Sensor Adhesion State Determination via Acoustic Emission Peak Frequency
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Solution Overview
Problem
Existing sensor adhesion state determination systems face challenges in accurately assessing the adhesion of sensors to structures, which can lead to reduced accuracy in structural deterioration evaluation and potential sensor detachment.
Innovation Solution
A sensor adhesion state determination system that utilizes a plurality of AE sensors and a signal processor to determine the adhesion state of sensors by calculating peak frequencies from AE source signals and comparing them to a reference range, thereby determining whether the adhesion is good or defective.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors are adhered to structure surfaces with adhesive for deterioration evaluation, then structural degradation can be detected through AE detection, but adhesion may become insufficient due to defective work or time passage, leading to reduced evaluation accuracy and sensor detachment risk
Solution Approach 1:
The sensor system performs self-diagnosis by utilizing its own AE detection capability to monitor its own adhesion state. The sensor detects elastic waves generated by structure deterioration and simultaneously uses these detection results to determine whether it is properly adhered to the structure, enabling automatic adhesion state monitoring without external intervention
Solution Approach 2:
The system establishes a feedback loop where AE detection results are fed back to the adhesion state determination unit. The determination unit analyzes the AE signal characteristics (such as frequency content and amplitude) to assess sensor adhesion quality, and this information can trigger alerts or corrective actions to maintain evaluation accuracy
2Reliability
If multiple sensors are deployed for comprehensive monitoring, then coverage and detection capability improve, but the complexity of determining individual sensor adhesion states increases
Solution Approach 1:
Each sensor in the network is equipped with the same dual functionality: it can detect AE signals from structure deterioration and simultaneously determine its own adhesion state. This universal design allows multiple sensors to operate independently with identical capabilities, simplifying the overall system architecture while maintaining comprehensive monitoring coverage
Solution Approach 2:
The adhesion determination function is segmented and distributed to each individual sensor rather than centralized in a single control unit. Each sensor independently analyzes its own adhesion state based on its AE detection results, reducing the complexity of centralized processing and enabling parallel operation of multiple sensors
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 determines the adhesion state of sensors, ensuring accurate structural deterioration evaluation and preventing sensor detachment, thereby enhancing the reliability of the monitoring process.
Implementation Method 1
Structures generate acoustic emissions (AEs) due to development of cracks, friction, or the like inside the structures. AEs are elastic waves that are generated due to development of fatigue cracks of a material.
Data Source
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AI summary
A sensor adhesion state determination system according to embodiments includes a plurality of sensors, a calculator, and a determiner. Each of the plurality of sensors detects elastic waves. The calculator calculates peak frequencies of the elastic waves on the basis of the elastic waves detected by the plurality of sensors. The determiner determines the adhesion state of each of the sensors by comparing the peak frequencies with information serving as a determination reference.