Evaluation of human exposure to vibration in the hand-arm system during motorcycle riding activities

Abstract

BACKGROUND:

The majority of Indians prefer to drive by two-wheeler. Hands are the most important interface between the rider and bike while riding a motorbike. The vibration is transferred to the physical structure by the handlebar as it travels. Long-term exposure to the vibrations may have an impact on various bodily structures.

OBJECTIVE:

To measure and analyse the human exposure to vibration in the hand-arm system while riding a motorcycle using a vibrometer.

METHODS:

The several types of bikes based on their cc’s were evaluated in three different road conditions during this investigation (tar road, concrete road, and gravel road). The subjective and quantitative data of each participant were recorded. The RMS A(8) values were supported for every combination of motorcycles and road conditions, and vibration intensity was evaluated using a tri-axial vibrometer.

RESULTS:

The exposure limit value for daily vibration exposure is 5 m/s² according to the UK Control of Vibration at Work Regulations 2005 standards.This study suggests that the bike with the least amount of vibration be used to prevent hand-arm vibration (HAV) syndrome. This study found that bike C had the least vibration across all three types of roads, which will benefit riders by reducing health issues as they ride. Therefore, it is further examined utilising the Taguchi method with various bike C age groups. Bike C with the lowest age had the least vibration when different bike C ages were compared, hence it was recommended for riding.

CONCLUSION:

The vibration level of each bike has a huge impact, which was measured using a tri-axial vibrometer. According to the results, bike C has the least vibration across three distinct types of roads and also provides riders with less health issues while riding bikes. As a result, a moped can drive in three different road circumstances with the least amount of vibration, delivering comfort and safety while lowering vibration levels.

Keywords

Hand-arm vibration syndrome long-term exposure ergonomics

1 Introduction

Vibration is stated as a body’s repetitive motion or oscillation around an equilibrium point. It is a mechanical event that causes the body to be displaced from its equilibrium position. The Latin word “vibrationem” was used to develop the term vibration. The motion could be periodic or not. Vibrational comfort is closely linked to human perception and from an engineering point of view, is related to the level of vibration transmitted from vibrating objects to humans [1]. For instance, the oscillation of a pendulum or the movement of a tire on a rough surface, or the disturbance produced by an engine’s flywheel. These vibrations are due to engines inertia and combustion force, road induced vibration and improper structural designs and they are quiet varying with respect to speed, fuel supply [2]. The vehicle was discovered to tremble in an up and down motion. We can also sense vibrations in the seat, handlebar, and even the brake pedal [3]. Vibrations in motorcycles are caused by a low oil level in the engine as a result of insufficient lubrication, which generates excessive friction within the gears and produces shattering vibrations. Motorcycle riders currently risk plenty of health problems. Vibration affects millions of people each year [4]. Exposure to hand-arm vibration (HAV) can cause vascular, neurological and muscular symptoms in the hands and arms [5]. Knee ligaments, lower back pain, shoulder pain, meniscus injuries, calluses and blistus on the hands, and other issues are common among motorcycle riders. The vibration delivered to the rider’s hand from the motorcycle handlebar can cause discomfort and health problems [6]. HAV syndrome is brought on by an increase in hand and arm vibration. This syndrome affects the nerves, blood vessels, muscles and joints of the hand, wrist and arm [7]. The hand-arm vibration syndrome (sometimes abbreviated to HAVS) causes changes in the sensation of the fingers which can lead to permanent numbness of fingers, muscle weakness and, in some cases, bouts of white finger [8]. Vibration from the motorcycles handle bars may contribute to the cause of discomfort and pain symptoms in the hand-arm system of motorcycle riders that eventually led to road fatalities and accidents [9]. The purpose of this study was to see how much vibration was conveyed to the hand from a motorcycle handlebar. The vibration will have an adverse effect on the riders and passengers health while also causingdiscomfort.

Therefore the main objectives are to use a vibrometer to measure and analyse human exposure to vibration in the hand-arm system while riding a motorcycle. This study primarily examines human exposure to vibration in the hand-arm while riding motorbikes. Each bike vibrates at a different rate on the roads. Roads are often equal significance to motorcycle. In this study, three distinct types of road circumstances will be used to measure the vibration level on seven various engine cc’s bikes. Finding the hand-arm vibration and comparing it to the standards to see whether it falls within the permissible range is the main objective of this study. And then provide recommendations based on thefindings.

