Vibroacoustic Signals Research Articles

Investigation of the influence of the trajectory of shaping movements on the surface roughness by vibroacoustic monitoring during milling

The principles of constructing a system of online monitoring and vibroacoustic diagnostics for milling spatially complex surfaces are considered. The high sensitivity of the vibroacoustic signal is shown when the cutting edges of the milling cutter are passing through the processing zone. An estimate of the influence of the motion trajectory on the roughness parameters is given. Keywords: spherical-cylindrical milling cutter, roughness, vibroacoustic diagnostics, industry 4.0, online monitoring, tool inclination, motion trajectory. 009063@pnu.edu.ru

Evolution of stridulatory mechanisms: vibroacoustic communication may be common in leaf-footed bugs and allies (Heteroptera: Coreoidea).

Intra- and interspecific communication is crucial to fitness via its role in facilitating mating, territoriality and defence. Yet, the evolution of animal communication systems is puzzling-how do they originate and change over time? Studying stridulatory morphology provides a tractable opportunity to deduce the origin and diversification of a communication mechanism. Stridulation occurs when two sclerotized structures rub together to produce vibratory and acoustic (vibroacoustic) signals, such as a cricket 'chirp'. We investigated the evolution of stridulatory mechanisms in the superfamily Coreoidea (Hemiptera: Heteroptera), a group of insects known for elaborate male fighting behaviours and enlarged hindlegs. We surveyed a large sampling of taxa and used a phylogenomic dataset to investigate the evolution of stridulatory mechanisms. We identified four mechanisms, with at least five evolutionary gains. One mechanism, occurring only in male Harmostini (Rhopalidae), is described for the first time. Some stridulatory mechanisms appear to be non-homoplastic apomorphies within Rhopalidae, while others are homoplastic or potentially homoplastic within Coreidae and Alydidae, respectively. We detected no losses of these mechanisms once evolved, suggesting they are adaptive. Our work sets the stage for further behavioural, evolutionary and ecological studies to better understand the context in which these traits evolve and change.

Vibro-Acoustic Sensing of Instrument Interactions as a Potential Source of Texture-Related Information in Robotic Palpation.

The direct tactile assessment of surface textures during palpation is an essential component of open surgery that is impeded in minimally invasive and robot-assisted surgery. When indirectly palpating with a surgical instrument, the structural vibrations from this interaction contain tactile information that can be extracted and analysed. This study investigates the influence of the parameters contact angle α and velocity v→ on the vibro-acoustic signals from this indirect palpation. A 7-DOF robotic arm, a standard surgical instrument, and a vibration measurement system were used to palpate three different materials with varying α and v→. The signals were processed based on continuous wavelet transformation. They showed material-specific signatures in the time-frequency domain that retained their general characteristic for varying α and v→. Energy-related and statistical features were extracted, and supervised classification was performed, where the testing data comprised only signals acquired with different palpation parameters than for training data. The classifiers support vector machine and k-nearest neighbours provided 99.67% and 96.00% accuracy for the differentiation of the materials. The results indicate the robustness of the features against variations in the palpation parameters. This is a prerequisite for an application in minimally invasive surgery but needs to be confirmed in realistic experiments with biological tissues.

