Networked Modular Technology for Integrated Aircraft Health Monitoring: Application to Rotary Structures

Hamza BOUKABACHE, Vincent Robert, Jean-Philippe FURLAN, Christophe Escriba, and Jean-Yves Fourniols
Submission Type: 
Full Paper
phmce_14_063.pdf940.59 KBMay 28, 2014 - 8:45am

Health management and damage assessment of rotary structures is one of the major issues that face Helicopter’s and fanjet’s manufacturers. In this context, PHM applications can actually provide a wide range of benefits for complex systems such as transmission gear boxes or jet engine turbine. Forecasting the remaining useful life of these subsystems can improve flight safety and reduce exploitation cost by reducing unscheduled events and regular maintenance. Moreover, a constant monitoring of critical subsystems reduces preventive aircraft grounding which could be time and costly efficient. However, due to the complex nature of these structures, the actual analytical studies based on predictive behavior models show their limit quite quickly.
We propose in this paper, an innovative diagnostic and prognostic health system based on a combination of modular acquisitions interfaces and processing units. Damage assessment approach is based on a smart differentiation between classified signatures acquired through distributed piezoelectric sensors and accelerometers. The developed technology is built around harsh networked electronic modules (Cf. Figure 1) where each one is dedicated to a specific task:
• Sensors instrumentation and acquisition (strain, acceleration and deformation)
• Multiple avionics protocol communication interfaces (ARINC429, CAN, Ethernet, R422 …. ) to connect the PHM system with on board calculators
• Waveform generation (current, voltage, resistive load …) to simulate avionics sensors behavior
Based on embedded CPUs, each module has lightweight signal processing capabilities to execute basics algorithms such as filtering or buffering. Moreover using hot swap and reconfiguration capabilities, the modules can be plugged and unplugged freely without damaging the PHM System. The theoretical maximum number of plugged modules is in fact only limited by the internal network bus bandwidth.
In addition, a central processing and control unit with advanced calculation capabilities manages the whole network scheduling and behavior. The command (brain) module is also responsible of sensors data collection, storage and processing as well as, the execution of diagnostic/prognostic algorithms. In fact, collected data could be exploited on ground with a post treatment for precise analysis or during flight using empiric thresholds for immediate alarm annunciations. The modular scalability of the proposed PHM architecture, allows immediate on flight installation to monitor in real time undesired events.
For this article, the proposed technology is applied for diagnosis of mechanical flows such as partly missing tooth, lubrication default or fatigue cracks in a gear of a demonstrator machine (Cf. Figure 2). A detailed description of data management and rooting from accelerometric and vibration sensors to the command (brain) cell will be exposed. Using joined time frequency analysis, an advanced decision making algorithm based on baseline correlation is implemented. A study comparison between different TF algorithms such as Morlet wavelet transform, windowed Fourier transform or synchrosqueezed transform will be shown.
Finally, a proof-of-concept experiment will be designed to demonstrate the integration of all the described system elements to detect any damage or anomaly into the monitored structure.

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Submission Keywords: 
Aircraft Avionics
diagnosis; prognosis; fault-tolerant control; reconfigurable control; PHM
Electronic PHM
Avionics Systems
PHM sensors and detection methodologies
Submission Topic Areas: 
Health management system design and engineering
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