2 Materials and methods

Human vibration exposure was measured using the below mentioned technique. To begin, data on various motorbike cc’s and road conditions (tar road, gravel road, concrete road) were collected. There are two stages to the methodology. The initial step is to gather information from users through subjective or qualitative analysis. The user’s data were acquired using Google Forms. The second part is quantitative analysis, the analysis was done using tri-axial vibrometer (CESVA VC431), which has been used to assess the various motorcycles based on their cc’s in three different driving circumstances.

2.1 Subjective analysis

This is the first stage of this study, in which people’s opinions on motorcycles, types and health issues were gathered using Google Forms. These viewpoints served as the study’s primary data. People were given a questionnaire that included several easy questions such as the type of motorcycle they ride, the maximum distance and time they travel per day, health difficulties they face, and so on. Using this information, we were able to determine a number of characteristics, including the model of motorcycle that the users preferred. The subjective data collected from the users is displayed in the Collecting Data section.

Fig. 1

Methodology.

2.2 Quantitative analysis

This is the study’s second phase, in which real-time vibration data was obtained. The AC031 piezoelectric sensor was used to measure hand-arm vibrations as the first piezoelectric sensor. The AC031 sensor has been put in the motorcycle and is now connected to the vibrometer to collect data in real time.

The daily vibration exposure value, A(8), of the total acceleration value, expressed as the square root of the sum of the squares of the RMS value of acceleration with frequency weighting, determined according to the orthogonal axes ahx, ahy, ahz as defined in the ISO 5349-1 standard, is used to calculate the level of exposure to the vibration transmitted to the hand-arm system. These tests require the use of the CESVA AC031 tri-axial vibrometer.

The VC431 measures the following functions at the same time: The RMS (Root Mean Square) value of acceleration on the X-axis is ahx. The RMS value of acceleration on the Y-axis is ahy. The RMS value of acceleration is ahz on the Z-axis, while the overall amount of acceleration is ahv shown in equation 1. The expected daily vibration exposure limit is A(8)p, and the daily vibration exposure is A(8). $ahv = \sqrt \bar{{({ahw}_{x})}^{2} + {({ahw}_{y})}^{2} + {({ahw}_{z})}^{2}}$ (1)

The A(8) value was found using the following formula, where T is amount of time exposed to vibration and T0 refers to eight hours of exposure respectively shown in equation 2. $A (8) = ahv \sqrt \bar{({T / T}_{0})}$ (2)

When the equipment is in the record mode, but not in the measurement mode, the real-time data can only be saved. The information is saved in the equipment as registers that can be accessed at any time. The data in the equipment can be displayed in both numerical and graphical formats, making it easier to deduce the results at any moment.

2.2.1 CESVA VC431–tri-axial vibrometer

A tri-axial vibrometer is a device that measures vibrations for occupational health at the workplace and builds standards for minimizing the risk to human health of the measurement. For each application, it measures all parameters at the same time for hand, arm, whole body, buildings and structure.

The VC431 can also be used to assess the effects of vibration on structures like buildings. With a single level of assessment, all parameters for each application are displayed at the same time. The CESVA Capture Studio software can rapidly and conveniently download the measurements obtained with the VC431 and assess the results. It is the hand-held device of choice for analysing vibration issues because to its light weight, versatility, and convenience of use. The optimal equipment for measuring vibration risks resulting from worker exposure to vibration in accordance with Directive 2002/44/econ. The CESVA VC431 is depicted inFig. 2.

Fig. 2

CESVA VC431.

2.2.2 Operational accessories

The IEPE accelerometer is a tri-axial accelerometer that measures workplace vibration exposure through the hand-arm system. The hand-arm application uses the AC031 (shown in Fig. 3), and the accelerometer wire is 2.9 metres long.

Fig. 3

Adapter AC031.

2.2.3 CESVA Capture Studio

Capture Studio is a complete software application that allows you to manage all of the instrument’s variables on a single screen, collect and present data from the instrument in instantaneously, save registers from the equipment storage to a PC, clear the device memory show data files graphically and numerically, and convert them into other formats. CAPTURE Studio is a user-friendly environment for getting digital data from the instrument. CAPTURE Studio was created as a working environment for the latest range of CESVA product line. CESVA sound level meter, vibrometers, and dosimeters are software available.

