Analysis of whole-body vibrations transmitted by earth moving machinery

Seixas, Adérito; Rodrigues, Tiago

doi:10.1201/9781315164809-85

Cited by 8 publications

(3 citation statements)

References 1 publication

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“…A high percentage of workers in the European Union are exposed to whole-body vibration (WBV), according to the European Agency for Safety and Health at Work (EU-OSHA) [1]. WBV exposure is an inseparable part of the operations performed by vehicle drivers and equipment operators [2][3][4][5][6]. This exposure is epidemiologically related to the most common work-related health problems in the EU, namely musculoskeletal disorders (MSDs) [7].…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network-Based Model for Assessing the Whole-Body Vibration of Vehicle Drivers

Aguilar,

de la Hoz-Torres,

Martínez-Aires

et al. 2024

Buildings

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Musculoskeletal disorders, which are epidemiologically related to exposure to whole-body vibration (WBV), are frequently self-reported by workers in the construction sector. Several activities during building construction and demolition expose workers to this physical agent. Directive 2002/44/CE defined a method of assessing WBV exposure that was limited to an eight-hour working day, and did not consider the cumulative and long-term effects on the health of drivers. This study aims to propose a methodology for generating individualised models for vehicle drivers exposed to WBV that are easy to implement by companies, to ensure that the health of workers is not compromised in the short or long term. A measurement campaign was conducted with a professional driver, and the collected data were used to formulate six artificial neural networks to predict the daily compressive dose on the lumbar spine and to assess the short- and long-term WBV exposure. Accurate results were obtained from the developed artificial neural network models, with R2 values above 0.90 for training, cross-validation, and testing. The approach proposed in this study offers a new tool that can be applied in the assessment of short- and long-term WBV to ensure that workers’ health is not compromised during their working life and subsequent retirement.

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Section: Introductionmentioning

confidence: 99%

Artificial Neural Network-Based Model for Assessing the Whole-Body Vibration of Vehicle Drivers

Aguilar,

de la Hoz-Torres,

Martínez-Aires

et al. 2024

Buildings

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show abstract

“…In these industries, driving heavy equipment vehicles (HEV) exposed workers to whole-body vibrations (WBV) on a daily basis [3][4][5][6][7]. Vibrations are mainly transmitted to the driver's body through the vehicle seat and the cabin floor [8,9].…”

Section: Introductionmentioning

confidence: 99%

Whole Body Vibration Exposure Transmitted to Drivers of Heavy Equipment Vehicles: A Comparative Case According to the Short- and Long-Term Exposure Assessment Methodologies Defined in ISO 2631-1 and ISO 2631-5

Hoz‐Torres

Aguilar

Ruiz

et al. 2022

IJERPH

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The construction and transport sectors are the industries with the highest proportions of workers exposed to vibrations in the European Union. Heavy equipment vehicle (HEV) drivers often perform operations on different uneven surfaces and are exposed to whole body vibration (WBV) on a daily basis. Recently, a new version of ISO 2631-5 was published. However, since this new method required as input the individual exposure profile and the acceleration signals recorded on more surfaces, limited studies have been carried out to evaluate HEV operations according to this standard. The objectives of this study were to assess the WBV exposure using the methods defined in ISO 2631-1:1997 and ISO 2631-5:2018 and to compare the obtained health risk assessments between drivers with different anthropometric characteristics. For this purpose, two drivers were selected and a field measurement campaign was conducted. Regarding short-term assessment, results showed that VDV was the most restrictive method with exposure levels above the exposure action limit value, while SdA indicated that the same exposures were safe for the worker. With respect to long-term assessment, Risk Factor RA showed that the driver with the highest body mass index was the only one who exceeded the low probability limit of adverse health effects.

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“…Agricultural tractors typically have a large mass and operate in terrain that has an uneven surface, exposing their operators more often to Whole Body Vibrations (WBV) than compared to on-road vehicles (de la Hoz -Torres et al, 2017;Kim et al, 2018). Heavy machine operators typically work for hours, thus being exposed to vibration for much of the day, which can lead to serious Adapted from ISO, 2631ISO, : 1978 health problems (Kia et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the vibration levels issued by agricultural tractors

Rosa¹,

Baesso²,

Modolo³

et al. 2021

Afr. J. Agric. Res.

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Vibration is one of the most relevant aspects, when dealing with the subject of ergonomics in agricultural tractors, although there are still few studies developed to evaluate this parameter and its implications for occupational health. This work aimed to evaluate the levels of vibration emitted by agricultural tractors with different powers, comparing the results with the norm in force in Brazil, in addition to evaluating these levels in three different types of surface. In its methodology, seven tractors , called A, B, C, D, E, F and G, were evaluated, from the same brand, with powers ranging from 75 to 215 hp. The frequency range chosen for the study varied from 5 to 10 Hz, the total data acquisition time was 20 min and the tractors operated under similar conditions, with five repetitions in each treatment (tractor x surface). Generally, the tractors studied showed higher vibration levels than the parameters set by the standard used by the International Organization for Standardization (ISO), in a daily working period of eight hours, in the frequency range varying from 5 to 10 Hz.

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Analysis of whole-body vibrations transmitted by earth moving machinery

Cited by 8 publications

References 1 publication

Artificial Neural Network-Based Model for Assessing the Whole-Body Vibration of Vehicle Drivers

Artificial Neural Network-Based Model for Assessing the Whole-Body Vibration of Vehicle Drivers

Whole Body Vibration Exposure Transmitted to Drivers of Heavy Equipment Vehicles: A Comparative Case According to the Short- and Long-Term Exposure Assessment Methodologies Defined in ISO 2631-1 and ISO 2631-5

Evaluation of the vibration levels issued by agricultural tractors

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