Termite exocrine systems: a review of current knowledge

AbstractIn this review, we summarize the 22 exocrine glands hitherto described for termites (Isoptera), highlighting their distribution, morphological features, and likely function. The secretion from such glands displays a very important role in termite communication, but is also attributed to many other activities performed by these insects, including defense, building, and foraging, as well as physiological processes such as the synthesis of digestive enzymes, and antiseptic and lubricant compounds. Here, glands are divided into those associated with termite mouthparts and other head appendages, tegumentary glands with epithelial arrangement, those related to the reproductive apparatus, and glands which do not fit into these divisions. The exocrine systems in termites may be composed of classes 1, 2, and 3 secretory cells, which differ in how the glandular secretion is released. Moreover, they may exhibit a varied composition of secretory cell classes. Different glands may be involved in specific tasks and therefore produce specific compounds, although there are cases in which the same content is secreted by different glands, suggesting a functional plasticity. The chemical nature of these secretions and their role are well known for some glands, such as the frontal, salivary, tergal, and sternal ones. On the other hand, such aspects remain speculative or completely unknown for other glands. The number of termite exocrine glands is extremely low when compared to those described for eusocial Hymenoptera, and is a likely consequence of the higher diversity of species and chemical communication in the latter group. Moreover, vibroacoustic signals represent an important type of communication in termites. Further studies are encouraged to provide new insights into the occurrence and function of the exocrine systems in termites and how they modulate the different activities displayed by them.

Application of the vibro-acoustic signal to evaluate wear in the spindle bearings of machining centres. In-service diagnostics in the automotive industry

The correct, undisturbed operation of machines and their components is one of the essential manifestations of an efficient production process. Continuous observation of a machine behaviour is essential to ensure correct and safe operation. The authors of current research focused on evaluation of the using a vibro-acoustic signal to diagnose the wear of spindle bearings of numeric machine tools applied in the automotive industry. More precisely, the effects of using the roll bearings vibrations for the operational diagnostics of spindles in numerical machining centres were investigated. The following parameters were used for analyzing such signals: the acceleration of vibration, the acceleration envelope and the velocity of the vibration. The first part of the research focused on determining the warning thresholds for the observed parameters. In the next stage of the research, the trends of the measured parameters were observed until the warning thresholds were exceeded and the alarm states occurred. An attempt was made to find the reasons for the observed alarm states by analyzing the frequency spectra of the recorded signals at the points where these states occurred. In addition, the diagnosed machine parts (machine tool spindle) were dismantled and inspected in order to link the damage found with the symptoms observed during the recording of diagnostic signals. The relationship between both the signal values and the condition of the diagnosed components as well as between the measured parameters was clearly demonstrated. In the presented article, the authors describe an experiment during which it was possible to register both the normal and emergency state of the object, which is extremely important in industrial diagnostics because one of its limitations is the lack of data from emergency states. In the final conclusions, the authors confirmed the validity of the assumed thesis that the vibroacoustic signal received from the spindle bearings of machines used in mass production in the automotive industry can be used to diagnose the spindles themselves and detect the symptoms of their wear. What can have a significant impact on the quality of manufactured products. This article summarizes the experimental research to date.

Choice of method for determining the concentration and fractional composition of dust and gas flow

The presence of industrial dust in concentrations exceeding the MPC leads to environmental pollution and threatens environmental safety. The article presents a method for determining the concentration and fractional composition of the dust and gas flow. The essence of the described method lies in the registration and analysis of vibroacoustic signals that occur due to vibrations of parts of the measuring system. The principle of operation of the system is based on the transmission of shock acts of oscillation generation along a chain that includes dust particles, a boundary layer, a dust pipeline wall, and, finally, a piezoceramic sensor of the system. The disperse composition of dust can be determined by two mathematical models (Fourier polynomials) - one reflects the energy spectrum, the other - the amplitude-phase. These polynomials are obtained by applying the Laplace transform to the signal and actually reveal the physical meaning of the process of formation of harmonics in the frequency subspectra. The processing of an acoustic signal on a computer by a fast discrete Fourier transform leads to an accurate description and calculation of the amplitude-frequency spectrum in real time. The main task is to isolate the frequency subspectra, consisting of the main and timbre harmonics for dust monofractions. The method of static moments is used to refine and form the frequency package of the main harmonics. The implementation of the method is carried out on a laboratory stand during the transfer of a dust-gas flow with pure monofractions and with a stepwise increase in concentration, the amplitudes of the main and timbre harmonics increase, which forms the frequency subspectrum of the analyzed dust monofraction. For further analysis and processing of AS spectra, a block diagram of an algorithm for determining the fractional composition of a moving dust and gas flow has been developed.

