Operational Transfer Path Analysis Research Articles

Operational transfer path analysis with crosstalk cancellation based on least variance spectrum estimation

Operational transfer path analysis with crosstalk cancellation based on least variance spectrum estimation

A development on the interior noise prediction technology using active noise control algorithm

When developing NVH of a vehicle, identifying a noise transmission vulnerable path is a very important task. The traditional TPA(Transfer Path Analysis) is based on a physical theoretical equation and calculates the contribution of each path by multiplying the ATF(Acoustic Transfer Function) of each path by the driving load. In this case, it is often difficult to calculate the driving load, and M/H consumption is also high. OTPA(Operational Transfer Path Analysis) performs transfer path analysis only with driving signals for each route, but has a disadvantage of insufficient physical causality. In this study, we proposed an efficient indoor noise TPA method that modifies the ANC algorithm by combining the reference signals while driving with the secondary path of Filtered-X LMS. The proposed method uses the secondary transfer function of Fx-LMS as the ATF for each path. It is not necessary to obtain physical load by predicting target noise with the Ref signal for each route. Therefore, it is possible to predict indoor noise with low M/H. In this study, it can be confirmed that the proposed method shows similar results compared to the existing methods and efficiently identifies main noise path for interior noise.

Exploring the application of a Bayesian framework in transfer path analysis

Transfer path analysis (TPA) is a methodology widely used in transmission identification of vibration and noise. Among the TPA families, the two prevailing approaches are classical TPA with the matrix inversion method and operational transfer path analysis (OTPA). Both methods rely on measurements within costly and complicated overdetermined systems. These experiment-based methods are also limited by sufficient space for the sensor mounting, which can result in difficulty when analyzing the transfer path in small objects. In this paper, we use an experimental setup that mimics an engine mounted on a suspension with resilient connections. The severity of errors stemming from the application of underdetermined measurement systems is assessed, alongside an exploration of how the Bayesian framework can be integrated into the analysis to mitigate errors and enhance the performance of TPA.

Operational transfer path analysis for the fixed shaft gear transmission system based on the simulation and experiment

Operational transfer path analysis for the fixed shaft gear transmission system based on the simulation and experiment

Sound source identification of a cylindrical shell by merging near-field acoustic holography with operational transfer path analysis

The purpose of this paper is to propose a new sound source identification method to identify and separate the sound sources generated by the cross-coupled vibration sources inside the cylindrical shell structure. Near-field acoustic holography (NAH) has fundamentally changed sound source identification in that it has enabled the identification of sound sources and the visualization of the 3-D sound field. Nevertheless, the NAH technique is still unable to identify the vibration sources inside a structure and also finds it difficult to identify the contribution of a single sound source to sound fields due to cross-coupling among the vibration sources. To overcome these limitations, a modified operational transfer path analysis (OPA) technique has also been proposed, which can address the cross-coupling between vibration sources. In practice, however, a single identification method often appears to be inadequate. Thus, in this paper, a novel method of merging the NAH technique and the modified OPA technique has been adopted and used to identify the structure-borne sound source of a cylindrical shell. Finally, the adaptability of the proposed method has been demonstrated by numerical simulations and experimentally and it has been shown that the novel method can not only compute the sound field distribution of a cylindrical surface, but also reconstruct other 3-D field distributions, and moreover, can locate a sound source and predict the sound field.

A study on active road noise control based on operational transfer path analysis and selective subband adaptive filtering

In the feedforward active road noise control (ARNC) system, the noise reduction performance relies on the correlation between the reference signals and the target noise signals. To achieve better noise reduction performance, the operational transfer path analysis (OTPA) model with singular value decomposition was proposed to separate the road noise component from the target noise. Combined with OTPA and multi-coherence sorting method (MCSM), simulation analysis and real vehicle tests under various speeds both showed that the system with optimized reference sensor set had better road noise reduction performance, especially at the peak frequencies. To further improve noise reduction performance and reduce computational load, a selective subband adaptive filtering (SSAF) algorithm was proposed to build an active road noise control model with optimized reference sensor set. Simulation results, employing real vehicle test data, showed that the proposed method further improved the noise reduction performance and effectively reduced the amount of computational load.

