Wireless Vibration Monitoring on Human Machine Operator

SCVT 2010 – IEEE Symposium on Communications and Vehicular Technology in the Benelux

1

Abstract—Human machine operators are often subject to

extreme shocks and vibrations while operating production machines and vehicles. To assess the impact on perceived comfort objectively, a wireless vibration monitoring system is needed that measures whole-body vibrations directly on the human body. To this end, we have developed a wireless body area network consisting of low-power vibration sensor nodes that have a small and ergonomic form factor and that are easy to install. Furthermore, we have validated the BAN along with the necessary post-processing of the raw vibration signals on a real industrial case, i.e. the driver of a forklift. Our system proves to be instrumental in optimizing critical tuning parameters of a machine, exemplified by the transmission control parameters of a forklift.

Index Terms—Personal and body area networks, Wireless condition monitoring, Whole-body vibration, Health and comfort, Forklift.

I. INTRODUCTION

OR many production machines and vehicles, their human machine operators (or passengers) are subject to extreme

shocks and vibrations during operation. Examples of such machines are forklifts, bulldozers, pneumatic hammers, drill hammers, trains [1][2], combine harvesters and tractors [3][4]. To safeguard human health, regulations such as the EU Vibrations Directive (2002/44/EC [5]) impose strict quota for these vibrations, making a distinction between hand-arm and whole-body vibrations. The measurement of whole-body vibration is defined in the ISO 2631 standard [6], which also specifies the impact of whole-body vibrations on human health and comfort.

Compliance with the regulations and the comfort for the operator is currently checked by defining a number of typical application scenarios and by having the human operator to score between 1 and 10 on perceived comfort. Given the very subjective nature of such an approach with observations

F. Petré, S. Gillijns, and M. Engels are with the Flanders’ Mechatronics

Technology Centre (FMTC), Celestijnenlaan 300D, B-3001 Leuven, Belgium (phone: +32-16-328053; fax: +32-16-328064; e-mail: [email protected]).

F. Bouwens, F. Massé, and B. Gyselinckx are with the Holst Centre / IMEC-NL, High Tech Campus 31, 5656 AE Eindhoven, The Netherlands (e-mail: [email protected]).

K. Vanstechelman, and C. Thomas are with the Spicer Off-Highway Product Division of Dana Holding Corporation, Ten Briele 3, B-8200 Brugge, Belgium (e-mail: [email protected]).

largely varying across different operators, it is very hard to obtain objective measures and hard facts. This often leads to “endless” discussions between a supplier of certain equipment (e.g. transmission controller software, mechanics, hydraulics) and its customer (e.g. OEM of forklifts) on perceived quality and comfort.

To increase the objectivity of compliance and comfort testing, a clear need exists for a wireless monitoring system that measures whole-body vibrations directly on the body of the human operator. The main benefit of a wireless solution is that it allows measuring on the right place, i.e. on the human body, while avoiding the hassle, the limitations on mobility or freedom of movement, and the installation effort associated with a cabled solution. For a pure monitoring scenario, it is anticipated that the system will be used for registration of a human machine operator’s total exposure to whole-body vibrations, much in the same way as total radiation exposure is being monitored in nuclear power plants.

Commercial wireless whole-body vibration measurement systems are limited to single seat sensors [7]. According to the ISO 2631-1 standard [6], this is sufficient for health assessments but not for perceived comfort. For comfort measurements, accelerations from multiple locations must be combined. We found a preliminary version of a wireless sensor network to measure vibrations on operators [8], but this network has a lot of limitations (e.g. high power consumption, large size, no real-time data transmission) and was clearly not yet industry-ready. Recently, Inertia Technology [9], a spin-off of the University of Twente, has engaged in the commercialization of wireless motion sensors, building further on the PhD dissertation of Marin-Perianu [10]. Because the nodes are based on a multi-sensor inertial platform, including gyroscopes, the energy autonomy is limited. Finally, as the measurement systems are not available, no work is reported on the analysis of the influence of machine parameters on comfort.

