College - Author 1

College of Engineering

Department - Author 1

Electrical Engineering Department

Degree Name - Author 1

BS in Electrical Engineering

College - Author 2

College of Engineering

Department - Author 2

Electrical Engineering Department

Degree - Author 2

BS in Electrical Engineering



Primary Advisor

Vladimir Prodanov, College of Engineering, Electrical Engineering Department


Bearings, a common component in rotating machinery, are essential components of modern rotating machines; thus, monitoring their health is crucial when reducing downtime and boosting production efficiency. The Bearing Health Detector (BHD), a hand-held device, captures and processes the sound of a machine under test in real time and estimates the level of wear and tear by comparing the sound to previous tests. The BHD encompasses audiences involved with roller bearings in rotating machinery and is designed to provide the diagnosis of wear through the universal detection of good, satisfactory, and very poor with the following color scheme: green, yellow, and red. The device offers a near real-time response rate within proximity of the machinery with a high accuracy of 90% in bearing health estimation. Furthermore, simple labeled button features signify when to start collecting data. This device will lower the long-term cost of owning machinery with bearings because device operation does not require a professional technical background and gives an insight into when to replace bearings, rather than seeking professional consultation.