Order Tracking Technique Research Articles

Further exploration of Vold–Kalman-filtering order tracking with shaft-speed information—II: Engineering applications

The first part of this series of papers addressed the theory, numerical implementation and parameter investigations of two further explored Vold–Kalman-filtering order-tracking techniques. A proposed tunable weighting factor for effectively distinguishing and separating both close and crossing order components of signals measured from rotary machines was implemented and examined. Additionally, parameters influencing waveform-tracking performance were investigated. Here, in the second paper of the series, geometric analysis to interpret dynamic signatures using order-tracking schemes is first summarised. To justify the effectiveness of applying developed techniques in practical works, three experimental tasks are accomplished. One is the separation of two close orders arising from flexible coupler imbalancing and gear meshing of a transmission-element test bench. The second task is the investigation of the dynamic characteristics of an electric scooter with a planetary gear set and four stages of speed-reduction gears using the implemented order-tracking techniques. The interactions between order components and structure resonances can be decoupled and distinguished precisely. The third task shows the successful ranking for different signature components of passby noise generated from an electric scooter with CVT transmission. This demonstrates the superiority of the angular-displacement Vold–Kalman-filtering order-tracking technique for analysing and interpreting dynamic signals arising from the operation of rotary machines.

An order-tracking technique for the diagnosis of faults in rotating machineries using a variable step-size affine projection algorithm

This paper describes principles and applications of an adaptive order tracking diagnosis technique for fault diagnosis in rotating machinery. An adaptive high-resolution order tracking method with a variable step-size affine-projection algorithm (VSS APA) is used to diagnose faults in the gear-set and centrifugal fan blades. In comparison with conventional order-tracking methods such as recursive least-square filtering algorithm, the proposed VSS APA technique has fast convergence speed for adaptive filtering process. The VSS APA-based order-tracking technique can overcome problems encountered in FFT based methods. The smearing problem is treated as the tracking of frequency-varying band-pass signals. Ordered amplitudes can be calculated with high-resolution adaptive filter algorithm after experimental implementations carried out to evaluate the proposed algorithm in gear-set and centrifugal fan blades defect diagnosis. The experimental result indicates that the proposed algorithm is effective in rotating machinery fault diagnosis.

Adaptive Order Tracking Technique Using Recursive Least-Square Algorithm

Order tracking technique is one of the important tools for diagnosis of rotating machinery. Conventional methods of order tracking are primarily based on Fourier analysis with reference to shaft speed. Resampling is generally required in the fast Fourier transform (FFT)-based methods to compromise between time and frequency resolution for varying shaft speeds. Conventional methods suffer from a number of shortcomings. In particular, smearing problems arise when closely spaced orders or crossing orders are present. Conventional methods also are ineffective for the applications involving multiple independent shaft speeds. This paper presents an adaptive order tracking technique based on the Recursive Least-Squares (RLS) algorithm to overcome the problems encountered in conventional methods. In the proposed method, the problem is treated as the tracking of frequency-varying bandpass signals. Order amplitudes can be calculated with high resolution by using the proposed method in real-time fashion. The RLS order tracking technique is applicable whether it is a single-axle or multi-axle system.

HYBRID COMPUTED ORDER TRACKING

Vibration analysis is an integral part of modern condition monitoring and fault diagnosis systems for rotating machinery. Orders (cycles per revolution) are used as a frequency base for this analysis, thus making speed-related vibrations easier to detect. Fundamental to the performance of such systems is the accuracy and reliability of the required synchronously sampled vibration data. In this paper, the accuracy of three different synchronous sampling schemes are studied: a traditional hardware solution, computed order tracking and a hybrid of the two. Run-ups and run-downs are of particular interest in condition monitoring systems as they highlight many shaft defects. Also, because of the sometimes rapid shaft speed changes, this is just where the traditional approaches to producing synchronous sampling are prone to producing erroneous results. The three methods are assessed on data produced from a simulation of the rundown of a gas turbine shaft, typical to those found in the power industry. The use of this simulation allows the true accuracy of the techniques to be accessed, and inadequacies of traditional methods are clearly highlighted. The different sampling schemes rely on various interpolation algorithms. The accuracy and reliability of these algorithms is fundamental to the performance of the different sampling schemes, and hence a survey of the state-of-the-art interpolation algorithms is presented. This ensures that the most appropriate algorithms are identified, and as a result the novel computed order tracking technique introduced in this paper is shown to produce superior results.