In this paper, we demonstrate the technical feasibility of wireless vibration monitoring for health and comfort on a human machine operator. To this end, we have developed a body area network (BAN) consisting of 4 sensor nodes that can each measure 3D linear accelerations. The sensor nodes are low-power, have a small and ergonomic form factor and are easy to install. Furthermore, we have created an offline post-processing tool for calculating the whole-body vibration from the raw vibration measurements. Finally, we have

Wireless Vibration Monitoring on Human Machine Operator

Frederik Petré, Frank Bouwens, Steven Gillijns, Fabien Massé, Marc Engels, Bert Gyselinckx, Kris Vanstechelman, and Christophe Thomas

F


validated the BAN and the post-processing tool on a real industrial case, i.e. the driver of a forklift, by identifying the relation between whole-body vibration and critical design and tuning parameters of the forklift.

Our paper is organized as follows. Sectionmeasurement and evaluation of wholeaccording to the ISO 2631-1 standard. Sectionthe BAN along with its sensor nodes that we have developed for performing wireless vibration measurements on a human operator. Section IV analyzes the measurement results we have obtained from an in-field test campaign on a forklift driver. Finally, Section V summarizes our major conclusions.

II. STANDARD EVALUATION OF WHOLE

We have evaluated the exposure of the human driver of a forklift to whole-body vibration according to the ISO 2631 standard [6]. This standard defines methods of quantifying whole-body vibration in relation to (i) humancomfort and probability of vibration perception; and (iii) incidence of motion sickness. The focus of the standard is on periodic, random and transient wholeexcluding extreme-magnitude single shocks. The frequency spectrum of interest ranges from 0.5 Hz to 80 Hz for evaluating the impact on health, comfort and perception; and from 0.1 Hz to 0.5 Hz for evaluating the impact on motion sickness.

In the next subsections, we will briefly discuss the standard’s guidelines on vibration measurement and vibration evaluation, respectively.

A. Vibration Measurement

In this subsection, we briefly review the standard’s main guidelines towards measuring wholeincluding the location and direction of measurement as well as some general requirements for signal conditioning.

The primary quantity of vibration magnitude is acceleration, which should be measured at the interface between the human body and the source of vibration. For seated persons, as is the case for the driver of a forklift, there are three principal locations of measurement, i.e. the supporting seat surface, the seat back and the feet (see Figure 1). More specificmeasurements on the supporting seat surface should be performed beneath the ischial tuberosities (also known as the sitz bone). Measurements on the seatperformed in the area of principal support of the body. Measurements at the feet should be performed on the surface on which the feet are most often supported.

Communications and Vehicular Technology in the Benelux

processing tool on a real industrial case, i.e. the driver of a forklift, by identifying the

body vibration and critical design and

Section II reviews the ation of whole-body vibration

Section III describes along with its sensor nodes that we have developed

wireless vibration measurements on a human analyzes the measurement results we

field test campaign on a forklift summarizes our major conclusions.

HOLE-BODY V IBRATION

We have evaluated the exposure of the human driver of a body vibration according to the ISO 2631

. This standard defines methods of quantifying body vibration in relation to (i) human health; (ii)

comfort and probability of vibration perception; and (iii) incidence of motion sickness. The focus of the standard is on periodic, random and transient whole-body vibration

magnitude single shocks. The frequency interest ranges from 0.5 Hz to 80 Hz for

evaluating the impact on health, comfort and perception; and from 0.1 Hz to 0.5 Hz for evaluating the impact on motion

In the next subsections, we will briefly discuss the n measurement and vibration

In this subsection, we briefly review the standard’s main guidelines towards measuring whole-body vibrations, including the location and direction of measurement as well as

eneral requirements for signal conditioning. The primary quantity of vibration magnitude is acceleration,

which should be measured at the interface between the human body and the source of vibration. For seated persons, as is the

orklift, there are three principal locations of measurement, i.e. the supporting seat surface, the

). More specifically, measurements on the supporting seat surface should be performed beneath the ischial tuberosities (also known as the

bone). Measurements on the seat-back should be performed in the area of principal support of the body.

hould be performed on the surface on which the feet are most often supported.

