CN-121977620-A - CEEMDAN-PCC-based signal processing method and system for phase sensitive optical time domain reflectometer

CN121977620ACN 121977620 ACN121977620 ACN 121977620ACN-121977620-A

Abstract

The invention discloses a CEEMDAN-PCC-based signal processing method and system of a phase sensitive optical time domain reflectometer, wherein the method comprises the steps of adopting CEEMDAN algorithm to decompose a backward Rayleigh scattered light signal output by the phase sensitive optical time domain reflectometer into a plurality of IMF components and residual components; and screening the components obtained by the decomposition according to the calculated pearson correlation coefficient between the backward Rayleigh scattered light signal and each IMF component, and determining the position of the disturbance point based on the screened components. The invention solves the problems that in the existing phase sensitive optical time domain reflectometer signal processing method relying on wavelet decomposition and EMD, the suitability of wavelet decomposition is weaker, and the EMD is easy to generate modal aliasing and end effect in the decomposition process.

Inventors

JIANG HAIMING
WEI JIAXIN
XIE KANG

Assignees

广东工业大学

Dates

Publication Date: 20260505
Application Date: 20260121

Claims (6)

1. The signal processing method of the phase sensitive optical time domain reflectometer based on CEEMDAN-PCC is characterized by comprising the following steps: step S1, inputting pulse signals to a phase sensitive optical time domain reflectometer according to preset frequency for processing, and outputting and collecting a plurality of backward Rayleigh scattered light signals; S2, decomposing each backward Rayleigh scattered light signal by adopting a fully adaptive noise set empirical mode decomposition CEEMDAN algorithm to obtain an intrinsic mode function IMF component and a residual component corresponding to each backward Rayleigh scattered light signal; S3, respectively calculating and obtaining pearson correlation coefficients between each backward Rayleigh scattered light signal and each IMF component obtained by corresponding decomposition; Step S4, setting a maximum value threshold of the Pearson correlation coefficient Minimum threshold for pearson correlation coefficient ; Step S5, traversing all backward Rayleigh scattering optical signals, and if the Pirson correlation coefficient between the ith backward Rayleigh scattering optical signal and the corresponding kth IMF component is in the traversing process Greater than When the i-th backward Rayleigh scattering optical signal is in the process, all the pearson correlation coefficients in the i-th backward Rayleigh scattering optical signal are reserved to be larger than If the pearson correlation coefficient between the ith backward Rayleigh scattered light signal and the corresponding all IMF components is less than or equal to When the method is used, the residual component of the ith backward Rayleigh scattered light signal is reserved, so that a screened component is obtained; and S6, determining the position of the disturbance point according to the screened components, and filtering out the components of the position of the non-disturbance point.
2. The method for processing a phase-sensitive optical time domain reflectometer signal based on CEEMDAN-PCC of claim 1, wherein in step S2, the ith backward Rayleigh scattered light signal is decomposed by adopting CEEMDAN algorithm to obtain an IMF component and a residual component corresponding to the ith backward Rayleigh scattered light signal, and the method specifically comprises the following substeps: Step S21, for the ith backward Rayleigh scattered light signal Sequentially adding M groups of independent Gaussian white noise to obtain M groups of noisy i-th backward Rayleigh scattered light signals, wherein the j-th group of noisy i-th backward Rayleigh scattered light signals The mathematical expression of (2) is as follows: ; Wherein, the Representation of M represents the total amount of Gaussian white noise; s22, adopting an EMD (empirical mode decomposition) algorithm to decompose the ith backward Rayleigh scattered light signal with noise in each group, and extracting corresponding first-layer IMF (inertial measurement unit) components from decomposition results of each group ; Step S23, connecting All corresponding first layer IMF components Carrying out summation average operation to obtain Corresponding final first IMF component , wherein, The specific calculation formula is as follows: ; Step S24, connecting Subtracting out Obtaining A corresponding residual component; Step S25, judging Whether the corresponding residual component is a monotonic function, if so, outputting If not, executing step S26; Step S26, M groups of independent Gaussian white noise are sequentially added to the current residual error component to obtain M groups of new noisy signals; Then adopting an EMD decomposition algorithm to decompose each group of new noisy signals respectively, and extracting first-layer IMF components corresponding to each group of new noisy signals respectively; then, the sum-average operation is carried out on the first layer IMF components corresponding to M groups of new noisy signals to obtain A corresponding final next IMF component; subtracting the current residual component from Obtaining a new residual error component by the corresponding final next IMF component; finally judging whether the new residual component is a monotonic function, if so, outputting the obtained final IMF component and the new residual component, otherwise, taking the new residual component as the current residual component, repeatedly executing the step S26 until the decomposed residual component is a monotonic function, and outputting Corresponding to all final IMF components and final residual components.
3. The method for processing a phase-sensitive optical time domain reflectometer signal based on CEEMDAN-PCC as claimed in claim 1, wherein in step S3, a Pearson correlation coefficient between the ith backward Rayleigh scattered light signal and the kth IMF component obtained by the corresponding decomposition is calculated, and specifically comprises the following sub-steps: step S31, extracting data points in the ith backward Rayleigh scattered light signal And data points in a kth IMF component obtained by decomposing the ith backward Rayleigh scattered light signal ; Step S32, calculating the average value of all data points in the ith backward Rayleigh scattered light signal And the average value of all data points in the kth IMF component obtained by decomposing the ith backward Rayleigh scattered light signal ; Step S33, according to 、、 And Calculating a pearson correlation coefficient between the ith backward Rayleigh scattered light signal and the kth IMF component obtained by corresponding decomposition , wherein, The specific calculation formula is as follows: ; Wherein, the Representing the coordinates of the first data point in the ith backward Rayleigh scattered light signal; And N represents the ith backward Rayleigh scattering optical signal or the total number of the data points in the kth IMF component obtained by decomposing the ith backward Rayleigh scattering optical signal.
