Subway tunnel drilling rig intrusion signal judgment method, device, equipment and medium

Abstract

The invention provides a subway tunnel drilling rig intrusion signal judgment method which can be applied to the technical field of optical fiber vibration measurement and signal identification. The method comprises the following steps: detecting a vibration signal of an invading drilling machine by using an optical fiber acceleration sensor; calculating time-frequency characteristics of the vibration signals to obtain a time-frequency matrix; performing wavelet ridge detection on each column of the time-frequency matrix to obtain a ridge boundary matrix; based on the ridge boundary matrix, obtaining an array of a target normalized ridge number; and taking the number of the target normalized ridges as a characteristic value, and discriminating the vibration signal by adopting a dual-threshold method to obtain a judgment result. By adopting the wavelet ridge detection method, the drilling machine intrusion signal can be simply and effectively identified, the wavelet basis and the decomposition scale are adjusted according to the actual situation, the signal multi-scale analysis is realized, and the problems that the subway intrusion drilling machine signal is difficult to distinguish and the calculation is complex are solved. The invention further provides a subway tunnel drilling rig intrusion signal judgment device and equipment and a medium.

Description

Technical Field

[0001] The invention relates to the technical field of optical fiber vibration measurement and signal recognition, and in particular to a method, device, equipment and medium for judging an intrusion signal of a subway tunnel drilling machine. Background Art

[0002] In recent years, many cities have invested in subway transportation construction. The subway, a large-capacity urban rail transit system, has undoubtedly provided effective assistance to alleviate urban traffic pressure. However, in the rapid development of the city, the frequent illegal drilling construction above the subway tunnel is like a hidden crisis, threatening the operational safety of the subway at all times. In order to meet this challenge, vibration measurement technology is often used to monitor the drilling rig intrusion signals above the subway line. However, the complex vibration interference sources inside the subway tunnel often cover up the weak traces of the drilling rig intrusion signals, making monitoring and identification work extremely difficult.

[0003] In order to break through this dilemma, Tongji University innovatively introduced a phase-sensitive optical time-domain reflectometer, and combined it with a two-layer classifier based on a convolutional neural network, successfully realizing the safety monitoring and real-time monitoring of subway tunnels, issuing intrusion alarms in a timely manner and accurately identifying intrusion signals. At the same time, Wuhan University of Technology also proposed a drilling rig illegal intrusion identification method based on an ultra-weak fiber Bragg grating (FBG) array, providing another powerful means for the safety protection of subway tunnels. Although these methods have significant advantages in theory, they are still restricted by many conditions during actual field testing and still need further exploration and improvement. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In order to solve the problem of difficulty in identifying drilling rig intrusion signals above subways in the prior art and to simply and effectively identify drilling rig intrusion events above subway tunnels, the embodiments of the present invention provide a subway tunnel drilling rig intrusion signal judgment method, device, equipment and medium. By adopting a wavelet ridge detection method, the drilling rig intrusion signal can be simply and effectively identified, and the calculation is simple and small. The wavelet basis and decomposition scale can be adjusted according to actual conditions to realize multi-scale signal analysis, thereby solving the problem of difficulty in distinguishing subway intrusion drilling rig signals and complex calculations.

[0006] (II) Technical solution

[0007] In view of the above problems, embodiments of the present invention provide a method, device, equipment and medium for determining an intrusion signal of a subway tunnel drilling machine.

[0008] According to a first aspect of the present invention, a method for judging an intrusion signal of a subway tunnel drilling rig is provided, comprising: using a fiber optic acceleration sensor to detect and obtain a vibration signal of the intrusion drilling rig; calculating the time-frequency characteristics of the vibration signal in a preset frequency band to obtain a time-frequency matrix; performing wavelet ridge detection on each column of the time-frequency matrix to obtain a ridge boundary matrix; based on the ridge boundary matrix, obtaining an array of target normalized ridge numbers; and using the target normalized ridge number as a eigenvalue and using a double threshold method to judge the vibration signal to obtain a judgment result.

[0009] In some exemplary embodiments, calculating the time-frequency characteristics of the vibration signal in a preset frequency band to obtain a time-frequency matrix includes: calculating the vibration signal with a 10 s sliding window and a 0.5 s step size to obtain the time-frequency matrix of the vibration signal.

[0010] In some exemplary embodiments, wavelet ridge detection is performed on each column of the time-frequency matrix to obtain a ridge boundary matrix, including: performing a wavelet transform on each column vector in the time-frequency matrix to obtain a wavelet coefficient; filtering out the peak points of each column based on the wavelet coefficients and a preset threshold; and using the peak points as the ridges of the matrix to obtain a ridge boundary matrix with the same dimension as the time-frequency matrix.

