Instantaneous Angular Speed Signal Research Articles

Research on Instantaneous Angular Speed Signal Separation Method for Planetary Gear Fault Diagnosis

Research on Instantaneous Angular Speed Signal Separation Method for Planetary Gear Fault Diagnosis

Cylindrical-cam modulation instantaneous angular speed sensor for reciprocating-rotary machine

This paper presents the theory and implementation of a novel sensor system for measuring the instantaneous angular speed (IAS) of a shaft with reciprocating rotary motion. The system comprises a laser displacement sensor and an S-shaped cylindrical cam sleeve fixed to the shaft. As the shaft rotates with reciprocating rotary motion, the cylindrical cam modulates the IAS signal of the machine to achieve a change in profile radius. The signal is then demodulated to obtain the IAS of the reciprocating rotary motion. The sensor system is experimentally validated using a vibration-assisted tapping machine. Results show that the IAS readings are consistent with the machine’s set parameters. Furthermore, the novel sensor produces considerably smooth and stable traces of the IAS, demonstrating its high accuracy and reliability in obtaining the IAS of reciprocating rotary motion transients. The frequency error rate of the system is less than 3%, and the highest resolution of the angular amplitude is 4.788″. Finally, a cutting experiment confirmed the feasibility and validity of the proposed sensor system in optimizing the parameters of the vibration-assisted tapping machine.

A Hydraulic Axial Piston Pump Fault Diagnosis Based on Instantaneous Angular Speed under Non-Stationary Conditions

Due to the intense noise interference in hydraulic systems, it is extremely difficult to detect component faults through vibration signals. Diagnostic performance is also constrained by highly time-varying and non-stationary operating conditions. This study proposes to use instantaneous angular speed (IAS) signals that are both operational and state parameters as sources of information. Firstly, the instantaneous angular speed fluctuation (IASF) of a piston pump is analyzed theoretically, and it is concluded that its fluctuating components contain the health status information of the components. The IASF can then be obtained by subtracting the speed trend term from IAS signals obtained via a magneto-electric speed sensor. A synchro-extraction of the normal S transform (SNST) is proposed to process it via line-pass filtering. Finally, the filtered and reconstructed IASF signal is utilized to draw a two-dimensional polar coordinate map online. A non-stationary-condition test is carried out on the test platform to monitor the morphological characteristics of the valve plate under normal, slight, and severe wear conditions. The polar plot shows significant increases in speed fluctuations and oscillation times within a range from 180° to 270°. The relevant research results reflect that the IAS signal can provide a new method for monitoring the operating status of and conducting fault diagnoses for hydraulic equipment.

Instantaneous-Angular-Speed-Based Synchronous Averaging Tool for Bearing Outer Race Fault Diagnosis

Synchronous averaging (SA) is a powerful signal processing tool to enhance the feature of interesting periodic events by suppressing non-synchronous components. However, the features related to the rolling element bearing (REB) fault may not be effectively enhanced by SA under random slip conditions. To address this issue, two instantaneous angular speed (IAS)-based synchronous averaging frameworks are proposed in this study. Then, an improved negentropy indicator is proposed to characterize the richness of the REB fault information. Additionally, based on the estimation feature of the IAS signal, the effects of the encoder resolution and structure damping factor on the waveform related to the faulty REB are studied, respectively. Simulation and experiment results show that the proposed schemes can be used to enhance the feature of the REB fault under random slip conditions.