2.2.4 Equipment setup

The piezoelectric sensor AC031 (hand-arm) was connected with the adaptor AA031 with the help of Philips screws, located at the bottom with x, y and z axes. After the sensor AC031 is mounted with the adapter AA031, then the adapter was placed in the left side of the handle bar as shown in Fig. 4 respectively. The vibration in the three axes x, y, and z was displayed in the display with the ahv, A(8), A(8)p, and the vibrometer automatically converted the short time data into eight hours data. When the experiment is finished, the data is saved in the equipment as registers.

Fig. 4

Experimental setup.

3 Results

In subjective analysis, the study was carried out on people between the ages of 20 and 30. In India, the majority of people ride motorcycles, with males being more likely than females to utilise public transport as their primary mode of transportation. Both opinions from male and female users were obtained with the total sample population of nearly 100 people. We found that male users are using more about 82% whereas female users are about 18%. The bike data and types of motorcycles are acquired from the bike riders. Motorcycles are used by many people for roughly 2 hours every day.57% of users are facing issues while riding motorcycle. Many people have pain in their shoulders, necks, elbows, and other areas. 54.9% of people drive all types of road. 44.9% of people feel vibration in handlebar when compared to seat and foot peg. Nearly everyone uses bikes with top-to-bottom cc’s (90–350cc), thus the vibration of those bikes has yet to be calculated on three distinct roads. The study’s final selection is seven cc motorcycles. The next stage is to ride these different cc’s motorcycles in three different road circumstances, gather real-time vibration data for HAV, and then use ANOVA to analyse the results and determine the importance of the motorcycle and road conditions.

The vibrometer was used to collect real-time data for each bike in various road conditions for quantitative study. The experiment was completed after the timer was set at 5 minutes. The reading time is set to 5 minutes because, when a motorcycle is driven at 20–30 km/hr, it typically covers a distance of 1.5 to 2.5 km. Despite this, the vibrometer still displays the reading for an 8-hour reference period, therefore 5 minutes is chosen for each bike. Data is collected and analyzed using CESVA Capture Studio software. Let’s have a look at the real-time data for the three combinations below.

The combination of bike C (125cc) vs tar road. Bike C (125cc) was driven for around 5 minutes on tar road, with the data displayed in Fig. 5. The projected vibration time is shown in the figure as A(8) at 5 minutes. The vibration level is indicated by A(8)p at 8 hours. A H vibration mode graph is coloured red for the y-axis, blue for the x-axis, and green for the z-axis. Additionally, three axes of vibration are displayed. The same is applicable forFigs. 6 and 7.

Fig. 5

Bike A(125cc) vs tar road.

Fig. 6

Bike E (160cc) vs concrete road.

Fig. 7

Bike C (125cc) vs gravel road.

The combination of bike E (160cc) vs concrete road. Bike E (160cc) was driven for around 5 minutes on a concrete road, with the data displayed inFig. 6.

The combination of bike C (125cc) vs gravel road. Bike C (125cc) was driven for around 5 minutes on a concrete road, with the data displayed in Fig. 7.

Data is gathered based on the different cc’s of bikes, the type of motorcycle, and the speed at which they are ridden in three different road conditions (Table 1).

Table 1

Details of the bikes

Bike name	Bike A	Bike B	Bike C	Bike D	Bike E	Bike F	Bike G
Bike cc	90	110	125	155	160	220	350

The levels of vibration and the types of motorcycles are compared. In three different roads, bike G shows the most vibration level when compared to the other bikes tested and is not suggested for riding, while bike C exhibits the lowest vibration level, as shown in Fig. 8.

Fig. 8

Comparison between types of bikes and vibration level.

4 Discussion

4.1 ANOVA: Vibration level versus bike cc, road type

At a significance level of 95%, the response variable is vibration intensity, and the ANOVA is used to evaluate if there is any significant difference between the two factors road condition and bike type. Vibration level has no effect on road conditions or bike type, according to the null hypothesis. Vibration level has an effect on road conditions and bike type, according to an alternative hypothesis. Minitab was used to solve the collected data.

