The main purpose of the presented research is to investigate the partial discharge (PD) phenomenon variability under long-term AC voltage with particular consideration of the selected physical quantities changes while measured and registered by the acoustic emission method (AE). During the research a PD model source generating surface discharges is immersed in the brand new insulation mineral oil. Acoustic signals generated by the continuously occurred PDs within 168 hours are registered. Several qualitative and quantitative indicators are assigned to describe the PD variability in time. Furthermore, some longterm characteristics of the applied PD model source in mineral oil, are also presented according to acoustic signals emitted by the PD. Finally, various statistical tools are applied for the results analysis and presentation. Despite there are numerous contemporary research papers dealing with long-term PD analysis, such complementary and multiparametric approach has not been presented so far, regarding the presented research. According to the presented research from among all assigned indicators there are discriminated descriptors that could depend on PD long-term duration. On the grounds of the regression models analysis there are discovered trends that potentially allow to apply the results for modeling of the PD variability in time using the acoustic emission method. Subsequently such an approach may potentially support the development and extend the abilities of the diagnostic tools and maintenance policy in electrical power industry.
Although the emotions and learning based on emotional reaction are individual-specific, the main features are consistent among all people. Depending on the emotional states of the persons, various physical and physiological changes can be observed in pulse and breathing, blood flow velocity, hormonal balance, sound properties, face expression and hand movements. The diversity, size and grade of these changes are shaped by different emotional states. Acoustic analysis, which is an objective evaluation method, is used to determine the emotional state of people’s voice characteristics. In this study, the reflection of anxiety disorder in people’s voices was investigated through acoustic parameters. The study is a case-control study in cross-sectional quality. Voice recordings were obtained from healthy people and patients. With acoustic analysis, 122 acoustic parameters were obtained from these voice recordings. The relation of these parameters to anxious state was investigated statistically. According to the results obtained, 42 acoustic parameters are variable in the anxious state. In the anxious state, the subglottic pressure increases and the vocalization of the vowels decreases. The MFCC parameter, which changes in the anxious state, indicates that people can perceive this situation while listening to the speech. It has also been shown that text reading is also effective in triggering the emotions. These findings show that there is a change in the voice in the anxious state and that the acoustic parameters are influenced by the anxious state. For this reason, acoustic analysis can be used as an expert decision support system for the diagnosis of anxiety.
A limited ability to discriminate between different materials is the fundamental problem with all conventional eddy-current-based metal detectors. This paper presents the use, evaluation and classification of nontraditional excitation signals for eddy-current metal detectors to improve their detection and discrimination ability. The presented multi-frequency excitation signals are as follows: a step sweep sine wave, a linear frequency sweep and sin(x)/x signals. All signals are evaluated in the frequency domain. Amplitude and phase spectra and polar graphs of the detector output signal are used for classification and discrimination of the tested objects. Four different classifiers are presented. The classification results obtained with the use of poly-harmonic signals are compared with those obtained with a classical single-tone method. Multifrequency signals provide more detailed information, due to the response function – the frequency characteristic of a detected object, than standard single-tone methods. Based on the measurements and analysis, a metal object can be better distinguished than when using a single-tone method.
This paper presents a new modification of the least-squares Prony’s method with reduced sampling, which allows for a significant reduction in the number of the analysed signal samples collected per unit time. The specific combination of non-uniform sampling with Prony’s method enables sampling of the analysed signals at virtually any average frequency, regardless of the Nyquist frequency, maintaining high accuracy in parameter estimation of sinusoidal signal components. This property allows using the method in measuring devices, such as for electric power quality testing equipped with low power signal processors, which in turn contributes to reducing complexity of these devices. This paper presents research on a method for selecting a sampling frequency and an analysis window length for the presented method, which provide maximum estimation accuracy for Prony’s model component parameters. This paper presents simulation tests performed in terms of the proposed method application for analysis of harmonics and interharmonics in electric power signals. Furthermore, the paper provides sensitivity analysis of the method, in terms of common interferences occurring in the actual measurement systems.
A checkweigher is an automatic machine to measure the weight of in-motion products. It is usually located around the end of the production process and ensures the weight of a product within specified limits. Any products are taken out of line if their weights are out of the specified limits. It is usually equipped with an optical device. It is used to make a trigger to set the time duration to allow a product to move completely on the weigh belt for sampling the weight. In this paper, a new method of mass measurement for checkweighers is proposed which uses just signal processing without the optical device. The effectiveness of the method is shown through experiments. Also a possibility of faster estimation of weight is shown.
