Distributed optical fiber sensing vehicle signal enhancement method, device and equipment

Abstract

The invention provides a distributed optical fiber sensing vehicle signal enhancement method, device and equipment, and the method comprises the steps: carrying out the framing processing of a to-be-processed vehicle signal, and obtaining a time-frequency feature corresponding to the to-be-processed signal; the time-frequency characteristics comprise frequency distribution characteristics and time-domain characteristics; constructing a template signal based on the time-frequency characteristics, and designing a corresponding matched filter by using the template signal to obtain a target filter; the template signal at least comprises a principal component of the time-frequency characteristic; and matching the target filter with the to-be-processed vehicle signal filtered by the band-pass filter to obtain a target vehicle signal. By analyzing the time-frequency characteristics of the to-be-processed vehicle signal, the template signal capable of being matched with the vehicle vibration signal is found, and the template signal is matched with the to-be-processed vehicle signal after band-pass filtering, so that the influence of interference noise on the original vehicle signal is removed, and the enhancement of the vehicle signal under the condition of strong interference noise is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of signal processing, and particularly to a method, device, and equipment for enhancing distributed optical fiber sensing vehicle signals. Background Art

[0002] In highway vehicle detection, the application of fiber optic grating sensing technology has gradually become an effective detection means. Through the vibration signals sensed by fiber optic sensors, high-precision monitoring of the tiny vibrations generated when vehicles pass by can be achieved. However, how to accurately extract vehicle-related information from these complex vibration signals remains a technical challenge currently faced. When processing the original signals of sensors, although some noise and temperature drift can be removed through traditional filtering methods. However, in the actual environment, fiber optic sensing signals are often affected by various interference sources, such as environmental vibrations, mechanical noises, vibration signals of other vehicles, etc. These interferences may mask the vibration signals of the target vehicle, affecting the accuracy of vehicle detection. Current filtering methods often only filter based on frequency intervals and cannot effectively filter out interference noises with frequencies close to and intensities greater than those of vehicle signals, resulting in inaccurate vehicle detection and positioning. Summary of the Invention

[0003] In view of this, the present invention proposes a method, device, and equipment for enhancing distributed optical fiber sensing vehicle signals.

[0004] The technical solution of the present invention is realized as follows: In the first aspect of the present invention, a method for enhancing distributed optical fiber sensing vehicle signals is provided, including:

[0005] Performing frame division processing on the vehicle signal to be processed to obtain the time-frequency characteristics corresponding to the signal to be processed; the time-frequency characteristics include frequency distribution characteristics and time-domain characteristics;

[0006] Constructing a template signal based on the time-frequency characteristics and designing a corresponding matching filter using the template signal to obtain a target filter; the template signal includes at least the main components of the time-frequency characteristics;

[0007] Matching the target filter with the vehicle signal to be processed filtered by a band-pass filter to obtain a target vehicle signal.

[0008] On the basis of the above technical solution, preferably, the performing frame division processing on the vehicle signal to be processed to obtain the time-frequency characteristics corresponding to the signal to be processed includes:

[0009] Performing frame division processing on the vehicle signal to be processed using the short-time Fourier transform STFT to obtain the time-frequency curve of the vehicle signal to be processed; the time-frequency curve includes signal frequency peaks;

[0010] Determine the signal within the preset interval where the signal frequency peak is located as the vibration signal, and determine the vehicle signal to be processed outside the preset interval where the signal frequency peak is located as the noise signal.

[0011] Based on the above technical solutions, preferably, the step of determining the signal within the preset interval where the signal frequency peak is located as the vibration signal, and determining the vehicle signal to be processed outside the preset interval where the signal frequency peak is located as the noise signal, includes:

[0012] Obtain the root mean square value RMS corresponding to the time-frequency curve, and determine the vehicle signal to be processed within the preset intervals on both sides of the signal frequency peak where RMS is greater than the threshold β as the vibration signal:

[0013]

[0014] Perform a short-time Fourier transform on the root mean square value RMS to determine the intensity of the vehicle signal to be processed at different times and frequencies:

[0015]

[0016] Where N is the frame length, ω(n) is the Hamming window function, x(n) is the original signal, w is the normalized angular frequency, f is the frequency, and ω = 2πf.