ANOVA was conducted to check whether the vibration level has impact on road conditions and bike cc (Table 3). Bike cc and road conditions has significant impact over the vibration level. The model was found to be 92.80% fit. The normal probability plot in Fig. 9 illustrates that the data fits into a normal probability distribution.

Table 2
Data collection of the bikes

S. no Bike type Bike cc Driven speed Motorcycle Type of road Vibration

(Kmph) type condition level m/s²

1 Bike A 90 20–30 Moped Tar 3.5379

2 Bike A 90 20–30 Moped Concrete 3.6932

3 Bike A 90 20–30 Moped Gravel 4.528

4 Bike B 110 20–30 Moped Tar 2.806

5 Bike B 110 20–30 Moped Concrete 3.349

6 Bike B 110 20–30 Moped Gravel 3.8406

7 Bike C 125 20–30 Moped Tar 1.983

8 Bike C 125 20–30 Moped Concrete 2.377

9 Bike C 125 20–30 Moped Gravel 2.935

10 Bike D 155 20–30 Street sport Tar 2.912

11 Bike D 155 20–30 Street sport Concrete 3.270

12 Bike D 155 20–30 Street sport Gravel 4.911

13 Bike E 160 20–30 Standard Tar 2.317

14 Bike E 160 20–30 Standard Concrete 2.512

15 Bike E 160 20–30 Standard Gravel 3.498

16 Bike F 220 20–30 Street sport Tar 3.767

17 Bike E 220 20–30 Street sport Concrete 5.505

18 Bike E 220 20–30 Street sport Gravel 5.524

19 Bike F 350 20–30 Retro classic Tar 4.960

20 Bike F 350 20–30 Retro classic Concrete 5.020

21 Bike F 350 20–30 Retro classic Gravel 6.524

S. no	Bike type	Bike cc	Driven speed	Motorcycle	Type of road	Vibration
1	Bike A	90	20–30	Moped	Tar	3.5379
2	Bike A	90	20–30	Moped	Concrete	3.6932
3	Bike A	90	20–30	Moped	Gravel	4.528
4	Bike B	110	20–30	Moped	Tar	2.806
5	Bike B	110	20–30	Moped	Concrete	3.349
6	Bike B	110	20–30	Moped	Gravel	3.8406
7	Bike C	125	20–30	Moped	Tar	1.983
8	Bike C	125	20–30	Moped	Concrete	2.377
9	Bike C	125	20–30	Moped	Gravel	2.935
10	Bike D	155	20–30	Street sport	Tar	2.912
11	Bike D	155	20–30	Street sport	Concrete	3.270
12	Bike D	155	20–30	Street sport	Gravel	4.911
13	Bike E	160	20–30	Standard	Tar	2.317
14	Bike E	160	20–30	Standard	Concrete	2.512
15	Bike E	160	20–30	Standard	Gravel	3.498
16	Bike F	220	20–30	Street sport	Tar	3.767
17	Bike E	220	20–30	Street sport	Concrete	5.505
18	Bike E	220	20–30	Street sport	Gravel	5.524
19	Bike F	350	20–30	Retro classic	Tar	4.960
20	Bike F	350	20–30	Retro classic	Concrete	5.020
21	Bike F	350	20–30	Retro classic	Gravel	6.524

Table 3

ANOVA results

Source	DF	Adj SS	Adj MS	F-value	P-value
Bike cc	6	22.663	3.7771	20.34	0.000
Road type	2	6.459	3.2297	17.39	0.000
Errors	12	2.229	0.1857
Total	20	31.351

Fig. 9

Normal probability plot.

Among all bikes, bike C showed the minimal vibrations. So this motorcycle type is further tested and analyzed with different ages, road conditions and driven speed.

Data is collected based on the various sorts of bike C ages, motorbike type, and speed at which they are ridden in three different road conditions (Table 4).

