Experimental investigation of modulation effects for contact-type interfaces in vibro-acoustic modulation tests

Machine fault diagnostic techniques by vibration signal analysis have been applied and widely developed in the industry. In recent years, using the least number of measuring devices to simplify the diagnostic process of gear fault has attracted many researchers. Various digital signal analysis methods in the time and frequency domains have been effectively applied to detect gear faults of gearboxes operated in stationary conditions or rotational speeds with minor fluctuations. However, in reality, gearboxes often work at rotational speeds with large fluctuations and variable loads due to technological progress. In such cases, the measured vibration signal is the amplitude–frequency modulated signal. Therefore, the traditional vibration analysis methods have become ineffective. The modulated signal analysis techniques often require additional key phase information measured using a tachometer to achieve good diagnostic results. However, setting up the tachometer while operating the machine is not effortless. This paper offers a new approach combining many methods to detect gear faults based on sideband analysis in the time–frequency distribution of measured vibration signals using only a single measurement channel. This study is applied in many cases where the machine cannot stop and reduce instrumentation requirements and can develop to build an online diagnostic system.

There are two main types of optical signals propagating in wired or wireless communication links: time continuously varied or analog, which corresponds to narrowband channels, and time discrete varied or pulse-shaped, which corresponds to wideband channels. Therefore, there are different types of modulation that are usually used for such types of signals. This chapter defines the process of modulation and demodulation. It describes the main principle of both kinds of modulation, analog and digital, and provides some examples of the most useful types of modulation adapted for both kinds of channels, narrowband and wideband. There are three types of modulation, depending on what characteristic is time varied in the modulating signal – amplitude modulation, phase modulation, and frequency modulation. There are three kinds of digital modulation: amplitude shift keying, frequency shift keying, and phase shift keying.

Context. The article considers the features of solving non-traditional problems of recognition of specified types modulation signals in automated radio monitoring. The practical features of this problem determine the increased a priori uncertainty, which consists in the absence of a priori information about the distribution densities of the given signals and the presence of unknown signals. Objective. It is proposed to solve the problem using an unconventional method for the recognition of statistically specified random signals in the presence of a class of unknown signals. This method assumes that for the given signals there is a classified training sample of realizations, according to which the unknown parameters of their distributions are estimated, as well as some threshold values that determine the probabilities of correct recognition of the given types of signal modulation in the presence of unknown signals. Method. A general solution to the problem of recognition of given signals in the presence of unknown signals is given, and recognition methods of types modulation based on the description of signals by probabilistic model in the form of a mixture of distributions are given. The method is based on the description of signals by a probabilistic model in the form of a mixture of distributions and construction of a closed area for given signals in the probabilistic space of signals. Results. Studies of the recognition problems of given types of modulation of signals have been carried out. The studies were performed by statistical tests on samples of signals for radio monitoring of communications. In this case, the decisive rule for recognizing the given types of signal modulation is implemented in software on a computer. As a result of the statistical tests carried out on control samples of signals, estimates of the probabilities of correct recognition of the given types of signal modulation in the presence of unknown signals were obtained. Conclusions. Values of indicators of quality of radio emissions recognition acceptable for the practice of radio monitoring are obtained. The dependences of quality indicators on some conditions and recognition parameters are property. As a result of the research, practical recommendations were obtained on the use of the proposed method for recognizing specified types of signal modulation in automated radio monitoring systems.

Experimental confirmation of the possibility of real-time measurement of the internal (deep) temperature of a biological object by thermal acoustic radiation with an accuracy of at least 0.2 °C using an acoustic thermometer implementing the modified zero modulation method is obtained. The model of a single-channel passive noninvasive focussed acoustic thermometer based on a plate piezoceramic electro-acoustic transducer, acoustic elliptical lens and blocks of two serial voltmeters is developed. Electronic switching of the output signals of the noise simulator and the equivalent circuit of the focused piezoelectric transducer is proposed, when resistance generates thermal noise with an intensity equal to the sum of intensities of acoustic radiation of the biological object and natural noise of the piezoelectric transducer. This circuitry solution made it possible to exclude the mechanical modulator (shutter) unit used in analogs from the acoustic thermometer circuit. When developing the original switching and detection unit, it was proposed to use the key mode of n-channel field-effect transistors to perform modulation of the input noise signal. Calculation of equivalent circuits of the piezoelectric electroacoustic transducer and noise simulator, which are connected circuits with a bandwidth in which the average noise voltage level is determined by the noise voltage at the electric resonance frequency of the piezoelectric element, is performed. The possibility of using the model of the single-channel passive noninvasive focussed acoustic thermometer, constructed according to the circuit implementing the modified zero modulation method, for measuring noise voltages in the range from 5 to 30 μV is proved. Since the process of manufacturing or operating a piezoceramic electroacoustic transducer may lead to a deviation of its parameters from theoretically calculated, a method is developed to measure the frequency response of the active and reactive components of electrical impedance. Using the proposed method, the assembly quality of the focused piezoelectric electro-acoustic transducer is monitored and the temperature dependence of electric noise voltage at the electrodes of the focused piezoelectric receiver is obtained.

