the product and the probability value of the vibration amplitude in a sample library; adding the two probability values, and determining the vehicle as heavy vehicle when the sum is greater than a set threshold value m;
calculating the running speed and direction of the heavy vehicle within the optical fiber detection range according to the moving track in the heavy vehicle signal wave crest;
according to the moving direction of the heavy vehicle, the possible threat position of the heavy vehicle is pre-warned, and the time from the heavy vehicle to a dangerous point is calculated according to the moving speed of the heavy vehicle.
And furthermore, the system also comprises a UI interface configuration device, the UI interface configuration device displays the map information along the optical fiber, displays the identified heavy vehicle running track, and an operator marks the possible threat position in advance on the map along the optical fiber to perform early warning according to the heavy vehicle speed and the moving direction.
Further, if the positioning accuracy of the optical fiber is Z, and the number of points at which the change of the vibration amplitude peak on the optical fiber is detected within the time T is N, the speed at which the heavy vehicle travels is (N × Z)/T.
Further, the driving direction of the vehicle is judged according to the peak moving direction of the vibration amplitude.
Further, when a sample library is established, the vibration amplitude, the frequency domain energy and the frequency domain energy distribution are divided into five levels, the probability distribution of each level of the vibration amplitude and the frequency domain energy is counted, and the average value of each level of the frequency domain energy distribution is counted.
Further, the threshold m is 0.6.
Furthermore, the similarity coefficient adopts a Pearson coefficient calculation formula.
The technical scheme shows that the invention has the following advantages: the automobile track is pre-judged in advance by combining the detection of the ultra-long distance laid along the pipeline by the optical fiber and the environmental information, the action route of the heavy vehicle is predicted, and enough early warning time is given to the alarm.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
According to the invention, the automobile track is pre-judged in advance by combining the ultra-long distance detection of the optical fiber along the pipeline and the environmental information, the action route of the heavy vehicle is predicted, the early warning time is sufficiently provided for the alarm, and the single-point resolution can reach 0.4 m by adopting a high-precision acquisition card. The following description will specifically describe an embodiment of the present invention with reference to fig. 1.
The optical fiber is buried along the pipeline, the optical fiber is connected with the server host, the data processing host receives signals transmitted by the optical fiber and demodulates the signals into vibration signals through the photoelectric demodulator, the vibration signals have the characteristics of stable linearity without upper limit, accurate frequency domain characteristic representation and the like, the signal demodulation basic parameters are vibration amplitude values, frequency domain information is obtained after fast Fourier transform, the frequency domain energy values are the sum of the values of all frequency domain points, and the frequency domain energy distribution is the average value of the percentage of all sectional vibration energy values in the total energy values. The frequency modulation circuit has the characteristic of different frequency distribution. Therefore, the type of the heavy vehicle is obtained according to a scoring mechanism through three parameters of amplitude, frequency domain energy and frequency domain energy distribution.
The distribution range of all heavy vehicle amplitude values obtained through statistical analysis of heavy vehicle data actually recorded by a large number of pipelines is 1.3-3.8, the frequency domain energy is 60-83, the frequency domain energy is distributed at 1-50hz, each amplitude value and energy are divided into 5 grades, and according to the probability of each grade of data statistics, a probability table is shown as follows:
amplitude distribution
| Range | Probability (percentage) |
| 1.3-1.8 | 8.3 |
| 1.8-2.3 | 21 |
| 2.3-2.8 | 49.3 |
| 2.8-3.3 | 16.7 |
| 3.3-3.8 | 4.7 |
Energy in frequency domain
Frequency domain energy distribution
| Range | Mean value of |
| 1-10 | 33.5 |
| 10-20 | 22.6 |
| 20-30 | 25.7 |
| 30-40 | 18.6 |
| 40-50 | 19.7 |
And taking the data as a sample library, comparing vibration data caused by passing of the heavy vehicle obtained in the monitoring process with the data in the sample library, and calculating a similarity coefficient r of vibration frequency domain energy distribution caused by the heavy vehicle and the average value of the frequency domain energy distribution of the heavy vehicle in the sample library, wherein the similarity coefficient is calculated by adopting a Pearson coefficient, and the formula is as follows:
after the similarity coefficient r is obtained, calculating the product of the similarity coefficient r and the detected vibration frequency domain energy caused by the heavy vehicle, and inquiring the product and the probability value of the vibration amplitude in a sample library; adding the two probability values, and determining the vehicle as heavy vehicle when the sum is greater than a set threshold value m; m is 0.6.