4. A CEEMDAN-PCC based phase sensitive optical time domain reflectometer signal processing system using a CEEMDAN-PCC based phase sensitive optical time domain reflectometer signal processing method as claimed in any one of claims 1 to 3, characterized in that the system comprises: The input module is used for inputting pulse signals to the phase sensitive optical time domain reflectometer according to a preset frequency for processing; the output and acquisition module is used for outputting and acquiring a plurality of backward Rayleigh scattered light signals; The decomposition module is used for decomposing each backward Rayleigh scattered light signal by adopting a complete self-adaptive noise set empirical mode decomposition CEEMDAN algorithm to obtain an intrinsic mode function IMF component and a residual component corresponding to each backward Rayleigh scattered light signal; the calculation module is used for respectively calculating and obtaining the pearson correlation coefficient between each backward Rayleigh scattered light signal and each IMF component obtained by corresponding decomposition; a setting module for setting the maximum value threshold of the pearson correlation coefficient Minimum threshold for pearson correlation coefficient ; The traversing module is used for traversing all backward Rayleigh scattered light signals, and executing the judging and screening module in the traversing process; a judging and screening module for determining the pearson correlation coefficient between the ith backward Rayleigh scattered light signal and the corresponding kth IMF component Greater than When the i-th backward Rayleigh scattering optical signal is in the process, all the pearson correlation coefficients in the i-th backward Rayleigh scattering optical signal are reserved to be larger than If the pearson correlation coefficient between the ith backward Rayleigh scattered light signal and the corresponding all IMF components is less than or equal to When the method is used, the residual component of the ith backward Rayleigh scattered light signal is reserved, so that a screened component is obtained; the determining module is used for determining the position of the disturbance point according to the screened components; and the filtering module is used for filtering the component of the position of the undisturbed point.
5. The CEEMDAN-PCC based phase sensitive optical time domain reflectometer signal processing system of claim 4, wherein the decomposition module comprises: a first noise adding sub-module for adding noise to the ith backward Rayleigh scattered light signal Sequentially adding M groups of independent Gaussian white noise to obtain M groups of noisy i-th backward Rayleigh scattered light signals, wherein the j-th group of noisy i-th backward Rayleigh scattered light signals The mathematical expression of (2) is as follows: ; Wherein, the Representation of M represents the total amount of Gaussian white noise; The first decomposition sub-module is used for decomposing the ith backward Rayleigh scattering light signal with noise of each group by adopting an EMD decomposition algorithm; a first extraction sub-module for extracting corresponding first layer IMF components from the decomposition results of each group ; A first summing average operator module for summing All corresponding first layer IMF components Carrying out summation average operation to obtain Corresponding final first IMF component , wherein, The specific calculation formula is as follows: ; a first difference operator module for comparing Subtracting out Obtaining A corresponding residual component; A first judging sub-module for judging If not, the second noise adding sub-module, the second decomposition sub-module, the second extraction sub-module, the second summation average operation sub-module, the second difference operation sub-module and the second judgment sub-module are sequentially executed; a first output sub-module for outputting And A corresponding residual component; the second noise adding sub-module is used for sequentially adding M groups of independent Gaussian white noise to the current residual error component to obtain M groups of new noisy signals; The second decomposition sub-module is used for decomposing each group of new noisy signals by adopting an EMD decomposition algorithm; the second extraction submodule is used for extracting first-layer IMF components corresponding to each group of new noisy signals; a second summation average operation sub-module for performing summation average operation on the first layer IMF components corresponding to the M groups of new noisy signals to obtain A corresponding final next IMF component; A second difference operator module for subtracting the current residual component from Obtaining a new residual error component by the corresponding final next IMF component; The second judging sub-module is used for judging whether the new residual error component is a monotonic function, if so, executing the second output sub-module, and if not, repeatedly executing the second noise adding sub-module, the second decomposition sub-module, the second extraction sub-module, the second summation average operation sub-module, the second difference operation sub-module and the second judging sub-module in sequence until the residual error component obtained by decomposition is a monotonic function, and executing the third output sub-module; A second output sub-module for outputting the obtained final IMF component and a new residual component; A third output sub-module for outputting Corresponding to all final IMF components and final residual components.
6. The CEEMDAN-PCC based phase sensitive optical time domain reflectometer signal processing system of claim 4, wherein the computing module comprises: a third extraction sub-module for extracting data points in the ith backward Rayleigh scattered light signal And data points in a kth IMF component obtained by decomposing the ith backward Rayleigh scattered light signal ; A first calculation sub-module for calculating the average value of all data points in the ith backward Rayleigh scattered light signal And the average value of all data points in the kth IMF component obtained by decomposing the ith backward Rayleigh scattered light signal ; A second calculation sub-module for according to 、、 And Calculating a pearson correlation coefficient between the ith backward Rayleigh scattered light signal and the kth IMF component obtained by corresponding decomposition , wherein, The specific calculation formula is as follows: ; Wherein, the Representing the coordinates of the first data point in the ith backward Rayleigh scattered light signal; And N represents the ith backward Rayleigh scattering optical signal or the total number of the data points in the kth IMF component obtained by decomposing the ith backward Rayleigh scattering optical signal.

