A long-distance detection optimization method based on a multi-channel ADC in a DAS system

Abstract

The application discloses a long-distance detection optimization method based on a multi-channel ADC in a DAS system, comprising the following steps: when processing a long-distance optical fiber intermediate frequency signal, the intermediate frequency signal is segmented according to the length of the optical fiber, the intensity of the intermediate frequency signal and the number of channels of the ADC; based on the intensity of the segmented signal, the intermediate frequency signal at different positions is amplified to maximize the adaptation of the ADC range of the segmented intermediate frequency signal; according to the time delay of the segmented signal, the trigger interval between different channels of the ADC is controlled; after synchronizing the multi-section intermediate frequency signal, the segmented signal is smoothed by a diagonal average algorithm, the reconstructed intermediate frequency signal is obtained after superposition, and the phase demodulation of the reconstructed signal is performed to obtain the vibration condition along the whole optical fiber. Without modifying the system hardware, the application can break through the inherent dynamic range of the ADC and improve the intermediate frequency signal demodulation effect of the whole long-distance optical fiber link.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of distributed optical fiber sensing signal processing, and particularly relates to a long-distance detection optimization method based on a multi-channel ADC in a DAS system. BACKGROUND

[0002] Phase-sensitive optical time domain reflectometry (Φ-OTDR) is an optical fiber sensing technology with high sensitivity and wide frequency band response, which can locate the micro disturbance at the position along the line of the whole optical fiber by monitoring the phase change in the optical fiber. It has been widely used in pipeline monitoring, infrastructure monitoring and other application fields. Φ-OTDR is mainly composed of an optical system and a digital signal processing system. When the optical signal passing through the optical path is converted into an electrical signal, the analog signal is converted into a digital signal through a high-speed digital-to-analog converter (ADC), and then the received signal is processed by combining digital signal processing (DSP), so as to analyze the specific position and nature of the disturbance. However, when monitoring a long-distance optical fiber, the optical signal needs to be fully amplified to prevent the tail-end signal from falling into noise, which will cause the head signal to be excessively saturated or even exceed the processing range of the ADC, thereby causing distortion of the signal demodulation. The tail-end signal is limited by the amplification multiple, and its intensity is insufficient, so that the dynamic range of the system is limited. At present, a high-precision high-quantization-bit ADC can be used to improve the dynamic range of the system by improving the quantization bit number of the ADC. However, the high-quantization-bit ADC has a high cost and is limited in engineering practice. Therefore, it is essential to develop a cost-effective solution to balance the demand for system monitoring distance and dynamic range, which is crucial for improving the overall performance of the DAS system and effectively reducing the system cost. SUMMARY

[0003] The technical problem solved by the present application is that a long-distance detection optimization method based on a multi-channel ADC in a DAS system is disclosed, which uses a multi-channel ADC to solve the problem of insufficient dynamic range when monitoring a long-distance optical fiber. By segmenting the optical fiber signal, the front-end signal is ensured not to exceed the range, and the tail-end signal can also fully utilize the data acquisition card to increase the accuracy of the digital system.

[0004] Technical scheme:

[0005] A long-distance detection optimization method based on a multi-channel ADC in a DAS system, the long-distance detection optimization method comprising the following steps:

[0006] S1, the DAS system acquires a long-distance optical fiber signal in real time, amplifies the optical signal using an EDFA, acquires the beat frequency signal of the backscattered Rayleigh scattering light and the intrinsic reference light of the probe light pulse, and performs bandpass filtering on the beat frequency signal to obtain an intermediate frequency signal;

[0007] S2, segmenting the signal according to the fiber distance, signal strength, and the number of ADC channels to obtain n segmented signals, each m continuous segmented signals being combined to represent a section signal, and there being overlapping segmented signals between each section signal; calculating the time delay between each segmented signal, controlling the trigger interval between different channels of the ADC, and synchronizing the multiple intermediate frequency signals;

[0008] S3, customizing amplification of the intermediate frequency signals at different positions according to the strength of each section signal, so that each section signal is maximally adapted to the ADC range to fully utilize the effective bits of the ADC;

[0009] S4, diagonally averaging the fiber signals of different sections, superimposing sub-sequences with the same signal to obtain a reconstructed intermediate frequency signal, and performing phase demodulation on the intermediate frequency signal to obtain the vibration along the entire fiber.