[0017] Based on the above technical solutions, preferably, the step of constructing a template signal based on the time-frequency characteristics and designing a corresponding matching filter using the template signal to obtain the target filter, includes:

[0018] Screen the vehicle signal to be processed based on the time-frequency characteristics to obtain a vibration data set;

[0019] Perform a spectral analysis on the vibration data set to obtain at least two different types of typical vibration signals;

[0020] Perform a convolution operation and a normalization process on the typical vibration signals to obtain a template signal.

[0021] Based on the above technical solutions, preferably, the step of performing a spectral analysis on the vibration data set to obtain at least two different types of typical vibration signals, includes:

[0022] Perform a window function process on the vibration data to obtain a corresponding discrete signal;

[0023] Perform a Fourier transform on the discrete signal to obtain the signal spectrum Z[K]: z(n) is the vehicle signal to be processed, and N is the frame length;

[0024] Determine the power distribution of the discrete signal at different frequencies based on the signal spectrum, determine the characteristic points corresponding to the maximum frequency and the maximum power, and screen to obtain at least two different types of typical vibration signals, where the power distribution of the discrete signal satisfies

[0025] On the basis of the above technical solution, preferably, before matching the target filter with the to-be-processed vehicle signal filtered by the band-pass filter to obtain the target vehicle signal, the method further includes:

[0026] Design a Chebyshev band-pass filter using the time-frequency characteristics, and use the Chebyshev band-pass filter to remove the temperature drift and at least part of the noise in the to-be-processed vehicle signal.

[0027] On the basis of the above technical solution, preferably, the designing the Chebyshev band-pass filter using the time-frequency characteristics includes determining the minimum order n of the Chebyshev band-pass filter using the following formula:

[0028]

[0029] where w s , w p are the normalized passband and stopband boundary frequencies respectively, and R s is the minimum stopband attenuation.

[0030] On the basis of the above technical solution, preferably, the matching the target filter with the to-be-processed vehicle signal filtered by the band-pass filter to obtain the target vehicle signal includes:

[0031] Construct the impulse response h(n) of the matched filter: h(n) = s * [N - n - 1]; where s * represents conjugation, and N is the length of the template signal;

[0032] Determine the target vehicle signal y(n) based on the impulse response h(n):

[0033]

[0034] Even more preferably, a second aspect of the present invention provides a distributed fiber optic sensing vehicle signal enhancement device, including: a frame division processing module, a construction design module, and a signal matching module; where

[0035] The frame division processing module is configured to perform frame division processing on the to-be-processed vehicle signal to obtain the time-frequency characteristics corresponding to the to-be-processed signal; the time-frequency characteristics include frequency distribution characteristics and time-domain characteristics;

[0036] The construction design module is configured to construct a template signal based on the time-frequency feature, and design a corresponding matching filter by using the template signal to obtain a target filter; the template signal includes at least the principal component of the time-frequency feature.

[0037] The signal matching module is configured to match the target filter with the to-be-processed vehicle signal filtered by the band-pass filter to obtain a target vehicle signal.

[0038] More preferably, a third aspect of the present invention provides a computer storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, the distributed optical fiber sensing vehicle signal enhancement method described in the first aspect is implemented.

[0039] A distributed optical fiber sensing vehicle signal enhancement method of the present invention has the following

[0040] Advantages:

[0041] 1. By combining the time domain and frequency domain features of the vehicle signal and designing a template signal for matched filtering, the enhancement of the highway vehicle target signal under a strong interference background is realized, and the interference noise with a frequency close to that of the vehicle signal and a large intensity is effectively filtered, so that subsequent work such as vehicle detection can be better carried out in a noisy environment.

[0042] 2. By using the short-time Fourier transform method to perform time-frequency analysis on the vehicle driving signal, not only the calculation complexity is reduced, the distribution of the vehicle target signal and the noise signal can be efficiently obtained, but also the influence caused by inaccurate filter bandwidth setting is avoided.

[0043] 3. Applying matched filtering to the extraction and enhancement of the distributed optical fiber acoustic wave sensing target signal, directly aiming at the target signal, has obvious advantages in signal detection and enhancement in a noisy environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to these drawings without creative efforts.

