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Impact echo audio detector
STL-IAES-B
The non-contact sensor does not need to touch the measured object, and it is less affected by environmental factors.
Test resolution and repeatability
product description
Impact echo audio detector
1. Industry standard of the People's Republic of China: Non-destructive testing regulations for railway tunnel lining quality (TB 10223-2004)
According to the standard
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Product Highlights
Detection object: concrete structures such as tunnels and bridges
Inspection content: internal defects, voids and thickness of tunnel lining and slab structure
Test items
This product is based on elastic wave detection technology, uses a professional
microphone as a receiving device, and uses a mature IE algorithm for fast imaging
analysis. The product can be used for non-destructive testing of concrete
structures (which are larger than the contact surface of the microphone), internal
defects or under-thickness. Typical applications are lining quality testing. At the
same time, based on the radar waveform scanning, the host has developed a
spectrum analysis scanning function, which greatly improves the accuracy and
efficiency of field detection and judgment.
Contactless:
Using industrial pickups, can achieve rapid movement detection and improve detection efficiency;
Good stability:
Avoids the resonance frequency shift caused by contact, which greatly improves the repeatability and
stability of the traditional IE method;
Powerful detection:
Detects defects on concrete surface / deep layer, such as voiding, non-compactness and thickness;
High detection accuracy:
It is less affected by the test surface and is not affected by the reinforcement;
The resolution and accuracy of defect / thickness detection are greatly improved compared to
traditional geological radars;
High detection efficiency:
Real-time drawing of contours of waveforms, spectra, etc. The determination of defects is simple and
clear, and results can be produced on the spot;
Combined with AI (Artificial Intelligence) determination, defects and types can be automatically
identified.