Vibroacoustic Signals Research Articles

Model-based estimation of rail roughness from axle box acceleration

Monitoring rail roughness in the railway network allows directing grinding actions to where they are needed to reduce rolling noise and large wheel/rail forces. To be able to measure rail roughness on a large scale, indirect measurements onboard railway vehicles have to be carried out. Existing methods use either axle box acceleration (ABA) or under-coach noise measurements to monitor the rail roughness indirectly. The two main challenges with rail roughness estimation from vibroacoustic signals measured onboard vehicles are to separate wheel and rail roughness and to take into account varying track dynamics in the railway network. Both questions have not yet been addressed sufficiently.In this paper, an enhanced method for estimating rail roughness from ABA is presented. In contrast to all existing methods in the literature, the presented method operates in the time domain. A time-domain method has the advantage that the spatial variations of roughness become visible and paves the way for the detection of localized defects such as squats or deteriorated welds. The method is based on a previously developed time-domain model for high-frequency wheel/rail interaction and estimates the time series of the roughness from the time series of ABA. In a first step, the time series of the contact force is calculated from the axle box acceleration using a Least Mean Square algorithm for source identification. In a second step, the combined wheel/rail roughness is obtained from the contact force based on a non-linear Hertzian contact model and a convolutional approach to determine wheel and rail displacement. Separation of wheel and rail roughness is possible by cycle-averaging the contact force over a distance corresponding to the wheel perimeter and performing the second step separately for the part of the contact force originating from the wheel and the rail roughness, respectively.The method was tested for simulated ABA obtained from measured wheel and rail roughness. In the relevant wavelength range from 0.5 m to 5 mm, the rail roughness could be estimated with good accuracy for known track dynamics. Overall, deviations in 1/3-octave bands between estimated and actual roughness were below 1 dB. Only for low rail roughness, higher deviations of less than 2.6 dB occurred around the pinned-pinned resonance frequency. Uncertainties in the track parameters affect the roughness estimation, where the most critical parameter is the rail pad stiffness. A deviation of 20% in rail pad stiffness leads to deviations in the rail roughness of up to 3.5 dB in single 1/3-octave bands. The results illustrate the need to extend the method for the simultaneous extraction of track parameters and roughness from measured axle box acceleration.

Identification of operating mode of a petrol chainsaw based on short-time parametrization and analysis of vibro-acoustic signals

Petrol chainsaws during operation, regardless of the type of their drive and power, generate vibrations and noise that usually exceed the permissible values which are specified in standards and/or regulations. The values of vibration accelerations and emitted noise levels declared by the manufacturers are determined in standardized conditions and they may significantly differ from the values affecting operators. In order to determine the actual impact on operators of chainsaws under nominal operating conditions (in situ) one have to identify the percentages of the chainsaw's operating modes: Idle – ID, Full load – FL, Racing – RA. The article presents the methodology of identifying the operating modes of petrol chainsaws based on recorded vibroacoustic signals. Moreover, a method of identifying these states based on a tachometric signal has been proposed. Different approaches were considered to the identification of operating modes. Basic method is based on tracking of changes of the instantaneous values of vector sums of frequency-weighted values of RMS vibration accelerations – ahv and linear sound pressure levels – Lp. Advanced methods are based on short-time analysis and parametrization in frequency bands of the acoustic signal, as well as the time–frequency maps of vibration and acoustic signals. Discriminants of vibroacoustic signal were determined that allowed us to identify the operating mode of the chainsaw.

The Vibroacoustic Characteristics Analysis of Transformer Core Faults Based on Multi-Physical Field Coupling

Power transformers play an important role in the safe and reliable operation of the whole power grid. Once a fault occurs, it will endanger the normal operation of the transformer, and even result in power grid accidents. Accurate and practical methods of transformer fault monitoring and type identification have attracted extensive attention in the field of electrical engineering. However, it is difficult to obtain a large number of measurement data for different fault types on a large power transformer. The vibroacoustic characteristics of transformer faults have significant asymmetry. For the power transformer in service, it is complex and uneconomic to obtain the vibroacoustic signals under different fault conditions. To handle this problem, this paper proposes simulation methods of several common transformer core faults, based on multi-physical field coupling, and then analyzes the vibroacoustic signals generated by the operating transformer. Finally, it verifies the results of acoustic and vibration signals under several faults, through physical experiments. The results show that the transformer fault simulation method is reasonable and accurate. Furthermore, a change in the transformer core state will cause a change in the transformer vibroacoustic characteristics, and different types of core faults can be distinguished by the analysis of vibroacoustic characteristics.

