Load characterization during transportation

Ramakrishnan, Arun; Pecht, Michael

doi:10.1016/s0026-2714(03)00189-6

Cited by 8 publications

(4 citation statements)

References 4 publications

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“…Based on the failure physical model generated under environmental stress, the prediction of electronic equipment can be realized. The "life consumption monitoring (LCM)" methodology of electronic products proposed by the University of Maryland is the main development direction at present [4,5]. LCM method flow chart is shown in figure 2, it mainly through early failure analysis to determine the failure physics model, and then use processing to detect the failure physical models were environmental stress information (such as outside temperature, humidity, pressure, vibration frequency), the calculation of monitoring equipment cumulative damage and estimate the residual service life of the equipment.…”

Section: Environmental/operational Stress Monitoring Methodsmentioning

confidence: 99%

ARMA-based fault prediction method for aviation digital equipment

Yang

Wen

et al. 2022

Seventh International Conference on Electromechanical Control Technology and Transportation (ICECTT 2022)

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Section: Environmental/operational Stress Monitoring Methodsmentioning

confidence: 99%

ARMA-based fault prediction method for aviation digital equipment

Yang

Wen

et al. 2022

Seventh International Conference on Electromechanical Control Technology and Transportation (ICECTT 2022)

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“…The vibration can be caused by the mechanical resonance of the ELF. Previous studies have reported that trucks exhibit mechanical resonance in the low-frequency range owing to their heavy mass and low rigidity (Hassan and McManus, 2002; Koayashi, 2012; Ramakrishnan and Pecht, 2004; Vanliem et al, 2020). Vibration negatively impacts yaw-rate control and the risk of cargo damage.…”

Section: Experimental Systemmentioning

confidence: 99%

“…The natural frequency of the vibration mode in a truck tends to be lower because of its mass and low rigidity (Soleimani and Ahmadi, 2014). In particular, large vibrations are known to occur at 1–3 Hz due to the unevenness of the road surface during the lateral control of the truck (Hassan and McManus, 2002; Koayashi, 2012; Ramakrishnan and Pecht, 2004; Vanliem et al, 2020). The control system can lose steering control through vibrations.…”

Section: Introductionmentioning

confidence: 99%

Compensation for low-frequency vibration in lateral control of truck by adaptive feed-forward cancellation

Yabui

Suzuki

Fukazawa

et al. 2023

Journal of Vibration and Control

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The role of truck transportation is becoming increasingly important in the growth of the e-commerce market. Self-driving trucks are being developed for efficient transportation. To realize a safe self-driving system, the control system should compensate for various vibrations while the truck is running. In the yaw direction, the mechanical resonance of the chassis suspension can cause low-frequency vibration. There are two approaches to compensate for the vibration. The first is a vibration control by using the truck suspension system. The method effectively compensates for vibration; implementing additional parts increases the cost. The second is vibration control based on the yaw-rate feedback control system. A notch filter or a lowpass filter decreases the gain at the vibration frequency and is effective in compensating for vibrations. The tracking performance of the reference signal can be degraded by decreasing the gain in the low-frequency range. Therefore, it is required that a solution can compensate for the vibration without the additional parts and no performance degradation. This paper proposes the use of an adaptive feed-forward cancellation (AFC) to compensate for low-frequency vibrations in the yaw-rate feedback control system. The AFC generates a compensation signal based on the difference between the reference signal and the actual yaw rate. The AFC does not reduce the gain near the vibration frequency; therefore, the AFC can achieve low-frequency vibration compensation while maintaining the tracking performance. In addition, the proposed control system does not require additional parts. The effectiveness of the proposed method was verified by experiments using an actual commercial truck.

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“…The life cycle loads (Table 1), either individually or in various combinations may lead to performance or physical degradation of the product and reduce its service life [30]. The extent and rate of product degradation depends upon the nature, magnitude, and duration of exposure to such loads.…”

Section: Introductionmentioning

confidence: 99%

Environment and Usage Monitoringof Electronic Products for Health Assessment and Product Design

Vichare

Rodgers²,

Eveloy³

et al. 2007

Quality Technology & Quantitative Management

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______________________________________________________________________Abstract: The life-cycle environmental and usage conditions of a product or system can be monitored and analyzed to assess its on-going health, provide advance warning of failure, and provide information to improve the design and qualification of fielded and future products. The challenge lies in the implementation of this method in application conditions. This paper presents methods to effectively collect and analyze life-cycle environmental and usage data for in-situ health assessments. An integrated hardware-software micro-programmable module for health and usage monitoring of electronic products in their application environment is presented. The hardware incorporates local sensors, and on-board processing power using embedded software. These data processing capabilities are intended to enable immediate and localized processing of the raw sensor data to reduce the power and memory consumption anticipated during load monitoring. Guidelines are also provided to develop a life cycle monitoring plan, that encompasses the selection of environmental and usage parameters. A case study is presented to illustrate the methodology.

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Load characterization during transportation

Cited by 8 publications

References 4 publications

ARMA-based fault prediction method for aviation digital equipment

ARMA-based fault prediction method for aviation digital equipment

Compensation for low-frequency vibration in lateral control of truck by adaptive feed-forward cancellation

Environment and Usage Monitoringof Electronic Products for Health Assessment and Product Design

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