Description

CEEMDAN-PCC-based signal processing method and system for phase sensitive optical time domain reflectometer Technical Field The invention relates to the technical field of signal processing of phase sensitive optical time domain reflectometers, in particular to a CEEMDAN-PCC-based signal processing method and system of a phase sensitive optical time domain reflectometer. Background The phase sensitive optical time domain reflectometer is a classical distributed optical fiber sensing system, and has the advantages of high sensitivity, high response speed and long-distance sensing in the aspect of detecting a slight disturbance event. The phase sensitive optical time domain reflectometer is characterized in that pulse light with strong coherence is injected into a sensing optical fiber, when weak disturbance exists on the sensing optical fiber, the refractive index of the optical fiber at a disturbance position changes to cause the light phase at a corresponding position to change accordingly, so that the amplitude of a backward Rayleigh scattering interference signal changes, and the position of an external disturbance point and relevant parameters of the disturbance can be determined. The phase sensitive optical time domain reflectometer needs to receive and collect scattered light signals in a sensing optical fiber in the sensing process, but the collected signals often carry a large amount of noise, such as interference fading noise of Rayleigh scattered light, phase noise caused by laser frequency drift and the like, and backward Rayleigh scattered light is very weak and is easily submerged by the noise to be unrecognizable. In addition, the high sensitivity of the phase sensitive optical time domain reflectometer also means that the external environment is very easy to influence the system signal, which results in that effective information can be obtained after a certain processing is required for the signal doped with noise. The signal processing element is therefore an essential part of the phase sensitive optical time domain reflectometer. In the signal processing method of the existing phase sensitive optical time domain reflectometer, aiming at a signal decomposition link, common means comprise methods such as wavelet decomposition, EMD (empirical mode decomposition) and the like, however, on one hand, the suitability of the wavelet decomposition is weak, scattering signals with different characteristics are difficult to flexibly match, on the other hand, the problem of modal aliasing is easy to occur in the decomposition process of the EMD, and meanwhile, the reliability of a decomposition result is also reduced due to interference of an end point effect. Disclosure of Invention Aiming at the defects, the invention provides a CEEMDAN-PCC-based phase-sensitive optical time domain reflectometer signal processing method and a CEEMDAN-PCC-based phase-sensitive optical time domain reflectometer signal processing system, and aims to solve the problems that in the existing phase-sensitive optical time domain reflectometer signal processing method which depends on wavelet decomposition and EMD, the suitability of the wavelet decomposition is weaker, and modal aliasing and end-point effects are easy to occur in the decomposition process of the EMD. To achieve the aim, the invention adopts the following technical scheme: A CEEMDAN-PCC-based phase sensitive optical time domain reflectometer signal processing method comprises the following steps: step S1, inputting pulse signals to a phase sensitive optical time domain reflectometer according to preset frequency for processing, and outputting and collecting a plurality of backward Rayleigh scattered light signals; S2, decomposing each backward Rayleigh scattered light signal by adopting a fully adaptive noise set empirical mode decomposition CEEMDAN algorithm to obtain an intrinsic mode function IMF component and a residual component corresponding to each backward Rayleigh scattered light signal; S3, respectively calculating and obtaining pearson correlation coefficients between each backward Rayleigh scattered light signal and each IMF component obtained by corresponding decomposition; Step S4, setting a maximum value threshold of the Pearson correlation coefficient Minimum threshold for pearson correlation coefficient; Step S5, traversing all backward Rayleigh scattering optical signals, and if the Pirson correlation coefficient between the ith backward Rayleigh scattering optical signal and the corresponding kth IMF component is in the traversing processGreater thanWhen the i-th backward Rayleigh scattering optical signal is in the process, all the pearson correlation coefficients in the i-th backward Rayleigh scattering optical signal are reserved to be larger thanIf the pearson correlation coefficient between the ith backward Rayleigh scattered light signal and the corresponding all IMF components is less than or equal toWhen the method is used, the res