Instantaneous Angular Speed-Based Fault Diagnosis of Multicylinder Marine Diesel Engine Using Intrinsic Multiscale Dispersion Entropy

Due to coupling of multiple cylinders during operation and association of high environmental noise, the existing waveform analysis is inefficient to identify the working status of large multi-cylinder marine diesel engines (MCMDE). In order to solve this problem, a new framework named intrinsic multiscale dispersion entropy (IMDE) is proposed by calculating the multiscale dispersion entropy (MDE) of intrinsically reconstructed instantaneous angular speed (IAS) signal. Firstly, intrinsic characteristic scale decomposition (ICD) has been utilized to decompose an IAS signal into principal components. Then, appropriate components are selected for reconstruction of the intrinsically denoised IAS signal. Lastly, working state of the MCMDE is identified by quantifying the intrinsically reconstructed IAS signal with the help of multiscale dispersion entropy (MDE) leading to concept of IMDE. Simulation model corresponding to a v-16 cylinder engine and experimental data collected from a real life v-16-cylinder marine diesel engine are utilized for validation. Results show that the proposed IMDE can extract the effective fault features under different working conditions and has the highest classification accuracy in compare to other existing techniques: MDE, MSE and MFE.

On the Behaviour of an AC Induction Motor as Sensor for Condition Monitoring of Driven Rotary Machines

This paper presents some advances in condition monitoring for rotary machines (particularly for a lathe headstock gearbox) running idle with a constant speed, based on the behaviour of a driving three-phase AC asynchronous induction motor used as a sensor of the mechanical power via the absorbed electrical power. The majority of the variable phenomena involved in this condition monitoring are periodical (machines having rotary parts) and should be mechanically supplied through a variable electrical power absorbed by a motor with periodical components (having frequencies equal to the rotational frequency of the machine parts). The paper proposes some signal processing and analysis methods for the variable part of the absorbed electrical power (or its constituents: active and instantaneous power, instantaneous current, power factor, etc.) in order to achieve a description of these periodical constituents, each one often described as a sum of sinusoidal components with a fundamental and some harmonics. In testing these methods, the paper confirms the hypothesis that the evolution of the electrical power (instantaneous and active) has a predominantly deterministic character. Two main signal analysis methods were used, with good, comparable results: the fast Fourier transform of short and long signal sequences (for the frequency domain) and the curve fitting estimation (in the time domain). The determination of the amplitude, frequency and phase at origin of time for each of these components helps to describe the condition (normal or abnormal) of the machine parts. Several achievements confirm the viability of this study: a characterization of a flat driving belt condition and a beating power phenomenon generated by two rotary shafts inside the gearbox. For comparison purposes, the same signal analysis methods were applied to describe the evolution of the vibration signal and the instantaneous angular speed signal at the gearbox output spindle. Many similarities in behaviour among certain mechanical parts (including their electrical power, vibration and instantaneous angular speed) were highlighted.

Экспериментальная проверка способа выравнивания мощностей цилиндров многоцилиндрового дизеля

Purpose: The purpose of the present work is to test experimentally equalization method for the outputs of multi-cylinder diesel engine cylinders basing on energy minimization of amplitude spectrum low-frequency band for diesel crankshaft instantaneous angular speed signal. Methods: The work uses the methods of digital signal processing, spectral analysis, differential calculus, multidimensional undifferentiated function optimization, experimental results processing. Results: The fulfilled experimental studies at bench diesel generator device as a part of locomotive diesel D50 (6CHN31.8/33) and traction generator MPT 84/39 ensure the possibility to use proposed earlier method for power equalization for the cylinders of multi-cylinder diesel engine basing on energy control of amplitude spectrum low-frequency band of crankshaft instantaneous angular speed signal. Unrvenness index for cylinder power is proposed, its sensitivity to cyclic supply change and the advance angle of fuel supply to diesel engine individual cylinders is estimated. Practical significance: The possibility to apply being proposed equalization method for the powers of multi-cylinder diesel engine cylinders for to adjust fuel equipment after diesel engine repair as with the systems of electronic fuel supply control as well as with hydromechanical fuel equipment has been confirmed experimentally. The use of given method eliminates the need to measure the temperature of exhaust gases and flash pressure in cylinders for fuel equipment adjustment that’s especially important for high-speed diesel engines which cylinder cover construction doesn’t imply indicated valves.

