•Array signal processing is highly appreciated for camera-based vibration measurements.•Correlated pixels can be used to increase output SNR via constructive interference.•A sinusoid-based piecewise ...function is proposed to approximate mode shape.•An adaptive filtering algorithm is developed to match mode shape and enhance signal power.
As a non-contact and full-field testing method, high-speed camera-based modal analysis has become a feasible and acknowledged approach. However, extracting small displacements from noisy images has experienced high level of difficulty, especially in high frequency range. This paper proposes a novel adaptive spatial filtering (beamforming) algorithm to extract the displacement signals using high-speed camera. In the proposed algorithm, one pixel is considered as a sensor measuring displacement and a set of pixels are therefore taken as the elements of sensor array. Then, an adaptive spatial filtering acting on this sensor array is proposed. The proposed approach mainly includes three steps. Firstly, a set of pixels are selected to compose a sensor array according to signal to distortion and noise (SINAD). Secondly, a node/antinode searching scheme is proposed based on sinusoid-based piecewise functions, which works as an adaptive filter to match mode shape and enhance modal displacement. Finally, the output of spatial filtering is adopted as the system response for the identification of modal parameters. To validate the performance of the proposed method, simulation and experiment studies are conducted based on measuring the vibration model properties of a free-free beam, which includes a comparison with LK optical flow method and conventional accelerometer-based method. The results show that the SNR of estimated displacement and computational efficiency is significantly improved without using additional sensors. The proposed method paves a way for broadening the applications of using high-speed camera for full-field vibration measurements.
•The friction heat generation of the spiral bevel gear is analysed by FE method.•The distribution of the contact stress and heat flux on the tooth are evaluated.•Both the steady state and transient ...temperature fields are explored.•The contact patterns are obtained for better efficiency and anti-scuffing capacity.
Friction loss and scuffing failure are two primary research subjects in improving the performance of spiral bevel gears. Aimed at improving the thermal characteristics with machine-setting parameter adjustment, a coupled thermo-elastic 3D finite element model has been developed to analyse the frictional heat generation and transient thermal behaviour of spiral bevel gears. The heat fluxes due to friction effects are applied to the gear tooth to investigate thermal characteristics and prediction of transient temperature fields. The resulting thermal characteristics agree with earlier work, thus verifying the model and numerical approach. This study permits an in-depth understanding of the temperature fields, together with the frictional heat generation process. Furthermore, by investigating the transient thermal behaviour among different pinion machine-setting parameters, the tilted and extended tooth contact pattern achieved by adjusting the machine-setting parameters can result in an optimal tooth contact pattern that produces a uniform temperature field of much lower value, thereby achieving higher efficiency of transmission along with stronger anti-scuffing performance.
Acoustic emission (AE) signals are useful for the condition monitoring of mechanical seals as tribological regimes affect the AE signatures. In this paper the investigation develops a mathematical ...model that can predict the energy of an AE signal under different tribological regimes. The developed model has been validated with experimental studies and satisfactory results have been perceived. Therefore, the model has strong potential to be used to obtain tribological behaviour of mechanical seals and hence develop a reliable and accurate condition monitoring system under varying operating conditions.
•The paper developed a comprehensive model of the AE energy discharge under different tribological regimes of mechanical seals.•To derive a comprehensive model that can explain the tribological behaviour of mechanical seals, the proposed equations for AE source mechanisms have been combined.•Any deviation from the predicted trends can be considered as a developing fault that may lead to failure of mechanical seals.•Some radial scratches were made on the mating ring to simulate leakage in the hydrodynamic lubrication regime. A significant difference has seen observed between the measured and predicted signals.
