Instantaneous Angular Speed Measurement Research Articles

Using the instantaneous angular speed measurement to characterize the transient dynamic response of an inertial system

Using the instantaneous angular speed measurement to characterize the transient dynamic response of an inertial system

Some approaches on instantaneous angular speed measurement using a two-phase n poles AC generator as sensor

The paper proposes an instantaneous angular speed (IAS) measurement method, based on computer-aided processing of two instantaneous induced electromotive force (EMF) signals (in phase quadrature) delivered by a two-phase n poles AC rotary generator used as sensor, which works also as a n poles sine and cosine waves rotary encoder. In this approach, firstly, an optional number of m virtual EMF signals are generated by computing the two real EMF signals. Afterwards, a high sampling rate and high accuracy IAS measurement method is proposed using the elapsed time between zero-crossing moments of each two consecutive virtual EMF signals. On the same generator, a known IAS measurement method (slightly adapted) is used also for comparison purposes. In this method, the two real EMF signals define by calculus a rotation angle whose numerical differentiation produces the IAS value. Both IAS measurement methods validate well each other through frequency domain signal processing and analysis, from 0 to 7000 Hz. Some experiments, achieved on a lathe headstock output spindle, confirm the availability of the proposed IAS measurement method for monitoring and diagnosis.

Partial Rub Detection Based on Instantaneous Angular Speed Measurement and Variational Mode Decomposition

During their lifetime, rotating machines experience various problems. Among others, rotor–stator rubbing is one of the most common problems encountered. Therefore, this paper proposes a two-step procedure for rotor–stator partial rub detection. The first step applies the instantaneous angular speed (IAS) measurement. In this paper, the IAS signal is measured at low to moderate sampling rates as an analog signal from the zebra tape encoder. The correction of encoder segment non-uniformity is also briefly presented in the paper. As a means of coping with the nonlinear signal of the partial rub, the variational mode decomposition (VMD) is proposed in the paper, as the second step of the detection procedure. The VMD is a relatively new method with promising results for machinery fault detection. The partial rub detection tool was tested on the laboratory test rig under three different rotor operating conditions; firstly, for constant rotor speed without rubbing, secondly for rotor running at near critical constant speed with light rotor–stator rubbing, and finally under the condition which describes capabilities of the proposed rubbing detection procedure during variable rotor speed operation. The measurements were taken with an optical phase sensor pointed at the zebra tape encoder. The results are presented in the shape of rotor orbits, IAS signals, FFT spectra of IAS signals and VMD spectrograms of IAS signals. It can be concluded that VMD spectrogram of IAS signal yields a clear detection criterion for light partial rotor–stator rubbing by the presence of 1/2×, 3/2× and 5/2× fractional harmonics. Depending on the analyzed conditions of partial rubbing, at least one of the mentioned fractional harmonics should appear.

Fault detection based on instantaneous angular speed measurement and variational mode decomposition

Rotating machinery encounter throughout their lifetime various problems. Among them, a rotor-stator rubbing problem is one of the most common. This paper proposes a procedure, which applies the instantaneous angular speed (IAS) measurement as a starting step for rotor-stator partial rub detection. There are various approaches regarding counting techniques and processing of signal. In this paper, an application of analog signals from toothed wheel encoder or zebra tape encoder is considered at low to moderate sampling rates. As the rubbing process is nonlinear, this paper is proposing a variational mode decomposition (VMD) as the second step of the detection procedure. The VMD is relatively new method with promising results especially interesting for machinery fault detection. Detection tool is tested on laboratory test rig at two different rotor operating conditions i.e. without rotor-stator rubbing and with light partial rotor-stator rub. Measurements were performed with non-contact eddy current displacement sensors pointed to toothed wheel encoder. Results are presented in the shape of rotor orbits, IAS signals, FFT spectra of IAS signals and VMD spectrograms. Developed fault detection procedure based on IAS measurement and VMD decomposition was successfully tested on laboratory test rig for no rubbing and light rotor to stator partial rub condition.

Online shaft encoder geometry compensation for arbitrary shaft speed profiles using Bayesian regression

The measurement of instantaneous angular speed is being increasingly investigated for its use in a wide range of condition monitoring and prognostic applications. Central to many measurement techniques are incremental shaft encoders recording the arrival times of shaft angular increments. The conventional approach to processing these signals assumes that the angular increments are equidistant. This assumption is generally incorrect when working with toothed wheels and especially zebra tape encoders and has been shown to introduce errors in the estimated shaft speed. There are some proposed methods in the literature that aim to compensate for this geometric irregularity. Some of the methods require the shaft speed to be perfectly constant for calibration, something rarely achieved in practice. Other methods assume the shaft speed to be nearly constant with minor deviations. Therefore existing methods cannot calibrate the entire shaft encoder geometry for arbitrary shaft speeds.The present article presents a method to calculate the shaft encoder geometry for arbitrary shaft speed profiles. The method uses Bayesian linear regression to calculate the encoder increment distances. The method is derived and then tested against simulated and laboratory experiments. The results indicate that the proposed method is capable of accurately determining the shaft encoder geometry for any shaft speed profile.

