Optical fiber subway tunnel intrusion monitoring method
By using wavelet packet decomposition and summing of power spectral density amplitudes in subway tunnels, vibrating signals are processed to identify drill rig intrusion signals, solving the problem of difficult rig signals in complex environments in subway tunnels, and achieving accurate intrusion monitoring.
Patent Information
- Application Number
- CN202411934189.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-26
- Publication Date
- 2025-04-11
AI Technical Summary
The vibration interference sources in subway tunnels are complex, making it difficult to accurately identify and monitor drilling rig intrusion signals.
The wavelet packet decomposition and summing of the power spectrum density amplitude are used to process the vibration signal through the sliding window, identify and block large signals caused by the train, thereby achieving accurate judgment of drilling rig intrusion signals.
It realizes accurate identification and monitoring of drilling rig signals in subway tunnel intrusion, and solves the problem of difficulty in identifying drilling rig signals in complex environments.
Smart Images
Figure CN119805541A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the technical fields of optical fiber vibration measurement and signal recognition, and in particular to an optical fiber subway tunnel intrusion monitoring method. Background Art
[0002] In recent years, more and more cities have built subway transportation. As a large-capacity urban rail transit system, subway can effectively alleviate the burden of urban traffic. However, in the process of urban development, a large number of illegal drilling rigs are prone to appear above subway tunnels, which seriously threatens the safety of subway operations. Vibration measurement is often used to monitor drilling rig intrusion signals above subway lines. However, the vibration interference sources in subway tunnels are complex, which obscures the measurement and identification of drilling rig intrusion signals.
[0003] Therefore, how to accurately identify and monitor drilling rig intrusion signals and monitor illegal intrusion of subway tunnel drilling rigs in real time needs to be addressed urgently. Summary of the invention
[0004] 1. Technical issues to be resolved
[0005] In view of the above-mentioned shortcomings, the main purpose of the present invention is to provide a fiber optic subway tunnel intrusion monitoring method. This method, through wavelet packet decomposition and power spectral density amplitude summation, not only realizes the effective identification of drilling rig intrusion signals, but also avoids the large signals caused by trains, thereby solving the problem of difficulty in distinguishing and monitoring intrusion drilling rig signals in the complex environment of subway tunnels.
[0006] (II) Technical solution
[0007] In order to achieve the above-mentioned purpose, the present invention provides a method for monitoring intrusion in an optical fiber subway tunnel, comprising: obtaining a vibration signal of a subway tunnel; performing wavelet packet decomposition on the vibration signal using a preset sliding window to obtain a plurality of wavelet packet coefficients, and respectively calculating the power spectrum densities corresponding to the plurality of wavelet packet coefficients; based on the amplitude of the power spectrum density and the comparison with the preset amplitude and threshold, performing entropy calculation of a target wavelet packet coefficient among the plurality of wavelet packet coefficients to obtain entropy of the target wavelet packet coefficient; performing median filtering on the entropy of the target wavelet packet coefficient to obtain a median filtering result; and determining that the vibration signal is an intrusion signal by performing double threshold judgment on the median filtering result to complete intrusion monitoring in the subway tunnel.
[0008] In the above scheme, a preset sliding window is used to perform wavelet packet decomposition on the vibration signal to obtain multiple wavelet packet coefficients, and the power spectral densities corresponding to the multiple wavelet packet coefficients are calculated respectively, including: using a preset sliding window with a time length of 10 seconds and a step length of 0.5 seconds, a 6-layer wavelet packet decomposition of the vibration signal is performed to obtain multiple wavelet packet coefficients; and the power spectral densities corresponding to the multiple wavelet packet coefficients are calculated respectively.
[0009] In the above scheme, the target wavelet packet coefficient is obtained by the following method, including: performing 6-layer wavelet packet decomposition on the vibration signal, dividing the frequency domain into 64 regions, and taking the 6th wavelet packet coefficient from the direct current as the target wavelet packet coefficient.
[0010] In the above scheme, based on the comparison between the amplitude sum of the power spectral density and the preset amplitude and threshold, the entropy of the target wavelet packet coefficients in multiple wavelet packet coefficients is calculated to obtain the target wavelet packet coefficient entropy, including: when the amplitude sum of the power spectral density is greater than the preset amplitude and threshold, the vibration signal is determined to be a limited signal, and the target wavelet packet coefficient entropy of the limited signal and the signal within the time threshold before and after the limited signal is set to 1; when it is determined that the amplitude sum of the power spectral density is less than or equal to the preset amplitude and threshold, the vibration signal is determined to be a non-limited signal, and the entropy of the target wavelet packet coefficient is calculated to obtain the target wavelet packet coefficient entropy.