Through the method for identifying the heavy vehicle, the accuracy can reach ninety-nine percent, and the false alarm rate is reduced.
After the heavy vehicle signal is acquired, the heavy vehicle signal calculates the running speed and direction of the heavy vehicle within the optical fiber detection range according to the moving track in the track wave crest, specifically as follows: if the positioning accuracy of the optical fiber is Z, the point number of the change of the vibration amplitude peak on the optical fiber is detected to be N in the time T, and the running speed of the heavy vehicle is (N x Z)/T. And judging the driving direction of the vehicle according to the peak moving direction of the vibration amplitude.
The invention also provides a UI interface for a user to configure environment information, the UI interface configuration device displays the map information along the optical fiber and displays the identified heavy vehicle running track, and an operator marks the possible threat position in advance on the map along the optical fiber to perform early warning according to the heavy vehicle speed and the moving direction. The time of the predicted arrival of the heavy vehicle at the concerned position can be calculated in real time, the heavy vehicle position is updated by the client and the server, and animation track reminding is carried out at the corresponding geographic position on the GIS, so that the heavy vehicle condition environment of the pipeline early warning system is controlled in real time, and the safety of the pipeline system is improved. The coordinate information formula is calculated according to the GIS track as follows: the longitude and latitude of the coordinate P1 are (X1, Y1), the earth radius of the longitude and latitude (X2, Y2) of the coordinate P2 is 6371.0km, and the distance d between two points is R arcos [ cos (Y1) cos (Y2) cos (X1-X2) + sin (Y1) sin (Y2) ].
Claims (5)
1. A DAS-based long-distance pipeline heavy vehicle early warning monitoring method comprises the following steps:
embedding an optical fiber along the pipeline, wherein the starting point of the optical fiber is connected with a vibration detection system, and the vibration detection system receives a signal transmitted by the optical fiber and demodulates the vibration signal;
carrying out Fourier transform on the vibration signal to finally obtain three parameters of vibration amplitude, frequency energy and frequency domain energy distribution;
counting various data when a large number of heavy vehicles pass through the pipeline, counting the probability distribution of the amplitude distribution range of vibration caused by the heavy vehicles, the frequency energy probability distribution and the frequency domain energy distribution average value, and establishing a sample library;
calculating a similarity coefficient r of the detected heavy vehicle data in the operation of the system and the average value of the frequency domain energy distribution in the system sample library through the frequency domain energy distribution of each data;
calculating the product of the similarity coefficient r and the detected vibration frequency domain energy caused by heavy vehicle, and inquiring the product and the probability value of the vibration amplitude in a sample library; adding the two probability values, and determining the vehicle as heavy vehicle when the sum is greater than a set threshold value m;
and (3) pre-warning the possible threat position according to the moving direction of the heavy vehicle, calculating the time from the dangerous point to the dangerous point according to the moving speed of the heavy vehicle, if the positioning precision of the optical fiber is Z, and the number of points of the change of the vibration amplitude wave peak on the optical fiber is N within the time T, then the driving speed of the heavy vehicle is (N x Z)/T, and judging the driving direction of the vehicle according to the wave peak moving direction of the vibration amplitude.
2. The DAS-based long-distance pipeline heavy vehicle early warning monitoring method of claim 1, wherein: the system also comprises a UI interface configuration device, the UI interface configuration device displays the map information along the optical fiber and displays the identified heavy vehicle running track, and an operator forwards marks the possible threat position on the map along the optical fiber to perform early warning according to the heavy vehicle speed and the moving direction.
3. The DAS-based long-haul pipeline heavy-duty vehicle early warning monitoring method of claim 1, wherein: when a sample library is established, the vibration amplitude, the frequency domain energy and the frequency domain energy distribution are divided into five levels, the probability distribution of each level of the vibration amplitude and the frequency domain energy is counted, and the average value of each level of the frequency domain energy distribution is counted.
4. The DAS long-haul pipeline heavy-duty vehicle early warning monitoring method of claim 1, wherein: the threshold value m is 0.6.
5. The DAS long-haul pipeline heavy-duty vehicle early warning monitoring method of claim 1, wherein: and the similarity coefficient adopts a Pearson coefficient calculation formula.
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Denomination of invention: A Long Distance Pipeline Heavy Vehicle Warning and Monitoring Method Based on DAS Effective date of registration: 20231214 Granted publication date: 20220311 Pledgee: China Co. truction Bank Corp Wuxi branch Pledgor: WUXI KEY-SENSOR PHOTONICS TECHNOLOGY Co.,Ltd. Registration number: Y2023980070562 |
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