[0011] In some exemplary embodiments, the value of the peak point in the ridge boundary matrix is ​​1, and the values ​​of the remaining points are 0.

[0012] In some exemplary embodiments, based on the ridge boundary matrix, obtaining an array of a target normalized number of ridges includes: counting the number of ridges in each column in the ridge boundary matrix; normalizing the number of ridges to obtain an array of an initial normalized number of ridges; and smoothing and filtering the array of the initial normalized number of ridges to obtain an array of a target normalized number of ridges.

[0013] In some exemplary embodiments, the method of smoothing and filtering the array of initial normalized ridge number comprises a median filtering method.

[0014] In some exemplary embodiments, the dual threshold includes a low threshold and a high threshold, and the target normalized ridge number is used as a eigenvalue. The dual threshold method is used to distinguish the vibration signal, including: when the eigenvalue is lower than the low threshold, the vibration signal is judged as a drilling rig intrusion signal; or when the eigenvalue is higher than the high threshold, the vibration signal is judged as a non-drilling rig intrusion signal; or when the eigenvalue is between the low threshold and the high threshold, the initial judgment result is maintained.

[0015] According to a second aspect of the present invention, a subway tunnel drilling rig intrusion signal judgment device is provided, comprising: an acquisition module, used to detect and obtain the vibration signal of the intrusion drilling rig using a fiber optic acceleration sensor; a first processing module, used to calculate the time-frequency characteristics of the vibration signal in a preset frequency band to obtain a time-frequency matrix; a second processing module, used to perform wavelet ridge detection on each column of the time-frequency matrix to obtain a ridge boundary matrix; a third processing module, used to obtain an array of target normalized ridge numbers based on the ridge boundary matrix; and a judgment module, used to use the target normalized ridge number as a eigenvalue, and adopt a double threshold method to judge the vibration signal to obtain a judgment result.

[0016] A third aspect of the present invention provides an electronic device, comprising: one or more processors; a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the above method.

[0017] The fourth aspect of the present invention further provides a computer-readable storage medium on which a computer program or instruction is stored, and the steps of the above method are implemented when the above computer program or instruction is executed by a processor.

[0018] (III) Beneficial effects

[0019] It can be seen from the above technical solutions that the subway tunnel drilling machine intrusion signal judgment method, device, equipment and medium provided by the embodiments of the present invention have at least the following beneficial effects:

[0020] (1) The wavelet ridge detection method can simply and effectively identify the drilling rig intrusion signal, and the calculation is simple and small. The wavelet basis and decomposition scale can be adjusted according to the actual situation to realize multi-scale signal analysis, thus solving the problem of difficult and complex calculation of subway intrusion drilling rig signal identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above contents and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0022] Figure 1 The structure diagram of a fiber optic subway tunnel intrusion monitoring system based on phase generation carrier demodulation according to an embodiment of the present invention is schematically shown;

[0023] Figure 2 A schematic diagram of a flow chart of a method for determining an intrusion signal of a subway tunnel drilling machine according to an embodiment of the present invention is shown;

[0024] Figure 3 A schematic diagram shows a structural block diagram of a subway tunnel drilling machine intrusion signal judgment device according to an embodiment of the present invention; and

[0025] Figure 4 A block diagram of an electronic device suitable for implementing a subway tunnel boring machine intrusion signal determination method according to an embodiment of the present invention is schematically shown. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] 10-laser; 20-isolator; 30-1:16 ring beam splitter; 40-fiber accelerometer array; 50-photodetector; 60-analog-to-digital conversion; 70-FPGA; 80-digital-to-analog conversion. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] Figure 1 The structure diagram of a fiber optic subway tunnel intrusion monitoring system based on phase generation carrier demodulation according to an embodiment of the present invention is schematically shown.

[0029] like Figure 1 As shown, according to an embodiment of the present invention, an optical fiber subway tunnel intrusion monitoring system based on phase-generated carrier demodulation includes: a laser 10, which is suitable for providing narrow linewidth laser; an isolator 20, which is suitable for protecting the laser and preventing reflected light from affecting the laser; a one-to-sixteen ring 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 the 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 converter 60, which is suitable for converting analog signals into digital signals; an FPGA 70 (Field-Programmable Gate Array, field programmable gate array), which is suitable for phase-generated carrier demodulation signals and carrier signal generation; and a digital-to-analog converter 80, which is suitable for converting carrier signals into analog signals for modulating the laser.

