Wyniki wyszukiwania - BazTech

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Fault Diagnosis of Three Phase Induction Motor Using Current Signal, MSAF-Ratio15 and Selected Classifiers

Glowacz A., Glowacz W., Glowacz Z., Kozik J., Gutten M., Korenciak D., Khan Z. F., Irfan M., Carletti E.

Archives of Metallurgy and Materials

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2017

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Vol. 62, iss. 4

2413--2419

EN

A degradation of metallurgical equipment is normal process depended on time. Some factors such as: operation process, friction, high temperature can accelerate the degradation process of metallurgical equipment. In this paper the authors analyzed three phase induction motors. These motors are common used in the metallurgy industry, for example in conveyor belt. The diagnostics of such motors is essential. An early detection of faults prevents financial loss and downtimes. The authors proposed a technique of fault diagnosis based on recognition of currents. The authors analyzed 4 states of three phase induction motor: healthy three phase induction motor, three phase induction motor with 1 faulty rotor bar, three phase induction motor with 2 faulty rotor bars, three phase induction motor with faulty ring of squirrel-cage. An analysis was carried out for original method of feature extraction called MSAF-RATIO15 (Method of Selection of Amplitudes of Frequencies – Ratio 15% of maximum of amplitude). A classification of feature vectors was performed by Bayes classifier, Linear Discriminant Analysis (LDA) and Nearest Neighbour classifier. The proposed technique of fault diagnosis can be used for protection of three phase induction motors and other rotating electrical machines. In the near future the authors will analyze other motors and faults. There is also idea to use thermal, acoustic, electrical, vibration signal together.

2

Recognition of images of finger skin with application of histogram, image filtration and K-NN classifier

Glowacz A., Glowacz Z.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 1

95--101

EN

In this paper, non-invasive method of recognition of finger skin was proposed. A plan of study of images of finger skin was proposed. Researches were carried out for three kinds of images: 60 h after injury, 160 h after injury, 450 h after injury. Proposed technique of recognition used methods of signal processing: extraction of magenta color, calculation of histogram, image filtration, calculation of perimeter, and K-NN classifier. A pattern creation process was conducted using 15 training images of finger skin. In the identification process 60 test images were used. The advantage of the presented method is analysis of the finger skin using a smartphone. The proposed approach will help to diagnose pathologies of human skin.

3

Recognition of armature current of DC generator depending on rotor speed using FFT, MSAF-1 and LDA

Glowacz A., Glowacz W., Glowacz Z.

Eksploatacja i Niezawodność

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2015

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Vol. 17, no. 1

64--69

EN

Recognition of states of electrical systems is very important in industrial plants. Article describes a recognition method of early fault detection of DC generator. The proposed approach is based on an analysis of the patterns. These patterns are the armature currents of selected electrical machine. Information contained in signals of armature current is depending on generator state. Researches were carried out for four states of generator with the use of Fast Fourier Transform (FFT), method of selection of amplitudes of frequencies (MSAF-1) and Linear Discriminant Analysis (LDA). The results of analysis show that the method is efficient and can be used to protect DC generators. This method was verified with the aid of acoustic signals recognition method.

PL

Rozpoznawanie stanów układów elektrycznych jest bardzo ważne w zakładach przemysłowych. W artykule opisano metodę rozpoznawania stanów przedawaryjnych generatora prądu stałego. Proponowane podejście jest oparte na badaniu wzorców. Wzorce te są prądami twornika wybranej maszyny elektrycznej. Informacja zawarta w sygnałach prądu twornika jest zależna od stanu generatora. Przeprowadzono badania dla czterech stanów generatora z zastosowaniem FFT, metody wyboru amplitud częstotliwości (MSAF-1) i liniowej analizy dyskryminacyjnej (LDA). Wyniki analizy pokazują, że metoda jest skuteczna i metoda może być stosowana do ochrony generatorów prądu stałego. Metoda została zweryfikowana za pomocą metody rozpoznawania sygnałów akustycznych.

4

Diagnostics of separately excited DC motor based on analysis and recognition of signals using FFT and Bayes classifier

Glowacz W., Glowacz Z.

Archives of Electrical Engineering

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2015

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Vol. 64, nr 1

29--35

EN

In this article results of diagnostic investigations of separately excited DC motor were presented. In diagnostics were applied a Fourier analysis method based on the fast Fourier transform (FFT) and a recognition method using Bayes classifier. In training process a set of the most important frequencies has been determined for which differences of corresponding signals in two states are the largest. Three categories of signals have been recognized in identification process: faultless state, state of the rotor broken one coil and state of the rotor shorted three coils