[0011] In the above scheme, the target wavelet packet coefficient entropy is subjected to median filtering to obtain a median filtering result, including: inputting the calculated target wavelet packet coefficient entropy into a median filter for median filtering to obtain a smooth target wavelet packet coefficient entropy median filtering result.
[0012] In the above scheme, the vibration signal is determined to be an intrusion signal by performing double threshold judgment on the median filtering result, including: when the target wavelet packet coefficient entropy median filtering result is lower than the first threshold, it is determined that there is no intrusion signal in the vibration signal; when the target wavelet packet coefficient entropy median filtering result is higher than the second threshold, it is determined that the vibration signal is an intrusion signal.
[0013] In the above scheme, the vibration signal is determined to be an intrusion signal by performing double threshold judgment on the median filtering result, and also includes: when the target wavelet packet coefficient entropy median filtering result is higher than the first threshold and lower than the second threshold, it is determined that there is no intrusion signal in the vibration signal.
[0014] In the above scheme, the vibration signal is determined to be an intrusion signal by performing double threshold judgment on the median filtering result, and also includes: when the target wavelet packet coefficient entropy median filtering result is higher than the first threshold and lower than the second threshold, the vibration signal is determined to be an intrusion signal.
[0015] (III) Beneficial effects
[0016] The technical solution of the embodiment of the present invention has at least the following beneficial effects:
[0017] The method can accurately identify the signals of intrusion drilling rigs in subway tunnels, determine and shield the signals of subway tunnel trains, and solve the problem of difficulty in identifying the signals of intrusion drilling rigs in the complex environment of subway tunnels. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] Figure 1A flowchart of a method for monitoring intrusion in an optical fiber subway tunnel according to an embodiment of the present invention is schematically shown;
[0019] Figure 2 The structure block diagram of the optical fiber subway tunnel intrusion monitoring system according to an embodiment of the present invention is schematically shown. DETAILED DESCRIPTION
[0020] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.
[0021] Figure 1 The flowchart of the optical fiber subway tunnel intrusion monitoring method according to an embodiment of the present invention is schematically shown.
[0022] like Figure 1 As shown, in the embodiment of the present invention, the optical fiber subway tunnel intrusion monitoring method further includes operations S1 to S5.
[0023] In operation S1 , a vibration signal of a subway tunnel is acquired.
[0024] In an embodiment of the present invention, a fiber optic acceleration sensor is installed in a subway tunnel to monitor the vibration acceleration signal of the subway tunnel in real time. The vibration signal may contain intrusion signals such as drilling signals operating above the tunnel surface or large signals during the train running. For example, when a drilling rig is drilling on the surface above the tunnel, the sensor records and demodulates the phase change in real time.
[0025] In operation S2, a preset sliding window is used to perform wavelet packet decomposition on the vibration signal to obtain a plurality of wavelet packet coefficients, and power spectrum densities corresponding to the plurality of wavelet packet coefficients are calculated respectively.
[0026] In operation S3, based on the comparison between the amplitude of the power spectrum density and a preset amplitude and a threshold, entropy calculation of a target wavelet packet coefficient among the plurality of wavelet packet coefficients is performed to obtain entropy of the target wavelet packet coefficient.
[0027] In an embodiment of the present invention, after obtaining the vibration signal of the subway tunnel, a preset sliding window is used to perform wavelet packet decomposition on the vibration signal to obtain multiple wavelet packet coefficients, and the power spectrum densities corresponding to the multiple wavelet packet coefficients are calculated respectively.
[0028] Specifically, a 6-layer wavelet packet decomposition is performed on the vibration signal using a preset sliding window of 10 seconds time length and 0.5 seconds step length to obtain 64 wavelet packet coefficients. Then, the power spectral density corresponding to the 64 wavelet packet coefficients is calculated for the phase data of the 10-second time length.
[0029] Furthermore, the entropy of the sixth wavelet packet coefficient from DC is calculated for the 10-second time-length phase data, that is, the vibration signal is decomposed into six layers of wavelet packets, the frequency domain is divided into 64 regions, and the sixth wavelet packet coefficient from DC is used as the target wavelet packet coefficient.
