Method, system and computer program for learning phase of an acoustic or vibratory analysis of a machine

    公开(公告)号:US10551830B2

    公开(公告)日:2020-02-04

    申请号:US15545837

    申请日:2016-01-28

    Abstract: A method of analysis of the state of operation of a machine including a learning step supplementing a reference database with one or more thresholds for one or more indicators calculated on the basis of signals delivered by a sensor associated with the machine, the learning step including the following operations implemented by a computer processing unit; an acquisition of signals characteristic of normal operation and of abnormal operation of the machine; of each of the signals characteristic of normal operation, formation of at least one so-called deviation signal by implementing a mathematical operation having as attributes the signal characteristic of normal operation and one of the signals characteristic of normal or abnormal operation other than the signal characteristic of the normal operation; for each of the deviation signals, calculation of an indicator; determination of an indicator threshold representative of a limit between normal operation and abnormal operation of the machine.

    Method for monitoring an epicyclic gear train by progressive mechanical wave measurement

    公开(公告)号:US12117364B2

    公开(公告)日:2024-10-15

    申请号:US17753376

    申请日:2020-09-04

    CPC classification number: G01M13/028 G01M13/021

    Abstract: A method for monitoring an epicyclic gear train of an aircraft includes the following steps: acquiring, at a predetermined sampling frequency, first values (5(ti)) of a signal formed by a progressive mechanical wave generated in the epicyclic gear train; measuring, at a plurality of successive instants, values (Vmes _r(tj)) of a speed of rotation of at least one of the toothed wheels of the gear train; calculating values (Vc(tj)) of a speed of rotation of a point of contact between two toothed wheels of the epicyclic gear train; determining second values (S(ç½)) of the signal formed by a progressive mechanical wave generated in the epicyclic gear train, the second values being sampled depending on a phase of the point of contact and forming secondary mechanical wave data; and using the secondary mechanical wave data (S(ç½)) to detect an anomaly related to the operation of the epicyclic gear train.

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