Characteristics of Agriculture Tractor Interior Noise

Abd-El-Tawwab, Ali M.; Abouel-Seoud, Shawki; Elsayed, Fahmi; Abdelhakim, T.

doi:10.1260/0263092001492822

Cited by 8 publications

(3 citation statements)

References 3 publications

(3 reference statements)

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“…The measurement of the generated noise level was conducted on the operator's seat in both tractors with and without cabins during the motion over an agrotechnical surface. The research determined that there is a higher level of noise in a cabinless tractor (94 dB) as opposed to a tractor with a cabin (88 dB) [7].…”

Section: Introductionmentioning

confidence: 99%

Noise in the Cabin of Agricultural Tractors

et al. 2018

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This paper represents the results of the research of generated noise levels measured in three different years (2010, 2013, and 2015), in accordance with the proscribed norms HRN ISO 6394, HRN ISO 6396 and HRN ISO 5131. The research was conducted on test sites of Belje d.d. company. The measurement was carried out on three tractors of the FENDT model 410 with the aim of determining the increase of generated noise relative to the time the tractors spent in exploitation. The obtained results showed that none of the tractors produced a higher level of noise than the permitted 90 dB. The main hypothesis of this experiment is that, exploitation-wise, tractors with a greater number of work hours will produce more noise than the ones with a smaller number of work hours.

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Section: Introductionmentioning

confidence: 99%

Noise in the Cabin of Agricultural Tractors

et al. 2018

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“…Kankar et al 13 used the complex Morlet wavelet based on minimum Shannon entropy criterion to extract the fault feature and presented a methodology for detection of bearing faults by classifying them using three artificial intelligence techniques where SVM is found to be superior to least vector quantization and self-organising maps. Advances in the field of condition monitoring indicators, signal processing and artificial intelligence techniques have been reported in the review papers by Nie et al, 14 Singh and Al Kazzaz, 15 Peng and Chu, 16 and Jardine et al 17 In addition to the above, there are some studies 18,19 on the cabin noise for tractor and car and it is found that the structure born sound due to gearbox is the most annoying noise and hence it is recommended that efforts should be made to control quality of gearbox on assembly line.…”

Section: Introductionmentioning

confidence: 99%

Application of psychoacoustics for gear fault diagnosis using artificial neural network

Kane

Andhare

2016

Journal of Low Frequency Noise, Vibration and Active Control

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Identification of correct working of gearbox is a very important function during end of line inspection in the assembly line while manufacturing the gearbox. Such inspection is performed by an operator by listening to the sound of gearbox while running it on a test bench. Based on the sound emitted by the gearbox combined with experience and judgment of the operator, the gearbox is passed or rejected for fitting inside the vehicle. This paper makes an attempt to use artificial intelligence techniques to identify gearbox condition in the above environment by using psychoacoustic features to replace human hearing. Experiments are carried out on a gearbox test rig and sound data are acquired for good and faulty gear conditions. Psychoacoustic features and statistical indices are extracted from the data and these are then used as input to an artificial neural network. The artificial neural network output is the condition of gearbox. Performances of psychoacoustic and statistical indices are then compared. It is found that psychoacoustic features are able to predict gearbox condition with an accuracy of 99% and 98% for good and faulty conditions, respectively, whereas the statistical features are able to do the same with 97% and 98% accuracy. Therefore, it is concluded that psychoacoustic features have the potential to be used for the end of line inspection of gearbox in manufacturing environment and the process of inspection can be made objective by eliminating operator's ability and judgment.

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“…s part of the solutions aimed at improving comfort and safety on board agricultural tractors with cabs, by reducing the driver's exposure to disturbing acoustic waves, traditional passive mitigation methods, which involve the use of sound-absorbing and sound-insulating materials, may be not very effective in controlling lowfrequency components. Within the car cabins and, mostly, the cabs of agricultural machinery, the noise at the driver's ear is characterized by low-and medium-frequency components deriving from sources such as the engine or road-tire interaction [1]. Since the late 1980s, studies on Active Noise Control (ANC) systems, mentioned for the first time in a patent from 1936 [2], for noise mitigation within car cabin have been carried out by Elliot et al [3].…”

mentioning

confidence: 99%

ANC: A Low-Cost Implementation Perspective

Belicchi¹,

Opinto²,

Martalò³

et al. 2022

SAE Technical Paper Series

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In the present work, we describe a low-cost implementation of an Active Noise Cancellation (ANC) system. The most interesting feature of our implementation is the use of general-purpose hardware, without the need of expensive and hard-to-program Digital Signal Processing (DSP) devices. In particular, the reference signals, collected with accelerometers properly placed on noise-generating parts and the error feedback signals are collected by means of an USB interface. All signal processing, aimed at primary path estimation and anti-noise audio signal generation, is performed using Simulink running on a commercial mini PC. The Exponential Sine Sweep (ESS) method is adopted for the measurement of the secondary path from the cancellation loudspeakers to the error microphones. An adaptive Filtered-X Least Mean Square (LMS) algorithm determines the anti-noise audio signal to be emitted. The system has been installed and tested on a commercial agricultural tractor cabin mounted over electromagnetic shakers to emulate realistic operating conditions. Two error microphones are attached to the headrest, close to the driver's ears. The resulting ANC system relies on the use of very small buffers (for audio/accelerometric data), with a latency comparable to that of more complex and expensive specific DSP systems used in this kind of applications. In terms of acoustic performance, a significant reduction of annoying peaks in the 200-500 Hz range and a broadband noise reduction at lower frequencies are observed, thus improving the overall sound quality experience. In conclusion, the implementation of an effective ANC system, employing common audio devices and a relatively simple Simulink program, was obtained. This paves the way to straightforward experimentation (in Matlab/Simulink) of new ANC processing algorithms, allowing direct testing of simulation-based solutions, without the need of porting them to a proprietary DSP-based platform.

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Characteristics of Agriculture Tractor Interior Noise

Abstract: ABSTRACT

Cited by 8 publications

References 3 publications

Noise in the Cabin of Agricultural Tractors

Noise in the Cabin of Agricultural Tractors

Application of psychoacoustics for gear fault diagnosis using artificial neural network

ANC: A Low-Cost Implementation Perspective

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