[0030] For example, the sliding window calculation of the phase data of the optical fiber vibration sensor with a sampling rate of 1 kHz is performed, the window length is 10 seconds, that is, 10 k data points, and the sliding window slides for 0.5 seconds each time. Then, the data in a sliding window is decomposed into 6 layers of bior3_1 wavelet packets to obtain 64 wavelet packet coefficients. The sixth wavelet packet coefficient from the DC is defined as the target wavelet packet coefficient, and the entropy of the target wavelet packet coefficient is calculated.
[0031] In an embodiment of the present invention, the power spectrum density-time matrix obtained by processing the phase signal detected by the optical fiber vibration sensor can be expressed by the following formula:
[0032]
[0033] in, is the power spectrum density column vector calculated with 10 seconds as data length and 1 kHz as sampling rate, in rad / Hz; The overlap length is 9.5 seconds.
[0034] In an embodiment of the present invention, based on the comparison between the sum of the amplitude of the power spectral density and the preset amplitude and threshold, the entropy of the target wavelet packet coefficients in multiple wavelet packet coefficients is calculated to obtain the target wavelet packet coefficient entropy, including: when the sum of the amplitude of the power spectral density is greater than the preset amplitude and threshold, the vibration signal is determined to be a limited signal, and the target wavelet packet coefficient entropy of the limited signal and the signal within the time threshold before and after the limited signal is set to 1; when it is determined that the sum of the amplitude of the power spectral density is less than or equal to the preset amplitude and threshold, the vibration signal is determined to be a non-limited signal, and the entropy of the target wavelet packet coefficient is calculated to obtain the target wavelet packet coefficient entropy.
[0035] Specifically, the power spectrum density amplitudes corresponding to the 64 wavelet packet coefficients are summed. If the power spectrum density amplitude sum is greater than the preset amplitude and threshold, the vibration signal is determined to be a limited signal, and the target wavelet packet coefficient entropy of the limited signal and the signal within the time threshold before and after the limited signal is set to 1. If the power spectrum density amplitude sum is less than or equal to the preset amplitude and threshold, the vibration signal is determined to be a non-limited signal, and the normal wavelet packet coefficient entropy calculation is performed, that is, the entropy calculation of the target wavelet packet coefficient is performed to obtain the target wavelet packet coefficient entropy.
[0036] For example, according to the drilling experiment above the subway tunnel, the sum of the power spectrum density amplitude is determined to be 400 as the limit to determine whether the amplitude limitation is appropriate and effective. That is, if the sum of the power spectrum density amplitude is greater than 400, the vibration signal is determined to be an amplitude limiting signal, and the target wavelet packet coefficient entropy calculated for the amplitude limiting signal and the data within the time threshold before and after it (for example, 10 seconds) is reset to 1.
[0037] In operation S4, median filtering is performed on the target wavelet packet coefficient entropy to obtain a median filtering result.
[0038] In an embodiment of the present invention, the target wavelet packet coefficient entropy is subjected to median filtering to obtain a median filtering result, including: inputting the calculated target wavelet packet coefficient entropy into a median filter for median filtering to obtain a smooth target wavelet packet coefficient entropy median filtering result.
[0039] It should be noted that the vibration signal may contain intrusion signals or large signals during the train's travel. However, due to the large signal caused by the train, the vibration amplitude is very strong, and the train signal lasts for less than 30 seconds. Therefore, in the identification of vibration signals that may contain drilling rig signals, the corresponding target wavelet packet coefficient entropy calculation result is obviously limited. By judging, the target wavelet packet coefficient entropy result of the limited signal is set to 1, and a median filter of 60 seconds (more than twice the duration of the train) is passed. Since 1 is much smaller than other wavelet packet coefficient entropy results, the median filter result will not contain the result of the large signal caused by the train, thereby achieving train signal avoidance.
[0040] In operation S5, a double threshold judgment is performed on the median filtering result to determine that the vibration signal is an intrusion signal, so as to complete the intrusion monitoring of the subway tunnel.
[0041] In an embodiment of the present invention, a vibration signal is determined to be an intrusion signal by performing a double threshold judgment on the median filtering result, including: when the target wavelet packet coefficient entropy median filtering result is lower than the first threshold, determining that there is no intrusion signal in the vibration signal.
[0042] Exemplarily, the target wavelet packet coefficient entropy median filtering result is used as the characteristic value, and the double threshold method is used for discrimination. First, the first threshold is defined as the low threshold, and the second threshold is defined as the high threshold. Under normal circumstances, the median filtering calculation result is lower than the low threshold, and it is determined that there is no intrusion signal in the vibration signal, and it is determined that there is no drilling rig intrusion on the surface of the subway tunnel, that is, there is no drilling.
