Fault Classification of Induction Motor Using Discrete Wavelet Transform and Fuzzy Inference System

Kuspijani, Kuspijani; Watiasih, Richa; Prihastono, Prihastono

doi:10.1109/icosta48221.2020.1570615773

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…, each of size k, to output variable Y using Fuzzy logic. A FIS consists of three blocks named Fuzzification block, Inference engine and De-fuzzifier block as explained in [18][19][20][21] for different applications. In this paper, we use the following steps to relate the signals of SUs at FC with the decision of hypothesis H 0 or H 1 .…”

Section: Fuzzy Inference Systemmentioning

confidence: 99%

Improving signal detection accuracy at FC of a CRN using machine learning and fuzzy rules

Azad

Majumder

Das

et al. 2021

IJEECS

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<span>The performance of a cognitive radio network (CRN) mainly depends on the faithful signal detection at fusion center (FC). In this paper, the concept of weighted Fuzzy rule in Iris data classification, as well as, four machine learning techniques named fuzzy inference system (FIS), fuzzy <em>c</em>-means clustering (FCMC), support vector machine (SVM) and convolutional neural network (CNN) are applied in signal detection at FC taking signal-to-interference plus noise ratio of secondary users as parameter. The weighted Fuzzy rule gave the detection accuracy of 86.6%, which resembles the energy detection model of majority rule of FC; however, CNN gave an accuracy of 91.3% at the expense of more decision time. The FIS, FCMC and SVM gave some intermediate results; however, the combined method gave the best result compared to that of any individual technique.</span>

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Section: Fuzzy Inference Systemmentioning

confidence: 99%

Improving signal detection accuracy at FC of a CRN using machine learning and fuzzy rules

Azad

Majumder

Das

et al. 2021

IJEECS

View full text Add to dashboard Cite

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Recognition of Bangla Handwritten Number Using Combination of PCA and FIS with the Aid of DWT

Khandakar¹,

Islam²,

Tabassum³

et al. 2020

JCC

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The structure of any Bangla numerical character is more complex compared to English numerical character. Two pairs of numerical character in Bangla resembles to be closed and they are: "one and nine" and "five and six". We found that, handwritten Bangla numerical character cannot be recognized using single machine learning algorithm or discrete wavelet transform (DWT). Above phenomenon motivated us to use combination of DWT, Fuzzy Inference System (FIS) and Principal Component Analysis (PCA) to recognize numerical characters of Bangla in handwritten format. The four lowest spectral components of a preprocessed image are taken using DWT, which is considered as the feature vector to recognize the digits in first phase. The feature vector is then applied to FIS and PCA separately. The combined method provides recognition accuracy of 95.8% whereas application of individual method gives less rate of accuracy. Instead of storing the images itself in a folder, if we can store the feature vector of images achieved from DWT in tabular form. The records of table can be applied in FIS, PCA or other object detection algorithm. Although the technique used in the paper can detect objects with moderate rate of accuracy but can save huge storage against a benchmark database of images. If a tradeoff is made between storage requirements and accuracy of recognition, the model of the paper is preferable compared to other present state-of-art. Another finding of the paper is that, the spectral components of images acquired by DWT only matched with FIS and PCA for classification but do not match properly with unsupervised (K-mean clustering) and supervised (support vector machine) learning.

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Fault Classification of Induction Motor Using Discrete Wavelet Transform and Fuzzy Inference System

Cited by 2 publications

References 3 publications

Improving signal detection accuracy at FC of a CRN using machine learning and fuzzy rules

Improving signal detection accuracy at FC of a CRN using machine learning and fuzzy rules

Recognition of Bangla Handwritten Number Using Combination of PCA and FIS with the Aid of DWT

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