Statistical Analysis of Vibration Signals for Condition Monitoring of Defects in Exhaust Fan Bearing

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ABSTRACT

Identification of exhaust fan bearing defects has its root foundations in the analysis of frequency modulation and sensing using mostly online techniques.

Centrifugal fans are the most commonly used fans in the industry today. They are preferred to axles because they are cheaper and constructed with simplicity. They are used in wind systems in vehicles and buildings and also in delivering gas or minerals. They are suitable for industrial and air pollution processes and systems.

Fans play a key role in the production of re-circulating applications, in the supply of combustion air and the movement of air through processes and equipment for the protection of the environment. As they are indispensable components in these and other fields, it is essential that they always work reliably and efficiently. Reliability prevents interruptions that result in downtime and product damage. While engine failures or bearings sometimes contribute to fan failure, bearings are the most common failure point. Bearings are the crucial link between the rotating fan shaft and the stationary drive base, two of the strongest components of the fan.

Mechanics form the difference between the direct drive fan and the belt drive. In design, the motor in the direct drive discharge fans is directly connected to the fan board. This system is generally more efficient and has fewer moving parts, which reduces the likelihood of repair. The belt conveyor fans use a belt and motor to control the motor shaft. While the vibration friction of this system might cause inefficiency, the lower price and the quiet operation make this fan a popular choice. Direct drive and belt drive will provide the necessary suction air to heat the heat, smoke and smoke of your commercial kitchen.
The focus of this research study is the identification of exhaust fan bearing defects and requisite solutions to the problems caused by such defects. The use of harmonic and frequency modulations analysis in relation to revolutions per minute is critical in the determination of the extent of such defects. Identification of a clear algorithm to be applied to achieve the underlying objectives of the research study is of crucial importance.

KEYWORDS: Bearings, Exhaust fan defects, harmonics, frequencies.
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APA

Waweru, A. (2021). Statistical Analysis of Vibration Signals for Condition Monitoring of Defects in Exhaust Fan Bearing. Afribary. Retrieved from https://afribary.com/works/statistical-analysis-of-vibration-signals-for-condition-monitoring-of-defects-in-exhaust-fan-bearing-1

MLA 8th

Waweru, Ashington "Statistical Analysis of Vibration Signals for Condition Monitoring of Defects in Exhaust Fan Bearing" Afribary. Afribary, 02 Jul. 2021, https://afribary.com/works/statistical-analysis-of-vibration-signals-for-condition-monitoring-of-defects-in-exhaust-fan-bearing-1. Accessed 28 Oct. 2021.

MLA7

Waweru, Ashington . "Statistical Analysis of Vibration Signals for Condition Monitoring of Defects in Exhaust Fan Bearing". Afribary, Afribary, 02 Jul. 2021. Web. 28 Oct. 2021. < https://afribary.com/works/statistical-analysis-of-vibration-signals-for-condition-monitoring-of-defects-in-exhaust-fan-bearing-1 >.

Chicago

Waweru, Ashington . "Statistical Analysis of Vibration Signals for Condition Monitoring of Defects in Exhaust Fan Bearing" Afribary (2021). Accessed October 28, 2021. https://afribary.com/works/statistical-analysis-of-vibration-signals-for-condition-monitoring-of-defects-in-exhaust-fan-bearing-1