Taking helicopter maintenance to the next level
Helicopter mishaps and accidents are often fatal and very costly on many levels, calling for more advanced preventive maintenance that takes advantage of modern technology. The EU-funded project 'Automated diagnosis for helicopter engines and rotating parts' (ADHER) envisioned an efficient system for failure diagnosis and prognosis of mechanical issues using automated sensor technology. It sought to reduce false alarms of current systems, minimise maintenance costs, increase availability in a helicopter fleet and enhance safety. The project worked on a health usage monitoring system (HUMS) that features sensor-based monitoring for condition-based maintenance (CBM) that can replace periodic physical inspections. It sought to better understand the behaviour of vibration, acoustics, helicopter gearboxes, ageing of parts and failure of rotating parts through advanced theoretical models and bench test experiments. ADHER then worked on developing automatic-learning software to analyse sensor data and produce more efficient diagnoses, as well as evaluating the feasibility of new HUMS. After collecting experimental data and monitoring rotating parts, including oil debris, vibration and acoustic emissions, ADHER used the data to develop innovative multi-sensor diagnosis software tools. Such tools would have the ability to combine data in novel ways and discard defective sensor data to achieve more accurate diagnosis. In more detail, the project team applied advanced signal processing techniques to vibration and other data. It established diagnosis parameters from data processing and assessed these parameters, and identified related parameters such as oil temperature, speed and load. After intensive testing, modelling and analysis of instrumentation and equipment, the team developed software tool prototypes that meet the project's objectives. The results were disseminated through press releases, contacts with partners and the website.
