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Undistorted boundary continuation method for wavelet online denoising

A technology without distortion and boundaries, applied in special data processing applications, instruments, electrical digital data processing, etc., to achieve the effect of improving denoising performance, speed, and good denoising effect

Inactive Publication Date: 2020-09-18
HARBIN ENG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0008] The purpose of the present invention is to provide a distortion-free boundary continuation scheme for online implementation of wavelet denoising, to suppress the boundary effect of wavelet algorithm and overcome the algorithm interference defects existing in traditional continuation schemes, and completely solve the distortion of wavelet online denoising problem, completely exclude the algorithmic interference of the boundary

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  • Undistorted boundary continuation method for wavelet online denoising
  • Undistorted boundary continuation method for wavelet online denoising
  • Undistorted boundary continuation method for wavelet online denoising

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Embodiment 1

[0072] Such as Figure 6 As shown, a distortion-free boundary extension method for wavelet online denoising includes the following steps:

[0073] S1 acquisition signal segment x n , carry out undistorted boundary continuation processing on the signal segment to obtain M+N+L data, where M is the number of historical data used for undistorted left continuation, L is the number of future data used for undistorted right continuation number, N is the number of data to be denoised

[0074] Such as Figure 7 As shown, the online denoising working sequence of the distortion-free continuation scheme is as follows (assuming that the sampling interval is 1):

[0075] Preparation stage: Apply for a cache area A that can accommodate M+N+L data. Here we define an operation step named "sliding window operation", which is defined as: once the buffer A is full, M+N+L data must be output to the next wavelet denoiser within a sampling interval, The M+L pieces of data in the back section of...

Embodiment 2

[0126] The present invention also provides a device for wavelet online denoising without distortion boundary extension, including a distortion-free boundary extension processing module and a wavelet denoiser;

[0127] The distortion-free boundary extension processing module is used to process the collected signal segment without distortion boundary extension to obtain M+N+L data, where M is the number of historical data used for distortion-free left extension, and L is the The number of future data to be extended without distortion, N is the number of data to be denoised;

[0128] Wavelet de-noising device, which is used to decompose the N data to be denoised by lifting wavelet j layer to obtain the approximate coefficient s j and detail coefficient {d j ,...,d 2 , d 1}; Calculate the threshold T of each layer of the lifting wavelet j ;For each layer of detail coefficient {d j ,...,d 2 , d 1} to perform threshold quantization to obtain the estimated value of the detail ...

Embodiment 3

[0143] A schematic diagram of a hardware structure of an electronic device provided by an embodiment of the present invention, the electronic device 800 includes: a processor, a memory, and a computer program; wherein

[0144] The memory is used to store computer programs, and the memory may also be a flash memory (flash). The computer program is, for example, an application program, a function module, etc. for realizing the above method.

[0145] The processor is configured to execute the computer program stored in the memory, so as to realize each step in the above method. For details, refer to the related descriptions in the foregoing method embodiments.

[0146] Optionally, the memory can be independent or integrated with the processor.

[0147] When the memory is a device independent of the processor, the electronic equipment may also include:

[0148] A bus that connects memory and processors.

[0149] The specific form of expression of the above-mentioned electronic...

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Abstract

The invention provides an undistorted boundary continuation scheme for wavelet online denoising. The method comprises the steps: S1, acquiring a signal segment xn, carrying out distortionless boundarycontinuation processing on the signal segment to obtain M + N + L data, wherein M is the number of historical data used for distortionless left continuation, L is the number of future data used for distortionless right continuation, and N is the number of data to be denoised; s2, performing lifting wavelet j-layer decomposition on the N pieces of to-be-denoised data to obtain an approximation coefficient sj and detail coefficients {dj,..., d2, d1}; s3, calculating a threshold value Tj of each layer of the lifting wavelet; s4, performing threshold quantification on the detail coefficient {dj,..., d2, d1} of each layer to obtain a detail coefficient estimated value; and S5, carrying out wavelet reconstruction by using the approximation coefficient sj and the detail coefficient estimated value after threshold quantization to obtain denoised reconstructed signal S6 output data. According to the method, the working time sequence of online denoising is designed, a distortionless continuation scheme is provided for the serious boundary interference problem during online denoising, and boundary interference is eliminated; and a fundamental wavelet, a decomposition layer number and a threshold estimation value adopted by an algorithm denoising algorithm are determined according to the actual characteristics of the magnetic flux leakage detection signal. A traditional threshold functionis improved, the denoising performance is further improved, and a better denoising effect is achieved.

Description

technical field [0001] The invention relates to an online implementation technology of wavelet signal denoising, in particular to an online implementation technology of wavelet denoising based on a distortion-free boundary extension method. Background technique [0002] Magnetic flux leakage testing has the advantages of high detection sensitivity, fast detection speed, low requirement on sample surface cleanliness, low cost and simple operation, so it is widely used in the field of nondestructive testing of ferromagnetic materials. Signal processing is the core part of the magnetic flux leakage detection system. How to obtain useful signals in a complex field environment, remove noise, and finally realize quantitative analysis of defect signals is the key to the entire detection system. This requires noise reduction processing for the magnetic flux leakage signal under noise interference. [0003] Wavelet denoising method is an excellent signal denoising algorithm, and it ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G01N27/83G01R33/12
CPCG01N27/83G01R33/12G06F2218/06G06F17/148G01N27/82
Inventor 张兰勇王梦琳刘胜李承羽
Owner HARBIN ENG UNIV
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