The paper presents a method of adaptation of the original second order Prony’s method for applications in lowcost digital measurement systems with low computing performance. The presented method can be used in measuring systems where it is important to obtain in real time the values of amplitude, frequency, initial phase and damping coefficient of a single sinusoidal component of an analysed signal. The paper presents optimized, in terms of the number of mathematical operations, implementation of the method in selected embedded devices as well as the calculation times of the method for each platform.
This article presents a way of analyzing the transfer function of electronic signal amplifiers. It also describes the possibility of using signal precorrection which improves the parasitic harmonics in the THD (Total Harmonic Distortion) of the amplified signal by correcting linearity of the tested amplifier’s transfer function. The proposed method of analyzing and presenting the transfer function allows to diagnose the causes of generating parasitic harmonics, what makes it a useful tool when designing low distortion amplifier systems, such as e.g. amplifiers in measurement systems. The presented THD correction can be used in e.g. amplifier systems that cooperate with arbitrary generators.
In this paper, we propose a new method of measuring the target velocity by estimating the scaling parameter of a chaos-generating system. First, we derive the relation between the target velocity and the scaling parameter of the chaos-generating system. Then a new method for scaling parameter estimation of the chaotic system is proposed by exploiting the chaotic synchronization property. Finally, numerical simulations show the effectiveness of the proposed method in target velocity measurement.
The article presents an application of Prony’s method with some known components in the analysis of electric power quality. Modifications of the Prony algorithm broaden the scope of method application. Modification of the filter of known components enables more accurate analysis of the parameters of unknown components and components with known or assumed frequencies. This article presents a comparison of the results of analyses conducted with the proposed algorithm for simulated and real signals and the results obtained by means of a commercial electric power quality testing device, operating in class A and using the Fourier transform. The proposed method enables to estimate the levels of the harmonic components, the frequency of the fundamental signal and real parameters of the interharmonic components, which are grouped and averaged in the contemporary monitoring equipment. Knowledge of the individual parameters of the interharmonics has considerable diagnostic importance while removing causes of incorrect operation affecting sensitive equipment in some electric power systems. Additionally, the algorithm is capable of analyzing exponentially damped components and finds its application in analysis of disturbances, for example, transient oscillations.
Enhanced Traffic Management System (ETMS) stores all the information gathered by the Federal Aviation Administration (FAA) from aircraft flying in the US airspace. The data stored from each flight includes the 4D trajectory (latitude, longitude, altitude and timestamp), radar data and flight plan information. Unfortunately, there is a data quality problem in the vertical channel and the altitude component of the trajectories contains some isolated samples in which a wrong value was stored. Overall, the data is generally accurate and it was found that only 0.3% of the altitude values were incorrect, however the impact of these erroneous data in some analyses could be important, motivating the development of a filtering procedure. The approach developed for filtering ETMS altitude data includes some specific algorithms for problems found in this particular dataset, and a novel filter to correct isolated bad samples (named Despeckle filter). As a result, all altitude errors were eliminated in 99.7% of the flights affected by noise, while preserving the original values of the samples without bad data. The algorithm presented in this paper attains better results than standard filters such as the median filter, and it could be applied to any signal affected by noise in the form of spikes
In the paper the idea of rational polynomial windows optimised towards low level of Fourier spectrum's sidelobes is presented. A relevant advantage of the polynomial windows family and their modifications is their ability to easily change their properties changing only the values of the polynomial coefficients. The obtained frequency characteristics demonstrate better properties of proposed rational Windows than their standard polynomial equivalents requiring only the additional division operation. Such approach does not increase the computational complexity in significant way and the great advantage of polynomial windows which is their low computational complexity is preserved.
A computer measurement system, designed and built by authors, dedicated to location and description of partial discharges (PD) in oil power transformers examined by means of the acoustic emission (AE) method is presented. The measurement system is equipped with 8 measurement channels and ensures: monitoring of signals, registration of data in real time within a band of 25–1000 kHz in laboratory and real conditions, basic and advanced analysis of recorded signals. The basic analysis carried out in the time, frequency and time-frequency domains deals with general properties of the AE signals coming from PDs. The advanced analysis, performed in the discrimination threshold domain, results in identification of signals coming from different acoustic sources as well as location of these sources in the examined transformers in terms of defined by authors descriptors and maps of these descriptors on the side walls of the tested transformer tank. Examples of typical results of laboratory tests carried out with the use of the built-in measurement system are presented.