Theoretical substantiation of the principles of continuous control of grinding equipment modes at the stage of cereal formation

In the article, the object of research is continuous control of the granulometric composition of the grain grinding mass at the exit of the roller mill, by analyzing the spectrum of acoustic noise generated during the grinding of grain products. The development of a vibroacoustic technique for continuous control of distribution according to the criteria of crushed grain products in the operational mode of mill enterprises is presented. Vibroacoustic noises emitted by the crushed fractions of a grain product are decomposed by a spectrum analyzer into additive spectral components according to consumer classification commodity grinding groups. Decomposition into spectra of vibroacoustic signals is carried out by an analogue spectrum analyzer SK4-56 with the establishment of a correspondence between subspectra and group commodity classification consumer units using the theory of pattern recognition by a training method based on the method of potential functions. To simplify the classification identification procedure, unambiguous correspondences are established between the subspectra and the relative noise level in the corresponding frequency range. In contrast to the existing methods of indirect control of the degree of product fineness, by the size of the roll gap or by the amount of power consumed from the network by the drive motor of the roller mill, or by the magnitude of pressure on a slowly rotating roll, or by the magnitude of the electrical resistance of the crushed grain mass coming out of the roll mill and other methods that give a very rough measurement of the particle size distribution, the proposed method of using spectrograms gives a better approximation model, since it relies on the use of Fourier spectra, which give more adequate correspondences between the spectral model and consumer classification groups. Granulometric analysis of the crushed grain mass is carried out in the frequency range from infrasonic frequencies to ultrasonic bandwidths not exceeding 60 kHz.

Monitoring soil state during compaction process using a vibrating rammer and a plate compactor

The aim of the work was to compare the operation of the proprietary intelligent compaction (IC) system for two types of machines: a vibrating rammer and a plate compactor. The tests were carried out for both types of machines on the field stand, using the analysis of the vibroacoustic signal received from the acceleration sensor located directly on the machine. The developed system allowed to determine the correlation of the parameters Q1 and Q2 with the degree of compaction of the studied soil. These parameters were also compared with commonly used (CMV and CCV) by leading manufacturers of compaction machines.

Nonlinear analysis of cylindrical gear dynamics under varying tooth breakage

Linear and nonlinear analyses served to detect the degree of tooth damage in a cylindrical gear. The gear in question is widely used in industrial applications and is often subject to gear tooth damage. Multiple-sourced vibrations affecting the test stand may distort or conceal the vibration components responsible for tooth failure. Given its construction, the test stand offers low stiffness, and additional control and measurement equipment further contribute to overall vibrations. Therefore, the vibration signal is likely to contain various disturbances, which further hinder correct diagnosis. Basic vibroacoustic signal analysis methods, which were employed at a preliminary stage, failed to produce unambiguous and satisfactory results. Hence, nonlinear recurrence analysis of gear operation dynamics was applied. It is assumed that the occurrence of damage to the gear will impede the regularity of drive transmission. The adopted research method addresses the limitations of a two-state diagnosis of gear condition (no damage/damage) by allowing the extent of gear tooth damage to be specified.

Design of a system for diagnosing the technical condition of a gas pumping unit based on the analysis of existing methods of processing vibroacoustic signals

The gas transportation system of Ukraine provides transportation of natural gas from deposits to consumers located both on the territory of Ukraine and outside its borders. One of the key elements of the gas transportation system of Ukraine are compressor stations, the task of which is to maintain the specified pressure in the system for uninterrupted transportation of natural gas. The main element of the compressor station is the gas pumping unit (GPU). It is a complex mechanical system consisting of many nodes. In the process of functioning of the gas pumping unit, in its nodes and units, the process of wear of parts occurs, which, subsequently, can lead to an accident. To avoid such situations, current and capital repairs of the system are periodically carried out. A number of non-destructive technical condition control methods have been developed to monitor the technical condition of the GPU between repairs, to optimize the periodicity of their carrying out and to provide early warning of the GPU leaving the nominal state. Such methods are divided into parametric methods, based on the analysis of the operating parameters of the system (temperature and pressure at various GPU nodes, turbine rotation frequency, chemical composition of combustion products), and vibroacoustic, based on the analysis of vibration and acoustic oscillations generated by the GPU nodes. The current state of vibroacoustic signal processing methods, such as Fourier transform, wavelet transform, artificial neural networks, discrete cosine transform, and autocorrelation functions are considered in the work. Based on the analysis, a system for diagnosing the technical state of the GPU based on the Fourier transform in combination with the wavelet transformation and an artificial neural network with two hidden layers is proposed, the task of which is to recognize the technical condition of the GPU, based on the result of the wavelet transformation, divided into separate images in primary colors.