Blade crack detection based on domain adaptation and autoencoder of multidimensional vibro-acoustic feature fusion

On the condition of variable speeds, the blade crack signal generated by the single-mode sensor is an inherent risk of being misled by noise. Besides, it is challenging to reach the required integrity of information through feature extraction in single analysis domain, leading to the loss of detection accuracy for blade cracks. Therefore, a blade crack detection method based on domain adaptation and autoencoder (AE) of multidimensional vibro-acoustic feature fusion is proposed to extract more complete fault information from multi-sensor and multi-analysis domains. This method extracts one-dimensional (1D) and two-dimensional (2D) features from the frequency domain and smoothed pseudo-wigner-ville distribution (SPWVD) spectrum of the vibro-acoustic signal. Firstly, the 1D and 2D features are extracted without supervision through Stacked Denoising Autoencoder (SDAE) and Convolution Denoising Autoencoder (CDAE), respectively. Then, the extracted multidimensional features are fused and classified through the fully connected network. Finally, for insufficient diagnosis accuracy and data imbalance under certain working condition models with variable speed and combined with inductive transfer mechanism and domain adaptation, the stable diagnosis model under specific speed is applied for transferring and learning the unsupervised networks of other models compensating the weak generalization ability and robustness of the model. The experimental results show that this method is characterized by higher accuracy and robustness compared with the diagnosis method of single-domain feature for the single-mode sensor. Moreover, the proposed migration mechanism can well solve the data imbalance under different working conditions and improve the generalization ability of the few-shot model.

Sexual selection and predation drive the repeated evolution of stridulation in Heteroptera and other arthropods.

Acoustic and substrate-borne vibrations are among the most widely used signalling modalities in animals. Arthropods display a staggering diversity of vibroacoustic organs generating acoustic sound and/or substrate-borne vibrations, and are fundamental to our broader understanding of the evolution of animal signalling. The primary mechanism that arthropods use to generate vibroacoustic signals is stridulation, which involves the rubbing together of opposing body parts. Although stridulation is common, its behavioural context and evolutionary drivers are often hard to pinpoint, owing to limited synthesis of empirical observations on stridulatory species. This is exacerbated by the diversity of mechanisms involved and the sparsity of their description in the literature, which renders their documentation a challenging task. Here, we present the most comprehensive review to date on the systematic distribution and behavioural context of stridulation. We use the megadiverse heteropteran insects as a model, together with multiple arthropod outgroups (arachnids, myriapods, and selected pancrustaceans). We find that stridulatory vibroacoustic signalling has evolved independently at least 84 times and is present in roughly 20% of Heteroptera, representing a remarkable case of convergent evolution. By studying the behavioural context of stridulation across Heteroptera and 189 outgroup lineages, we find that predation pressure and sexual selection are the main behaviours associated with stridulation across arthropods, adding further evidence for their role as drivers of large-scale signalling and morphological innovation in animals. Remarkably, the absence of tympanal ears in most Heteroptera suggests that they typically cannot detect the acoustic component of their stridulatory signals. This demonstrates that the adoption of new signalling modalities is not always correlated with the ability to perceive those signals, especially when these signals are directed towards interspecific receivers in defensive contexts. Furthermore, by mapping their morphology and systematic distribution, we show that stridulatory organs tend to evolve in specific body parts, likely originating from cleaning motions and pre-copulatory displays that are common to most arthropods. By synthesising our understanding of stridulation and stridulatory organs across major arthropod groups, we create the necessary framework for future studies to explore their systematic and behavioural significance, their potential role in sensory evolution and innovation, and the biomechanics of this mode of signalling.