[0045] Figure 1 It is a schematic flowchart of a distributed optical fiber sensing vehicle signal enhancement method provided by an embodiment of the present invention;

[0046] Figure 2 It is a schematic diagram of the original signal frame division provided by an embodiment of the present invention;

[0047] Figure 3 Schematic diagram of vehicle detection by band - pass filtering in a strong interference area provided by an embodiment of the present invention;

[0048] Figure 4 Waveform schematic diagram of the template signal provided by an embodiment of the present invention;

[0049] Figure 5 Enhanced comparison diagram of the original waveform of the vehicle vibration signal and the vehicle target signal after matched filtering provided by an embodiment of the present invention;

[0050] Figure 6 Comparison diagram of vehicle detection by band - pass filtering and matched filtering in a strong interference area provided by an embodiment of the present invention;

[0051] Figure 7 Schematic diagram of the entire signal processing flow provided by an embodiment of the present invention;

[0052] Figure 8 Schematic diagram of the structure of a distributed optical fiber sensing vehicle signal enhancement device provided by an embodiment of the present invention;

[0053] Figure 9 Schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0054] Next, in combination with the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0055] In some embodiments, as Figure 1 shown, Figure 1 Schematic diagram of the process of a distributed optical fiber sensing vehicle signal enhancement method provided by an embodiment of the present invention; A distributed optical fiber sensing vehicle signal enhancement method provided by the present invention includes:

[0056] S110, perform frame - by - frame processing on the vehicle signal to be processed, and obtain the time - frequency characteristics corresponding to the signal to be processed; the time - frequency characteristics include frequency distribution characteristics and time - domain characteristics.

[0057] Frame processing is to divide continuous vehicle signals to be processed into a series of shorter segments (frames) that are either temporally overlapping or non - overlapping. Frame processing can include steps such as determining the frame length, determining the frame shift, and windowing. Among them, the frame length is usually set according to the characteristics of the signal and the analysis requirements. A shorter frame length can capture finer temporal variations but may reduce the frequency resolution; a longer frame length can improve the frequency resolution but may not be able to capture rapidly changing temporal characteristics. The frame shift is the overlapping part between adjacent frames. A larger frame shift can increase the continuity between frames but will increase the computational amount; a smaller frame shift may lead to discontinuity between frames. To reduce the discontinuity at the frame edges, a window function, such as the Hanning window, Hamming window, Blackman window, etc., can be applied to each frame. The window function can smoothly transition to zero, thereby reducing spectral leakage. Here, the vehicle signal to be processed is subjected to frame processing to obtain frequency distribution characteristics and time - domain characteristics, which can reflect the characteristics of the vehicle signal to be processed at different times and frequencies.

[0058] In some embodiments, S110, perform frame processing on the vehicle signal to be processed to obtain the time - frequency characteristics corresponding to the signal to be processed, including:

[0059] S111, use the Short - Time Fourier Transform (STFT) to perform frame processing on the vehicle signal to be processed, obtaining the time - frequency curve of the vehicle signal to be processed; the time - frequency curve includes the signal frequency peak.

[0060] S112, determine the signal within the preset interval where the signal frequency peak is located as the vibration signal, and determine the vehicle signal to be processed outside the preset interval where the signal frequency peak is located as the noise signal.

[0061] In this embodiment, the vehicle signal to be processed is divided into smaller time windows using the Short - Time Fourier Transform, obtaining the time - frequency representation of the signal, visualizing the time - frequency result, and analyzing the frequency distribution characteristics and time - domain characteristics of the signal according to the time - frequency diagram. According to the time - frequency diagram, the frequency distributions of the vibration signal and the noise signal generated during vehicle driving are in different intervals, where the signal frequency distribution generated by vehicle vibration is near the signal frequency peak. Here, using the Short - Time Fourier Transform method not only reduces the computational complexity and can efficiently obtain the distribution of vehicle target signals and noise signals, but also avoids the influence caused by inaccurate filter bandwidth settings.

[0062] In some embodiments, S112, determine the signal within the preset interval where the signal frequency peak is located as the vibration signal, and determine the vehicle signal to be processed outside the preset interval where the signal frequency peak is located as the noise signal, including:

[0063] Obtain the Root Mean Square (RMS) value corresponding to the time - frequency curve, and determine the vehicle signal to be processed within the preset intervals on both sides of the signal frequency peak where the RMS is greater than the threshold β as the vibration signal:

[0064]

[0065] Perform a short-time Fourier transform on the root mean square value RMS to determine the intensity of the vehicle signal to be processed at different times and frequencies:

[0066]

[0067] Where N is the frame length, ω(n) is the Hamming window function, x(n) is the original signal, w is the normalized angular frequency, f is the frequency, and ω = 2πf.