This paper proposes a blind modulation classification method for adaptive coding and modulation signals base on the difference in high-order cumulants of different modulation types. Use high-order cumulants to establish features to design modulation classification algorithm and decision thresholds. Because of the time-varying characteristics of adaptive coding and modulation signals, the segmentation classification method is used to realize the modulation classification of each frame in the time dimension. Finally, the designed algorithm is simulated, and the classification performance of the algorithm under different modulation types, segment lengths and signal-to-noise ratios is analyzed.

With the rising number of modulation types used in multiuser communication systems, we need to find efficient methods to discriminate them. Indeed, modulation recognition has become important in wireless communications for both civilian and military applications. Traditionally, to classify modulation types, most studies assume abundant a priori knowledge about modulated signals such as binary data rate, baud rate or carrier frequency. However, new transmission receiver systems need to classify automatically digital modulations without specific information. In the course of making decision on modulation type, these parameters may have to be estimated in order to perform efficient demodulation. This paper proposes a new way of estimating baud rate of digital modulated signals. This approach is based on abrupt changes detection in time-frequency plane and on abrupt change periodicity analysis using Kalman filtering.

Understanding the nonlinearity of pendulum tuned mass dampers (PTMDs) under large-amplitude vibration is important to enhance control performance. Here, the nonlinear effects of PTMDs on vibration control of a single-degree-of-freedom (SDOF) system under harmonic excitation are explored. The nonlinear governing equations of the linear SDOF structure coupled with the PTMD are formulated. The results obtained via the method of harmonic balance under various excitation amplitudes are compared with those obtained employing the linearized system. It is shown that the effects of PTMD nonlinearity can be ignored when the PTMD rotation angle is below about 9°. Upon increasing the excitation amplitude, remarkable differences are observed between the nonlinear and linear frequency response functions (FRFs). Large mass ratios of PTMD are found to lead to reduced PTMD motion and attenuated nonlinear effects. A parametric study is performed to find the optimal parameters of the nonlinear PTMD under various excitation amplitudes. The results indicate that the optimal tuning frequency ratio increases significantly with excitation amplitudes, whereas the optimal damping is less sensitive to excitation amplitudes. Finally, a 61-m-high steel chimney structure subjected to harmonic and random wind loadings is investigated to verify the proposed PTMD design method.

Little research about the out-of-plane dynamic stability of arches under in-plane loading has been reported in the literature hitherto. This paper presents analytical and experimental investigations of the out-of-plane dynamic instability of elastic shallow circular arches under an in-plane central concentrated periodic load owing to parametric resonance. Differential equations of out-of-plane motion of shallow arches are established using the Hamilton principle by accounting for the effects of geometric nonlinearity, additional concentrated weights and damping. The analytical solutions of the critical excitation frequencies of the concentrated periodic load for out-of-plane dynamic instability of arches are obtained. The corresponding experimental investigations are also carried out to verify the analytical solutions. Agreements between the analytical and experimental results are very good. In addition, the effects of the central concentrated weight and the in-plane excitation amplitude on out-of-plane dynamic instability of arches are investigated. It is found that as the weight increases, the bandwidth of the critical in-plane excitation frequencies for out-of-plane dynamic instability of the arch decreases. It is also found that the bandwidth of critical frequencies increases with an increase in the excitation amplitude. Furthermore, the nonlinear inertial force is derived, which is essential in determining the out-of-plane parametric resonance. It is shown that the curve of the excitation frequency versus amplitude of out-of-plane vibration bends toward the low-frequency region and that the “traction” out-of-plane instability may occur owing to “amplitude” perturbation. To authors’ knowledge, the analytical solutions and experimental investigations for out-of-plane dynamic instability of arches owing to parametric resonance presented in the paper are first time reported in the literature. The new findings in the paper can provide an in-depth understanding of out-of-plane dynamic instability behavior of arches under a periodic load.

Spatially periodic temperature modulation of a compressible fluid

Most of the research on identifying and classifying signal models is limited to single signals such as AM, QAM or PSK, and there is a lack of research on the parameters of the identified signals. To make up for this deficiency, an OA (Optimality Confidence and Amplitude Ratio factor) algorithm model is proposed to identify and classify 13 kinds of modulation signals, including 2 kinds of analogue modulation signals (AM and FM), 11 kinds of signal digital modulation (M-SK and M-QAM). Based on the characteristics of the constellation diagram, Confidence and Amplitude Ratio factors are constructed to identify and classify signals with different parameters such as ’Format“, ”Centre Frequency“ and ”Sample Rate’ and different modulation types. In addition, because of the mis-judgement and confusion problems in identifying classification signals, a three-layer optimisation algorithm is proposed to optimise the OA algorithm model. Numerical simulation results show that the comprehensive identification efficiency of the proposed optimisation algorithm is increased by 18.84%.

