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Neural Classifiers of Vibroacoustic Signals in Implementation on Programmable Devices (FPGA) - Comparison

100%
Dąbrowski D., Cioch W.
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issue 6A
946-949
EN
The research includes comparative analysis of the effect of the recording of weight vectors and input data of selected neural classifiers with fixed-point numbers. Research has been conducted due to insufficient literature on the influence of such a recording on the correct classification of vibroacoustic signals by neural networks. This current issue was brought up in authors' earlier researches, concerning realization of neural classifiers on programmable logical devices field programmable gate array, with the application of fixed-point processor. During the analysis, three types of neural classifiers were compared in the tests: classifier based on neural network - length vector quantization, classifier using radial neural networks - radial basis functions, and third - counter propagation neural network. The problem stated was to recognize technical state of gear transmission DMA-1 in variable operating conditions. Vectors, based on estimates derived from processed vibroacoustic signals were used as teaching material.
2
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Analysis of Signals Pre-processing Algorithm in Case οf Hardware and Software Implementation οn Diagnostic Programmable Device PUD-2

100%
Dąbrowski D., Cioch W.
Acta Physica Polonica A
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2013
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vol. 123
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issue 6
1020-1023
EN
In the paper, two-stage signal pre-processing algorithm based on the filtration is presented. The developed algorithm is dedicated for the diagnostic programmable device PUD-2. The PUD-2 is the real-time analyzer based on programmable logic devices FPGA, as well as on ARM processor. Application of FPGA programmable devices and ARM processors allows to merge advantages of hardware and software implementations. Further, analysis of digital filters parameters in case of its efficient realization on the FPGA is presented. The aim of the study is to select digital-filter parameters in such way that the available resources of FPGA are used efficiently and filter characteristics meet established criteria. In the study, low pass finite impulse response and infinite impulse response filters are compared. For the first stage of the signal pre-processing algorithm, hardware implementation of the infinite impulse response filter is proposed, contrary to the second stage, where software realization of the finite impulse response filter is suggested. Combination of hardware and software filtration algorithms allows for fast and efficient realization of signal pre-processing algorithm used in analysis carried out on the PUD-2.
3
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Hardware Implementation of Artificial Neural Networks for Vibroacoustic Signals Classification

81%
Dąbrowski D., Jamro E., Cioch W.
Acta Physica Polonica A
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2010
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vol. 118
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issue 1
41-44
EN
This paper studies the architecture of a neural classifier designed to identify technical condition of machines, based on vibroacoustic signals. The designed neural network is optimized for implementation on Field Programmable Gate Arrays (FPGA) programmable devices. FPGA allows massive parallelism and thus real-time classification as each neuron can execute arithmetic operations simultaneously. The classifier of vibroacoustic signals was designed and tested for the self - organized neural network. The teaching vectors are based on estimates derived from processed vibroacoustic signals generated by rotary machines. The created classifier was applied for recognizing technical state of demonstrative toothed gear DMA1 in variable operating conditions.
4
Content available remote

Model of the Gears Based on Multibody System and Its Validation by Application of Non-Contact Methods

81%
Dąbrowski D., Batko W., Cioch W., Plascencia-Mora H.
Acta Physica Polonica A
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2013
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vol. 123
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issue 6
1016-1019
EN
In the paper an application of laser measurements for validation of the gears dynamic model have been presented. The model of the gears was compared with an experimental data in case of diagnostics of manufacturing failures. The comparison was done on the basis of vibration signals generated by the model and the real object. In the experiment correct work as well as incorrect one of the gears was studied. Purpose of the paper is to compare the model with the experimental data; to this end, the Multibody model of the gears was build in MSC ADMS software. The model consists of two gears and two shafts, with both gears and shafts treated as rigid bodies, but contact surfaces between them are flexible. To conclude, in the study comparison of acceleration signals estimates behavior due to other gears faults in the experiment and in the model has been presented. For optimal model validation, laser measurements on the shaft in the experiment were conducted.
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