[0043] Furthermore, in an embodiment of the present invention, a vibration signal is determined to be an intrusion signal by performing a double threshold judgment on the median filtering result, and also includes: when the target wavelet packet coefficient entropy median filtering result is higher than a first threshold and lower than a second threshold, it is determined that there is no intrusion signal in the vibration signal.
[0044] For example, if the drilling operation is not carried out on the surface directly above the subway tunnel, but at a certain distance and in an area that poses no threat to the subway tunnel, the median filter calculation result will be higher than the low threshold, but still lower than the high threshold, maintaining the judgment result of no intrusion signal.
[0045] In an embodiment of the present invention, a vibration signal is determined to be an intrusion signal by performing a double threshold judgment on the median filtering result, including: when the target wavelet packet coefficient entropy median filtering result is higher than the second threshold, the vibration signal is determined to be an intrusion signal.
[0046] For example, when drilling activities are carried out at a close distance above a subway tunnel, posing a threat to the safety of the subway tunnel, the median filter calculation result will be higher than the high threshold, and the vibration signal will be determined to be an intrusion signal, that is, it will be judged as a drilling signal.
[0047] Furthermore, in an embodiment of the present invention, the vibration signal is determined to be an intrusion signal by performing a double threshold judgment on the median filtering result, and also includes: when the target wavelet packet coefficient entropy median filtering result is higher than the first threshold and lower than the second threshold, the vibration signal is determined to be an intrusion signal.
[0048] For example, when a drilling rig is operating at close range above a subway tunnel, the drilling rig performs an air drilling operation after drilling to a certain depth. At this time, the vibration is weakened, and the median filter calculation result will be lower than the high threshold, but still higher than the low threshold. The vibration signal is determined to be an intrusion signal, that is, it is judged to be a drilling signal.
[0049] Through the embodiments of the present invention, the method can realize accurate identification of subway tunnel intrusion drilling rig signals, determine and shield subway tunnel train signals, and solve the problem of difficulty in identifying intrusion drilling rig signals in the complex environment of subway tunnels.
[0050] Based on the above optical fiber subway tunnel intrusion monitoring method, an optical fiber subway tunnel intrusion monitoring system is also proposed in an embodiment of the present invention.
[0051] Figure 2 The structure block diagram of the optical fiber subway tunnel intrusion monitoring system according to an embodiment of the present invention is schematically shown.
[0052] The optical fiber subway tunnel intrusion monitoring system includes a laser 10, which is suitable for providing narrow line width laser; an isolator 20, which is suitable for protecting the laser and preventing reflected light from affecting the laser; a one-to-sixteen annular beam splitter 30, which is suitable for transmitting the laser to sixteen optical fiber acceleration sensor arrays 40, and transmitting the interference fringes of the optical fiber acceleration sensor arrays 40 to a photodetector 50; the optical fiber acceleration sensor array 40 is suitable for recording acceleration signals and converting lasers into interference fringes containing acceleration signals; the photodetector 50 is suitable for converting light interference fringes into electrical signals; an analog-to-digital conversion 60, which is suitable for converting analog signals into digital signals; an FPGA 70, which is suitable for phase generation of carrier demodulation signals and carrier signal generation; and a digital-to-analog conversion 80, which is suitable for converting carrier signals into analog signals for modulating the laser.
[0053] like Figure 2 As shown, FPGA70 generates a carrier signal, and the laser 10 is carrier modulated by the digital-to-analog converter 80. The laser 10 emits a narrow linewidth laser modulated by the carrier, and passes through the isolator 20 and the one-to-sixteen ring splitter 30 to the fiber optic acceleration sensor array 40. The basic principle of the fiber optic acceleration sensor array 40 is a Michelson interferometer; each Michelson interferometer is composed of a fiber coupler and two Faraday rotation mirrors. The two laser beams reflected by the Faraday reflector interfere in the coupler, and the interference signal is then passed through the one-to-sixteen ring splitter 30 to the photoelectric detector 50 and the analog-to-digital converter 60 to achieve photoelectric and analog-to-digital conversion. Finally, it is demodulated in FPGA70 to obtain a demodulated acceleration signal (that is, the subway tunnel vibration acceleration signal obtained in this embodiment). Based on the obtained vibration acceleration signal, the above-mentioned fiber optic subway tunnel intrusion monitoring method is implemented to identify the drilling rig intrusion signal.