Correlation of Vibroacoustic Signal with Ceramic Component Wear During Frictional Interaction with a Steel Disc

Correlation of Vibroacoustic Signal with Ceramic Component Wear During Frictional Interaction with a Steel Disc

USE OF DISCRETE WAVELET ANALYSIS OF VIBRO-ACOUSTIC SIGNALS TO DETECT BEARING DEFECTS OF ROTATING ELECTRIC MACHINES

The paper shows that one of the most effective methods for processing the time realization of a vibro-acoustic signal from electrical machines is a discrete wavelet transform. At the same time, due to the lack of built-in tools for separating periodic and aperiodic components in the latter, it significantly complicates the process of identifying periodic disturbing factors, which makes it necessary to develop new approaches to identifying periodic components of vibration based on discrete wavelet transform, which can be caused by a number of defects in rotating electrical machines. A new integral highly informative numerical criterion for the presence of bearing defects, obtained on the basis of a discrete wavelet transform of a vibro-acoustic signal of an electric machine, is proposed. It has been found that upon detection of the indicated defect, it is advisable to analyze the frequency bands, which include the rotor frequency and its first harmonic components. The expediency of using the parent wavelet function of higher orders upon detection of the indicated defect has been theoretically substantiated and experimentally proved. It is shown that, based on considerations of simplifying the mathematical apparatus of calculation and increasing the flexibility of the diagnostic system, it is advisable to use the Daubechies wavelet family, the calculation of the coefficients of which involves the use of a clear mathematical algorithm. The necessary duration of time realizations of vibration is theoretically substantiated and experimentally confirmed, which is advisable to use when determining the proposed highly informative numerical criterion. It is shown that the duration of such realizations should be significantly longer than the period of rotation of the rotor of the electric machine.

ПРИМЕНЕНИЕ ТЕХНОЛОГИИ ИДЕНТИФИКАЦИОННЫХ ИЗМЕРЕНИЙ ДЛЯ КОНТРОЛЯ СОСТОЯНИЯ ПОДШИПНИКА ВЕТРОГЕНЕРАТОРА

The article is concerned with solving the problem of the wind turbine bearing condition monitoring. A method for the wind turbine bearing condition monitoring is proposed, based on the using of the vibration signals identification measurements technology. Identification measurement is a type of measurements resulting in a number that quantitatively characterizes the shape of some informative signal characteristic. The proposed method application for the vibroacoustic signals analysis received from the wind turbine bearing in real time is described. The proposed method makes it possible to detect the bearing degradation processes at an early stage in a more efficient way compared to available methods.

VIBRATION PARAMETERS WHEN CHANGING THE CONDITION AND QUALITY OF FASTENING OF CUTTING INSERTS OF MODULAR TOOLS IN CONDITIONS OF AUTOMATED MACHINING

In automated production, monitoring of the cutting process is urgently needed as the cutting tool wears out, paints and can suddenly break. In the absence of an operator, all this threatens accidents and equipment downtime. The parameters of the vibroacoustic signals accompanying cutting have long been considered as a source of information about the condition of the tool and the quality of the processing process itself. The article presents the results of studies of changes in the spectral composition of vibrations in time during the cutting process due to wear of the cutting edge, changes in the state of fixing cutting inserts and the use of modular tools with a large number of elements.

Statistical Features in Time and Frequency Domain of Vibro-Acoustic Signals Applied to Detection of Early Browning in Pears

Statistical Features in Time and Frequency Domain of Vibro-Acoustic Signals Applied to Detection of Early Browning in Pears

Analysis of differences in vibroacoustic signals between healthy and osteoarthritic knees using EMD algorithm and statistical analysis

The knee joint is the largest and one of the most vulnerable and most frequently damaged joints in the human body. It is characterized by a complex structure. All articular surfaces are covered with hyaline cartilage. This cartilage has minimal regenerative capacity. Under the influence of cyclical micro-injuries, inflammatory mediators, prolonged excessive pressure or immobility, and thus disturbance of tissue nutrition, the cartilage becomes susceptible to damage and is easily covered with villi, cracks and abrasion. As a result, this translates into changes in the friction and lubrication processes within the joint and may affect the generated vibroacoustic processes. In this study, the signals recorded in a group of 28 volunteers were analysed, 15 of them were healthy people (HC) and 13 were people diagnosed with osteoarthritis (OA) qualified for surgery. The study aims to check the usefulness of the EMD (Empirical Mode Decomposition) algorithm in the filtration procedures of vibroacoustic signals. This algorithm is most often used in the analysis of signals that are most often nonlinear and non-stationary. Selected statistical indicators, such as RMS, VMS, variance and energy, were determined for the signals constituting the sum of the IMFs (Intrinsic Mode Functions) 1-8, having a normal distribution in the assessment of damage to the articular cartilage of the knee joint. Statistical analysis was performed for the values of individual indicators obtained. The vibroacoustic signals were recorded using CM-01B contact microphones placed in the central part of the medial and lateral joint fissure for movement in the range of 90°–0°–90° in closed kinetic chains (CKC) in the control group (HC) and the group of patients diagnosed with osteoarthritis (OA).