Assessment of local faults in helical geared system using vibro-acoustic signals based on higher order spectrum analysis

Geared transmission system plays an important role in modern technology to transmit both power and motion. The power transmission and control requirements in manufacturing, aviation, transportation, energy industries require uninterrupted operation under high efficiency.Increase in fatigue load cycles in a geared transmission system thereby leading to negative impact on contact surfaces of gear tooth, which result in non-unifor m power transmission, increase in dynamic response, and decrease in efficiency followed by catastrophic tooth failure.The wear propagated on gear teeth contact causes a variation in the dynamic response of geared system. It is widely acceptedthat the local/distributed faults developed on rolling/sliding contact elements can be detected by using vibration and/oracoustic monitoring and analysis techniques.This paper describes the results of experimental studies carried out to detect and diagnose the simulated faults in the helical gear tooth of a two stage helical gearbox.The helical gear was mounted in a two-stage gearbox operating under controlled speed and load conditions. The vibration and airborne sound signals obtained from the gearbox were considered to attain a reliable fault related information by using a higher-order spectrum analysis technique. The fault related features extracted from the vibration and the acoustic data post processed by using bispectrum analysis provided a better diagnostic information to detect progressive faulty operating conditions viz., 20%, 40%, 60%, 80% and 100% tooth removal cases in the gearbox.

ResNet-integrated very early bolt looseness monitoring based on intrinsic feature extraction of percussion sounds

Very early bolt looseness monitoring has been a challenge in the field of structural health monitoring. The authors have conducted a further study of the previous researches, with the aim of detecting very early bolt looseness conditions. The intrinsic features of vibro-acoustic signals contain the underlying dynamic characteristics denoting full range bolt looseness conditions. Correspondingly, this paper proposes a novel ResNet-integrated very early bolt looseness monitoring approach based on intrinsic feature extraction of percussion sounds. The intrinsic features of percussion-caused sound signals were extracted by variational mode decomposition (VMD), where the parameters of VMD were determined by grey wolf optimization algorithm. The optimal band-limited intrinsic mode functions were converted into two-dimensional time–frequency maps by continuous wavelet transform. The (red green blue) RGB images were adopted as the input of residual network (ResNet) to monitor very early bolt looseness conditions. The results and analysis illustrate the validity and superiority of the novel ResNet-integrated very early bolt looseness monitoring approach. The proposed approach in our researches provides a novel solution for very early bolt looseness monitoring in the field of structural health monitoring. The strategy can also be extended to other nonlinear signal processing-involved fields.

Investigation of the Information Possibilities of the Parameters of Vibroacoustic Signals Accompanying the Processing of Materials by Concentrated Energy Flows

Creating systems for monitoring technology processes based on concentrated energy flows is an urgent and challenging task for automated production. Similar processes accompany such processing technologies: intensive thermal energy transfer to the substance, heating, development of the melting and evaporation or sublimation, ionization, and expansion of the released substance. It is accompanied by structural and phase rearrangements, local changes in volumes, chemical reactions that cause perturbations of the elastic medium, and the propagation of longitudinal and transverse waves in a wide frequency range. Vibrational energy propagates through the machine's elastic system, making it possible to register vibrations on surfaces remotely. Vibration parameters can be used in monitoring systems to prevent negative phenomena during processing and to be a tool for understanding the processes' kinetics. In some cases, it is the only source of information about the progress in the processing zone.

An Overview of Vibration Analysis Techniques for the Fault Diagnostics of Rolling Bearings in Machinery

The perfection of methods and means of nondestructive testing and technical diagnostics is determined by the level of development of science and modern industrial technologies. The desire to develop technologies determines the extent and degree to which the monitoring of the state of substances, materials, products—and now the state of the natural environment—are becoming increasingly relevant. The methods and means of condition monitoring and the diagnostics of rolling bearings have been in development for more than 60 years. Despite some successes, however, there is currently no information concerning the veracity of means to completely resolve the bearing diagnostics problem. This paper provides a fairly brief overview of methods and means 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 (VA) 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 VA signal are very effective criteria for assessing the technical condition of a rolling bearing.

