The effects of a back belt on posture, strength, and spinal compressive force during static lift exertions

The experiment reported in this paper evaluated changes in lifting posture, static lifting strength and the estimated L3/L4 spinal compressive force resulting from the use of an abdominal support or ‘back' belt. Torso posture and maximum static lift strength were measured for eight male and eight female subjects using symmetric and asymmetric hand positions at calf height and elbow height. Body posture, and hand forces were also used as input to a three-dimensional static biomechanical model of the torso used to estimate L3/L4 spinal compressive force. The results showed axial twist of the torso to be significantly lower for calf height asymmetric exertions when the abdominal support belt was worn. The measured reduction in axial twist was approximately four degrees. No other significant effects on posture due to the support belt were found. Static lift strength was not significantly increased or reduced when the support belt was used. Predicted spinal compressive force was significantly lower when a support belt was worn (2840 N compared to 3125 N when the belt was not worn). Overall, the results of the experiment demonstrate a very limited benefit to the user of abdominal support belts, primarily due to reduced or restricted motion during asymmetric and lower-level lifts.Relevance to industryBack belts are commonly used in industry to mitigate manual materials handling hazards. One assumption often made by those recommending the use of back belts is that they substantially reduce the bending and twisting of the torso. The experiment reported in this paper tests this assumption and provides information on the utility of back belts.     

A study on the subjective feeling affecting tactile satisfaction of leather in automobile: A structural equation modeling approach

Customer expectations for automotive design are increasingly rising, which plays an important role in purchasing behavior. Among them, automobile interior materials are one of the factors that have a significant influence on the overall luxuriousness and satisfaction of automobiles. One of the main affective responses to automotive interior materials is a tactile sensation, and since it is complexly constructed, systematic modeling is required. The current research proposed and tested a structural equation model (SEM) that describes hypothesized relationships among affective variables affecting tactile satisfaction such as luxury, soft, slippery, smooth, bumpy, and thick. A total of 26 samples including natural and synthetic leather using interior material in an automobile was selected as a stimulus to recruit 53 participants. All affective variables were found to affect luxuriousness that subsequently affected tactile satisfaction (path coefficient = 0.652). In particular, perceived softness was a dominant factor affecting tactile luxuriousness in leather (path coefficient = 0.305). The findings of the present study have significant implications for both theory and practice on affective responses and levels that affect tactile satisfaction in leather using automobile interior.     

基于SVM和RBFN的汽车主动降噪系统传感器故障诊断

汽车主动降噪系统的工作依赖于多个噪声传感器,一旦传感器发生故障,将严重影响降噪效果。为保证汽车主动降噪系统的性能,提出了由支持向量机(SVM)预测模型和径向基神经网络(RBFN)预测模型构成的传感器故障诊断系统,SVM模型判断是否发生传感器故障,RBFN模型则利用各传感器间的信息冗余关系定位故障传感器并对其信号进行重构。仿真结果表明,该诊断系统可有效实现汽车主动降噪系统中的传感器故障诊断及信号重构。与传统的汽车主动降噪系统相比,引入传感器故障诊断系统可保证更稳定的降噪性能。