The paper presents a novel implementation of a time-to-digital converter (TDC) in field-programmable gate array (FPGA) devices. The design employs FPGA digital signal processing (DSP) blocks and gives more than two-fold improvement in mean resolution in comparison with the common conversion method (carry chain-based time coding line). Two TDCs are presented and tested depending on DSP configuration. The converters were implemented in a Kintex-7 FPGA device manufactured by Xilinx in 28 nm CMOS process. The tests performed show possibilities to obtain mean resolution of 4.2 ps but measurement precision is limited to at most 15 ps mainly due to high conversion nonlinearities. The presented solution saves FPGA programmable logic blocks and has an advantage of a wider operation range when compared with a carry chain-based time coding line.
The paper presents a technique for measuring membrane displacements with one motionless camera. The method consists in measuring the distance to an object based on one image obtained from a motionless camera with a fixed-focus lens. The essence of the proposed measurement technique is to determine changes of the distance between a membrane and a video camera based on analysis of changes in the focus view of a marker placed on the membrane plane. It is proven that the used technique allows to monitor the frequency and amplitude of the membrane vibration. The tests were performed for the oscillation frequency in the range from 0.5 Hz to 6 Hz and deviations from the neutral position in the range of ±3 mm.
Videoplethysmography is currently recognized as a promising noninvasive heart rate measurement method advantageous for ubiquitous monitoring of humans in natural living conditions. Although the method is considered for application in several areas including telemedicine, sports and assisted living, its dependence on lighting conditions and camera performance is still not investigated enough. In this paper we report on research of various image acquisition aspects including the lighting spectrum, frame rate and compression. In the experimental part, we recorded five video sequences in various lighting conditions (fluorescent artificial light, dim daylight, infrared light, incandescent light bulb) using a programmable frame rate camera and a pulse oximeter as the reference. For a video sequence-based heart rate measurement we implemented a pulse detection algorithm based on the power spectral density, estimated using Welch’s technique. The results showed that lighting conditions and selected video camera settings including compression and the sampling frequency influence the heart rate detection accuracy. The average heart rate error also varies from 0.35 beats per minute (bpm) for fluorescent light to 6.6 bpm for dim daylight.
This paper presents an overview of algorithms for one-phase active power estimation using digital signal processing in the time domain and in the frequency domain, and compares the properties of these algorithms for a sinusoidal test signal. The comparison involves not only algorithms that have already been published, but also a new algorithm. Additional information concerning some known algorithms is also included. We present the results of computer simulations in MATLAB and measurement results gained by means of computer plug-in boards, both multiplexed and using simultaneous signal sampling. The use of new cosine windows with a recently published iterative algorithm is also included, and the influence of additive noise in the test signal is evaluated.
The purpose of this work is to distinguish between Acoustic Emission (AE) signals coming from mechanical friction and AE signals coming from concrete cracking, recorded during fourteen seismic simulations conducted with the shaking table of the University of Granada on a reinforced concrete slab supported on four steel columns. To this end, a particular criterion is established based on the Root Mean Square of the AE waveforms calculated in two different temporal windows. This criterion includes a parameter calculated by optimizing the correlation between the mechanical energy dissipated by the specimen (calculated by means of measurements with accelerometers and displacement transducers) and the energy obtained from the AE signals recorded by low-frequency piezoelectric sensors located on the specimen. The final goal of this project, initiated four years ago, is to provide a reliable evaluation of the level of damage of Reinforced Concrete specimens by means of AE signals to be used in future Structural Health Monitoring strategies involving RC structures.
The paper analyzes the estimation of the fundamental frequency from the real speech signal which is obtained by recording the speaker in the real acoustic environment modeled by the MP3 method. The estimation was performed by the Picking-Peaks algorithm with implemented parametric cubic convolution (PCC) interpolation. The efficiency of PCC was tested for Catmull-Rom, Greville, and Greville two- parametric kernel. Depending on MSE, a window that gives optimal results was chosen.