[0068] In this embodiment, after obtaining the vehicle signal to be processed, the signal is framed, and the framed length is set to N and the frame shift is set to α. Specifically, s seconds before and after the peak point where the RMS intensity is greater than the threshold β can be taken as the original vehicle signal, that is, the vibration signal. It should be noted that through the short-time Fourier transform, the framed matrix can represent the intensity of the signal at different times and frequencies by calculating the power spectrum and plotting the time-frequency diagram.

[0069] S120. Construct a template signal based on the time-frequency characteristics, and design a corresponding matched filter using the template signal to obtain a target filter; the template signal includes at least the main components of the time-frequency characteristics.

[0070] In this embodiment, the template signal can represent the main characteristics of the original vehicle signal in the time-frequency domain. By extracting the main components of the time-frequency characteristics, one or more template signals can be synthesized. After obtaining the template signal, a matched filter is further designed. The matched filter is a linear filter, and its output is the correlation function between the input signal and the template signal. During the design process, the parameters of the matched filter, such as the filter length, sampling rate, etc., can be adjusted to complete the optimization and obtain the target filter.

[0071] In some embodiments, S120. Construct a template signal based on the time-frequency characteristics, and design a corresponding matched filter using the template signal to obtain a target filter, including:

[0072] S121. Screen the vehicle signal to be processed based on the time-frequency characteristics to obtain a vibration data set.

[0073] S122. Perform spectral analysis on the vibration data set to obtain at least two different types of typical vibration signals.

[0074] S123. Perform convolution operation and normalization processing on the typical vibration signals to obtain a template signal.

[0075] In this embodiment, the vibration data set contains multiple vibration signals. The vibration signals show non-standard sine waves in the time domain. Here, data sets are established using data from typical measurement areas with better signals to ensure data quality. According to the spectral characteristics of the vibration data, clustering algorithms, classifiers, or expert knowledge can be used to classify the vibration signals into at least two different types of typical vibration signals. On this basis, convolution operations are performed, and the part similar to the sine wave is taken and normalized to obtain the template signal for matched filtering.

[0076] In some embodiments, in S122, perform spectral analysis on the vibration data set to obtain at least two different types of typical vibration signals, including:

[0077] Perform window function processing on the vibration data to obtain corresponding discrete signals;

[0078] Perform Fourier transform on the discrete signals to obtain the signal spectrum Z[k]: z(n) is the vehicle signal to be processed, and N is the frame length;

[0079] Based on the signal spectrum, determine the power distribution of the discrete signals at different frequencies, determine the characteristic points corresponding to the maximum frequency and the maximum power, and filter to obtain at least two different types of typical vibration signals, where the power distribution of the discrete signals satisfies

[0080] S130, match the target filter with the vehicle signal to be processed after being filtered by the band-pass filter to obtain the target vehicle signal.

[0081] In this embodiment, after obtaining the time-frequency analysis result of the signal, a suitable band-pass filter can be selected according to the frequency distribution of the vehicle target signal to remove background noise and temperature drift signals. On this basis, perform a matching operation on the signal filtered by the band-pass filter with the target filter to obtain the target vehicle signal.

[0082] In some embodiments, before S130, where the target filter is matched with the vehicle signal to be processed after being filtered by the band-pass filter to obtain the target vehicle signal, the method further includes:

[0083] Design a Chebyshev band-pass filter using time-frequency characteristics, and use the Chebyshev band-pass filter to remove temperature drift and at least part of the noise in the vehicle signal to be processed.

[0084] Here, the Chebyshev band-pass filter can have a passband of [f low , f high hz, a transition band of [0.5f low , f low hz and [f high , 2f highhz, the maximum attenuation in the passband is R p db, the minimum attenuation in the stopband is R s db IIR Chebyshev band-pass filter.

[0085] In some embodiments, the Chebyshev band-pass filter is designed using time-frequency features, including determining the minimum order n of the Chebyshev band-pass filter using the following formula:

[0086]

[0087] where w s , w p are the normalized passband and stopband boundary frequencies respectively, and R s is the minimum attenuation in the stopband.

[0088] In some embodiments, S130, matching the target filter with the vehicle signal to be processed filtered by the band-pass filter to obtain the target vehicle signal, includes:

[0089] Construct the impulse response h(n) of the matched filter: h(n) = s * [N - n - 1]; where s * denotes conjugate, and N is the length of the template signal;

[0090] Determine the target vehicle signal y(n) based on the impulse response h(n):

[0091]

[0092] The maximum value of the detected output signal y(n) corresponds to the position of the template signal s(n) in the input signal. Normalize the output y(n) according to the detection area, which realizes the enhancement of the highway vehicle target signal under strong interference background.

