Low-Pressure Optical Detection, Location, and Quantification of Electrical Discharges in Aircraft Wiring Systems

AEROSPACE(2023)

引用 2|浏览0
暂无评分
摘要
Strict regulations issued by international administrative bodies limit the CO2 equivalent emissions for new aircraft, while increasing efficiency requirements. To reach this goal, next generations of aircraft will use more electrical power than their predecessors, so distribution voltage levels will inevitably increase to limit the weight of the electrical wiring interconnect system (EWIS). However, such increased voltage levels generate higher electric stresses in insulation materials as well as in electric and electronic components; thus new failure modes triggered by electrical discharges will appear, their effects being aggravated by harsh environments typical of aircraft systems. The combined effect of higher electrical stresses, compact designs, and low-pressure operating conditions greatly intensifies the risks of premature insulation failure due to electrical discharge activity. This paper shows that by using image sensors, it is possible to detect, localize, and quantify the intensity of electrical discharges occurring in aircraft environments. Through experiments carried out in a low-pressure chamber using an image sensor, this work detects and determines the intensity of electrical discharges generated in electrical wires in their initial stage, long before major faults develop. This paper also shows that the intensity of the discharges calculated from the digital images obtained with the image sensor is directly proportional to the electrical energy involved in the discharge process and increases linearly with the applied voltage. Due to the difficulty of detecting these failure modes at a very early stage, this strategy could potentially facilitate predictive maintenance tasks while contributing to increased levels of aircraft safety.
更多
查看译文
关键词
aircraft power systems,electrical discharge,electrical wiring interconnect system,fault diagnosis,image sensor,state of health,low pressure
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要