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In today's industrial sphere, machines are the key supporting various sectors and their operations. Over time, due to extensive usage, these machines undergo wear and tear, introducing subtle yet consequential faults that may go unnoticed. Given the pervasive dependence on machinery, the early and precise detection of these faults becomes a critical necessity. Detecting faults at an early stage not only prevents expensive downtimes but also significantly improves operational efficiency and safety standards. This research focuses on addressing this crucial need by proposing an effective system for condition monitoring and fault detection, leveraging the capabilities of advanced deep learning techniques. The study delves into the application of five diverse deep learning models—LSTM, Deep LSTM, Bi LSTM, GRU, and 1DCNN—in the context of fault detection in bearings using accelerometer data. Accelerometer data is instrumental in capturing vital vibrations within the machinery.

Faults if not detected and processed will create catastrophe in closed loop system for safety critical applications in automotive, space, medical, nuclear, and aerospace domains. In aerospace applications such as stall warning and protection/prevention system (SWPS), algorithms detect stall condition and provide protection by deploying the elevator stick pusher. Failure to detect and prevent stall leads to loss of lives and aircraft. Traditional Functional Hazard and Fault Tree analyses are inadequate to capture all failures due to the complex hardware-software interactions for stall warning and protection system. Hence, an improved methodology for failure detection and identification is proposed. This paper discusses a hybrid formal method and model-based technique using STPA to identify and diagnose faults and provide monitors to process the identified faults to ensure robust design of the indigenous stall warning and protection system (SWPS).

Modern combat aircraft demands efficient maintenance strategies to ensure operational readiness while minimizing downtime and costs. Innovative approaches using Digital Twining models are being explored to capture inter system behaviours and assessing health of systems which will help maintenance aspects. This approach employs advanced deep learning protocols to analyze the intricate interactions among various systems using the data collected from various systems. The research involves extensive data collection from sensors within combat aircraft, followed by data preprocessing and feature selection, using domain knowledge and correlation analysis. Neural networks are designed for individual systems, and hyper parameter tuning is performed to optimize their performance. By combining the outputs of these during the model integration phase, an overall health assessment of the aircraft will be generated.

If you’re working to balance the implementation of today’s urban ground mobility (UGM) vehicles with tomorrow’s biggest challenges and opportunities, then you belong at the premier of SAE’s Urban Ground Mobility Digital Summit.

Contact a member of the 2024 SAE On-Board Diagnostics Symposium-Europe team for any questions regarding the event.

Contact a member of the 2022 Thermal Management Systems Symposium team.

September 17-19, 2019 │ Garden Grove, CA, USA

Contact a member of the Thermal Management Systems Symposium sales team for more information about exhibiting or sponsoring.

Learn more about how you can exhibit or sponsor at the 2022 Thermal Management Systems Symposium.

If you’re working to balance the implementation of today’s urban ground mobility (UGM) vehicles with tomorrow’s biggest challenges and opportunities, then you belong at the premier of SAE’s Urban Ground Mobility Digital Summit.

The ADAS to Automated Driving Digital Summit will virtually bring together engineering professionals from OEMs, suppliers, technology and corporate and academic research. And now, with no travel required, the digital summit will reach an even broader international audience from North America, Europe, and Asia.

Thermal Management Systems Symposium industry discusses latest regulatory impacts, applications to reduce engine emissions, conserve energy, reduce noise, improve the cabin environment, increase overall vehicle performance passenger, commercial vehicle industry.

Contact a member of the Thermal Management Systems Symposium team.

Meet like-minded mobility engineersto discuss new legislation and regulations around thermal management, emissions control, safety, and energy conservation.

September 17-19, 2019 │ Garden Grove, CA, USA

September 17-19, 2019 │ Garden Grove, CA, USA

September 17-19, 2019 │ Garden Grove, CA, USA

A FREE networking event for ground mobility executives, startups and tech companies, UGM brings together leaders in development, software, design, quality assurance and urban planning for a productive and powerful summit that solves challenges — and secures long-term strategies for success in urban ground mobility.

Request information about exhibiting or sponsoring at On-Board Diagnostics Symposium-Europe.