[0030] During operation, FPGA70 generates a carrier signal, and performs carrier modulation on the laser 10 through 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 consists 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 passes through the one-to-sixteen ring splitter 30 to the photoelectric detector 50 and the analog-to-digital converter 60 to realize photoelectric and analog-to-digital conversion, and finally the algorithm demodulation is performed in FPGA70.

[0031] based on Figure 1 The system shown, combined with Figure 2 A subway tunnel drilling rig intrusion signal determination method according to an embodiment of the present invention is introduced.

[0032] Figure 2 A schematic flow chart of a method for determining an intrusion signal of a subway tunnel boring machine according to an embodiment of the present invention is schematically shown.

[0033] like Figure 2 As shown, a subway tunnel boring machine intrusion signal determination method according to an embodiment of the present invention includes steps S110 to S150.

[0034] In step S110, a fiber optic acceleration sensor is used to detect and obtain a vibration signal of the intruding drilling rig.

[0035] For example, fiber optic acceleration sensors are installed in subway tunnels to monitor acceleration signals in the tunnel in real time. When a drill is drilling on the surface above the tunnel, the sensor records and demodulates the vibration signal of the intruding drill in real time, including phase changes.

[0036] In step S120, the time-frequency characteristics of the vibration signal in a preset frequency band are calculated to obtain a time-frequency matrix.

[0037] In some exemplary embodiments, calculating the time-frequency characteristics of the vibration signal in a preset frequency band to obtain a time-frequency matrix includes: calculating the vibration signal with a 10 s sliding window and a 0.5 s step size to obtain the time-frequency matrix of the vibration signal.

[0038] For example, by processing the vibration signal detected by the optical fiber vibration sensor, a power spectrum density-time matrix is ​​obtained, and the power spectrum density-time matrix can be expressed as follows:

[0039]

[0040] Among them, PSD iThe power spectral density column vector is calculated based on a data length of 10 s, where i = 1, 2, 3, ... n, n is a positive integer, and 1 kHz is the sampling rate. The unit is rad / √Hz, PSD i The overlap length between them is 9.5 s.

[0041] In step S130, wavelet ridge detection is performed on each column of the time-frequency matrix to obtain a ridge boundary matrix.

[0042] In some exemplary embodiments, wavelet ridge detection is performed on each column of the time-frequency matrix to obtain a ridge boundary matrix, including: performing a wavelet transform on each column vector in the time-frequency matrix to obtain a wavelet coefficient; filtering out the peak points of each column based on the wavelet coefficient and a preset threshold; using the peak points as the ridges of the matrix to obtain a ridge boundary matrix with the same dimension as the time-frequency matrix, wherein the values ​​of the peak points in the ridge boundary matrix are 1, and the values ​​of the remaining points are 0.

[0043] For example, wavelet multiscale ridge detection based on the virtual instrument work platform (LabVIEW) calculates the array of power spectral density: first, a discrete wavelet transform (for example, db3 wavelet transform) is performed on each column vector of the power spectral density-time matrix to obtain the wavelet coefficient. Based on whether a wavelet coefficient is greater than its adjacent wavelet coefficient and whether its sign is positive, possible peak points are screened out. Then, the peak point is finally determined by setting the threshold. The peak point is set to 1, and the remaining points are set to 0, thereby obtaining a ridge boundary matrix of the same dimension as the two-dimensional matrix of the power spectral density, where the ridge is composed of peak points. The expression of the ridge boundary matrix is ​​as follows:

[0044] (2)

[0045] Among them, P t is a ridge matrix that only includes 0 and 1 values, and its dimension and PSD t The dimensions are the same.

[0046] In step S140, an array of target normalized ridge numbers is obtained based on the ridge boundary matrix.

[0047] In some exemplary embodiments, based on the ridge boundary matrix, obtaining an array of target normalized ridge numbers includes: counting the number of ridges in each column of the ridge boundary matrix; normalizing the number of ridges to obtain an array of initial normalized ridge numbers; and smoothing and filtering the array of initial normalized ridge numbers to obtain an array of target normalized ridge numbers. The method of smoothing and filtering the array of initial normalized ridge numbers includes a median filtering method.

[0048] For example, for P t Each P iSum and normalize to get the array Num of the initial normalized ridge number t , expressed as:

[0049] (3)

[0050] Among them, Num i Represents the number of initial normalized ridges, where i=1, 2, 3, ... n, and n is a positive integer.

[0051] In step S150, the target normalized ridge number is used as a characteristic value, and a double threshold method is used to judge the vibration signal to obtain a judgment result.