[0093] In an alternative embodiment, the distributed fiber optic sensing vehicle signal enhancement method may specifically include the following steps:

[0094] Step 1: After obtaining the vehicle signal to be processed, take the frame length as 1000 and the frame shift as 0.5. The frame division schematic diagram is as follows Figure 2 shown, Figure 2 which is the original signal frame division schematic diagram provided by the embodiment of the present invention. Take the RMS of the frame division matrix, and take the 2.5s before and after those with a threshold greater than 0.4. Analyze the time-frequency diagram of the signal, and it can be obtained that the signal frequency generated by vehicle vibration is distributed around 10hz, while the noise signal frequency is distributed around 30hz.

[0095] Step 2: Data preprocessing. Design a Chebyshev band-pass filter with a passband of [4, 15] Hz, transition bands of [2, 4] Hz and [15, 30] Hz, a maximum attenuation of 2 dB in the passband, and a minimum attenuation of 50 dB in the stopband for filtering. When the frequency of the noise signal is similar to that of the vibration signal generated by vehicle driving, i.e., the original vehicle signal, after band-pass filtering, the signal-to-noise ratio of the noise signal is higher than that of the vibration signal, and the vibration signal may be submerged by the noise, resulting in the inability to accurately detect the vehicle. Perform root mean square (RMS) processing on the data after band-pass filtering. The waterfall plot of a typical measurement area with large interference is as follows Figure 3 as shown Figure 3 is the schematic diagram of vehicle detection by band-pass filtering in a strong interference measurement area provided by an embodiment of the present invention. It can be seen from Figure 3 that when the vehicle passes through a measurement area with large interference, due to the excessive background noise, it is impossible to accurately detect and locate the vehicle driving trajectory.

[0096] Step 3: Design a template signal by combining multi-dimensional features. Analyze the vehicle driving characteristics. The vibration signal generated by the vehicle passing through the measurement area ideally represents a sine signal in the time domain. However, due to various interferences, it is often not a standard sine wave. By combining the frequency characteristics obtained through time-frequency analysis and analyzing the power spectra of a large number of typical vehicle vibration signal datasets, two typical vehicle vibration signals are selected for convolution to generate a template signal for matched filtering, such as Figure 4 , Figure 4 is the waveform schematic diagram of the template signal provided by an embodiment of the present invention. The template signal for matched filtering is similar to an idealized sine wave signal, and its spectral distribution is concentrated within a specific range.

[0097] Step 4: After designing the template signal, further design a matched filter and perform secondary filtering on the vehicle signal to be processed that has undergone band-pass filtering. This process significantly enhances the vibration signal in the vehicle signal to be processed and reduces the influence of background noise and strong interference signals. The waveform of the signal after matched filtering is smoother. While enhancing the vehicle target signal, it also smooths the time characteristics of the signal. However, compared with the original vehicle signal to be processed, there is a broadening phenomenon in time. This broadening may be caused by the convolution operation on the template signal during the matched filtering process. Nevertheless, compared with the original vehicle signal to be processed and the signal after band-pass filtering, the signal-to-noise ratio of the vehicle target signal in the signal after matched filtering is significantly improved.

[0098] When matching the vehicle target signal in a strong interference measurement area, the matched filter shows the characteristic of being insensitive to the spike signals generated by strong background noise. This characteristic enables the matched filtering to effectively detect the vehicle vibration signal in the strong interference measurement area, thereby reducing the influence of the noise signal on the vehicle detection accuracy. Here, please refer to Figure 5 , Figure 5This is a contrast graph of the original waveform of the vehicle vibration signal and the enhanced vehicle target signal after matched filtering provided by the embodiment of the present invention. From Figure 5 It can be seen that the signal after matched filtering can improve the signal-to-noise ratio of the vehicle target signal while suppressing the noise signal of strong interference.