Figure 1. Measurement locations and directions for a seated person

The direction of measurement should be according to a basicentric coordinate system originating from a point where whole-body vibration is considered to enter the human body. This is illustrated in Error! Reference source not found.The sensitive axes of the vibration transducer may deviate from the preferred axes by up to 15°.

The standard also imposes three general requirements for signal conditioning. First, the vibration transducer and the associated signal conditioning prior to signal processing should be appropriate to the range of frequencies. Second, the dynamic range of the signal conditioning should be adequate for the highest and signals. Third, a low-pass filter can be applied with a cutfrequency (-3 dB) of approximately 1.5 times the highest frequency of interest, namely 120 Hz, and a phase characteristic that is linear within the range of frequencies.

B. Vibration Evaluation

In this subsection, we briefly summarize the standard’s approach towards evaluating wholemeasurements. The basic evaluation method uses sofrequency-weighted root-meanBefore calculating the RMS acsignal is filtered with the appropriate frequency weighting. The frequency weighting emphasizes certain parts of the spectrum while de-emphasizing others. The principal frequency weightings Wd, Wk

2.

Figure 2. Principal frequency

2

locations and directions for a

seated person [6]. The direction of measurement should be according to a

basicentric coordinate system originating from a point where body vibration is considered to enter the human body.

Error! Reference source not found.. The sensitive axes of the vibration transducer may deviate from the preferred axes by up to 15°.

The standard also imposes three general requirements for signal conditioning. First, the frequency response of the vibration transducer and the associated signal conditioning prior to signal processing should be appropriate to the range of frequencies. Second, the dynamic range of the signal conditioning should be adequate for the highest and lowest

pass filter can be applied with a cut-off 3 dB) of approximately 1.5 times the highest

frequency of interest, namely 120 Hz, and a phase characteristic that is linear within the range of frequencies.

In this subsection, we briefly summarize the standard’s approach towards evaluating whole-body vibration measurements. The basic evaluation method uses so-called

mean-square (RMS) accelerations. Before calculating the RMS acceleration, the acceleration time signal is filtered with the appropriate frequency weighting. The frequency weighting emphasizes certain parts of the

emphasizing others. The principal Wk and Wf are illustrated in Figure

frequency weightings [6].


The applicability of the basic evaluation method depends on the so-called crest factor of the frequencyacceleration signal, which is defined by the standard as the modulus of the ratio of the maximum instantaneous peak of the frequency-weighted acceleration signal to its RMS value. The basic evaluation method is applicable for vibrations with a crest factor at most equal to 9, hence excluding the presence of extreme-magnitude single shocks. For signals with a crest factor larger than 9, the basic evaluation method is not sufficient and additional methods are needed for adequate evaluation, such as the running RMS method, the fourth power vibration dose method and ratios used for comparison of the basic and additional evaluation methods. In this work, however, we have exclusively used the basic evaluation method, since this proved to be sufficient for most of our measurements (see Section IV).

Once the frequency-weighted RMS accelerations have been determined in the three orthogonal directions, they should be combined into a single RMS value for that location. The total vibration value of the weighted RMS acceleration is calculas follows:

akaka wyywxxv

2222 ⋅+⋅=where awx, awy, awz, are the weighted RMS accelerations with respect to the orthogonal axes x, y, z, respectively, and kz, are the multiplying factors.

To investigate the effects of periodic, random and tranvibration on the health of persons in normal health condition exposed to whole-body vibration at work, the weighted RMS acceleration for each axis on the supporting seat surface should be evaluated at frequencies from 0.5 Hz to 80 Hz. In specific, the frequency weightings and vibration combination should be made as follows:

• X-axis: Wd, kx = 1,4; • Y-axis: Wd, ky = 1,4; • Z-axis: Wk, kz = 1.

