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Lorenzo Peretto, Renato Sasdelli, Roberto Tinarelli
ON THE UNCERTAINTY COMPONENTS IN SPECTRAL ANALYSIS OF BI -TONE WAVEFORMS ARISING FROM THE VIRTUAL TIME-DOMAIN APPROACH

Multi-tone signals are discrete-spectrum signals with spectral components located at non-harmonically related frequencies. Their spectral analysis can be performed in short observation intervals by means of a method that combines the use of a virtual time domain and statistical techniques. The contributions to uncertainty that specifically arise from the implementation of the method are discussed in the paper and a study is developed to optimize the measurement technique in the case of bi-tone, periodic or not, signals. Finally, experimental results, which confirm theory, are reported and discussed.

Peter J. Kral, Stefan Pausch
MEASUREMENT OF THE TEMPERATURE ON TOOTH FLANKS OF GEARS WHILE RUNNING

This paper presents a measurement method for measuring temperature values of test gears on a test bed. For better understanding of the wear behaviour of worm gears and for analysing the contact conditions between the flanks of worm and worm wheel in presence of lubricating oil, it is necessary to know the temperature of the contact area. The oil between the flanks is heated by the hot flanks and therefore the viscosity of the lubricating oil is reduced. For this reason the temperature curve of the contact area and thus the oil temperature between the flanks was measured and afterwards applied to a mathematical simulation for calculating the wear. The measurement of the temperatures on the surface of the tooth flank, of the oil temperature in the contact area and in the oil sump is done with aid of thermocouples and temperature-dependent resistors, type PT 100. The construction of the test bed and the measurement circuit is also presented in detail.

Sergey Y. Yurish, Nikolay V. Kirianaki, Nestor O. Shpak
VIRTUAL INSTRUMENTATION FOR FREQUENCY OUTPUT SMART SENSORS

The universal solution for precise virtual instrument system realisation permitting to connect any frequency-time domain (quasi-digital) sensor to IBM PC compatible computers is described in the paper. The virtual instrument system for smart sensors with frequency-time domain output is based on the novel adaptive program-oriented method for frequency-to-code conversion – method of dependent count. The main advantages of this method for virtual sensor instrumentation applications are: high accuracy, constant quantization error in all frequency range, non-redundant conversion time, minimum possible hardware and self-adopting possibilities. The example of virtual instrument for duty-cycle output temperature sensor is given.

Raul Carneiro Martins, António Cruz Serra
NONLINEARITIES, THE GENERATORS PERSPECTIVE IN ADC STATISTICAL TESTING TECHNIQUES

In this paper we present an experimental method that is suitable to ascertain the degree of nonlinearity present in a given signal as well as its adequacy to be used as a stimulus signal in a statistical method, such as the histogram test of ADCs. We show one possible implementation of the method as well as its theoretical substrate and some preliminary experimental results. Finally we show the importance of determining the distribution of the stimulus signal when using noise.

M. Fonseca da Silva, A. Cruz Serra
IMPROVING CONVERGENCE OF SINE FITTING ALGORITHMS

Signal-processing applications frequently use least-square sine fitting algorithms. The parameter estimation provided by these algorithms is exposed to errors due to different causes. Good results in sinewave estimation may be achieved when the frequency is unknown by applying the new method presented in this paper.

Fabrizio Russo
A RECURSIVE ALGORITHM FOR THE REDUCTION OF QUANTIZATION EFFECTS OF IMAGE COMPRESSION

A simple technique for the restoration of color images degraded by lossy compression is presented. The proposed approach deals with the YIQ color space and processes the luminance component by means of a recursive algorithm based on fuzzy models. This design choice combines effectiveness and simplicity. Indeed, the method can satisfactorily reduce quantization errors produced by lossy compression such as the popular JPEG technique. On the other hand, the tuning process is very fast because it requires one parameter only.

Bruno Andò, Salvatore Baglio, Nicola Pitrone
REMOTE CONNECTION FOR EXTENDED AVAILABILITY OF THE EDUCATIONAL LAB

A virtual instrument for the remote control of measurement instruments has been realised. It enables the user to control the characteristic parameters of the instruments, to start the measurement process and to acquire the obtained results. At this step the implemented approach can enhance the availability of the lab.

C. Fosalau, M. Cretu, O. Postolache, C. Donciu, B. Baraboi
A VIRTUAL INSTRUMENT FOR REAL SYSTEMS IDENTIFICATION AND MODELING

The paper describes a virtual instrument designed to fast and accurately identify systems working in a large range of frequencies. It comprises both the hardware aimed on input-output data generation and acquisition and the software dedicated to signal processing and all the calculus ended with the model estimation. The instrument offers all the facilities provided by the LabVIEW environment, being also interfaced with the powerful toolboxes of Matlab.

B. Baraboi, M. Cretu, C. Fosalau, C. Donciu
GAS ANALYSIS SYSTEM BASED ON ARTIFICIAL NEURAL NETWORKS

The paper presents the design and implementation of an automated system for the analysis of gas mixtures. Using low-cost, non-selective gas sensors in combination with signal processing algorithm based on artificial neural networks, the prototype system is able to correctly classify three combustible gases (methane, isobutane, and hydrogen) and to indicate when the total gas concentration in the air exceeds a preset alarm point. The system is designed using LabVIEW and virtual instrumentation concept and is capable of performing online analysis of gas mixtures.

Marinel Temneanu, Traian Balan, Dana Balan, Octavian Postolache
IRON LOSSES PREDICTION USING NEURAL NETWORK BASED MAGNETIC MODEL

The possibility to predict the iron losses under nonsinusoidal waveform of magnetic flux density using neural network based magnetic models is analyzed in this paper. Two different types of model structures (predictors with and without feedback) have been used. The predictions are compared to the measured output for different magnetic materials and induction waveforms.

Page 425 of 977 Results 4241 - 4250 of 9762