The dynamic parameters of a dangerous rock mass reflect the degree of damage of the structure of its surface. There is still an urgent problem to identify the dynamic parameters of a dangerous rock mass based on the characteristics of the constant micromotion at its site. To address this problem, a method is proposed to identify the dynamic characteristics of a dangerous rock mass undergoing excitation caused by constant micromotion: (1) the vibration of a dangerous rock mass undergoing excitation from constant micromotion is classified as forced undamped structural vibration with a single degree of freedom. The ratio of the amplitude of the spectrum of the dangerous rock mass to the amplitude of the spectrum of the bedrock is defined as the relative amplitude spectrum. The first-order natural frequency is identified from the relative amplitude spectrum. (2) Bedrock is the source of excitation of a dangerous rock mass. When a mechanical wave propagates to a dangerous rock mass, it crosses the porous surface of media with structural damage, and mechanical wave scattering occurs. The frequency domain of the mechanical wave changes. The center frequency shifts to a low frequency. By means of laboratory model tests, the changes in the dynamic parameters of models of a cantilevered dangerous rock mass and a sliding dangerous rock mass with structural surface damage are analyzed. It is concluded that (1) based on the theory of vibration mechanics, the first-order natural frequencies of dangerous rock masses can be obtained from their relative amplitude spectra. The first-order natural frequencies of dangerous rock masses undergoing constant micromotion are measurable. (2) The damage of the structural surface of a dangerous rock mass with macroscopic fractures can be identified by its first-order natural frequency. The center frequency cannot reflect the development of fractures. The damage of the structure of the surface of a dangerous rock mass with microscopic fractures can be identified by the change in the center frequency in its high-frequency band. The first-order natural frequency cannot reflect the development of fractures. (3) There are limitations in using single vibration mechanics theory or elastic wave scattering theory to analyze the damage of the structure of the surface of a dangerous rock mass; it is more effective to integrate both methods.

A study of silver-nickel electrical contact materials : L.Janqiong et al, (Guilin Research Inst. for Electrical Appliance Science, China.) PM Technology, Vol 9, No 4, 1991, 209–214. (In Chinese.)

This paper discusses the design on the front-end that is compatible with analog modulation signal (compliance with PAL) and digital modulation signal (compliance with DVB-C). Although the PAL signal and the DVB-C signal are two signals with different types of modulation, they can use one RF tuner together to save the cost. These two signals have different spectrum characteristics, so they need different in-band response of the channel filter to satisfy the receiving requirement. Meanwhile, we choose two appropriate intermediate frequencies to make them in the same range. We design a programmable intermediate frequency (IF) and a switching circuit for the IF signal.

Introduction . The introduction describes the main characteristics of bit errors. These sources of bit errors in discrete channels. Also listed scientists who worked on the study opportunities monitoring bit error in discrete channels. The main purpose of the article is to conduct research and theoretical modeling of processes in discrete channels to control error measurement and forecasting parameter BER bit error depending on the signal/noise ratio. Theoretical analysis . A comparison of some types of digital modulation for effective use in systems transmitting information. Comparisons were made using the correlation function, power spectral density and distance between signals. It was proved that through this you can control the real value of bit error (BER) for each type of modulation. Important here is the dependence of the BER signal/noise ratio in the test communication channel. Determined that efficiency could be described bit error probability value of the output of the receiver, which is determined by the expression (4). Control parameters BER modulation in digital signals . At this paragraph the examples of control parameter BER at different modulation signals. The simulation results show that with an increase in the signal/noise bit error probability for different types of demodulation will decrease.

The increasingly complex electromagnetic environment and limited spectrum resources pose serious challenges for the recognition of communication signal. The technique of manually feature extraction no longer meets the actual needs. In order to solve the problem of high error rate of communication signal recognition under low Signal-to-Noise Ratio (SNR), we propose a recognition technique that can recognize eight types of modulations. First, we propose Fusion Deep Belief Network (FDBN) that extracts shape features while extracting the essential features of the signal by self-training. Furthermore, considering the problem that the features extracted by FDBN at low SNR are susceptible to noise, we explore the denoising technique based on Variational Mode Decomposition (VMD). The simulation results show that when the SNR is 0dB, the overall recognition rate of the proposed algorithm reaches 98.78%. The proposed recognition algorithm can also be used to recognize the modulation of radar signal.