Operational transfer path analysis based on neural network

Noise, vibration, and harshness (NVH) issues induced by vibrating source to receivers are sensitive concerns in the automotive industry, significantly determining the product quality. Transfer path analysis (TPA) serves as a crucial tool in addressing these concerns. However, classical and component-based TPA methods necessitate the measurement of all transfer functions associated with the NVH phenomenon, causing high experimental costs; moreover, operational TPA (OTPA) involves matrix inversion processes that may result in the loss of important information. In this study, a neural network-based OTPA (NOTPA) method is proposed that eliminates the need for a matrix inversion process and utilizes only operational measurement. To derive the physical meaning of transmissibility obtained from the trained neural network model, the learning algorithm for NOTPA was developed, and appropriate learning rules were applied to the model. In the general neural network model, training was performed using real-valued parameters. However, the phase of the signal is crucial information in the theoretical formulation of TPA; thus, a complex-valued propagation algorithm was established. Furthermore, an appropriate activation function was chosen to derive the actual transfer mechanism from the trained complex-valued parameters. To experimentally verify the NOTPA method, a testbed resembling automotive vehicle structure was constructed. Estimation of sound pressure and noise contribution analysis were conducted using the NOTPA method and compared with conventional TPA methods. The proposed method demonstrated higher accuracy compared to the conventional OTPA method and successfully identified the main transfer path compared to the classical TPA. Furthermore, by comparing the estimated sound pressure according to the architecture of the model, the consistency of the proposed model was verified.

Extraction of high contributing vibration mode to the loudness of industrial sewing machine radiated noise using operational TPA

In this study, we analyzed the factor increasing the loudness of an industrial sewing machine radiated noise using operational transfer path analysis (OTPA). At first, radiated noise of a sewing machine was recorded and the loudness was calculated to evaluate the noise level considering human auditory perception characteristics. The reduction target frequency band was then determined according to the specific loudness. Subsequently, the vibration acceleration at around the machine was measured and vibration mode analysis was conducted to understand the vibration characteristics of the machine and the factor increasing the noise at the target frequency band. In addition, OTPA principal component model was applied to the sewing machine to estimate the high contributing vibration mode to the radiated noise at the target frequency band. Finally, the loudness at the target frequency band could be decreased well by applying intensive countermeasure to the obtained high contributing vibration mode by the analyses.

Deep Learning Approach for Operational Transfer Path Analysis: Case Study of Electric Vehicles

This paper presents a new approach to fault diagnosis of the drivetrains of the electric vehicle. Most commercially available electric vehicles do not have accelerometers on electric drivetrains making it difficult to detect fault characteristics of the drivetrains of the electric vehicle, whereas accelerometers exist on the driver's seat. The proposed approach’s key idea is based on the operational transfer path analysis that determines the transfer function between the source and receiver. The transfer function is derived by training a deep learning model. The deep learning model converts the driver's seat vibration signals into drivetrains vibration signals. The validity of the proposed approach is evaluated using data from the durability test of real electric vehicles. It is anticipated that the proposed approach is effective to diagnose electric vehicle drivetrains subjected to external noise conditions.

Turbo generator vibration source identification based on operational transfer path analysis technology

Unstable vibrations in rotating machinery can stem from various causes, making it challenging to determine their origins. This research introduces the operational transfer path analysis method (OTPA) as a means to identify the causes of turbo generator vibrations. The model takes operational parameters, such as power and current, as input, and the vibration amplitude as output, to establish the source analysis model. To address the ill-conditioned input matrix, the singular value decomposition method is employed. By solving the transmissibility matrix and analyzing parameter contributions, the primary factors influencing vibration are identified. This method is applied to analyze the vibration sources in a 660 MW turbine generator unit. The generator experienced unstable vibration of unknown origin for a certain period. Operational transfer path analysis revealed that hydrogen pressure, hydrogen temperature, and bearing temperature significantly impacted the vibrations. Thermal imbalances and shaft misalignment in the generator rotor were inferred as the likely causes. Through adjustments to hydrogen pressure and temperature, the generator vibration was controlled until the next overhaul. Subsequent maintenance revealed partial blockage of the hydrogen ventilation holes, leading to rotor thermal imbalances. The feasibility of this method was confirmed. The objective of this study is to present an effective data-driven model for identifying the main influential parameters among numerous variables. This model can be applied to intelligent fault diagnosis in power generation units.

