A multi-order probabilistic approach for Instantaneous Angular Speed tracking debriefing of the CMMNO׳14 diagnosis contest

Abstract

The aim of this work is to propose a novel approach for the estimation of the Instantaneous Angular Speed (IAS) of rotating machines from vibration measurements. This work is originated from the organisation, by the authors of this paper, of a contest during the conference CMMNO 2014, that was held in Lyon, december 2014. One purpose of the contest was to extract the IAS of a wind turbine from a gearbox accelerometer signal. The analysis of contestant contributions led to the observation that the main source of error in this exercise was the wrong association of one selected and tracked harmonic component with one mechanical periodic phenomenon, this association being assumed as an a priori hypothesis by all the methods used by the contestants. The approach proposed in this work does not need this kind of a priori assumption. A majority (but not necessarily all) periodical mechanical events are considered from a preliminary analysis of the kinematics of the machine (harmonics of shaft rotation speeds, meshing frequencies ...). The IAS is then determined from probability density functions that are constructed from instantaneous spectra of the signal. The efficiency and robustness of the proposed approach are illustrated in the frame of the CMMNO 2014 contest case.

A Simple Condition Monitoring Method for Gearboxes Operating in Impulsive Environments

“…Since, the mechanical components have fixed kinematics that govern their movement, the vibration signals are cyclostationary in the angle domain, with the cyclostationarity in the time domain being a special case [20]. Hence, the time domain signal is transformed to an angle domain representation using order tracking to ensure that the impulses are periodic [21,22].…”

An open set recognition methodology utilising discrepancy analysis for gear diagnostics under varying operating conditions

“…Hence, the Continuous Wavelet Transform (CWT), which is popular for analysing non-stationary signals for rotating machine diagnostics [4,12,23,40], is used with a Mexican hat basis function to obtain an angle-order distribution of the order tracked vibration signal, with the order tracking performed with the available rotational speed (or phase) information. The rotational speed can be estimated from measurement equipment [41] or estimated from the vibration signal [42,43] depending on the available equipment. The wavelet coefficients of the first three gear mesh components are extracted for different shaft angles, whereafter a windowing procedure is used to extract localised features from the wavelet coefficient signals.…”

A tacholess order tracking methodology based on a probabilistic approach to incorporate angular acceleration information into the maxima tracking process

“…Incremental shaft encoders, such as zebra tape and digital shaft encoders, provide much finer resolutions to measure the large angular accelerations in the system [6]. However, incremental shaft encoders require large sampling frequencies to accurately estimate the zero crossing times [7,8], the procurement and installation of additional expensive instrumentation and equipment and the storage of additional data [9,10]. The shaft encoders are also in some cases impractical or even impossible to install and are not durable in the harsh operating conditions [11,12].…”