Real-Time Classification of Rotating Shaft Loading Conditions Using Artificial Neural Networks  

Oleh:

McCormick, A. C. ; Nandi, A. K.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 8 no. 3 (1997), page 748-757.
Topik: LOADING; real - time; classification; rotating shaft; loading condition; artificial; neural networks

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Vibration analysis can give an indication of the condition of a rotating shaft highlighting potential faults such as unbalance and rubbing. Faults may however only occur intermittently and consequently to detect these requires continuous monitoring with real time analysis. This paper describes the use of artificial neural networks (ANN s) for classification of condition and compares these with other discriminant analysis methods. Moments calculated from time series are used as input features as they can be quickly computed from the measured data. Orthogonal vibrations are considered as a two - dimensional vector, the magnitude of which can be expressed as time series. Some simple signal processing operations are applied to the data to enhance the differences between signals and comparison is made with frequency domain analysis.

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