THE INFLUENCE OF THE DIMENSIONAL PARAMETERS OF THE MICROCUTTERS ON THE QUALITY OF PROCESSING OF SMALL PARTS ON CNC TURNING ROD MACHINES

Based on the study of the parameters of vibroacoustic signals, the size of the microcutters was optimized. The influence of the parameters of microcutters on the roughness of the holes of small-sized parts processed on lathe bar machines has been determined. The dependencies of the roughness parameters of the treated holes on the sortie the cutter insert in the assembly of the boring tool in a wide range of feeds are obtained. A value for ensuring that the requirements of the roughness of the holes of small-sized parts has been determined.

Experience of operation of the UDP-2001SM railway wheelset bearing vibration diagnostics installation and the OMSD-02 mechanism diagnostics system

The Aim of the paper is to compare the UDP-2001SM installation for vibration diagnostics of bearings of freight, refrigerator and passenger car wheels and the OMSD-02 mechanism diagnostics system that since recently has been used in the Belarusian Railway.Methods. By way of analysis of the UDP-2001SM vibration diagnostics installation and the OMSD-02 mechanism diagnostics system, the authors considered the list of identifiable defects, method for defining threshold values (reference levels) of vibroacoustic pulses and noises for the criteria of “faulty” and “good”, statistical data for rejected axleboxes of freight and passenger car wheelsets in respect to the overall number of conducted measurements, the experience of operation in various car shops of the Belarusian Railway. Results. The paper describes the process of vibration diagnostics of wheelset bearings of freight and passenger cars using the case of stationary acquisition of vibroacoustic signals from acoustic plates that interact with the diagnosed axlebox. The authors present the diagrams of the UDP-2001SM installation and OMSD-02 system, as well as the defects of bearings that are to be identified using the above diagnostics equipment. Conclusion. The paper showed the advantages and disadvantages of the above diagnostics systems based on the experience of their application in a number of car shops of the Belarusian Railway.

Contrast Estimation in Vibroacoustic Signals for Diagnosing Early Faults of Short-Circuited Turns in Transformers under Different Load Conditions

The transformer is one of the most important electrical machines in electrical systems. Its proper operation is fundamental for the distribution and transmission of electrical energy. During its service life, it is under continuous electrical and mechanical stresses that can produce diverse types of damage. Among them, short-circuited turns (SCTs) in the windings are one of the main causes of the transformer fault; therefore, their detection in an early stage can help to increase the transformer life and reduce the maintenance costs. In this regard, this paper proposes a signal processing-based methodology to detect early SCTs (i.e., damage of low severity) through the analysis of vibroacoustic signals in steady state under different load conditions, i.e., no load, linear load, nonlinear load, and both linear and nonlinear loads, where the transformer is adapted to emulate different conditions, i.e., healthy (0 SCTs) and with damage of low severity (1 and 2 SCTs). In the signal processing stage, the contrast index is analyzed as a fault indicator, where the Unser and Tamura definitions are tested. For the automatic classification of the obtained indices, an artificial neural network is used. It showed better results than the ones provided by a support vector machine. Results demonstrate that the contrast estimation is suitable as a fault indicator for all the load conditions since 89.78% of accuracy is obtained if the Unser definition is used.

ADJUSTMENT OF THE ELECTRICAL DISCHARGE MACHINING PROCESS BY MEANS OF VIBROACOUSTIC SIGNAL ANALYSIS

Expanding industry demand for machining of critical products from hard-to-machine materials and hard alloys makes the research aimed at finding optimal modes of electrical discharge machining topical. This is, for example, the determination of modes that provide the highest productivity or efficiency, or minimum tool wear, while ensuring the necessary roughness and accuracy of the product. In the present work, it is proposed to supplement the parameters monitored in electric discharge machining with non-electrical parameters, which include the parameters of vibroacoustic signals that accompany the working process. The paper shows that parallel recording of the discharge current vibration signals makes it possible to reveal the drawbacks of processing conditions and to influence purposefully the technological process modes in order to bring the processing conditions closer to the optimum ones.