[0010] In step S1, the collected intermediate frequency signal is represented as:

[0011]

[0012] wherein I IF represents the filtered intermediate frequency signal, E(t) represents the electric field intensity of the RBS signal, and E LO represents the electric field intensity of the local oscillator light;

[0013] Step S2 further includes:

[0014] The segmented signal is represented as There are n signals, wherein A1, A2, α, A n respectively represent the signal intensity of different segments, and x1, x2, …, x n represent these segmented signals; each m continuous segmented signal forms a section signal, and the kth section signal is defined as B k The kth section signal is represented as:

[0015] B k ={x k , x k+1 , x k+2 , …, x k+m-1}

[0016] wherein k represents the serial number of the section signal, and k = 1, 2, …, n-m+;

[0017] The complete signal after segmentation is represented as a section signal:

[0018] X = {B1, B2, B3, …, B n-m+1}

[0019] After being converted into segmented signals, the composition is a (n-m+1) x m matrix:

[0020]

[0021] Wherein, each element in the matrix represents a segment signal, each list represents a section signal composed of m segment signals, and there are n-m+1 section signals in total.

[0022] Further, in step S2, the time delay between each segment signal is:

[0023]

[0024] Wherein, L represents the length of the optical fiber corresponding to the segment signal, v represents the propagation speed of light in the optical fiber, and the trigger interval set between different channels of the ADC is mτ.

[0025] Further, in step S3, for the segment signal, after self-defined amplification, it is represented as:

[0026] X amp ={j1B1,j2B2,j3B3,…,j n-m+1 B n-m+1}

[0027] Wherein, X amp represents the segment signal after self-defined amplification, j1, j2, …, j n-m+1 represent the amplification multiples of different section signals, and the expansion of the section signal into the segment signal is represented as:

[0028]

[0029] Further, in step S3, the range of self-defined amplification of each section signal intensity is [0.3R ADC ,1.2R ADc ], the head intensity of each section signal is not more than 1.2 times the maximum range R ADc of the ADC, and the tail intensity is not less than 0.3 times the maximum range R ADC of the ADC. If it cannot be met, the section signal is further subdivided.

[0030] Further, in step S4, the diagonal line average of the optical fiber signals of different sections is performed using the following formula:

[0031]

[0032] Wherein, X new represents the segment signal vector after diagonal line averaging, p represents the diagonal line index, p=0,1,2,…,n-1, corresponding to the sequence order of the segment signal, and n=p-1 is satisfied; all signal trajectory components are arranged in time sequence to obtain the reconstructed intermediate frequency signal after segment processing.

[0033] Advantages:

[0034] The long-distance detection optimization method based on a multi-channel ADC in the DAS system of the application can break through the dynamic range of the DAS system for long-distance optical fiber monitoring and optimize the signal demodulation effect without modifying the optical path structure and the hardware system of the DAS system. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 is a flowchart of the long-distance detection optimization method based on a multi-channel ADC in the DAS system of the application;

[0036] Figure 2 is a schematic diagram of the intermediate frequency signal collected by the DAS system for a 60km optical fiber;

[0037] Figure 3 is a schematic diagram of the intermediate frequency signal waveform, the phase time-domain waveform and the phase spectrum characteristics when the head signal is saturated;

[0038] Figure 4 is a schematic diagram of the segmented signal. DETAILED DESCRIPTION

[0039] The following examples enable those skilled in the art to more fully understand the application, but do not limit the application in any way.

[0040] The embodiment of the application discloses a long-distance detection optimization method based on a multi-channel ADC in a DAS system, mainly including the following steps:

[0041] S1, the DAS system collects long-distance optical fiber signals in real time, uses an EDFA to amplify the optical signals, the system collects the beat frequency signal of the backscattering Rayleigh signal of the probe light pulse and the intrinsic reference light, performs band-pass filtering on the beat frequency signal, and obtains an intermediate frequency signal;

[0042] The intermediate frequency signal collected by the system can be expressed as:

[0043]

[0044] wherein, I IF represents the filtered intermediate frequency signal, E(t) represents the electric field intensity of the RBS signal, E LO represents the electric field intensity of the local oscillator light.

[0045] S2, segment the signal according to the fiber distance, signal strength and the number of ADC channels, the number of segments is n, each segment of the signal is called a "segment signal", every m continuous segment signals are combined to represent a section signal, and it is ensured that there is an overlapping segment signal between each section signal; calculate the time delay between each segment signal, control the trigger interval between different channels of the ADC, and synchronize the multiple segment intermediate frequency signals;

[0046] The segmented signal can be represented as There are n segments of signals, wherein A1, A2, …, An represent the signal strength of different segments, and x1, x2, …, xn represent the signal strength of different segment signals. n There are n segments of signals, wherein A1, A2, …, An represent the signal strength of different segments, and x1, x2, …, xn represent the signal strength of different segment signals. n represent these segment signals. Every m continuous segment signals form a section signal, and the kth section signal is defined as Bk. k The kth section signal can be represented as:

[0047] B k ={x k ,x k+1 ,x k+2 ,…,x k+m-1}

[0048] Wherein, k represents the serial number of the section signal, k = 1, 2, …, n-m+1. Thus, the complete signal after segmentation is represented as a section signal:

[0049] X={B1,B2,xB3,…,B n-m+1}

[0050] After being converted into segment signals:

[0051]

[0052] The composition is an (n-m+1) x m matrix, which is represented as m segment signals constitute each section signal, and there is an overlapping part with the adjacent section signal, and there are n-m+1 section signals.