Natural roller bearing fault detection by angular measurement of true instantaneous angular speed

The challenge in many production activities involving large mechanical devices like power transmissions consists in reducing the machine downtime, in managing repairs and in improving operating time. Most online monitoring systems are based on conventional vibration measurement devices for gear transmissions or bearings in mechanical components. In this paper, we propose an alternative way of bearing condition monitoring based on the instantaneous angular speed measurement. By the help of a large experimental investigation on two different applications, we prove that localized faults like pitting in bearing generate small angular speed fluctuations which are measurable with optical or magnetic encoders. We also emphasize the benefits of measuring instantaneous angular speed with the pulse timing method through an implicit angular sampling which ensures insensitivity to speed fluctuation. A wide range of operating conditions have been tested for the two applications with varying speed, load, external excitations, gear ratio, etc. The tests performed on an automotive gearbox or on actual operating vehicle wheels also establish the robustness of the proposed methodology. By the means of a conventional Fourier transform, angular frequency channels kinematically related to the fault periodicity show significant magnitude differences related to the damage severity. Sideband effects are evidently seen when the fault is located on rotating parts of the bearing due to load modulation. Additionally, slip effects are also suspected to be at the origin of enlargement of spectrum peaks in the case of double row bearings loaded in a pure radial direction.

Design and Optimization of Neural Networks To Estimate the Chamber Pressure in Internal Combustion Engines by an Indirect Method

A particular type of artificial neural network (ANN), with the aim of estimating the indicated pressure into cylinders from instantaneous angular speed measurement, has been developed: radial basis function (RBF). This is the main component of a methodology where input and output curves are parametrized. A modified RBF network from its general structure is designed to reduce the size of the network, approaching the hidden layer weights by means of polynomial functions. It makes it possible to use it in medium requirement PCs, such as in automobile applications. Results corresponding to different operating conditions of a single-cylinder diesel engine (DE), a three-cylinder spark ignition engine (SIE), and a 16-cylinder vee power plant DE (V-16 DE) are presented. Results show the accuracy and fast response of the network, making it feasible to use in online diagnostics and control systems in engines, with very low cost (removing the use of piezoelectric sensors).

An investigation of the effects of measurement noise in the use of instantaneous angular speed for machine diagnosis

In order to discriminate small changes for early fault diagnosis of rotating machines, condition monitoring demands that the measurement of instantaneous angular speed (IAS) of the machines be as accurate as possible. This paper develops the theoretical basis and practical implementation of IAS data acquisition and IAS estimation when noise influence is included. IAS data is modelled as a frequency modulated signal of which the signal-to-noise ratio can be improved by using a high-resolution encoder. From this signal model and analysis, optimal configurations for IAS data collection are addressed for high accuracy IAS measurement. Simultaneously, a method based on analytic signal concept and fast Fourier transform is also developed for efficient and accurate estimation of IAS. Finally, a fault diagnosis is carried out on an electric induction motor driving system using IAS measurement. The diagnosis results show that using a high-resolution encoder and a long data stream can achieve noise reduction by more than 10 dB in the frequency range of interest, validating the model and algorithm developed. Moreover, the results demonstrate that IAS measurement outperforms conventional vibration in diagnosis of incipient faults of motor rotor bar defects and shaft misalignment.

The measurement of instantaneous angular speed

Many different methods have been developed for the measurement of angular speed. Each successive method has attempted to improve measurement performance using a different strategy to process encoder signals based on two basic principles: counting the number of pulses in a given time duration and measuring the elapsed time for a single cycle of encoder signal. A review of existing methods reveals that little effort has been made in the measurement of instantaneous, multi-channel, wide-range angular speed. As a result, this paper aims to develop a method that provides instantaneous speed information in the form of angular displacement. It addresses the general process and considerations that ensure effective measurement of instantaneous angular speed (IAS). The paper then presents two different techniques: one is based on a general-purpose data acquisition system, another uses pure software implementation. Both methods aim to maximise the use of hardware resources without incurring additional costs in the form of upgrades to the measurement system. Finally, an optimisation of measurement system parameters for a reliable IAS measurement has been carried out based on measurement error analysis.