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Pipeline corrosion grade evaluation method based on multilayer convolution sparse coding

A technology of convolutional sparse coding and level evaluation, applied in the field of level evaluation, can solve the problems of a large number of parameters, large amount of calculation, lack of interpretability, etc., and achieve the effect of high accuracy and efficient extraction

Active Publication Date: 2021-09-03
BEIHANG UNIV
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Problems solved by technology

However, the working mechanism of the network is difficult to clarify, lacks interpretability, and a model with perfect performance often requires a large number of parameters and a huge amount of calculation

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  • Pipeline corrosion grade evaluation method based on multilayer convolution sparse coding
  • Pipeline corrosion grade evaluation method based on multilayer convolution sparse coding
  • Pipeline corrosion grade evaluation method based on multilayer convolution sparse coding

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Embodiment Construction

[0046] In order to better understand the technical solutions of the present invention, the specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and examples. The same reference numbers in the figures indicate functionally identical or similar elements. While various aspects of the embodiments are shown in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

[0047] Such as figure 2 As shown, a pipeline corrosion level assessment method based on multi-layer convolutional sparse coding includes the following steps:

[0048] S1: Install the first acceleration sensor and the second acceleration sensor on the outer surface of the pipeline. The first acceleration sensor and the second acceleration sensor are respectively located on both sides of the area of ​​interest of the pipeline. Use a hammer to hit the area of ​​interest to obtain the shock respons...

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Abstract

The invention provides a pipeline corrosion grade evaluation method based on multilayer convolution sparse coding, and the method comprises the following steps: S1, installing a first acceleration sensor and a second acceleration sensor on the outer surface of a pipeline, knocking a region of interest through a force hammer, and obtaining an impact response signal; S2, constructing a grade evaluation model based on multilayer convolution sparse coding; S3, collecting force hammer actual measurement data of a to-be-tested pipeline, and after preprocessing is conducted, taking time domain signals as a test set and inputting into the model trained in the step S2; and S4, giving a pipeline corrosion grade evaluation result according to the evaluation model based on multilayer convolution sparse coding. According to the method, multilayer convolution sparse coding is adopted as a model, effective features in multiple frequency bands are extracted by using an oscillation attenuation function, weak damage features in vibration signals under pipeline corrosion can be effectively extracted, automatic corrosion grade evaluation is completed, dependence of a traditional method on manual threshold selection is avoided, and the method is suitable for online pipeline corrosion monitoring.

Description

technical field [0001] The invention relates to the technical field of non-destructive testing, in particular to a pipeline corrosion level evaluation method based on multi-layer convolution sparse coding. Background technique [0002] Corrosion damage of pipelines is one of the main problems faced by industries such as petroleum and construction. Pipelines will inevitably be affected by external forces and environmental changes during their service, which will cause aging problems such as corrosion and wear, and then cause accidents. Therefore, it is of great significance to carry out the research on non-destructive testing and evaluation methods of pipelines to ensure the safe and reliable service of pipelines. At present, non-destructive testing technologies for pipeline corrosion mainly include ultrasonic testing, magnetic flux leakage testing, and radiographic testing. However, the service conditions of pipelines are complex, and the above-mentioned conventional metho...

Claims

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Application Information

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IPC IPC(8): G06F30/18G06F30/27G06K9/62G06N3/04G06N3/08G06F113/14
CPCG06F30/18G06F30/27G06N3/08G06F2113/14G06N3/045G06F18/24G06F18/214
Inventor 华佳东张晗彭勃高飞童彤梁振霖林京
Owner BEIHANG UNIV
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