Low speed lifting cable diagnosis using instantaneous angular speed

This paper describes an experimental study of lifting cable fault diagnostic based on instantaneous angular speed (IAS) technique. During the study load tests on a selection of damaged cables, it is shown that IAS increases significantly after the damage is inflicted. The relationship between IAS signal characteristics and strand defects is investigated and it is found that the most influent parameters over IAS are speed, load and defects size. The pattern of IAS signals during a detection fault test is studied and a suggestion is made for a filtering technique to improve the recognition of imminent failure. Finally, an evaluation of the common statistical indicators was implemented. The study gave satisfactory results and shown that IAS measurement is a promising tool for the health monitoring of low speed cables.

A Bayesian inference-based approach for performance prognostics towards uncertainty quantification and its applications on the marine diesel engine

In this paper, the Bayesian analysis is introduced for the performance prognostics of the marine diesel engine to address the uncertainty of inferences and results by using probability distributions. Two Bayesian models are presented: the Bayesian neural networks model is used to implement health monitoring whilst the Bayesian logistic regression model quantifies the run-to-failure process of the marine diesel engine. The Variational Inference and the Markov Chain Monte Carlo algorithms learn and infer these two models’ parameters, respectively. Additionally, by analyzing characteristics of the marine diesel engine, the instantaneous angular speed signals are selected as the condition monitoring data, which can be used to indirectly predict the indicated mean effective pressure and further assess the performance of the marine engine. To verify the superiority of the proposed framework based on the Bayesian models and indirect estimation, operational datasets from a real engine under normal and fault conditions are acquired. The proposed framework and other conventional methods are adopted to analyze the attained data. The results demonstrate that the proposed approach is superior to the other methods and has the potential to be applied as an on-line condition monitoring tool for the performance prognostics of the marine diesel engine.

An accurate instantaneous angular speed estimation method based on a dual detector setup

Instantaneous angular speed (IAS), or ‘true IAS’, is an inherent signature directly related to the mechanical dynamics of rotor systems and has been employed extensively in different rotating machines. Due to various uncertainties, such as manufacturing error or the inaccurate installation of encoders, the acquired IAS signals often contains significant contents of ‘false IAS’ which can mask the small variations of IAS, lead to low accuracy and consequently affect the understanding of the dynamic behaviour of a rotor system. This study proposes a dual detector method to minimize the influence of encoder errors and hence obtain more accurate IAS estimation. Through theoretical study, it is proved that the false IAS induced by encoder errors from the two detectors have the same amplitudes but with a phase difference, whereas the true IAS components from the two detectors are identical. On this basis, an algorithm is developed firstly to acquire the encoder errors through a phase alignment operation and then estimate the true IAS after removing the estimated encoder errors. The proposed method is evaluated by both numerical simulations and experimental studies. The results show that the proposed method can more significantly suppress the encoder errors associated with encoder eccentricities in comparison with conventional reference methods, thereby yielding an accurate true IAS from the measurement. The proposed method can be particularly effective when the encoder has very low accuracy, allowing a more cost-effective IAS monitoring system to be achieved.

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.

Misfire Fault Diagnosis of Range Extender Based on Harmonic Analysis

For an Extended-Range Electric Vehicle (E-REV), the misfire failure of the range extender can result in working condition deterioration, mileage decrease, vibration and noise increase, and other adverse consequences. The relationship of the shaft instantaneous angular speed (IAS) signal and the misfire fault of the range extender was studied by harmonic analysis. Based on the theory of shafting torsional vibration, the range extender dynamics model was developed to analyze the changing trend of the shaft IAS theoretically. Then, the shaft IAS signal under different working conditions was simulated using a developed range extender rigid-flexible hybrid multi-body dynamics model. It is found that the 0.5-order harmonic phase and the amplitude of range extender IAS can be used as the characteristic parameters in misfire fault diagnosis, which has been verified by experiments on an engine bench.