[0053] S3, for the intermediate frequency signals at different positions, self-defined amplification is performed according to the strength of each section signal, so that each section signal can fully utilize the input range of the ADC;

[0054] For the segment signal, after self-defined amplification, it can be represented as:

[0055] X amp ={j1B1,j2B2,j3B3,…,j n-m +1B n-m+1}

[0056] Wherein, X amp represents the segment signal after self-defined amplification, j1, j2, …, j n-m+1respectively, the expansion of the section signal into the segmented signal can be expressed as:

[0057]

[0058] S4, the diagonal average of the fiber signal of different sections is performed, so that the sub-sequences with the same signal are superimposed to obtain the reconstructed intermediate frequency signal, and the phase demodulation is performed on the intermediate frequency signal to obtain the vibration along the line of the whole optical fiber;

[0059] For the segmented signal, the position of the same segmented signal is parallel to the anti-diagonal line of the matrix, and the average of the same elements is taken to complete the smoothing processing of the recombination of the segmented signal, so that for the diagonal line index p

[0060]

[0061] And for p≥m:

[0062]

[0063] Wherein, the value range of p is: 0, 1, 2, …, n-1, a total of n points, corresponding to the sequence order of the segmented signal, satisfying n=p-1. Then, all signal trajectory components are arranged in time sequence to obtain the reconstructed intermediate frequency signal after the segmentation processing.

[0064] Examples

[0065] The technical solutions of the present application will be further described in detail in combination with the drawings of the specification and an example. As Figure 1 shown, the specific process of the example is as follows:

[0066] Step one, use the DAS system to collect the signal of 60km optical fiber, the actual effective number of bits of the ADC used this time is 8, the head signal of the optical fiber is amplified and saturated by the EDFA, so that the tail signal does not fall into the noise, the display of the signal after amplification on the system is as Figure 2 shown, wherein the amplitude fluctuation difference of the tail intermediate frequency signal is about 54, and the amplitude fluctuation difference of the noise is about 20.

[0067] Step two, for the collected intermediate frequency signal, the peak-to-peak value of the amplitude fluctuation is about 750 after the head signal is fully saturated, which is much larger than the amplitude of the tail signal, as Figure 3As shown, the time-domain waveform of the phase has a certain distortion, and the phase spectrum appears frequency doubling phenomenon, so the intermediate frequency signal needs to be segmented. Since the average loss of the used optical fiber is 0.20 dB / km, that is, the intensity of the intermediate frequency signal is attenuated by half every 15 km of optical fiber, and according to the number of ADC channels, the signal is divided into 8 segments, that is, the signal of about 7.5 km is a segment, and each 3 segments of signal is defined as a section, and there are 6 sections of signal, which are 1, 2, 3 segments, 2, 3, 4 segments, 3, 4, 5 segments, 4, 5, 6 segments, 5, 6, 7 segments, and 6, 7, 8 segments. Figure 4 is a schematic diagram of the segmented signal.

[0068] Step three, it can be calculated that for the first 4 sections of signal, the head signal intensity is greater than the ADC range, and the 4 sections of signal need to be attenuated respectively, for the first section of signal, the amplitude fluctuation difference of the head and tail is about 750, 265 respectively, in order to make the signal intensity meet the ADC range, the signal needs to be attenuated by 3 times, and the amplitude fluctuation difference of the head and tail of the signal after attenuation is about 250, 88, and the attenuation operation of the second, third and fourth sections of signal is the same. For the last 2 sections of signal, the head signal intensity is less than the ADC range, and the two sections of signal need to be amplified respectively, for the sixth section of signal, the amplitude fluctuation difference of the head and tail is about 132, 47 respectively, and the signal needs to be amplified by 2 times, and the amplitude fluctuation difference of the signal after amplification is about 264, 96 respectively, and the amplification operation of the fifth section of signal is the same.

