This paper presents a study of aero-engine exhaust gas electrostatic sensor array to estimate the spatial position, charge amount and velocity of charged particle. Firstly, this study establishes a mathematical model to analyze the inducing characteristics and obtain the spatial sensitivity distribution of sensor array. Then, Tikhonov regularization and compressed sensing are used to estimate the spatial position and charge amount of particle based on the obtained sensitivity distribution; cross-correlation algorithm is used to determine particle’s velocity. An oil calibration test rig is established to verify the proposed methods. Thirteen spatial positions are selected as the test points. The estimation errors of spatial positions and charge amounts are both within 5% when the particles are locating at central area. The errors are higher when the particles are closer to the wall and may exceed 10%. The estimation errors of velocities by using cross-correlation are all within 2%. An air-gun test rig is further established to simulate the high velocity condition and distinguish different kinds of particles such as metal particles and non-metal particles.

In view of the high false alarm rate in the oil debris monitoring results of the triple-coil inductive sensor in the transmission lubrication system of the aero-engine, a new debris signal processing method based on inductive monitoring is proposed. A time domain analysis is carried out first, and the signal energy is the most effective index to distinguish the debris signature from the noise signature. On this basis, signal energy values within a fixed-length sliding window is processed through the histogram. Finally, a threshold is set for the detection of the debris signature, which is based on the distribution of data within the histogram. This method is applied to the experimental data from a test run of an aero-engine, and the results show that all the debris is detected even if part of it appears during a change in the working condition of the aero-engine. Therefore, this method shows satisfactory results in debris detection accuracy and especially the inhibition of false alarms. It is also applicable for real-time monitoring due to the similarity between the movement of the sliding window and real-time data acquisition. In addition, it is applicable for various sensing principles, including but not limited to the inductive sensor signal, since the detection performance is only related to the signal itself.

Auxiliary power unit is one of the indispensable systems for civil aviation aircraft but the traditional planned maintenance cannot meet the actual needs of airlines. In this work, the key performance parameters of the auxiliary power unit are selected by using recursive feature elimination method. With the selected parameters, the remaining useful flight cycle of the auxiliary power unit is predicted by applying particle filter techniques. Some improved algorithms such as Gaussian particle filter and auxiliary particle filter are also compared. The experimental results demonstrate that the particle filter-based method has high prediction accuracy and engineering application value.

In the processing of particulate solids, particle–particle and particle-wall collisions can generate electrostatics. This is called contact/impact/frictional electrification and can lead to many problems such as affecting powder flow and explosion hazards. It is necessary to research the tribo-electrification charging due to single particle impacts on a target as the fundamental understanding of tribo-electrification. A new impact charging test rig based on an electrostatic sensor array that can measure charge transfer caused by a single impact between a particle and a target plane has been designed and established. Combined with the electrostatic sensor array, the compressed sensing algorithm is used to estimate not only the spatial position but also the charge amount of particle. The cross-correlation algorithm is used to determine particle’s velocity instead of using other devices such as a photodetector. The new instrument allows single particles impacting target planes at different angles with a velocity exceeding 100 m/s. An oil calibration test rig has been constructed to verify the proposed methods. The estimation errors of the spatial position and charge amount are both within 5% when the particle is located at the central area of the pipeline and the estimation errors of velocities are within 2%. The impact charging experiments show a special initial charge prior to impact for which no net charge transfer would occur for polymer particles, but the charge would completely transfer for metal particles.