A wearable low-cost device for measurement of human exposure to transmitted vibration on motorcycle

The comfort experienced driving a motorcycle is becoming a subject of great importance, indeed, the driver is exposed to vibrations, which in some cases may cause troublesome problems. The vibrations, during the driving of a motorcycles, are caused by irregular profiles of the road surface or by the wear of the latter; these conditions, unfortunately, are present in almost all the driving conditions, reason why each driver is exposed to it. The aim of the paper is to give the opportunity for the driver to know the exposure to the vibration during a ride using a low-cost wearable device (smart watch) considering the suggestion of the ISO 5349 for the calculation of the hand transmitted vibrations index. A suitable measurement system has been designed and tested on a real motorcycle in order to acquire in real-time the acceleration signals through a Bluetooth communication, which interface a wearable device with a microcontroller unit useful to calculate the hand transmitted vibrations index suggested by the ISO 5349 and store it into a data logger.

[1]  Paolo Sommella,et al.  ANN-based IFD in motorcycle rear suspension , 2017 .

[2]  Vincenzo Paciello,et al.  Velocity prediction from acceleration measurements in motorcycle suspensions , 2017, 2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[3]  K. Krajnak Health effects associated with occupational exposure to hand-arm or whole body vibration , 2018, Journal of toxicology and environmental health. Part B, Critical reviews.

[4]  Antonio Pietrosanto,et al.  Real-time implementation of an IFD scheme for motorcycle sensors , 2018, 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[5]  Vincenzo Paciello,et al.  Measuring suspension velocity from acceleration integration , 2018, 2018 IEEE 16th International Conference on Industrial Informatics (INDIN).

[6]  Antonio Pietrosanto,et al.  Analytically Redundancy Based IFDI Scheme for Semi-Active Suspension Systems in Motorcycle , 2018 .

[7]  Antonio Pietrosanto,et al.  Online Fault Detection of Rear Stroke Suspension Sensor in Motorcycle , 2019, IEEE Transactions on Instrumentation and Measurement.

[8]  Michael J. Griffin,et al.  Handbook of Human Vibration , 1990 .

[9]  Karen Jackson,et al.  Rotorcraft Full Spectrum Crashworthiness and Occupant Injury Requirements , 2011 .

[10]  Vincenzo Paciello,et al.  Real-Time Detection of Low-Frequency Components , 2013, IEEE Transactions on Instrumentation and Measurement.

[11]  Ying Yang,et al.  Modeling and Simulation of Motorcycle Ride Comfort Based on Bump Road , 2010 .

[12]  Vincenzo Paciello,et al.  Characterization of motorcycle suspension systems: Comfort and handling performance evaluation , 2013, 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[13]  Vincenzo Paciello,et al.  Semi-active suspension system for motorcycles: From the idea to the industrial product , 2018, 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[14]  O. Sename,et al.  Survey and performance evaluation on some automotive semi-active suspension control methods: A comparative study on a single-corner model , 2012, Annu. Rev. Control..

[15]  M. Griffin,et al.  EVALUATION OF WHOLE-BODY VIBRATION IN VEHICLES , 2002 .