[0054] Through the disclosed embodiments, the optical fiber subway tunnel intrusion monitoring system eliminates the influence of large train signals and effectively and simply identifies drilling rig intrusion above the subway tunnel, thereby realizing the monitoring of drilling rig intrusion events and improving the efficiency of subway tunnel safety monitoring.
[0055] The above specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.
Claims
1. A method for monitoring intrusion in optical fiber subway tunnels, characterized in that: The method comprises: Obtain vibration signals from subway tunnels; Using a preset sliding window to perform wavelet packet decomposition on the vibration signal to obtain a plurality of wavelet packet coefficients, and respectively calculating the power spectrum density corresponding to the plurality of wavelet packet coefficients; Based on the comparison between the amplitude of the power spectrum density and a preset amplitude and a threshold, entropy calculation of a target wavelet packet coefficient among the plurality of wavelet packet coefficients is performed to obtain entropy of the target wavelet packet coefficient; Performing median filtering on the target wavelet packet coefficient entropy to obtain a median filtering result; By performing double threshold judgment on the median filtering result, it is determined that the vibration signal is an intrusion signal, so as to complete the intrusion monitoring of the subway tunnel.
2. The optical fiber subway tunnel intrusion monitoring method according to claim 1 is characterized in that: The method of using a preset sliding window to perform wavelet packet decomposition on the vibration signal to obtain a plurality of wavelet packet coefficients, and respectively calculating the power spectrum densities corresponding to the plurality of wavelet packet coefficients, comprises: Using a preset sliding window of 10 seconds time length and 0.5 seconds step length, the vibration signal is decomposed into 6 layers of wavelet packets to obtain multiple wavelet packet coefficients; The power spectrum densities corresponding to the plurality of wavelet packet coefficients are calculated respectively.
3. The optical fiber subway tunnel intrusion monitoring method according to claim 1 or 2, characterized in that: The target wavelet packet coefficients are obtained by the following method, including: The vibration signal is subjected to 6-layer wavelet packet decomposition, the frequency domain is divided into 64 regions, and the sixth wavelet packet coefficient from the direct current is taken as the target wavelet packet coefficient.
4. The optical fiber subway tunnel intrusion monitoring method according to claim 3 is characterized in that: The step of calculating the target wavelet packet coefficient entropy among the plurality of wavelet packet coefficients based on the comparison of the amplitude of the power spectrum density with a preset amplitude and a threshold value to obtain the target wavelet packet coefficient entropy includes: When the power spectrum density amplitude and the power spectrum density amplitude are greater than the preset amplitude and threshold, the vibration signal is determined to be a limited amplitude signal, and the target wavelet packet coefficient entropy of the limited amplitude signal and the signal within the time threshold before and after the limited amplitude signal is set to 1; When it is determined that the power spectrum density amplitude is less than or equal to the preset amplitude and threshold, the vibration signal is determined to be a non-amplitude-limited signal, and the entropy of the target wavelet packet coefficient is calculated to obtain the target wavelet packet coefficient entropy.
5. The optical fiber subway tunnel intrusion monitoring method according to claim 1 or 4, characterized in that: The step of performing median filtering on the target wavelet packet coefficient entropy to obtain a median filtering result includes: The calculated target wavelet packet coefficient entropy is input into the median filter for median filtering to obtain a smooth target wavelet packet coefficient entropy median filtering result.
6. The optical fiber subway tunnel intrusion monitoring method according to claim 5, characterized in that: The step of performing double threshold judgment on the median filtering result to determine that the vibration signal is an intrusion signal includes: When the target wavelet packet coefficient entropy median filtering result is lower than a first threshold, determining that there is no intrusion signal in the vibration signal; When the target wavelet packet coefficient entropy median filtering result is higher than a second threshold, the vibration signal is determined to be an intrusion signal.
7. The optical fiber subway tunnel intrusion monitoring method according to claim 1 or 6, characterized in that: The step of determining that the vibration signal is an intrusion signal by performing a double threshold judgment on the median filtering result further includes: When the target wavelet packet coefficient entropy median filtering result is higher than a first threshold value and lower than a second threshold value, it is determined that there is no intrusion signal in the vibration signal.
8. The optical fiber subway tunnel intrusion monitoring method according to claim 1 or 6, characterized in that: The step of determining that the vibration signal is an intrusion signal by performing a double threshold judgment on the median filtering result further includes: When the target wavelet packet coefficient entropy median filtering result is higher than a first threshold value and lower than a second threshold value, the vibration signal is determined to be an intrusion signal.