Compressor Surge Precursors for a Turbocharger Coupled to a Pressure Vessel

Abstract Dynamic compressors operating region is mainly constrained by fluid-dynamic instabilities occurring at low mass flow rate conditions, such as surge and rotating stall. This work presents a vibro-acoustic experimental investigation on a centrifugal compressor of an automotive turbocharger aimed to identify and confirm some surge precursor values in correspondence of its inception conditions. The experimental campaign was carried out on a turbocharger equipped by a vaneless diffuser compressor exploited for the pressurization of an innovative solid oxide fuel cell (SOFC) emulator. The investigated turbocharger is coupled with a pressure vessel for a former emulation activity on a pressurized SOFC. In such kind of plants, the joint effect of large volume size downstream the compressor makes more complex the dynamic behavior of the whole system during transients, thus significantly increasing surge onset risk. The main goal is to define a suitable quantitative indicator to detect in advance surge inception by relying only on system vibro-acoustic response. Several transient from a compressor stable condition to surge instability onset were performed by progressively closing specific valves in the air line. When moving close to surge , vibro-acoustic signals were acquired at a high sampling rate to investigate blade passage phenomena which might interact with rotating stall inception. Meanwhile, pressures, temperatures and mass flow rates measured at a lower sampling rate to correlate compressor vibro-acoustic and performance behavior. Cyclostationary analysis was performed on vibro-acoustic acquired signals to provide innovative diagnostic and predictive solutions (precursors) for early surge detection.

A PROPOSAL FOR A MOBILE SYSTEM OF VEHICLE AND RAIL TRACK DIAGNOSTICS

The proper technical condition of a vehicle and rail track in operation is a key aspect in terms of safety and travel comfort. This issue is of particular importance for operators and managers of rolling stock and rail infrastructure. Currently, many diagnostic systems have been developed to monitor the technical condition of selected vehicle systems or rail track from the viewpoints of both the vehicle and track. This article proposes the use of vibration signals in selected quantitative and qualitative analyses as the main diagnostic parameter. For this purpose, over a dozen vibration measurements were carried out during the normal operation of a freight wagon as part of a so-called passive experiment. Measurement points were located on the axle boxes of the wheelsets. The proposed research methodology served as a basis for comparative analyses of the selected operational cases that were investigated. The most important conclusion from the study is that it is possible to monitor the technical condition of vehicles and tracks in real time on the basis of measurements of vibration accelerations at the vehicle level. This directly increases the service life of rolling stock and optimises operating costs by changing the maintenance strategy to one that takes into account the idea of modern on-board technical diagnostics. Another important aspect is the possibility of the varied use of the proposed measurement system, depending on the purpose of the research, which is also associated with the diagnostician’s experience in processing vibroacoustic signals and the utilisation of simple or complex quantitative and qualitative analyses.

A centrifugal fan blade damage identification method based on the multi-level fusion of vibro-acoustic signals and CNN

A single sensor's blade damage identification is difficult because of the complex noise environment. At the same time, the multi-source signals include complete information of fault characteristics. Aiming to effectively fuse multi-sensor signals and improve identification accuracy, a centrifugal fan blade damage identification method based on the multi-level fusion of vibro-acoustic signals and a one-dimensional convolutional neural network (1D-CNN) is proposed. Firstly, acoustic and vibration signals are fused at the data level respectively by a data-adaptive synchronization weighted fusion algorithm. Secondly, the proposed 1D-CNN network extracts feature from the fused acoustic and vibration signals. Finally, the extracted features are fused by a fully connected layer. The experimental results show that the proposed method achieves 100% recognition accuracy at four speeds. By analyzing different signal to noise ratios (SNR), this method has higher diagnostic accuracy and better robustness compared with single sensor, single-level fusion, and other diagnostic methods.

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.