Table 4

Bike C data collection

S. no	Bike name	Bike cc	Age	Driven speed	Motorcycle	Type of road	Vibration
					type	condition	level (m/s²)
1	Bike C	125	1	20–30	Moped	Tar	1.983
2	Bike C	125	1	20–30	Moped	Concrete	2.377
3	Bike C	125	1	20–30	Moped	Gravel	2.935
4	Bike C	125	5	20–30	Moped	Tar	3.339
5	Bike C	125	5	20–30	Moped	Concrete	3.493
6	Bike C	125	5	20–30	Moped	Gravel	5.118
7	Bike C	125	10	20–30	Moped	Tar	4.116
8	Bike C	125	10	20–30	Moped	Concrete	4.138
9	Bike C	125	10	20–30	Moped	Gravel	5.567

The Taguchi method’s crucial steps for parametric analysis are the selection of parameters and levels. The characteristics linked to elements that influence vibration exposure are taken into account in this study. The current study makes use of a L9 orthogonal array. The factors are listed in the table, along with their corresponding levels. Taguchi devised a unique orthogonal array architecture that allowed him to investigate the whole parameter space with a limited number of experiments. The results of the experiment are then converted into a signal-to-noise (S/N) ratio. In the analysis of the S/N ratio, there are three types of quality characteristics. For our study, vibration should be at a minimum, therefore the smaller the better.

Three parameters and three levels are examined in this study in order to achieve optimal operating parameters that will limit vibration exposure (Table 6).

Table 5

Field study at three factors and levels

Factor	Level 1	Level 2	Level 3
Bike age	1	5	10
Road type	1	2	3
Driven speed	20	25	30

Table 6

Field data using L9 orthogonal array

Bike age	Road type	Driven speed	Vibrations
			(m/s²)
1	1	20	1.983
1	2	25	2.512
1	3	30	2.935
5	1	20	3.339
5	2	25	3.493
5	3	30	5.118
10	1	20	4.116
10	2	25	4.138
10	3	30	5.567

4.2 Response table for signal to noise ratios

The Taguchi technique determines the critical parameters and calculates their quantitative influence on various quality aspects. The use of the S/N ratio strategy reduces the time it takes to analyse the results and, as a result, speeds up the time it takes to reach the conclusion illustrated in Fig. 10. Because the vibration level of motorcycles should be low, smaller is better is preferable. The rank is determined by the delta value; in our study, we examined bike age, road type, and driven speed, and found that the delta value for bike age is higher than for road condition and driven speed. The various plots of the s/n ratio are also displayed.

Fig. 10

S/N ratio result.

Table 7

Taguchi analysis: Vibrations versus bike age, road type and driven speed

Level	Bike age	Road type	Driven speed
1	–7.766	–9.569	–10.821
2	–11.839	–10.400	–11.128
3	–13.179	–12.816	–10.835
Delta	5.413	3.246	0.307
Rank	1	2	3

ANOVA was used to see if the vibration level had an effect on the type of road, the age of the bike, and the speed at which it was driven shown in Table 8. At a 95% confidence level, the bike’s age has a significant impact on the vibration level, whereas the road conditions and driving speed have little effect. The model was determined to be 97.30% accurate. The vibration level vs road type, bike age and driven speed interval plot is shown inFig. 11.

Table 8

Bike C ANOVA: Vibration level versus bike cc, road type and driven speed

Source	DF	Adj SS	Adj MS	F-value	P-value
Road type	2	3.3417	1.67087	11.26	0.082
Driven speed	2	0.1421	0.07105	0.48	0.676
Bike age	2	7.1973	3.59866	24.24	0.040
Errors	2	0.2969	0.14844
Total	8	10.9781

Fig. 11

Interval plot of vibration vs bike age, road type, driven speed.

The vibrometer was used to find A(8)p values for various combinations of experiments, which were then evaluated using the CESVA Capture Studio software, giving us greater insight into the vibration level. The exposure limit value for daily vibration exposure is 5 m/s² according to the UK Control of Vibration at Work Regulations 2005 standards [10]. Among all bikes, bike C showed the minimal vibrations. So it is further tested and analyzed with different ages, road conditions and driven speed. If the vibration level is higher above the minimum level, it can lead to both direct and indirect health problems. On the other side, there is a greater chance that producers will lose market share. For all combinations, the A(8)p vibration value.

According to Table 9, for the three road conditions listed above, Bike C bs6 vibration limit is actually lower than the standards. Bike C bs2 and bike C bs4 have higher vibration levels than the industry standard. In comparison to other bikes, bike C bs6 has the lowest vibration level in all types of road conditions, depending on the age. In comparison to the others, bike C bs2-Gravel road combination has the highest vibration level. The vibrations of the bike will rise as the age of the bike increases.