[0099] Step 5, select a typical strong interference measurement area. After the original signal passes through band-pass filtering and matched filtering, the vehicle detection waterfall diagrams of a typical strong interference measurement area on a certain highway are respectively drawn. Here, please refer to Figure 6 , Figure 6 This is a contrast graph of vehicle detection with band-pass filtering and matched filtering in the strong interference measurement area provided by the embodiment of the present invention. Figure 6 The bright line in is the trajectory generated by the vehicle running. By comparing the vehicle detection waterfall diagram after band-pass filtering with the vehicle detection waterfall diagram after matched filtering, it can be seen that in the waterfall diagram obtained after matched filtering, the vehicle running signal not only enhances the vibration signal in the weak interference measurement area, but also significantly removes the influence that the vehicle running trajectory is submerged due to the too strong noise signal in the strong interference measurement area, realizing the enhancement of the vehicle target signal in the strong interference measurement area.

[0100] In an optional embodiment, please refer to Figure 7 , Figure 7 This is a schematic diagram of the full process of signal processing provided by the embodiment of the present invention. The vehicle signal data in each measurement area of the highway is detected by a distributed vibration sensor, and then the signal is framed and the RMS value is calculated. The peak value in the RMS is found, and the power spectrum is calculated by performing STFT on the data 2.5s before and after each peak point and adding a Hamming window to draw the time-frequency diagram. Based on this, the time-domain characteristics and frequency-domain characteristics of the vehicle vibration signal are obtained. A Chebyshev band-pass filter is designed according to the frequency-domain characteristics, and a matched filtering template signal is designed by convolution combining the frequency-domain and time-domain signal characteristics. The RMS value of the signal after normalized matched filtering is taken logarithmically, and the trajectory waterfall diagram of the vehicle is drawn. It should be noted that in this embodiment, by using the coherent demodulation technology of the distributed acoustic sensing system (DAS), according to the proportional relationship between the external strain change and the phase of the interference signal, each coherent optical signal is demodulated to restore the strain change information. Finally, these demodulated information are transmitted to the host computer for further data processing to generate data information that can be read by the monitoring party, that is, the vehicle original signal.

[0101] In some embodiments, please refer to Figure 8 , Figure 8 This is a schematic diagram of the structure of a distributed optical fiber sensing vehicle signal enhancement device provided by the embodiment of the present invention. The present invention provides a distributed optical fiber sensing vehicle signal enhancement device 800, including: a frame processing module 810, a construction design module 820, and a signal matching module 830; wherein,

[0102] The frame processing module 810 is configured to perform frame processing on the vehicle signal to be processed and obtain the time-frequency characteristics corresponding to the signal to be processed; the time-frequency characteristics include frequency distribution characteristics and time-domain characteristics.

[0103] The construction design module 820 is configured to construct a template signal based on the time-frequency characteristics and design a corresponding matching filter using the template signal to obtain a target filter; the template signal includes at least the principal components of the time-frequency characteristics.

[0104] The signal matching module 830 is configured to match the target filter with the vehicle signal to be processed filtered by the band-pass filter to obtain a target vehicle signal.

[0105] In some embodiments, the frame processing module 810 is specifically configured to:

[0106] Perform frame processing on the vehicle signal to be processed using the short-time Fourier transform (STFT) to obtain the time-frequency curve of the vehicle signal to be processed; the time-frequency curve includes the signal frequency peak.

[0107] Determine the signal within the preset interval where the signal frequency peak is located as the vibration signal, and determine the vehicle signal to be processed outside the preset interval where the signal frequency peak is located as the noise signal.

[0108] In some embodiments, the frame processing module 810 is further specifically configured to:

[0109] Obtain the root mean square (RMS) value corresponding to the time-frequency curve, and determine the vehicle signal to be processed within the preset intervals on both sides of the signal frequency peak where the RMS is greater than the threshold β as the vibration signal:

[0110]

[0111] Perform short-time Fourier transform on the root mean square value (RMS) to determine the intensity of the vehicle signal to be processed at different times and frequencies:

[0112]

[0113] Where N is the frame length, ω(n) is the Hamming window function, x(n) is the original signal, w is the normalized angular frequency, f is the frequency, and ω = 2πf.

[0114] In some embodiments, the construction design module 820 is specifically configured to:

[0115] Screen the vehicle signal to be processed based on the time-frequency characteristics to obtain a vibration data set.

[0116] Perform spectral analysis on the vibration data set to obtain at least two different types of typical vibration signals.

[0117] Perform convolution operation and normalization processing on the typical vibration signal to obtain a template signal.

