Structure Evaluation System Using Elastic Wave Source Density Distribution
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Solution Overview
Problem
The accuracy of structure evaluation systems that use elastic waves to detect damage within structures is compromised due to pseudo-density distribution patterns generated by random noise, leading to reduced evaluation accuracy of structural deterioration.
Innovation Solution
A structure evaluation system comprising sensors, a position locator, a distribution generator, and an evaluator, which uses reference distributions simulated with random numbers to correct elastic wave source density distributions, thereby improving the accuracy of damage assessment within structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If event extraction algorithm is used to locate elastic wave sources, then position location capability is improved, but pseudo-density distribution patterns are generated due to random noise
Solution Approach 1:
The patent creates a reference distribution that copies the statistical characteristics of random noise by simulating elastic wave propagation with randomly generated source positions. This reference distribution serves as a model of what noise alone would produce, allowing differentiation between real damage patterns and noise artifacts.
Solution Approach 2:
The reference distribution acts as an intermediary between the raw hit data and the final evaluation. By comparing the actual elastic wave source density distribution against this reference, the system mediates the interpretation process to distinguish genuine damage from noise-induced pseudo-patterns.
2Reliability
If elastic wave source density distribution is generated from position location results, then damage detection capability is improved, but evaluation accuracy decreases due to noise-induced pseudo-patterns
Solution Approach 1:
The patent converts the harmful effect of random noise into a beneficial reference model. By deliberately generating a reference distribution using the same random noise characteristics, the system transforms noise from an obstacle into a tool for identifying and eliminating false damage patterns.
Solution Approach 2:
The system changes the parameter of comparison by not just looking at the absolute density distribution, but comparing it against a reference distribution generated with identical noise parameters. This parameter transformation allows the system to filter out noise effects while preserving genuine damage signals.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively suppresses the decrease in evaluation accuracy by incorporating reference distributions that account for random noise, providing a more accurate assessment of structural deterioration.
Implementation Method 1
detect elastic waves generated inside the structure
Implementation Method 2
detect elastic waves generated inside the structure
Data Source
AI summary
According to one embodiment, a structure evaluation system of an embodiment includes a plurality of sensors, a position locator, a distribution generator, and an evaluator. The plurality of sensors detect elastic waves generated inside a structure. The position locator locates positions of one or more elastic wave generation sources on the basis of a plurality of elastic waves detected by each of the plurality of sensors. The distribution generator generates an elastic wave source density distribution representing a density distribution of the one or more elastic wave generation sources on the basis of a position location result of the one or more elastic wave generation sources obtained by the position locator. The evaluator evaluates damage to the structure on the basis of one or more reference distributions generated on the basis of a simulation including a random number and the elastic wave source density distribution generated by the distribution generator.