Biodynamic research has proven an elevated risk of health problems due to long-term exposure with highwhole-body vibration. Mainly the lumbar spine and the connected nervous system may be affected. Since responses are related to energy, what really matters is the sovibration dose or vibration exposure, which is the product of vibration intensity and exposure duration. This is illustrated inFigure 3, which defines health guidance caution zones in the weighted acceleration versus exposure duratiohealth guidance caution zone is defined by the region in between the two dashed lines (or, alternatively, in between the two dotted lines) in Figure 3. For exposures below the zone, health effects have not been objectively observed. For exposures within the zone, caution with respect to potential health risks is indicated. For exposures above the zone, health risks are likely.

Communications and Vehicular Technology in the Benelux

The applicability of the basic evaluation method depends on called crest factor of the frequency-weighted

acceleration signal, which is defined by the standard as the modulus of the ratio of the maximum instantaneous peak value

weighted acceleration signal to its RMS value. The basic evaluation method is applicable for vibrations with a crest factor at most equal to 9, hence excluding the

magnitude single shocks. For signals with factor larger than 9, the basic evaluation method is not

sufficient and additional methods are needed for adequate evaluation, such as the running RMS method, the fourth power vibration dose method and ratios used for comparison of the

l evaluation methods. In this work, however, we have exclusively used the basic evaluation method, since this proved to be sufficient for most of our

weighted RMS accelerations have been determined in the three orthogonal directions, they should be combined into a single RMS value for that location. The total vibration value of the weighted RMS acceleration is calculated

ak wzz

22 ⋅+

, are the weighted RMS accelerations with respect to the orthogonal axes x, y, z, respectively, and kx, ky,

To investigate the effects of periodic, random and transient vibration on the health of persons in normal health condition

body vibration at work, the weighted RMS acceleration for each axis on the supporting seat surface should be evaluated at frequencies from 0.5 Hz to 80 Hz. In

e frequency weightings and vibration combination

Biodynamic research has proven an elevated risk of health term exposure with high-intensity

body vibration. Mainly the lumbar spine and the connected nervous system may be affected. Since responses are related to energy, what really matters is the so-called vibration dose or vibration exposure, which is the product of

d exposure duration. This is illustrated in , which defines health guidance caution zones in the

weighted acceleration versus exposure duration plane. The health guidance caution zone is defined by the region in between the two dashed lines (or, alternatively, in between the

. For exposures below the zone, health effects have not been objectively observed. For exposures within the zone, caution with respect to potential health risks is indicated. For exposures above the zone, health

Figure 3. Health guidance caution zones To investigate the effects of periodic, random and transient

vibration on the comfort and perceptionnormal health exposed to wholeweighted RMS acceleration for each axis on the supporting seat surface should be evaluated at frequencies from 0.5 Hz to 80 Hz. For this case, the frequency weightings and vibcombination should be made as follows:

• X-axis: Wd, kx = 1;• Y-axis: Wd, ky = 1;• Z-axis: Wk, kz = 1.

The impact of whole-body vibration on comfort depends on many factors that vary with each applicshown in Table 1 give approximate indications of likely reactions to various vibration magnitudes encountered in public transport. However, these reactions dependpassenger expectations with regard to trip duration, the type of activities performed by passengers (e.g. reading, writing, eating, etc.), and many other factors such as acoustic noise and temperature.

Table 1. Reaction at various vibration magnitudes in

public transport Less than 0.315 m/s2

0.315 m/s2 to 0.63 m/s2 0.5 m/s2 to 1 m/s2 0.8 m/s2 to 1.6 m/s2 1.25 m/s2 to 2.5 m/s2 Greater than 2 m/s2

III. SENSOR NODES FOR

MEASUREMENTS

In this section, we introducenodes that we have developed for performing wireless vibration measurements on a human operator.measurements are continuously obtained from 3D accelerometers via a wireless link from a sensor node. The UniNode, as depicted in Figure platform that is designed for BANUniNode filters the vibrations in the x, y, and zbandwidth of 0 – 120 Hz and samples them with a frequency of 250 Hz. It transmits the samples at a rate of 3.75 kbps via a

3

. Health guidance caution zones [6].