[0118] In some embodiments, the construction design module is further specifically configured to:

[0119] Perform window function processing on the vibration data to obtain corresponding discrete signals;

[0120] Perform Fourier transform on the discrete signals to obtain the signal spectrum Z[K]: z(n) is the vehicle signal to be processed, and N is the frame length;

[0121] Based on the signal spectrum, determine the power distribution of the discrete signals at different frequencies, determine the characteristic points corresponding to the maximum frequency and the maximum power, and screen at least two different types of typical vibration signals. Among them, the power distribution of the discrete signals satisfies

[0122] In some embodiments, the distributed fiber optic sensing vehicle signal enhancement device further includes a filter design module; the filter design module is specifically configured to:

[0123] Design a Chebyshev band-pass filter using time-frequency characteristics, and use the Chebyshev band-pass filter to remove the temperature drift and at least part of the noise in the vehicle signal to be processed.

[0124] In some embodiments, the filter design module is further specifically configured to determine the minimum order n of the Chebyshev band-pass filter using the following formula:

[0125]

[0126] Among them, w s , w p are the normalized passband and stopband boundary frequencies respectively, and R s is the minimum stopband attenuation.

[0127] In some embodiments, the signal matching module 830 is specifically configured to:

[0128] Construct the impulse response h(n) of the matched filter: h(n) = s * [N - n - 1]; where s * represents the conjugate, and N is the length of the template signal;

[0129] Determine the target vehicle signal y(n) based on the impulse response h(n):

[0130]

[0131] It should be noted that the distributed optical fiber sensing vehicle signal enhancement device provided in the embodiments of the present application and the distributed optical fiber sensing vehicle signal enhancement method provided in the embodiments of the present application are based on the same inventive concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned distributed optical fiber sensing vehicle signal enhancement method, and the repeated parts will not be elaborated here.

[0132] In some embodiments, please refer to Figure 9 , Figure 9 which is a schematic structural diagram of an electronic device provided in an embodiment of the present application. An electronic device 900 provided in an embodiment of the present application includes a processor 910 and a memory 920; the memory 920 stores a computer program, and when the computer program is executed by the processor, the above-mentioned distributed optical fiber sensing vehicle signal enhancement method is implemented.

[0133] Specifically, the processor 910 may include, for example, a general microprocessor, an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (such as an application specific integrated circuit (ASIC)), and so on. The processor 910 may also include on-board memory for caching purposes. The processor 910 may be a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiments of the present application.

[0134] The memory 920 may be, for example, any medium capable of containing, storing, transmitting, propagating, or transferring instructions. For example, the memory 920 may include, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium. Specific examples of the memory 920 include: a magnetic storage device, such as a magnetic tape or a hard disk drive (HDD); an optical storage device, such as a compact disc (CD-ROM); it may also be, for example, a random access memory (RAM) or a flash memory; and / or a wired / wireless communication link.

[0135] The present application also provides a computer-readable medium, on which a computer program is stored, and when the program is executed by the processor, the above-mentioned distributed optical fiber sensing vehicle signal enhancement method is implemented. The computer-readable medium may be included in the device / device / system described in the above embodiments; it may also exist separately and not be assembled into the device / device / system. The above computer-readable medium carries one or more programs, and when the one or more programs are executed, the method according to the embodiments of the present application is implemented.

[0136] According to embodiments of the present application, a computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, 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), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted by any appropriate medium, including but not limited to: wireless, wired, optical fiber cable, radio frequency signal, etc., or any suitable combination of the above.

[0137] Those skilled in the art can understand that the features recited in the various embodiments and / or claims of the present application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly recited in the present application. In particular, without departing from the spirit and teachings of the present application, the features recited in the various embodiments and / or claims of the present application can be combined and / or combined in various ways. All such combinations and / or combinations fall within the scope of the present application. Therefore, the scope of the present application should not be limited to the above embodiments, but should be determined not only by the appended claims, but also by the equivalents of the appended claims. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A distributed optical fiber sensing vehicle signal enhancement method, characterized in that Including: Performing frame division processing on the vehicle signal to be processed to obtain the time-frequency characteristics corresponding to the signal to be processed; the time-frequency characteristics include frequency distribution characteristics and time-domain characteristics; Constructing a template signal based on the time-frequency characteristics, and designing a corresponding matching filter using the template signal to obtain a target filter; the template signal includes at least the principal components of the time-frequency characteristics; Matching the target filter with the vehicle signal to be processed filtered by a band-pass filter to obtain a target vehicle signal.