Research on simulated operational path analysis applied to structure-borne road noise

The accurate identification of noise sources inside vehicles is the basis of optimizing structure-borne noise problems, and transfer path analysis (TPA) is one of the most commonly used methods. The load-response type TPA represented by the classical TPA has high accuracy but low experimental efficiency. The response-response type TPA represented by the Operational TPA (OTPA) has high efficiency but cannot guarantee its accuracy when the relevant excitation sources act on the system simultaneously or there is a strong coupling between the transfer paths. In this paper, a novel response-response type TPA, simulated operational path analysis (SOPA), balancing efficiency and accuracy is proposed and tested. Without severing the connection between the source and receiver, the system is decoupled by running the simulated loads separately, and the proposed inverse transmissibility matrix method is used to cancel the crosstalk between reference signals, thus solving the problems of path cross-coupling and path neglection of OTPA in multi-input systems. For validation purpose, a four-shaker bench test is analysed, it is found that SOPA is more accurate than OTPA in path contributions analysis. Finally, SOPA is applied to the transfer path analysis of structure-borne road noise inside the vehicle, and it is also shown that the noise can be well predicted. Therefore, the proposed method may be an alternative method in addition to the traditional source-path-contribution analysis.

A novel formulation for transfer path identification and vibration prediction in the over-track building induced by trains.

Over-track buildings in metro depots become more and more prevalent in metropolis with the increase in population and the decrease of construction land. However, the train-induced vibration greatly reduces the comfort of occupants living in the over-track buildings. Owing to complex vibration sources and numerous transfer paths, it is a challenging task to analyze and predict the vibration characteristics accurately in the building. In this paper, a field measurement campaign of vibration was conducted in the Guanhu metro depot in Guangzhou, China. A novel formulation based on the operational transfer path analysis (OTPA) and singular value decomposition (SVD) is proposed to analyze the measured data and predict the train-induced vibration in the building. In this study, the vibration contributions from each transfer path to the target points in the building were obtained and the predominant transfer paths were identified further. Besides, the vibration at target points in the building was predicted using the vibration at path points and transmissibility functions from transfer paths. This study provides insights into the prediction and evaluation of vibration transmissions from vibration source to upper floors of over-track building.

Appropriate usage of multi-layered OTPA to identify intensive measuring part among sequential parts

Conducting effective countermeasure to the vehicle interior noise is important for compatible with the other vehicle performances such as light weight. Operational transfer path analysis (OTPA) was proposed to identify high contributing parts (OTPA reference model) and vibration behaviors (OTPA principal component model) to the interior noise with small man-hours. By using this method, we can determine which parts should be measured intensively. In case we apply the method to a vehicle body panel, the method tells us suitable measuring part of the body panel at the target frequency band. However, if the body panel is excited by a forced vibration from the suspension, we had better to apply countermeasure to the suspension. Then in this study, we applied the OTPA several times to identify which sequential parts from frame, body to interior noise makes the large noise using a simple plate model. In the analysis, both OTPA models (reference model and principal component model) were applied at various part and considered appropriate procedure of OTPA to obtain useful information for finding out the modification target part accurately. Through the verification test, the effectiveness of the proposed procedure was confirmed.

Operational transfer path analysis with regularized total least-squares method

Operational transfer path analysis (OTPA) uses only operational responses to characterize the paths, so it is efficient and widely used in various engineering fields. However, the operational responses are inevitably contaminated by errors, which seriously reduce the accuracy of OTPA. To reduce the influence of errors and improve the accuracy of OTPA, a Tikhonov regularized total least-squares method (RTLSM) which is based on the Tikhonov regularized least-squares method (RLSM) is used to estimate the transmissibility matrix, and then the individual contributions are calculated. The total least-squares method takes into account not only the influence of the errors in the target point responses but also the influence of the errors in the indicator point responses. Tikhonov regularization is introduced to regularize the total least-squares method to improve the ill-conditioning of the indicator point response matrix in the process of estimating the transmissibility matrix. An OTPA simulation on a lumped mass model and an OTPA experiment on an aluminum plate are studied to test the performance of the RLSM and RTLSM. Both simulation and experimental results show that the RTLSM is better than the RLSM in OTPA, and improved the accuracy of OTPA effectively.

Transfer Path Contribution to Floor Vibration of Metro Vehicles Based on Operational Transfer Path Analysis Method

Operational transfer path analysis (OTPA) is an advanced vibration and noise transfer path identification and contribution evaluation method. However, the application of OTPA to rail transit vehicles considers only the excitation amplitude and ignores the influence of the excitation phase. This study considers the influence of the excitation amplitude and phase, and analyzes the contribution of the secondary suspension path to the floor vibration when the metro vehicle runs at 60 km/h, using an analysis based on the OTPA method. The results show that the vertical direction of the anti-rolling torsion bar area provides the maximum contribution to the floor vibration, with a contribution of 22.1%, followed by the longitudinal vibration of the air spring area, with a contribution of 17.1%. Based on the contribution analysis, a transfer path optimization scheme is proposed, which may provide a reference for the optimization of the transfer path of metro vehicles in the future.