The article presents methods that help in the elimination of mutual clutter as well as the consequences of two FM sounding signal sonars operating in the same body of water and frequency band. An in-depth analysis of mutual clutter was carried out. The effects of sounding signal differentiation were determined, as was the Doppler effect on mutual clutter suppression. One of the methods analysed is of particular interest in a situation in which collaborating sonars are operating in opposite frequency modulation directions. This method is effective for both linear and hyperbolic frequency modulations. A formula was derived, identifying exactly how much quantities of clutter may be lessened. The work included comprehensive computer simulations and measurements as well as tests in real-life conditions.
Based on recent advances in non-linear analysis, the surface electromyography (sEMG) signal has been studied from the viewpoints of self-affinity and complexity. In this study, we examine usage of critical exponent analysis (CE) method, a fractal dimension (FD) estimator, to study properties of the sEMG signal and to deploy these properties to characterize different movements for gesture recognition. SEMG signals were recorded from thirty subjects with seven hand movements and eight muscle channels. Mean values and coefficient of variations of the CE from all experiments show that there are larger variations between hand movement types but there is small variation within the same type. It also shows that the CE feature related to the self-affine property for the sEMG signal extracted from different activities is in the range of 1.855~2.754. These results have also been evaluated by analysis-of-variance (p-value). Results show that the CE feature is more suitable to use as a learning parameter for a classifier compared with other representative features including root mean square, median frequency and Higuchi's method. Most p-values of the CE feature were less than 0.0001. Thus the FD that is computed by the CE method can be applied to be used as a feature for a wide variety of sEMG applications.
This article discusses a system of recognition of acoustic signals of loaded synchronous motor. This software can recognize various types of incipient failures by means of analysis of the acoustic signals. Proposed approach uses the acoustic signals generated by loaded synchronous motor. A plan of study of the acoustic signals of loaded synchronous motor is proposed. Studies include following states: healthy loaded synchronous motor, loaded synchronous motor with shorted stator coil, loaded synchronous motor with shorted stator coil and broken coil, loaded synchronous motor with shorted stator coil and two broken coils. The methods such as FFT, method of selection of amplitudes of frequencies (MSAF-5), Linear Support Vector Machine were used to identify specific state of the motor. The proposed approach can keep high recognition rate and reduce the maintenance cost of synchronous motors.
In this work problems associated with requirements related to pollution emissions in compliance with more restrictive standards, low-emission combustion technology, technical realization of the monitoring system as well as algorithms allowing combustion process diagnostics are discussed. Results of semi-industrial laboratory facility and industrial (power station) research are presented as well as the possibility of application of information obtained from the optical fibre monitoring system for combustion process control. Moreover, directions of further research aimed to limit combustion process environmental negative effects are presented.
In this paper a concept of finite impulse response (FIR) narrow band-stop (notch) filter with non-zero initial conditions, based on infinite impulse response (IIR) prototype filter, is proposed. The filter described in this paper is used to suppress power line noise from ECG signals. In order to reduce the transient response of the proposed FIR notch filter, optimal initial conditions for the filter have been determined. The algorithm for finding the length of the initial conditions vector is presented. The proposed values of the length of initial conditions vector, for several ECG signals and interfering frequencies, are calculated. The proposed filters are tested using various ECG signals. Computer simulations demonstrate that the proposed FIR filters outperform traditional FIR filters with initial conditions set to zero.
This paper describes the theoretical background of electromagnetic induction from metal objects modelling. The response function of a specific case of object shape - a homogenous sphere from ferromagnetic and non-ferromagnetic material is introduced. Experimental data measured by a metal detector excited with a linearly frequency-swept signal are presented. As a testing target various spheres from different materials and sizes were used. These results should lead to better identification of the buried object.
Fast and accurate grid signal frequency estimation is a very important issue in the control of renewable energy systems. Important factors that influence the estimation accuracy include the A/D converter parameters in the inverter control system. This paper presents the influence of the number of A/D converter bits b, the phase shift of the grid signal relative to the time window, the width of the time window relative to the grid signal period (expressed as a cycle in range (CiR) parameter) and the number of N samples obtained in this window with the A/D converter on the developed estimation method results. An increase in the number b by 8 decreases the estimation error by approximately 256 times. The largest estimation error occurs when the signal module maximum is in the time window center (for small values of CiR) or when the signal value is zero in the time window center (for large values of CiR). In practical applications, the dominant component of the frequency estimation error is the error caused by the quantization noise, and its range is from approximately 8×10-10 to 6×10-4.