Noise Reduction Method for Running TPA Using Significance Probability

Noumura, Kousuke

doi:10.1299/jsdd.5.1572

Cited by 4 publications

(8 citation statements)

References 3 publications

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“…In the first step, the transfer function from the reference point to the response point is calculated using various operational data measured at the reference and response points. In the second step, each contribution is obtained by multiplying the reference point signal by the calculated transfer function (2), (12), (14) . The transfer function in this method is calculated using a principal component regression method.…”

Section: Target Level Setting Methods For Reference Signals 21 Procementioning

confidence: 99%

“…The accuracy of the transfer function is increased by reducing the noise PC, which is generated by the measurement noise depending on the measurement condition. The amplitude or the significance probability of each PC is used to extract the noise PC (12) . The contribution to the response signal from each reference signal [A out cont ] can be obtained by multiplying the measured reference signal [A in ] by the calculated transfer function [H]:…”

Section: Target Level Setting Methods For Reference Signals 21 Procementioning

confidence: 99%

“…Moreover, several orthogonal vibration modes, which are excited during operation, are included in the measured reference signals. Hence, an orthogonal principal component is considered to be the same as a vibration mode excited during operation (12), (14) . The target setting method using the principal component can obtain the target levels of reference signals considering the relationship among reference signals.…”

Section: Target Setting Using the Principal Componentsmentioning

confidence: 99%

“…Selecting a principal component having the maximum contribution to the response signal, and calculating the level of the response point signal after the principal component is reduced by a certain amount (e.g., 0.5 dB) using Eq. (12).…”

Section: Target Setting Using the Principal Componentsmentioning

confidence: 99%

“…Operational TPA is a recently developed TPA method that enables the contributions to be obtained in a few man-hours because this method requires only sound pressure or vibration acceleration data during operation, and does not require an impulse hammering test in order to obtain transfer functions (2) . A number of studies on operational TPA have examined theoretical verification and application examples in vehicle development (3) - (10) , as well as assessing the accuracy and possible improvement methods for such techniques (12), (14) .…”

Section: Introductionmentioning

confidence: 99%

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Target Level Setting Method for the Reference Signal of Operational TPA

Yamashita

2013

JSDD

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In the present study, a target level setting method for the reference signal of operational TPA was considered using the principal component regression method. A principal component having a high contribution to the response signal was selected and target levels of the reference signals were set through principal component sensitivity analysis. In addition, a method that can extract the behavior of a principal component having a high contribution to the response signal was considered for the countermeasure. In order to verify the effectiveness of these methods, operational TPA and the proposed methods were applied to a small model vehicle. In the experiment, floor vibration was set as the response signal and nine measurement points, such as motor attachment points, were used as the reference signals. Here, we set the target reduction level of the response point vibration as 5 dB. Next, the target levels of the reference signal were calculated by principal component sensitive analysis and the countermeasure was considered through the principal component behavior analysis. By referring to the analytical result, a countermeasure to reduce the floor vibration was sought. As a result, the floor vibration level was almost reduced to the target level (5 dB). These considerations and experiments indicate that operational TPA could have additional functionality, whereby the method could set reference signal targets and suggest countermeasure guidelines in addition to performing contribution separation.

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Section: Target Level Setting Methods For Reference Signals 21 Procementioning

confidence: 99%

Section: Target Level Setting Methods For Reference Signals 21 Procementioning

confidence: 99%

Section: Target Setting Using the Principal Componentsmentioning

confidence: 99%

Section: Target Setting Using the Principal Componentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Target Level Setting Method for the Reference Signal of Operational TPA

Yamashita

2013

JSDD

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Consideration and Verification of Accuracy Evaluation Indices for Operational TPA

Onishi

Narita

2012

JSDD

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In this study, we considered accuracy evaluation indices for operational transfer path analysis (TPA) that employs the principal component regression method, and we verified their reliability. To evaluate the accuracy of TPA, the consistency of the response signals, in which the calculated response signal from the TPA model is compared with the measured response signal, has been frequently used in the past. Also, some cases use the condition number that indicates the inverse matrix condition used in the calculation procedure of the acceleration transfer function. In addition to these accuracy evaluation indices, a correlated principal component number (CPCN), which indicates the number of principal components that correlate with the response signal generated at the running test, has been proposed. The reliability of these accuracy evaluation indices has been verified through a simple simulation. The results show that the two conventional indices (the consistency method and the condition number) do not satisfactorily evaluate the accuracy. However, a CPCN can indicate the frequency bands where the TPA accuracy is high or low. Consequently, the new index was found to be a suitable index for evaluating the accuracy of the operational TPA.

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Improvement of Bicycle Riding Comfort by Reduction of Seat Vibration

Kawagoe

Kawamura

2013

JSDD

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Bicycles are popular with the general public because of their low price and easy maintenance, and they will be an important vehicle in the future because of their low environmental load. Improving the comfort of the ride is one of the important factors that will lead to increased popularity. We attempted to increase comfort by reducing vibration, and evaluated the results with a subjective test. We determined that low frequency vibration of the seat greatly affected the comfort of the ride. We then performed a transfer path analysis (TPA) and a hammering test to investigate how the vibration characteristics of the bicycle affected the vibration of the seat. Through TPA, the rear of the bicycle frame was found to have a high influence on the seat vibration, and the vibration behavior was obtained by modal analysis. In order to reduce seat vibration, a spring was inserted in the front of the seat and, to increase the stiffness, a steel plate and bolts were attached to the rear of the frame. As a result, the seat vibration while riding was decreased by about 10 dB, and the comfort of the ride was greatly improved.

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Noise Reduction Method for Running TPA Using Significance Probability

Cited by 4 publications

References 3 publications

Target Level Setting Method for the Reference Signal of Operational TPA

Target Level Setting Method for the Reference Signal of Operational TPA

Consideration and Verification of Accuracy Evaluation Indices for Operational TPA

Improvement of Bicycle Riding Comfort by Reduction of Seat Vibration

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