In order to rolling bearing fault diagnosis using vibration signal analysis, this paper presents a new procedure based on the Improved Complete Ensemble Empirical Mode Decomposition ICEMD. In this procedure, firstly, ...
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ISBN:
(纸本)9781509010554
In order to rolling bearing fault diagnosis using vibration signal analysis, this paper presents a new procedure based on the Improved Complete Ensemble Empirical Mode Decomposition ICEMD. In this procedure, firstly, in order to calculate the feature vector, we propose the use a combination of the Improved Complete Ensemble Empirical Mode Decomposition ICEMD and Entropy techniques for determining the entropy values for each one of the five first intrinsic mode functions (IMFs) of the ICEMD. Lastly, using the calculated feature vector, the Adaptive-Network-based Fuzzy Inference System anfis algorithm is used as a classifier system. In the experimental step, twelve different health bearing conditions were introduced to provide that the proposed approach can be an effective and efficient method for processing bearing fault signals.
The Langelier Saturation Index (LSI) and Puckorius Scaling Index (PSI) were used to study the incrustation/corrosion potential of groundwaters in Hamedan Province, Iran. The LSI and PSI indices correlated strongly wit...
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The Langelier Saturation Index (LSI) and Puckorius Scaling Index (PSI) were used to study the incrustation/corrosion potential of groundwaters in Hamedan Province, Iran. The LSI and PSI indices correlated strongly with total dissolved solids (TDS) (mgL(-1)), pH and HCO (3) (-) (mmolL(-1)) as revealed by determination coefficients of 0.90 and 0.99 for LSI and PSI, respectively. Subsequently, a trained adaptive neuro-fuzzy inference system (anfis) was deployed to predict the corrosion behavior of water in unsampled or partially sampled locations using available total dissolved solids (TDS), pH and HCO (3) (-) as input data. Excellent agreement between the anfis simulations and the indices determined using conventional LSI and PSI techniques confirms that modeling using the anfis approach will allow water corrosion potential to be determined reliably and inexpensively using only TDS, pH, and HCO (3) (-) data.
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