Effect of Hammer Type on Generated Mechanical Signals in Impact-Echo Testing

Area of Science:

• Civil Engineering
• Materials Science
• Nondestructive Testing

Background:

• The impact-echo method is a common nondestructive technique for concrete assessment, relying on signal analysis for defect detection.
• Interpreting impact-echo signals traditionally requires experienced technicians, limiting widespread automated analysis.
• Machine learning classification models can simplify interpretation but need assurance of optimal measurement conditions.

Purpose of the Study:

• To develop a procedure for evaluating and comparing different impact-echo measurement setups.
• To create a scoring system for acquired signals based on predefined feature demands.
• To enable automated pre-processing and filtering of impact-echo data, especially for resource-limited applications.

Main Methods:

• A series of impact-echo measurements were conducted using varied tip types, hammer handles, and impact forces.
• Multi-criteria evaluation was employed to compare the different measurement configurations.
• A scoring system was developed to quantify how well each measurement met desired signal characteristics.

Main Results:

• The proposed procedure provides a quantitative score for each measurement, reflecting its quality.
• The method allows for the adjustment of evaluation criteria through settable thresholds for specific applications.
• The scoring system facilitates the understanding of signal characteristics during automated data pre-processing.

Conclusions:

• The developed method offers a tool for evaluating and filtering impact-echo data, enhancing automated analysis.
• This approach supports the pre-processing of measured data, even with limited computing power.
• The technique is suitable for applications like remote long-term monitoring and acoustic emission signal pre-processing.