scholarly journals ANN-Based Pattern Recognition for Induction Motor Broken Rotor Bar Monitoring under Supply Frequency Regulation

Machines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 87
Author(s):  
Ashish Kumar Sinha ◽  
Ananda Shankar Hati ◽  
Mohamed Benbouzid ◽  
Prasun Chakrabarti
Keyword(s):  
Pattern Recognition ◽  
Underground Mines ◽  
Frequency Regulation ◽  
Discrete Wavelet ◽  
Detection Scheme ◽  
Broken Rotor Bar ◽  
Stator Current ◽  
Multi Resolution Analysis ◽  
On Line ◽  
Artificial Neural Network Ann

The requisite of direct-on-line (DOL) starting for various applications in underground mines subjects the rotor bars of heavy-duty squirrel cage induction motors (SCIMs) to severe stresses, resulting in sustained fault in the rotor bars, unlike the applications where mostly reduced voltage starting is preferred. Furthermore, SCIMs working in underground mines are also affected by unforeseen frequency fluctuations. Hence, the paper proposes a discrete wavelet transform (DWT)-based broken rotor bar detection scheme using the stator current analysis of SCIM when subjected to a frequency regulation (±4% of 50 Hz supply) in steady-state, as prevalent in underground mines. In this regard, the level-seven detailed coefficient obtained by the DWT-based multi-resolution analysis of stator current corresponding to the healthy rotor is compared with that of the faulty rotor to extract the necessary features to identify the fault. Further implementation of the proposed scheme is done using artificial neural network (ANN)-based pattern recognition techniques, wherein both feed-forward backdrops and cascaded forward backdrop type ANNs have been used for fault pinpointing based on the feature extraction results obtained from DWT. The scheme is developed and analysed in MATLAB/Simulink using 5.5 kW, 415 V, 50 Hz SCIM, which is further validated using the LabVIEW-based real-time implementation.

Software pattern recognition applied to nanodiffraction patterns from a STEM instrument

1986 ◽  
Vol 44 ◽  
pp. 694-695
Author(s):  
G.Y. Fan ◽  
J.M. Cowley
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Computer Software ◽  
Processing System ◽  
Light Level ◽  
Host Computer ◽  
Low Light ◽  
Image Processing System ◽  
Recent Developments ◽  
On Line

In recent developments, the ASU HB5 has been modified so that the timing, positioning, and scanning of the finely focused electron probe can be entirely controlled by a host computer. This made the asynchronized handshake possible between the HB5 STEM and the image processing system which consists of host computer (PDP 11/34), DeAnza image processor (IP 5000) which is interfaced with a low-light level TV camera, array processor (AP 400) and various peripheral devices. This greatly facilitates the pattern recognition technique initiated by Monosmith and Cowley. Software called NANHB5 is under development which, instead of employing a set of photo-diodes to detect strong spots on a TV screen, uses various software techniques including on-line fast Fourier transform (FFT) to recognize patterns of greater complexity, taking advantage of the sophistication of our image processing system and the flexibility of computer software.

scholarly journals On-line Ham Grading using pattern recognition models based on available data in commercial pig slaughterhouses

Meat Science ◽  
2018 ◽  
Vol 143 ◽  
pp. 39-45 ◽  
Author(s):  
Gerard Masferrer ◽  
Ricard Carreras ◽  
Maria Font-i-Furnols ◽  
Marina Gispert ◽  
Pere Marti-Puig ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
On Line

scholarly journals The experimental identification method of the dynamic efficiency for frequency regulation algorithms of AEDs

2021 ◽  
Vol 12 (1) ◽  
pp. 59 ◽  
Author(s):  
Vladimir L. Kodkin ◽  
Aleksandr S. Anikin
Keyword(s):  
Control Method ◽  
Frequency Control ◽  
Reference Signal ◽  
Frequency Regulation ◽  
Current Feedback ◽  
Electric Drives ◽  
Stator Current ◽  
Asynchronous Electric Drive ◽  
Input Side ◽  
Mechanical Moment

The article proposes and substantiates a method for studying the dynamics of an asynchronous electric drives with frequency control from the input side of the signal for setting the speed of rotation of the electric motor. In this method, a constant speed reference signal is added to a harmonic variable frequency signal. The set of amplitude changes and phase shifts of velocity oscillations are the initial data for identifying the dynamics of the studied control method. The logic of this method is determined by the previously obtained nonlinear transfer function of the link that forms the mechanical moment in the asynchronous electric drive with frequency control. Experiments have shown the dynamic benefits of the drive with positive stator current feedback.