Table 9

Projected A(8) vibration values

S. no	Bikes	Road condition	A(8)p, vibration
			level(m/s²)
1	Bike C bs6	Tar road	1.983
2	Bike C bs6	Concrete road	2.512
3	Bike C bs6	Gravel road	2.935
4	Bike C bs4	Tar road	3.339
5	Bike C bs4	Concrete road	3.493
6	Bike C bs4	Gravel road	5.118
7	Bike C bs2	Tar road	4.116
8	Bike C bs2	Concrete road	4.138
9	Bike C bs2	Gravel road	5.567

In a previous study, Jalil et al. recorded the vibration for the riders hand in static condition. The gear of the motorcycles was not engaged throughout the experiment [11]. The engine speeds for motorcycle speed of 10 km/h and 20 km/h were selected in their study to ensure that the subjects were not being exposed to high noise level due to the speed of the engine during the experiment. It indicates that a person, who is using motorcycle for more than four hours per day, could have a risk of obtaining HAV syndrome. The level of vibration exposure is however, expected to be less than the action limit value if the motorcycle is used for less than two hours per day. The vibration that is transmitted to the hand should be monitored especially on riders who are using for more than two hours per day. Only two roads were taken into consideration by Mohamad et al. when assessing hand-arm vibration exposure while riding a motorcycle [12].

In present study, three separate roads were used to dynamically evaluate the vibration of each motorcycle. Considering this study, the bike with the lowest vibration intensity is recommended to prevent HAV syndrome.

This study was done to determine the hand-arm vibration on three distinct roads at a speed of 20 to 30 km/hr for motorcycles from top to bottom cc’s. Then the UK advised that the exposure vibration limit should exceed 5 m/s² in accordance with control work regulations. Out of all bikes, bike C vibrated the least on all three roads. Then, according to bike C its ages, it is once more grouped using the Taguchi method. When different bike C ages were examined, the one with the fewest age had the least vibration and was recommended for riding.

The scientific literature is relatively inconsistent, but it does suggest that the vibration on the motorcycle’s handlebar can be of a magnitude that can cause HAVS, according to an information note from the Industrial Injuries Advisory Council of the United Kingdom [13]. The different handlebars mounts are not effective in the reduction of vibration. The methods for reducing the vibration increase the exposure at high frequencies, thus increasing the risk of HAVS [14]. So the bike with minimal vibration will reduce the risk of HAV syndrome.

5 Conclusion

Vibration from the handlebar of the motorcycle can be reduced by using gloves but it may not be effective to use glove on the finger compared to the palm [15]. Therefore, wearing gloves will not reduce the rider’s exposure to vibration. The vibration level of each bike has a major impact, which was measured using a vibrometer. According to the results, bike C has the least vibration in three types of roads and also provides riders with less health difficulties while riding bikes. Furthermore, it reduces the HAV Syndrome. Overall, this bike can be ridden in three distinct road conditions with the least amount of vibration, delivering comfort and safety while lowering vibration levels. Other types of bikes did not meet the guidelines, thus they are not recommended for user comfort and safety, and they are more likely to cause health problems.

Manufacturers can utilize their R&D solutions to increase ergonomic aspects, making their goods more user-friendly and directed. They can, for example, improve suspension, frame, and engine design to lower vibration levels in order to increase sales while also supplying users with high-quality products.

As one of the world’s major manufacturers and consumers of motorcycles, it’s critical to consider vibration as one of the essential parameters to consider in order to prevent user fatigue and health issues and to live a safe and healthy life.

The present study has a few limitations, including the use of a rider to drive all motorbikes on three different roads and the calculation and analysis of only hand-arm vibration. Future studies should be carried out to compute and analyse the hand-arm vibrations of various cc bikes at varies ages and riding speeds. Further analysis should be done for each bike’s exposure to whole-body vibration. Moreover, a comparison of how much vibration people experience while riding a motorcycle in their hands, arms and entire bodies should be carried out.

Footnotes

Acknowledgments

The authors have no acknowledgments.

Ethical approval

Not applicable.

Informed consent

Not applicable.

Conflict of interest

The authors declare that they have no conflict of interest.

Funding

The DST - Fund for Improvement in Science and Technology Infrastructure (FIST 2000) – supported the Vibrometer VC431 instrument used in this study (Project No.SR/FST/ETI-310 /2012).

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