METHODS OF CONDITION MONITORING AND DIAGNOSTICS OF ROLLING BEARINGS OF CENTRIFUGAL MACHINES AND MECHANISMS

The perfection of methods and means of non-destructive testing and technical diagnostics is determined by the level of development of science and modern industrial technologies. The desire to develop technologies determines the growing needs for monitoring the state of substances, materials, products, and now the control of the state of the natural environment is becoming more and more relevant. Methods and means of condition monitoring and diagnostics of rolling bearings have been developed and developed for more than 60 years. Despite certain successes, today there is no information about the veracity of ways to solve this problem. The paper provides a fairly brief overview of methods and methods for monitoring the condition and diagnosis of rolling bearings, and also describes one of the newest trends in this field – the analysis of the properties of the characteristic function of vibroacoustic signals in order to determine the condition of the objects of control and, in particular, rolling bearings. It is shown that the magnitude of the module and the area of the characteristic function of the vibroacoustic signal are very effective criteria for assessing the technical condition of a rolling bearing.

Estimation of differences in selected indices of vibroacoustic signals between healthy and osteoarthritic patellofemoral joints as a potential non-invasive diagnostic tool

Osteoarthritis (OA) is currently the most generic form of joint disease. It is a complex process in which degenerative changes occur in the articular cartilage [AC], subchondral bone, and synovial membrane and can lead to permanent joint failure. The primary and most commonly used method of diagnosing degenerative changes is classic radiography. Magnetic resonance imaging (MRI) may be used to assess the extent of damage to joint surfaces, but this method is limited by the availability of specialised equipment and the excessive cost of the examination. Arthroscopy, an invasive procedure, is considered the “gold standard” in joint diagnosis. The occurrence of degenerative changes is closely related to the friction and lubrication processes within the joint. The main causes of osteoarthritis are a change or lack of synovial fluid, deformation of the joint bones, local damage to the articular cartilage, and a change in the mechanical properties of the articular cartilage due to water loss from the damaged superficial layer. An alternative, non-invasive method that allows for a delicate assessment of the condition of moving joints is vibroarthrography (VAG). The analysis of vibroacoustic signals generated by moving joint surfaces has an immense potential in the non-invasive assessment of the degree of damage to articular cartilage, meniscus and ligaments and the general diagnosis of degenerative diseases. The purpose of this study is to analyse and statistically compare the basic characteristics of vibroacoustic signals recorded with a CM-01B contact microphone placed on the patella for motion in the 90°–0°–90° range in a closed kinetic chain (CKC) in a control group (HC) and a group of patients diagnosed with osteoarthritis (OA), qualified for the knee alloplasty.

Sensitivity of a vibroacoustic signal to a change in the state of the surface layer of ceramics during frictio

The high information content of the vibroacoustic signal in the frequency range of 10‒16 kHz to the change in the state of the surface layer of the ceramic sample during frictional interaction with the steel disk was established. The results obtained indicate the possibility of using vibration diagnostics systems for monitoring the state of ceramic parts during operation and fi tests.

The correlation of the vibroacoustic signal with the wear of a ceramic part during frictional interaction with a steel disc

.

Methods and techniques of protecting information from leakage by technical channels via side electromagnetic radiation

The rapid development and constant growth of the use of computer equipment, wireless radio access systems, increasing the functionality of electronic means of personal use require a timely response to threats of information leakage through technical channels. This state of affairs has exacerbated the problem of identifying technical channels of information leakage arising from technical progress, and with it the need to ensure the required level of efficiency and cost of the process of searching and identifying technical channels of information leakage. The next important issue is the adequacy of measures to protect information from leakage through technical channels, verification and control of their effectiveness, determining the economic feasibility of the proposed set of measures. The use of existing means of search and detection of technical channels of information leakage, its further protection are based on the use of both active and passive methods. The article highlights methods and tools of protecting information from leakage by technical channels via side electromagnetic radiation and guidance during their processing using technical means, when transmitting via radio and optical communication channels, channels of leakage of acoustic (speech) and visual information. Basic steps to protect information from leakage by acoustic, vibroacoustic and optoelectronic channels are defined, which centre around reducing the level of acoustic and vibroacoustic signals, voicing information, to a certain signal-to-interference ratio. The passive and active measures analysed in the article are aimed at achieving the required signal-to-interference ratio. Passive information protection measures and their focus on improving the sound insulation of enclosing structures of information activity objects are highlighted. Active information protection measures and their impact on reducing the signal-to-interference ratio to normal by creating acoustic and vibroacoustic interference at the border of enclosing structures of information activity objects are analysed. The conceptual foundations of technical information protection, its basic principles are given, with the principal methods and means of ensuring information security for each of the possible leakage channels defined.