[0052] In some exemplary embodiments, the dual threshold includes a low threshold and a high threshold, and the target normalized ridge number is used as a eigenvalue. The dual threshold method is used to distinguish the vibration signal, including: when the eigenvalue is lower than the low threshold, the vibration signal is judged as a drilling rig intrusion signal; or when the eigenvalue is higher than the high threshold, the vibration signal is judged as a non-drilling rig intrusion signal; or when the eigenvalue is between the low threshold and the high threshold, the initial judgment result is maintained.

[0053] For example, the number of target normalized ridges is detected based on the double threshold method, and the high and low thresholds are set to 0.05 and 0.04 respectively. If the number of target normalized ridges is lower than 0.04, it is judged as a drilling rig intrusion signal. If the number of target normalized ridges is higher than 0.05, it is judged as a non-drilling rig intrusion signal. If the number of normalized ridges is between 0.04 and 0.05, the original judgment result is maintained.

[0054] The embodiment of the present invention adopts wavelet ridge detection to simply and effectively identify drilling rig intrusion signals, and the calculation is simple and small. The wavelet basis and decomposition scale can be adjusted according to actual conditions to realize multi-scale signal analysis, thus solving the problem of difficult and complex calculation in identifying subway intrusion drilling rig signals.

[0055] Based on the above subway tunnel drilling machine intrusion signal judgment method, the present invention also provides a subway tunnel drilling machine intrusion signal judgment device. Figure 3 The device is described in detail.

[0056] Figure 3 The structure block diagram of the subway tunnel drilling machine intrusion signal judgment device according to an embodiment of the present invention is schematically shown.

[0057] like Figure 3 As shown, the subway tunnel boring machine intrusion signal judgment device 800 of this embodiment includes an acquisition module 810, a first processing module 820, a second processing module 830, a third processing module 840 and a judgment module 850.

[0058] The acquisition module 810 is used to detect and obtain the vibration signal of the intruding drilling rig using the optical fiber acceleration sensor.

[0059] The first processing module 820 is used to calculate the time-frequency characteristics of the vibration signal in a preset frequency band to obtain a time-frequency matrix.

[0060] The second processing module 830 is used to perform wavelet ridge detection on each column of the time-frequency matrix to obtain a ridge boundary matrix.

[0061] The third processing module 840 is used to obtain an array of target normalized ridge numbers based on the ridge boundary matrix.

[0062] The judgment module 850 is used to use the target normalized ridge number as a characteristic value and adopt a double threshold method to judge the vibration signal to obtain a judgment result.

[0063] According to an embodiment of the present invention, any multiple modules among the acquisition module 810, the first processing module 820, the second processing module 830, the third processing module 840 and the judgment module 850 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present invention, at least one of the acquisition module 810, the first processing module 820, the second processing module 830, the third processing module 840 and the judgment module 850 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in a proper combination of any of them. Alternatively, at least one of the acquisition module 810, the first processing module 820, the second processing module 830, the third processing module 840 and the judgment module 850 can be at least partially implemented as a computer program module, and when the computer program module is executed, the corresponding function can be executed.

[0064] Figure 4 A block diagram of an electronic device for determining a subway tunnel boring machine intrusion signal according to an embodiment of the present invention is schematically shown.

[0065] like Figure 4As shown, the electronic device 900 according to an embodiment of the present invention includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage part 908 to a random access memory (RAM) 903. The processor 901 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 901 may also include an onboard memory for caching purposes. The processor 901 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0066] In RAM 903, various programs and data required for the operation of electronic device 900 are stored. Processor 901, ROM 902 and RAM 903 are connected to each other via bus 904. Processor 901 performs various operations of the method flow according to the embodiment of the present invention by executing the program in ROM 902 and / or RAM 903. It should be noted that the program can also be stored in one or more memories other than ROM 902 and RAM 903. Processor 901 can also perform various operations of the method flow according to the embodiment of the present invention by executing the program stored in one or more memories.

[0067] According to an embodiment of the present invention, the electronic device 900 may further include an input / output (I / O) interface 905, which is also connected to the bus 904. The electronic device 900 may further include one or more of the following components connected to the input / output (I / O) interface 905: an input portion 906 including a keyboard, a mouse, etc.; an output portion 907 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 908 including a hard disk, etc.; and a communication portion 909 including a network interface card such as a LAN card, a modem, etc. The communication portion 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the input / output (I / O) interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 910 as needed, so that a computer program read therefrom is installed into the storage portion 908 as needed.

[0068] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiment; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present invention is implemented.