[0069] Step four, the segmented signals with the same position after attenuation or amplification are diagonally averaged, and the segmented signals after self-defined amplification can be represented in the form of matrix as follows:

[0070]

[0071] Therefore, the segmented signal after diagonal averaging can be represented as:

[0072]

[0073] Then, the segmented signals are arranged in time sequence to obtain the reconstructed intermediate frequency signal, and the intermediate frequency signal is phase demodulated to realize the vibration condition monitoring along the whole optical fiber.

[0074] The above is only the preferred embodiment of the present application, and the protection scope of the present application is not limited to the above-mentioned embodiments, and any technical solution belonging to the idea of the present application shall belong to the protection scope of the present application. It should be noted that for ordinary technical personnel in the technical field, some improvements and decorations without departing from the principle of the present application shall be regarded as the protection scope of the present application.

Claims

1. A long-range detection optimization method based on a multi-channel ADC in a DAS system, characterized in that, The long-distance detection optimization method includes the following steps: S1, the DAS system acquires long-distance fiber optic signals in real time, amplifies the optical signals using EDFA, acquires the beat frequency signal between the back Rayleigh scattering light of the probe light pulse and the intrinsic reference light, and performs bandpass filtering on the beat frequency signal to obtain the intermediate frequency signal; S2, the signal is segmented according to the fiber distance, signal strength and number of ADC channels to obtain n segmented signals. Each m consecutive segmented signals are combined to represent a section of signal. There are overlapping segmented signals between each section of signal. The time delay between each segmented signal is calculated to control the trigger interval between different channels of ADC and synchronize multiple intermediate frequency signals. S3, for intermediate frequency signals at different locations, performs custom amplification based on the strength of each signal segment, so that each signal segment can be adapted to the ADC range to make full use of the ADC's effective bit number. S4. Diagonal averaging of the optical fiber signals from different sections is performed to superimpose subsequences with the same signal to obtain the reconstructed intermediate frequency signal. Phase demodulation of the intermediate frequency signal is then performed to obtain the vibration status along the entire optical fiber. In step S3, the segmented signal, after custom amplification, is represented as follows: X amp ={j1B1,j2,B2,j3B3,…,j n-m+1 B n-m+1 } Among them, X amp This represents the segmented signal after custom amplification, j1, j2, ..., j n-m+1 These represent the amplification factors for different sections of the signal. The section signal is expanded into a segmented signal as follows:

2. The long-range detection optimization method based on multi-channel ADC in the DAS system according to claim 1, characterized in that, In step S1, the acquired intermediate frequency signal is represented as follows: Among them, I IF E(t) represents the filtered intermediate frequency signal, and E(t) represents the electric field strength of the RBS signal. LO This represents the electric field strength of the local oscillator light.

3. The long-range detection optimization method based on multi-channel ADC in the DAS system according to claim 1, characterized in that, Step S2 further includes: The segmented signal is represented as follows: There are n signal segments, where A1, A2, ..., A n To represent the signal strength of different segments, use x1, x2, ..., x n These segmented signals represent the m consecutive segments; each segment consists of m consecutive segments, and the k-th segment is defined as B. k The signal in section k is represented as: B k ={x k ,x k+1 ,x k+2 ,…,x k+m-1 } Where k represents the sequence number of the segment signal, k = 1, 2, ..., n-m+; The complete signal after segmentation is represented as a segment signal as follows: X={B1,B2,B3,…,B n-m+1 } After being converted into segmented signals, they are combined into a (n-m+1)×m matrix: In this matrix, each element represents a segmented signal, and each column represents a segment composed of m segmented signals, for a total of n-m+1 segments.

4. The long-range detection optimization method based on multi-channel ADC in the DAS system according to claim 1, characterized in that, In step S2, the time delay between each segment of the signal is: Where L represents the fiber length corresponding to the segmented signal, v represents the speed of light propagation in the light ray, and the trigger interval set between different channels of the ADC is mτ.

5. The long-range detection optimization method based on multi-channel ADC in the DAS system according to claim 1, characterized in that, In step S3, the range of signal strength amplification for each section is defined as [0.3R]. ADC 1.2R ADC The head strength of each signal segment shall not exceed 1.2 times the maximum range R of the ADC. ADC The tail strength is not less than 0.3 times the maximum range of the ADC R. ADC If the condition cannot be met, the segment signal will be further subdivided.

6. The long-range detection optimization method based on multi-channel ADC in the DAS system according to claim 1, characterized in that, In step S4, the diagonal average of the optical fiber signals from different sections is performed using the following formula: Among them, X new Let p represent the segmented signal vector after diagonal averaging, where p = 0, 1, 2, ..., n-1, corresponding to the sequence order of the segmented signals, satisfying n = p-1. Arrange all signal trajectory components in time order to obtain the reconstructed intermediate frequency signal after segmentation.

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