scholarly journals HOUGH TRANSFORM GENERATED STRONG IMAGE HASHING SCHEME FOR COPY DETECTION

2018 ◽  
Author(s):  
Mayank Srivastava ◽  
Jamshed M Siddiqui ◽  
Mohammad Athar Ali
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Hough Transform ◽  
Rapid Development ◽  
Discrimination Performance ◽  
Discrete Wavelet ◽  
Image Hashing ◽  
Copy Detection ◽  
Detection Scheme

The rapid development of image editing software has resulted in widespread unauthorized duplication of original images. This has given rise to the need to develop robust image hashing technique which can easily identify duplicate copies of the original images apart from differentiating it from different images. In this paper, we have proposed an image hashing technique based on discrete wavelet transform and Hough transform, which is robust to large number of image processing attacks including shifting and shearing. The input image is initially pre-processed to remove any kind of minor effects. Discrete wavelet transform is then applied to the pre-processed image to produce different wavelet coefficients from which different edges are detected by using a canny edge detector. Hough transform is finally applied to the edge-detected image to generate an image hash which is used for image identification. Different experiments were conducted to show that the proposed hashing technique has better robustness and discrimination performance as compared to the state-of-the-art techniques. Normalized average mean value difference is also calculated to show the performance of the proposed technique towards various image processing attacks. The proposed copy detection scheme can perform copy detection over large databases and can be considered to be a prototype for developing online real-time copy detection system.   

scholarly journals Classification & Feature extraction of Brain tumor from MRI Images using Modified ANN Approach

2021 ◽  
Vol 9 (2) ◽  
pp. 10-15
Author(s):  
Harendra Singh ◽  
Roop Singh Solanki
Keyword(s):  
Feature Extraction ◽  
Brain Tumor ◽  
Computational Time ◽  
Discrete Wavelet ◽  
Classification Feature ◽  
Proposed Model ◽  
Magnetic Resonance Imaging Mri ◽  
Artificial Neural Network Ann ◽  
High Degree

In this research paper, a new modified approach is proposed for brain tumor classification as well as feature extraction from Magnetic Resonance Imaging (MRI) after pre-processing of the images. The discrete wavelet transformation (DWT) technique is used for feature extraction from MRI images and Artificial Neural Network (ANN) is used for the classification of the type of tumor according to extracted features. Mean, Standard deviation, Variance, Entropy, Skewness, Homogeneity, Contrast, Correlation are the main features used to classify the type of tumor. The proposed model can give a better result in comparison with other available techniques in less computational time as well as a high degree of accuracy. The training and testing accuracies of the proposed model are 100% and 98.20% with a 98.70 % degree of precision respectively.

scholarly journals A Low Power Shift Add Multiplier for Lifting Based Dwt using Kogge Stone Adder

2020 ◽  
Vol 9 (4) ◽  
pp. 1080-1086
Keyword(s):  
The Other ◽  
Discrete Wavelet ◽  
Limited Memory ◽  
Power Shift ◽  
Multi Resolution Analysis ◽  
Suggested Technique ◽  
Field Programmable ◽  
Resolution Analysis ◽  
Common Technique

The most common technique used for image processing applications is ‘The wavelet transformation’. The Discrete Wavelet Transform (DWT) keeps the time as well as frequency information depend on a multi resolution analysis structure, where the other classical transforms like Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT) will not do that. Because of this feature, the quality of the repaired image is improved when comparing to the other transforms. To implement the DWT on a real time codec, a fast device needs to be targeted. While comparing with the other implementation such as PCs, ARM processors, DSPs etc, Field Programmable Gate Array (FPGA) implementation of DWT had better processing speed and costs were vey less. A Fast Architecture based DWT using Kogge Stone Adder is proposed in this paper where the coefficients of lifting scheme are calculated by using Shift adder and Kogge Stone Adder where other techniques used multiplier. The most important intention of the suggested technique is to use minimum calculation and limited memory. The simulation of the suggested design is dole out on the Xilinx 14.1 style tool and also the performance is evaluated and compared with the present architectures.

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