[0069] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present invention, the computer-readable storage medium may include the ROM 902 and / or RAM 903 described above and / or one or more memories other than ROM 902 and RAM 903.

[0070] The embodiment of the present invention also includes a computer program product, which includes a computer program, and the computer program includes a program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the subway tunnel boring machine intrusion signal judgment method provided by the embodiment of the present invention.

[0071] The computer program executes the above functions defined in the system / device of the embodiment of the present invention when it is executed by the processor 901. According to the embodiment of the present invention, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0072] In one embodiment, the computer program may be based on a tangible storage medium such as an optical storage device, a magnetic storage device, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of a signal on a network medium, and downloaded and installed through the communication part 909, and / or installed from a removable medium 911. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0073] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 909, and / or installed from the removable medium 911. When the computer program is executed by the processor 901, the above functions defined in the system of the embodiment of the present invention are performed. According to the embodiment of the present invention, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0074] According to an embodiment of the present invention, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0075] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0076] It will be appreciated by those skilled in the art that the features described in the various embodiments of the present invention may be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, without departing from the spirit and teachings of the present invention, the features described in the various embodiments of the present invention may be combined and / or combined in various ways. All of these combinations and / or combinations fall within the scope of the present invention.

[0077] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although each embodiment is described above, it does not mean that the measures in each embodiment cannot be used in combination advantageously. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A method for determining a subway tunnel drilling machine intrusion signal, characterized in that: The method comprises: The vibration signal of the intruding drilling rig is detected by using the optical fiber acceleration sensor; Calculating the time-frequency characteristics of the vibration signal in a preset frequency band to obtain a time-frequency matrix; Perform wavelet ridge detection on each column of the time-frequency matrix to obtain a ridge boundary matrix; Based on the ridge boundary matrix, obtaining an array of target normalized ridge numbers; and The target normalized ridge number is used as a characteristic value, and a double threshold method is used to judge the vibration signal to obtain a judgment result.

2. The method according to claim 1, characterized in that: The step of calculating the time-frequency characteristics of the vibration signal in a preset frequency band to obtain a time-frequency matrix includes: The vibration signal is calculated with a 10 s sliding window and a 0.5 s step size to obtain a time-frequency matrix of the vibration signal.

3. The method according to claim 1, characterized in that: The wavelet ridge detection is performed on each column of the time-frequency matrix to obtain a ridge boundary matrix, which includes: Performing wavelet transform on each column vector in the time-frequency matrix to obtain wavelet coefficients; Filtering out the peak point of each column based on the wavelet coefficient and a preset threshold; The peak point is used as the ridge line of the matrix to obtain a ridge line boundary matrix with the same dimension as the time-frequency matrix.

4. The method according to claim 3, characterized in that The value of the peak point in the ridge boundary matrix is ​​1, and the values ​​of the remaining points are 0.

5. The method according to claim 1, characterized in that The array of target normalized ridge number obtained based on the ridge boundary matrix includes: Counting the number of ridges in each column of the ridge boundary matrix; Normalizing the number of ridges to obtain an array of initial normalized number of ridges; The array of the initial normalized number of ridges is smoothed and filtered to obtain an array of the target normalized number of ridges.

6. The method according to claim 5, characterized in that The method for smoothing and filtering the array of the initial normalized ridge number includes a median filtering method.

7. The method according to claim 1, characterized in that The dual thresholds include a low threshold and a high threshold. The step of using the target normalized ridge number as a characteristic value and using a double threshold method to discriminate the vibration signal includes: The characteristic value is lower than the lower threshold, and the vibration signal is determined to be a drilling rig intrusion signal; or The characteristic value is higher than the high threshold, and the vibration signal is determined to be a non-drilling rig intrusion signal; or The characteristic value is between the lower threshold and the upper threshold, and the initial judgment result is maintained.

8. A subway tunnel drilling machine intrusion signal judgment device, characterized in that: The device comprises: An acquisition module is used to detect and obtain the vibration signal of the intrusion drilling rig using a fiber optic acceleration sensor; A first processing module, used to calculate the time-frequency characteristics of the vibration signal in a preset frequency band to obtain a time-frequency matrix; A second processing module is used to perform wavelet ridge detection on each column of the time-frequency matrix to obtain a ridge boundary matrix; A third processing module is used to obtain an array of target normalized ridge numbers based on the ridge boundary matrix; and The judgment module is used to use the target normalized ridge number as a characteristic value and adopt a double threshold method to judge the vibration signal to obtain a judgment result.

9. An electronic device, comprising: one or more processors; a memory for storing one or more computer programs, It is characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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