Incipient Surge Analysis in Time and Frequency Domain for Centrifugal Compressors

Abstract The use of centrifugal compressors has been increasing tremendously in the last decade as they are a key component in the present energy scenario both in the modern internal combustion engine design and in advanced cycles and innovative plant layouts as fuel cell systems. Instability phenomena limit the operating range of the whole compressor system, especially during fast transients. The target is therefore to extend the minimum flow limit in order to improve the operability of each unit while avoiding compressor surge operation and guaranteeing safe operation. For this reason, it is necessary to develop a monitoring system capable of preventing surge and extending the operating range of these machines, their performance, and reliability to allow the integration with the other plant components. The experimental investigation carried out at the University of Genoa turbocharger test facility and presented in this work, consists of steady-state and transient measurements used to characterize and identify compressor behavior in correspondence of surge inception conditions to determine different techniques which could represent surge precursors. The data analysis concentrates on pressure and vibro-acoustic signals by applying different signal processing techniques in the time and frequency domain to classify compressor operation as stable or unstable. The cross correlation function and wavelet analysis have been identified as techniques to define a precursor able to detect incipient surge conditions. Through cross correlation function analysis, it has been possible to identify the presence of propagation phenomena in the system and to evaluate how these events become more significant near an unstable low-mass flow rate condition. At low mass flow rate condition, spikes of significant amplitude are well detectable in the cross correlation function indicating the rise of significant random content in the system responses associated with the rise of incipient surge condition. Additionally, the continuous wavelet transform has been applied to operational signals to show how their time-dependent spectral structure responses can highlight the rise of unstable phenomena, not easily identifiable with traditional signal processing techniques. Exploiting its features in terms of good frequency and time resolution allowed us to identify different contents in system responses regarding phenomena that take place close to surge line and were able to detect their nature in conditions very close to deep surge ones (e.g., rotating stall with its intermitting characteristic nature). Moreover, system response was studied in high frequency range and through a demodulation technique, it was found how blade passes frequency energy content change interacting with rotating stall inception, moving close to surge line. The obtained results provide an interesting diagnostic and predictive solution to detect compressor instabilities at low mass flow rate operating conditions and to prevent compressor fails.

Evaluation of Wear of Disc Brake Friction Linings and the Variability of the Friction Coefficient on the Basis of Vibroacoustic Signals

The article presents the results of friction and vibroacoustic tests of a railway disc brake carried out on a brake stand. The vibration signal generated by the friction linings provides information on their wear and offers evaluation of the braking process, i.e., changes in the average friction coefficient. The algorithm presents simple regression linear and non-linear models for the thickness of the friction linings and the average coefficient of friction based on the effective value of vibration acceleration. The vibration acceleration signals were analyzed in the amplitude and frequency domains. In both cases, satisfactory values of the dynamics of changes above 6 dB were obtained. In the case of spectral analysis using a mid-band filter, more accurate models of the friction lining thickness and the average coefficient of friction were obtained. However, the spectral analysis does not allow the estimation of the lining thickness and the friction coefficient at low braking speeds, i.e., 50 and 80 km/h. The analysis of amplitudes leads to the determination of models in the entire braking speed range from 50 to 200 km/h, despite the lower accuracy compared to the model, based on the spectral analysis. The vibroacoustic literature presents methods of diagnosis of the wear of various machine elements such as bearings or friction linings, based on amplitude or frequency analysis of vibrations. These signal analysis methods have their limitations with regard to their scope of use and the accuracy of diagnosis. There are no cases of simultaneous use of different methods of analysis. This article presents the simultaneous application of the amplitude and frequency methods in the analysis of vibroacoustic signals generated by brake linings. Moreover, algorithms for assessing the wear of friction linings and the average coefficient of friction were presented. The algorithm enables determination of the time at which the friction linings should be replaced with new ones. The final algorithm analyzes the vibration acceleration signals using both amplitude analysis for low braking speeds, as well as spectral analysis for medium and high braking speeds.