To investigate the effects of periodic, random and transient vibration on the comfort and perception of seated persons in normal health exposed to whole-body vibration at work, the weighted RMS acceleration for each axis on the supporting seat surface should be evaluated at frequencies from 0.5 Hz to 80 Hz. For this case, the frequency weightings and vibration combination should be made as follows:

= 1; = 1; = 1.

body vibration on comfort depends on many factors that vary with each application. The values

give approximate indications of likely reactions to various vibration magnitudes encountered in public transport. However, these reactions depend on passenger expectations with regard to trip duration, the type of activities performed by passengers (e.g. reading, writing, eating, etc.), and many other factors such as acoustic noise and

ious vibration magnitudes in public transport [6].

Not uncomfortable Little uncomfortable

Fairly uncomfortable Uncomfortable Very uncomfortable Extremely uncomfortable

ODES FOR WIRELESS VIBRATION

EASUREMENTS

introduce the BAN along with its sensor nodes that we have developed for performing wireless vibration measurements on a human operator. The vibration measurements are continuously obtained from 3D accelerometers via a wireless link from a sensor node. The

Figure 4, is a small and generic s designed for BANs as described in [11]. The

UniNode filters the vibrations in the x, y, and z-axis with a 120 Hz and samples them with a frequency

of 250 Hz. It transmits the samples at a rate of 3.75 kbps via a


4

2.4 GHz star-network link to the sensor base station that is connected to the computer. The 3D accelerometer has a range of -3.6G – 3.6G [12] and is sampled with a 12-bit ADC, which gives a sensitivity of 2.4 mG. The node marks each sample that is transmitted with a time stamp for synchronization of the data and future analysis. To reduce power consumption and increase the battery life time of the sensor nodes, several power management techniques were applied. In this application case, the node is able to operate for 64 hours consecutively on a fully charged battery of 150 mAh.

Figure 4. UniNode for Body Area Networks.

There are three UniNodes located on the human body at the

principal areas (as noted in Subsection II.A) for seated persons: seat surface, lower back, and right foot. All sensors are tightly worn on the body to avoid movement artifacts of the node. A fourth node is attached to the forklift itself (and more specifically to its counterweight in the back) to isolate the vibrations caused by the device and to perform a sanity check of the nodes. Additionally, the forklift is also equipped with a tachometer to determine its speed. The axes directions of all UniNodes are the same as depicted in Figure 5 for ease of discussion. The sensor base station, which is connected to the computer, is located in the forklift’s cabin.

Figure 5. Orientation of UniNode in test cases.

IV. MEASUREMENT RESULTS

In this section, we analyze the measurement results obtained from an in-field test campaign on a forklift driver. Three test cases were defined to measure vibrations on the human driver of a forklift under realistic conditions. The forklift has the capability to change transmission controller parameters according to the terrain. In the first and second test cases the forklift drives over flat terrain with different directions (forward and reverse) and speeds. In the first test case, the parameters are set such that a good transmission quality is obtained, while in the second test case the transmission is purposely configured for degraded transmission quality. In the third test case the forklift drives over an obstacle to create two harsh impulses due to forward and backward driving direction. In all the test cases the suspension of the machine and chair

are not changed during the experiment. These do have influence on the measured results, but are not quantified in this experiment.

The low-pass filtered acceleration and absolute value of the velocity in the first test case (“good transmission quality”) are depicted in Figure 6 in a time frame of 120 seconds. The consecutive actions consist of a series of forward and backward driving with different accelerations. The vibrations of the seat-surface (in all test cases) showed most activity and are depicted as a blue line in Figure 10. The frequency spectra of the signals are shown in Figure 8. The latter shows that the vibrations in all three axes are well present in the range of 0 – 30 Hz.

Figure 6. Test case 1 acceleration and velocity of forklift. Further processing of the data consists of filtering

(frequency weighting) the signals as shown as a red signal in Figure 7. The basic evaluation both for “Health” and “Comfort” is selected for weighting the accelerations, as discussed in Subsection II.B. This weighs the x- and y-axes with Wd and the z-axis with Wk as shown in Figure 2. Even though the z-axis seems to have the lowest intensity in Figure 7, the post-processed results clearly shows the significance of the z-axis.

