Browse Publications Technical Papers 2019-26-0217
2019-01-09

Non-Invasive Real Time Error State Detection for Tractors Using Smart Phone Sensors & Machine Learning 2019-26-0217

Condition Monitoring is the process of identifying any significant change in operating parameters of a machine, which can be indicative of a failure in future. This paper discuss a non-invasive condition monitoring methodology for sensing and investigating the problems which could be identified by noise and vibrations. This could be an easy solution for predicting failures in tractors which are operational in the field. An example of engine tappet is used to demonstrate the methodology. A disturbed setting causes a distinguishable noise, referred to as “tappet rattle”. Android smartphones (with inbuilt sensors - accelerometer, gyroscope and microphone) are used to record noise and vibration from tractors in good condition as well as in disturbed condition. Time series data analysis is done to extract relevant features and then Fourier Transform is applied to the signals for extracting frequency domain signatures. Frequency domain-based features have shown significant improvements in the model prediction accuracy. This paper compares different classification algorithms and evaluate the results on performance and accuracy. The trained model is then used along with a smartphone application to do the real-time detection without any additional sensors.

SAE MOBILUS

Subscribers can view annotate, and download all of SAE's content. Learn More »

Access SAE MOBILUS »

Members save up to 18% off list price.
Login to see discount.
Special Offer: Download multiple Technical Papers each year? TechSelect is a cost-effective subscription option to select and download 12-100 full-text Technical Papers per year. Find more information here.
We also recommend:
TECHNICAL PAPER

Designing In-Cab Sound of Vehicles as per the Customer Driving Pattern on Roads

2019-26-0170

View Details

JOURNAL ARTICLE

An Active Control System for Improving the Sound Quality of Vehicle Interior Noise

2015-01-2224

View Details

JOURNAL ARTICLE

Blind Source Separation Applied to Indoor Vehicle Pass-By Measurements

2015-01-2320

View Details

X