2. The distributed optical fiber sensing vehicle signal enhancement method according to claim 1, wherein The performing frame division processing on the vehicle signal to be processed to obtain the time-frequency characteristics corresponding to the signal to be processed includes: Using the short-time Fourier transform (STFT) to perform frame division processing on the vehicle signal to be processed to obtain the time-frequency curve of the vehicle signal to be processed; the time-frequency curve includes signal frequency peaks; Determining the signal within a preset interval where the signal frequency peak is located as a vibration signal, and determining the vehicle signal to be processed outside the preset interval where the signal frequency peak is located as a noise signal.

3. The distributed optical fiber sensing vehicle signal enhancement method according to claim 2, wherein The determining the signal within a preset interval where the signal frequency peak is located as a vibration signal, and determining the vehicle signal to be processed outside the preset interval where the signal frequency peak is located as a noise signal includes: Obtaining the root mean square value (RMS) corresponding to the time-frequency curve, and determining the vehicle signal to be processed within a preset interval on both sides of the signal frequency peak where the RMS is greater than the threshold β as a vibration signal: Performing a short-time Fourier transform on the root mean square value (RMS) to determine the intensity of the vehicle signal to be processed at different times and frequencies: Where N is the frame length, ω(n) is the Hamming window function, x(n) is the original signal, w is the normalized angular frequency, f is the frequency, and ω = 2πf.

4. The distributed optical fiber sensing vehicle signal enhancement method according to claim 1, wherein The constructing a template signal based on the time-frequency characteristics, and designing a corresponding matching filter using the template signal to obtain a target filter includes: Screening the vehicle signal to be processed based on the time-frequency characteristics to obtain a vibration data set; Performing spectral analysis on the vibration data set to obtain at least two different types of typical vibration signals; Performing convolution operation and normalization processing on the typical vibration signals to obtain a template signal.

5. The distributed optical fiber sensing vehicle signal enhancement method according to claim 4, wherein The performing spectral analysis on the vibration data set to obtain at least two different types of typical vibration signals includes: Performing window function processing on the vibration data to obtain a corresponding discrete signal; Performing Fourier transform on the discrete signal to obtain the signal spectrum Z[K]; z(n) is the vehicle signal to be processed, and N is the frame length; Determine the power distribution of the discrete signal at different frequencies based on the signal spectrum, determine the characteristic points corresponding to the maximum frequency and the maximum power, and screen to obtain at least two different types of typical vibration signals, where the power distribution of the discrete signal satisfies 6. The distributed optical fiber sensing vehicle signal enhancement method according to claim 1, characterized in that Before matching the target filter with the vehicle signal to be processed filtered by a band-pass filter to obtain a target vehicle signal, the method further includes: Designing a Chebyshev band-pass filter using the time-frequency characteristics, and using the Chebyshev band-pass filter to remove the temperature drift and at least part of the noise in the vehicle signal to be processed.

7. The distributed optical fiber sensing vehicle signal enhancement method according to claim 6, wherein The designing a Chebyshev band-pass filter using the time-frequency characteristics includes, Using the following formula to determine the minimum order n of the Chebyshev band-pass filter: where, w s , w p are the normalized passband and stopband edge frequencies respectively, and R s is the minimum stopband attenuation.

8. The distributed optical fiber sensing vehicle signal enhancement method according to claim 1, characterized in that The matching the target filter with the vehicle signal to be processed filtered by a band-pass filter to obtain a target vehicle signal includes: Construct the impulse response h(n) of the matched filter: h(n) = s * [N - n - 1]; where s * denotes conjugate, and N is the length of the template signal; Determining the target vehicle signal y(n) based on the impulse response h(n):

9. A distributed optical fiber sensing vehicle signal enhancement device, characterized in that, Including: A frame segmentation processing module, a construction design module, and a signal matching module; wherein, The frame segmentation processing module is configured to perform frame segmentation processing on the vehicle signal to be processed, and obtain the time-frequency characteristics corresponding to the signal to be processed; the time-frequency characteristics include frequency distribution characteristics and time-domain characteristics; The construction design module is configured to construct a template signal based on the time-frequency characteristics, and design a corresponding matching filter using the template signal to obtain a target filter; the template signal at least includes the principal components of the time-frequency characteristics; The signal matching module is configured to match the target filter with the vehicle signal to be processed after being filtered by a band-pass filter to obtain a target vehicle signal.

10. A computer storage medium, characterized in that, A computer program is stored thereon, wherein when the computer program is executed by a processor, it implements the distributed optical fiber sensing vehicle signal enhancement method according to any one of claims 1 to 8.

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