Outliers Identification From Instantaneous Angular Speed Signal Generated by Zebra Tapes

Instantaneous angular speed (IAS) measurement using zebra tape has been presented as an advantageous tool for rotating machinery surveillance. Unfortunately, both butt joint and mounting imperfection of the zebra tape result in stripes with different widths, which cause the outliers appear in the acquired signal. This paper proposed a solution to accurately identify the outliers and define the angular displacement values represented by outliers in the condition of periodic fluctuation of speed. The procedure is based on K-means clustering method and Fourier series model. Specially, a series of algorithms take K-means clustering partitioning method as core, and is used for outliers identification; the Fourier series fitting model is used to analyze the angular displacement values represented by outliers. Experimental study was performed on a test rig to validate the method under different measurement conditions. The result of error analysis shows the effectiveness of the algorithm.

Measurement of Instantaneous Angular Displacement Fluctuation and its applications on gearbox fault detection

Recently, Instantaneous Angular Speed (IAS) measurement is successfully established and prevalently applied to a wide variety of machines due to the hypothesis that the speed fluctuation of rotating machinery carries plentiful dynamic responses. Nevertheless, exploration and application based on angular signal are still insufficient. Under the same hypothesis, in this paper, we introduced an extended algorithm named Instantaneous Angular Phase Demodulation (IAPD), together with the selection of optimal sideband family to extract the Instantaneous Angular Displacement Fluctuation (IADF) signal. In order to evaluate the performance of IADF signal, an effective approach was demonstrated using IADF signal to address the fault detection and diagnosis issue. After extracting the IADF signal, a much effective method was developed to deal with the large amount of data generated during the signal collection process. Then, we used the well-developed techniques, i.e., empirical mode decomposition (EMD) and envelope analysis, to undertake the signal de-noising and feature extraction task. The effectiveness and capability of the IADF signal were evaluated by two kinds of gearboxes under differentconditions in practice. In particular, the prevalent IAS signal and vibration signal were also involved and testified by the proposed procedure. Experimental results demonstrated that by means of the IADF signal, the combination of EMD and envelope analysis not only provided accurate identification results with a higher signal-to-noise ratio, but was also capable of revealing the fault characteristics significantly and effectively. In contrast, although the IAS signal had the potential ability to diagnose the serious fault, it failed for the slight crack case. Moreover, the same procedure even its improvements, i.e., ensemble empirical mode decomposition and local mean decomposition, all failed to recognize the faults in terms of vibration signals.

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.

A new strategy of instantaneous angular speed extraction and its application to multistage gearbox fault diagnosis

Owing to its unique benefits, Instantaneous Angular Speed (IAS) has become the focus of a great deal of research for monitoring mechanical parts of rotating machines in the past few years. However, the efficacy of IAS-based signal processing techniques essentially depends on the estimation method of IAS and the complexity of the mechanical system. When it is applied to complex systems like turbines, gearboxes, conventional IAS itself still has some flaws and insufficiencies such as longer data stream, quantization noise and structural noise. In order to address these issues, this paper proposes an alternative IAS estimation approach named Instantaneous Angular Phase Demodulation (IAPD) IAS together with an improved procedure involving signal reconstruction, empirical mode decomposition (EMD) and envelope analysis. Thereafter, two kinds of multistage gearboxes under different working conditions are developed to experimentally demonstrate the accuracy and effectiveness of the new IAS measurement. Analysis results suggest that the quantization noise can be significantly reduced or even avoided in the IAPD-IAS signal compared with the conventional IAS signal. Moreover, by means of the new procedure, the computational efficiency can be greatly improved and fault characteristics are dramatically enhanced in the envelope spectrum where deterministic frequency component and its harmonics corresponding to fault characteristics are displayed clearly.

Use of rotary optical encoder for firing detection in a spark ignition engine

Abstract Detection of spark ignition engine firing is an important parameter to understand proper and improper combustion inside the engine cylinder. The engine firing can be detected by direct measurement of in-cylinder pressure by using piezo-electric sensor. However, the cost of the sensor is really high. Therefore, in this paper, engine firing has been detected by analysis of instantaneous angular speed (IAS) signal from output shaft measured by cheap device like rotary encoder. The direct short time Fourier transform (STFT) is unable to detect engine firing clearly as the signal contains various frequencies (rotational frequency and its harmonics) other than engine firing frequency. Therefore, an algorithm has been developed based on complementary ensemble empirical mode decomposition (CEEMD) and followed by STFT and applied on IAS signal to detect engine firing. Moreover, a comparative study has been performed between laser vibrometer signal and IAS signal to understand the efficacy of these signals.

