Abstract The electromagnetic acoustic resonance (EMAR) method provides accurate and stable evaluation and its capability has been demonstrated through online monitoring using a large-scale corrosion test loop in oper ation at high temperature. This study applies EMAR with the signal processing method of the superposition of n'“ compression to the thickness evaluation of piping in a nuclear power plant during shutdown. Sections of piping evaluated by EMAR include those having long-term service, where thinni...
英字タイトル:
Implementation applicability of piping inspection using electromagneticacoustic resonance

The acoustic data remotely measured by handy type microphones are investigated for monitoring and diagnosing the ball bearing type rotational machine integrity in nucle ar power plants. The present study proposes the new signal pre-processing method which normalizes the fundamental oscillation period into the same length and timing by using zero-crossing interval of filtered acoustic signal. The pre-processed signal patterns are classified by kernel-based principal component analysis (KPCA) and prob abilis...
英字タイトル:
Acoustic Diagnosis Using Kernel Based Principal Component Analysis

The acoustic data remotely measured by handy type microphones are investigated for monitoring and diagnosing the ball bearing type rotational machine integrity in nuclear power plants. The present study evaluates the state-of-the-art statistical signal processing and machine learning methods from the viewpoints of both sensitive and robust acoustic signal discrimination capability. The methods consist of feature extractions such as Fourier transformation or Cepstrum analysis, feature vector dimension compr...
英字タイトル:
Improvement of Acoustic Monitoring of Rotating Machine by non-linear classification method