Force modelling of the crankshaft pin grinding process.

A force model was developed for crankshaft pin grinding to predict the forces generated during grinding. The force model developed builds on the authors’ previously developed model, which predicted the out-of-roundness in crankshaft pin grinding. The model includes key grinding variables, such as the work removal parameter (WRP), system sti€ ness and Young’s modulus to determine the end forces produced. The model also includes the important geometrical relationships that are unique to this type of grinding. The model was veriŽ ed using an experiential set-up involving sophisticated strain gauge force measurements on a commercial Landis CP grinding machine, with close correlation between the results and the model.

Reliability of normalisation methods for EMG analysis of neck muscles

Acceptable reliability of normalisation contractions in electromyography (EMG) is paramount for testing conducted over a number of days or if normal laboratory strength testing equipment is unavailable. This study examined the reliability of maximal voluntary isometric contractions (MVIC) and sub-maximal (60%) isometric contractions for use in neck muscle EMG studies. Surface EMG was recorded bilaterally from eight sites around the neck at C4/5 level from five healthy male subjects. Subjects performed MVIC and sub-maximal normalisation contractions using an isokinetic dynamometer (ID) and a portable cable dynamometer with attached strain gauge (PCD) in addition to a MVIC against a manual resistance (MR). Subjects were tested in flexion, extension, left and right lateral bending and were retested by the same tester within a two-week period. Intra class correlation co-efficients (ICC) were calculated for each testing method and contraction direction and a mean ICC was calculated across all contraction directions. All normalisation methods produced excellent within-day reliability (mean ICC >0.80) but only the MVICs using the ID and PCD had acceptable reliability when assessed between-days. This study confirmed the validity of using MVICs elicited using the ID and PCD as reliable reference contractions for the normalisation of neck EMG.

Computer aided ultrasonic thickness strain analysis of automotive sheet metal stampings using FEA information

This paper discusses a computer-aided methodology for thickness strain analysis (TSA) of sheet metal stampings using geometry and strain information that is extracted from finite element analysis (FEA) results. The system utilises both FEA results and an ultrasonic gauge capability expert system to assist press shop personnel, providing them with capabilities such as optimum measurement point location and an estimate of gauge error. Key advantages of this enhanced TSA methodology are related to overall efficiency and accuracy gains.

Knitted strain sensor textiles of highly conductive all-polymeric fibers

A scaled-up fiber wet-spinning production of electrically conductive and highly stretchable PU/PEDOT:PSS fibers is demonstrated for the first time. The PU/PEDOT:PSS fibers possess the mechanical properties appropriate for knitting various textile structures. The knitted textiles exhibit strain sensing properties that were dependent upon the number of PU/PEDOT:PSS fibers used in knitting. The knitted textiles show sensitivity (as measured by the gauge factor) that increases with the number of PU/PEDOT:PSS fibers deployed. A highly stable sensor response was observed when four PU/PEDOT:PSS fibers were co-knitted with a commercial Spandex yarn. The knitted textile sensor can distinguish different magnitudes of applied strain with cyclically repeatable sensor responses at applied strains of up to 160%. When used in conjunction with a commercial wireless transmitter, the knitted textile responded well to the magnitude of bending deformations, demonstrating potential for remote strain sensing applications. The feasibility of an all-polymeric knitted textile wearable strain sensor was demonstrated in a knee sleeve prototype with application in personal training and rehabilitation following injury.

Strain sensors with adjustable sensitivity by tailoring the microstructure of graphene aerogel/PDMS nanocomposites

Strain sensors with high elastic limit and high sensitivity are required to meet the rising demand for wearable electronics. Here, we present the fabrication of highly sensitive strain sensors based on nanocomposites consisting of graphene aerogel (GA) and polydimethylsiloxane (PDMS), with the primary focus being to tune the sensitivity of the sensors by tailoring the cellular microstructure through controlling the manufacturing processes. The resultant nanocomposite sensors exhibit a high sensitivity with a gauge factor of up to approximately 61.3. Of significant importance is that the sensitivity of the strain sensors can be readily altered by changing the concentration of the precursor (i.e., an aqueous dispersion of graphene oxide) and the freezing temperature used to process the GA. The results reveal that these two parameters control the cell size and cell-wall thickness of the resultant GA, which may be correlated to the observed variations in the sensitivities of the strain sensors. The higher is the concentration of graphene oxide, then the lower is the sensitivity of the resultant nanocomposite strain sensor. Upon increasing the freezing temperature from −196 to −20 °C, the sensitivity increases and reaches a maximum value of 61.3 at −50 °C and then decreases with a further increase in freezing temperature to −20 °C. Furthermore, the strain sensors offer excellent durability and stability, with their piezoresistivities remaining virtually unchanged even after 10 000 cycles of high-strain loading−unloading. These novel findings pave the way to custom design strain sensors with a desirable piezoresistive behavior.