Figure 7. Showing corresponding (original and filtered) vibrations of seat-surface UniNode in test case 1. Vibrations are filtered with frequency weightings defined in ISO2631-1.

+z

+x

+y

Fro

nt

Ba

ck

UniNode

Forward Backward Forward Backward


5

Figure 8. Frequency Spectrum of seat-surface UniNode in Test case 1. Highest intensity in the range of 0 – 30 Hz.

From each axis both the RMS value and the crest factor are

calculated. The crest factor for each axis is in the range of 3.5 – 5, which justifies the use of the basic evaluation method. By using the appropriate multiplying factors kx, ky, and kz, the frequency-weighted RMS values per axis are combined into an overall RMS acceleration for “Health” (0.7982 m/s2) and “Comfort” (0.7515 m/s2), respectively. Using the chart in Figure 3 for “Health”, the severity of the vibrations in this test case is still within the safety zone when operating less than four hours as shown in Figure 9. On the comfort level, the vibrations in test case 1 are experienced by the driver as “fairly uncomfortable” according to Table 1.

In test case 2 (“degraded transmission quality”) the same driving actions are performed as in test case 1 (see Figure 6). The pre- and post-processed results are depicted in Figure 10. Notice that only the z-axis signal has maintained its intensity thanks to the frequency weighting as was also the case in test case 1.

Figure 9. Health caution zones for test cases 1, 2, and 3.

We noticed that the highest frequency intensity is also in the

range from 0 – 30 Hz similar as in test case 1, which is as expected. From each axis the RMS value is calculated that results in a crest factor less than 9. In test case 2, the overall RMS value for “Health” is now 0.9022 m/s2, while for

“Comfort” it is 0.8467 m/s2. The severity of vibrations for human health is depicted in Figure 9, indicating the health risk has increased w.r.t. the first test case with “good transmission quality”. On the comfort level, the vibrations are now experienced as “fairly uncomfortable” to “uncomfortable”, clearly indicating the comfort level has decreased w.r.t. the first test case.

Figure 10. Showing corresponding (original and filtered) vibrations of seat-surface UniNode in test case 2. Vibrations are filtered with frequency weightings defined in ISO2631-1.

The sporadic vibrations in the third test case are depicted in

Figure 11. The frequency spectrum in Figure 12 shows most intensity in the y and z-axis in the range of 0 – 40Hz. After processing the highest intensity originates in the z-axis when driving over the obstacles. Combining the RMS values of the different axes into the overall RMS acceleration results in a value of 1.4333 m/s2 for “Health” and 1.3529 m/s2 for “Comfort”. The value for “Health” is now in the danger zone (above the health guidance caution zone) when operating for longer than 4 hours as depicted in Figure 9. Hence, health risks are likely. From the viewpoint of “Comfort”, this is determined as an “uncomfortable” to “very uncomfortable” situation for the driver. It is interesting to note that the crest factor is slightly above 9 in the z-direction as it is caused by an impulse. As noted in Subsection II.B, in the strict sense the basic evaluation method is not sufficient anymore and additional evaluation methods such as “running RMS” or “fourth power vibration dose” are required. Implementing these analysis tools was out of scope in this experiment, but should be considered when analyzing signals with extreme-magnitude single shocks.

TC1: 0,7982 m/s2

TC2: 0,9022 m/s2

TC3: 1,4333 m/s2


6

Figure 11. Third test case measurements when driving over an obstacle in forward and backward direction. Original and filtered vibrations of seat-surface UniNode according to frequency weightings defined in ISO2631-1.

Figure 12. Frequency Spectrum of seat-surface UniNode in Test case 3. High intensity till 40Hz in y- and z-axes.