AR model-based crosstalk cancellation method for operational transfer path analysis

AR model-based crosstalk cancellation method for operational transfer path analysis

Estimation Method for Vehicle Interior Noise and Vibration Contribution Estimation by Operational and Component TPA

In this study, we proposed a method to estimate vehicle interior noise and vibration and identify the main contributing point efficiently by combining operational (OTPA) and component transfer path analysis (CTPA) methods. In the method, OTPA and CTPA were applied in the following three steps. In the first step, OTPA was applied to a vehicle model at the operational condition to obtain the contribution and transfer function from reference points to response point. In the second step, CTPA was applied to another motor placed on a test bench to obtain blocked force and estimate the reference point vibration on the vehicle model. Finally, the estimated reference point vibration was integrated into OTPA model, and the response point vibration was estimated in case the motor on the test bench was replaced to the vehicle model. Through the simple verification test using the vehicle model and test bench, the response point vibration was observed to be estimated accurately by the method. In addition, the high contributing motor mount point was also indicated correctly.

A customized scheme of crosstalk cancellation for operational transfer path analysis and experimental validation

To overcome crosstalk effects in operational transfer path analysis (OTPA) for effective identification and evaluation of vibration transfer path contributions based on measured response signals, a customized scheme of crosstalk cancellation for OTPA is proposed in this paper, which flexibly adopts different crosstalk cancellation methods for different path stages, and quantitatively evaluates transfer path contributions with high accuracy and efficiency. Firstly, the fundamental theories of OTPA and two crosstalk cancellation methods, prior transmissibility function-based method and independent component analysis (ICA) based method, are introduced. Secondly, an OTPA model is constructed for the test bed with shell structures, and the effects of airborne path contributions on OTPA is also analysed. Thirdly, the proposed customized scheme is applied to the two-stage transfer path of the test bed, and the vibration path contributions are comprehensively evaluated and analysed. Generally, this study proposes a flexible crosstalk cancellation scheme of OTPA for complex mechanical systems, which can provide reliable evidences for vibration and noise reduction and control.

On the resonance sound generated in a vehicle cabin moving at low speed due to breaking force

To improve the comfortability in a vehicle cabin, unwanted noise which is recognized as an allophone generated from automobile wheels was experimentally studied to investigate its generation mechanism and to develop its reduction countermeasures. In this experiment, simultaneous measurements of sound pressure and vibrational acceleration of the wheel surface were performed. Then, frequency analysis, vibrational modal analysis and operational transfer path analysis were performed by using measured data. The results show that this kind of noise started in a low frequency first and then became higher. Furthermore, the high-frequency noise was mainly generated by vibrational acceleration at its center and near the rim when the wheel spoke gets close to the brake caliper. The high-frequency noise is around 250Hz, 750Hz, 1000Hz and 1250Hz, and the wheel spoke easily gets vibration and resonance mainly from around 750Hz and 1000Hz. Vibration at 750Hz occurs on the side of the wheel spoke in the rotation direction, while vibration at 1000Hz occurs at the midpoint of the wheel spoke. The closer to the brake caliper, louder noise was generated at the wheel spoke.

OTPA method-based contribution analysis of components on the vibration of fuel cell in fuel cell vehicles

Due to the introduction of auxiliary components in fuel cell vehicle powertrains and absence of internal combustion engine, the vibration sources and transfer paths are very different from conventional vehicles. These vibrations interact on the output performance of the fuel cell system. Therefore, it is necessary to investigate the vibration characteristics of the fuel cell system under vehicle operating conditions. IPEK conducted vehicle measurements regarding different driving manoeuvres and environments. In order to quantitatively evaluate contributions of each vibration source on the total vibration of fuel cell, frequency-domain contribution was investigated based on Operational Transfer Path Analysis method with the singular value decomposition as well as principal component. The results of vibration in Z-direction in the vehicle coordinate system show that the hydrogen pump dominantly contributes to the vibration of fuel cell in a wide range of frequency in the majority of the driving manoeuvres. However, the results vary in various driving manoeuvres, environments and frequencies. The Paper will discuss in detail the vibrational contributions in X-, Y- and Z-direction.