New procedure for gear fault detection and diagnosis using instantaneous angular speed

Besides the extreme complexity of gear dynamics, the fault diagnosis results in terms of vibration signal are sometimes easily misled and even distorted by the interference of transmission channel or other components like bearings, bars. Recently, the research field of Instantaneous Angular Speed (IAS) has attracted significant attentions due to its own advantages over conventional vibration analysis. On the basis of IAS signal's advantages, this paper presents a new feature extraction method by combining the Empirical Mode Decomposition (EMD) and Autocorrelation Local Cepstrum (ALC) for fault diagnosis of sophisticated multistage gearbox. Firstly, as a pre-processing step, signal reconstruction is employed to address the oversampled issue caused by the high resolution of the angular sensor and the test speed. Then the adaptive EMD is used to acquire a number of Intrinsic Mode Functions (IMFs). Nevertheless, not all the IMFs are needed for the further analysis since different IMFs have different sensitivities to fault. Hence, the cosine similarity metric is introduced to select the most sensitive IMF. Even though, the sensitive IMF is still insufficient for the gear fault diagnosis due to the weakness of the fault component related to the gear fault. Therefore, as the final step, ALC is used for the purpose of signal de-noising and feature extraction. The effectiveness and robustness of the new approach has been validated experimentally on the basis of two gear test rigs with gears under different working conditions. Diagnosis results show that the new approach is capable of effectively handling the gear fault diagnosis i.e., the highlighted quefrency and its rahmonics corresponding to the rotary period and its multiple are displayed clearly in the cepstrum record of the proposed method.

Non-intrusive rattle noise detection in non-stationary conditions by an angle/time cyclostationary approach

This work proposes an original non-intrusive approach to detect and quantify rattle noise in automotive gearboxes operating under non-stationary conditions by means of vibration or instantaneous angular speed measurements. Rattle noise is produced by vibro impacts between teeth of unloaded gears excited by the engine acyclism. It appears during acceleration or deceleration phases and its detection requires the analysis of non-stationary signals. In order to take advantage of the repetitive nature of the impacts, an angle/time cyclostationary approach is introduced. Rattle noise is thus characterized through the angle/time duality: the cyclic frequency expressed in events per revolution is directly linked to the periodicity of the impacts while their frequency content is expressed in Hertz. The proposed detection method uses an order/frequency spectral coherence and may be applied either on vibration signals or instantaneous angular speed signals. For validation purposes, a specific instrumentation of a gearbox is set up. The relative speed of the unloaded meshing gears is observed by means of optical encoders to directly detect the instants of impact which then serve as a basis for validation of the non-intrusive detection method proposed in this paper.

Fault detection in a multistage gearbox by time synchronous averaging of the instantaneous angular speed

The paper deals with an instantaneous angular speed (IAS) based algorithm for fault detection in a multistage gearbox. Fast Fourier transform (FFT) is a well established technique for analysis of a stationary signal. However, the IAS signal from the multistage gearbox is a combination of periodic signal and structure borne noise. This structure borne noise makes the IAS signal non stationary. Hence, FFT is no longer suitable for this non stationary signal analysis. Therefore in this paper, the IAS signal is time synchronously averaged with respect to lay shaft speed and then followed by FFT reveals the gear mesh frequency and rotational frequencies which are synchronous with the gearbox’s rotating speed. Thus, the algorithm can accurately and reliably detect the fault in multistage gearbox using the IAS. The paper also investigated the behavior of IAS signal for three different gearboxes (healthy, one tooth and two teeth broken) under two different speeds and three different loading conditions.