V. CONCLUSION

Our wireless vibration monitoring system is a suitable tool to measure and evaluate whole-body vibrations in relation to human health and perceived comfort of a human machine operator. The system was successfully validated on an industrial application case involving a human driver operating a forklift under various test conditions. The wireless sensor nodes correctly captured the 3D accelerometer data in different locations on the human body, while avoiding the hassle, the limitations on mobility, and the installation effort associated with a cabled solution.

The results from the field test campaign showed that our wireless vibration monitoring system can reliably detect differences in terms of experienced health effects and perceived comfort between two levels of transmission quality (“good” versus “degraded”). In all cases, care should be taken to minimize shocks and avoid uncomfortable driving conditions and health risks over a longer period of time.

The post-processing tool implementing the basic evaluation

method based on weighted RMS acceleration proved to be adequate for most of our test cases. However, situations with extreme-magnitude shocks, e.g. caused by driving over obstacles, require additional analysis techniques, such as “running RMS” or “fourth power vibration dose”.

We believe our wireless vibration monitoring system should prove instrumental in optimizing critical tuning parameters of a machine, as exemplified by the transmission control parameters of a forklift. Besides the transmission, other factors such as the suspension and the chair influence the measured whole-body vibrations and the resulting health effects and perceived comfort. However, by careful design-of-experiments, it should be feasible to isolate the effect of the transmission. This is a topic for further research.

In the long term, we envision our wireless vibration monitoring system to be part of an intelligent transmission system that adjusts critical parameters in real-time for optimal comfort according to the situation.

REFERENCES [1] A. R. Ismail, M. Z. Nuawi, C. W. How, N. F. Kamaruddin, M. J. M. Nor

and N. K. Makhtar, “Whole Body Vibration Exposure to Train Passenger”, American Journal of Applied Sciences, Vol. 7, No. 3, pp. 352–359, 2010.

[2] G. Birlik, “Occupational Exposure to Whole Body Vibration-Train Drivers”, Industrial Health, Vol. 47, pp. 5–10, 2009.

[3] Makoto Futatsuka, Setsuo Maeda, Tsukasa Inaoka, Megumi Nagano, Masahiro Shono, Takashi Miyakita, “Whole-Body Vibration and Health Effects in the Agricultural Machinery Drivers”, Industrial Health, Vol. 36, pp. 127-132, 1998.

[4] Huub H.E. Oude Vrielink, “Exposure to Whole-Body Vibration and Effectiveness of Chair Damping in High-Power Agricultural Tractors Having Different Damping Systems in Practice”, ErgoLab Research, Report 1-10-2009.

[5] DIRECTIVE 2002/44/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 25 June 2002 on the minimum health and safety requirements regarding the exposure of workers to the risks arising from physical agents (vibration) (sixteenth individual Directive within the meaning of Article 16(1) of Directive 89/391/EEC).

[6] “Mechanical Vibration and Shock – Evaluation of Human Exposure to Whole-Body Vibration – Part 1: General Requirements”, International Organization for Standardization, ISO 2631-1, May 1997.

[7] Castle Group, “Evec – Standardized Measurement and Evaluation of Whole-Body Vibration”, Datasheet.

[8] Diogo Koenig, Marilda S. Chiaramonte, Alexandre Balbinot, “Wireless Network for Measurement of Whole-Body Vibration”, MDPI Journal on Sensors, Vol. 8, pp. 3067-3081, 2008.

[9] www.inertia-technology.com [10] R. S. Marin-Perianu, “Wireless Sensor Networks in Motion – Clustering

Algorithms for Service Discovery and Provisioning”, Ph. D. dissertation, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, The Netherlands, 2008.

[11] Lindsay Brown, Bernard Grundlehner, Jef van de Molengraft, Julien Penders, and Bert Gyselinckx, “Body Area Networks for Monitoring Autonomic Nervous System Responses”, Proceedings of 3rd International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth 2009), pp 1-3, April 2009.

[12] Analog Devices, “ADXL330”, 3D accelerometer datasheet.

Forward drive

wheels bump

Backward drive

wheels bump

Wireless Vibration Monitoring on Human Machine Operator

Documents

Transcript of Wireless Vibration Monitoring on Human Machine Operator