SHIP HULL DIAGNOSTICS WITH THE USE OF REMOTELY OPERATED UNDERWATER VEHICLE
Abstract and keywords
Abstract (English):
Introduction. Nowadays ship hull diagnostics is carried out in dry-dock or using divers in the road. The both technologies are time consuming, labour and material resource demanding. Specialists from Bauman Moscow State Technical University have developed a diagnostics system that allows the ship hull underwater part inspection to be performed without calling at dry-dock and without divers. The system includes the following main elements: remotely operated vehicle that contains diagnostics tools; hydro acoustic navigation system; software; and diagnostics technology. Method. The technology is based on an acoustic method of non-destructive testing (NDT). SH-waves with elastic vibrations excitation by non-contact method are used without necessity of thorough surface preparation before testing. SH-waves are also used for flaw detection within damaged areas (areas of different thicknesses). As the research has shown, the mirror-shadow technique with bottom signal attenuation as a criterion for corrosion crack detection is most effective. The minimum detectable deep of the corrosion cracks is 1.5–2 mm. The proposed diagnostics technology uses electromagnetic acoustic transducers (EMAT) with a 5 MHz frequency. Results. The diagnostics system was successfully tested in the pool. The test results confirmed the system’s ability to perform automatic metal diagnostics with wall thickness measurements and defect detection within areas of corrosion. Discussions. Nowadays the system is under the process of Russian Maritime Register of Shipping approval. It is planned to develop a system with arc welding tools for underwater objects repair. Prospects of diagnostics system usage for the various underwater steel structures including ones located on the Russian Federation Arctic shelf are under consideration.

Keywords:
thickness measurement, technical condition, ships, monitoring system, remotely operated underwater vehicles, deterioration, corrosion, flaw detection
References

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