The nonlinearity degree of the system can be sensitively revealed by the methods based on Nonlinear Output Frequency Response Functions (NOFRFs). However, there is a lack of methods based on NOFRFs ...that work with only response signals under stochastic excitation, which limits the application of NOFRFs in practical engineering. In this study, a new concept of normalized NOFRFs is proposed, and a corresponding estimation method that employs only stochastic output response is established. Firstly, a method of estimating NOFRFs by Power Spectral Density (PSD) is established, and therefrom the normalized NOFRFs and a corresponding nonlinearity index are proposed. Then, by taking the PSD of the excitation signal as the input and the PSD of the response signal as the output, a general estimation method of normalized NOFRFs is built, and an output measured only estimation method of normalized NOFRFs is further deduced and established. In these two estimation methods, the assumption of white noise excitation is not required, and the estimated results are insensitive to the change of excitation intensity. Finally, the experiments of fatigue damage detection of three-point bending fatigue steel plate specimens and reducer box cases under stochastic excitation are carried out. The results demonstrate that, compared with the NOFRFs, the degree of fatigue damage can be effectively revealed by the normalized NOFRFs with output.
•A method for estimating the NOFRFs by PSD is proposed.•Normalized NOFRFs and associated nonlinearity index are proposed.•Output measured only estimation method of normalized NOFRFs is established.•Assumption of white noise excitation is not required in the estimation method.•Fatigue damage can be revealed by normalized NOFRFs as well as the NOFRFs.
This paper investigates the mechanism and characteristics of Acoustic Emission (AE) generated from the dynamic Fluid-Asperities Shearing (FAS) in the hydrodynamic lubrication (HL) regime. Firstly, a ...FAS model is derived to take into account the dynamic effect of surface asperities. Then, the influence of surface profiles, lubricants and operating conditions are illustrated on AE characteristics, i.e. magnitudes and frequency bandwidths. It has been found that the correlation length of surface roughness parameters and shear rate are two main factors affecting FAS behaviours and consequently AE characteristics. Finally, the corresponding experiments are carried out based on a rheometer rig, which validate the predictability of the model and new findings, paving the foundation for developing AE based monitoring techniques.
•AE generated from the dynamic fluid-asperity shearing in the hydrodynamic lubrication is analysed.•A model of dynamic FAS regarding the spatial power spectral density of a non-Gaussian surface is derived.•The frequency bandwidth of AE signals depending on the shear rate and the correlation length is verified.•The simulations and the experimental measurements at the different conditions validate the predictability of the model.
Abstract
Online monitoring of cutting conditions is essential in intelligent manufacturing, and vibrations are one of the most effective signals in monitoring machining conditions. Generally, ...traditional wired accelerometers should be installed on a motionless or stable platform, such as a tool holder or lathe bed, to sense vibrations. Such installation methods would cause the signals to suffer more serious noise interferences and a low signal-to-noise ratio, resulting in less sensitivity to valuable information. Therefore, this study developed a novel three-axis wireless on-rotor sensing (ORS) system for monitoring the turning process. The Micro Electromechanical System (MEMS) accelerometer sensor node can be mounted on a rotating workpiece or spindle rotor and is more sensitive in detecting the vibrations of the entire rotor system without any modification of the lathe system and interference in the cutting procedure. The processor, data acquisition, and Bluetooth Low Energy (BLE) 5.0+ modules were developed and debugged to cooperate with a piezoelectric triaxial accelerometer, with a vibration amplitude not larger than ± 16 g. A series of turning tests were conducted and the results were compared with those from the commercial wired accelerometers, which proved that the ORS system can measure the vibration signal of the rotor system more effectively and sensitively than wired accelerometers, thus demonstrating the accurate monitoring of machining parameters.
Epicyclic gearboxes are prevalent in a variety of important engineering systems such as automotive, aerospace, wind turbines, civil equipment and industrial robots owing to the merits of compact ...structure and high power density. To ensure the productivities of such important systems, condition monitoring techniques are being actively studied to resolve the challenge of varying transmission paths and multiple modulations in vibration signals acquired from ring gear housing. This paper proposes a new Modulation Signal Bispectrum (MSB) Enhanced Squared Envelope method to analyse the vibration signals acquired by a special On-Rotor Sensing (ORS) transducer that is mounted on the shaft of an epicyclic gearbox. A vibration signal model of ORS measurements from epicyclic gearboxes is presented to show the multiple modulation influences. Moreover, inevitable noise influences are also investigated on the conventional squared envelope and the state-of-the-art spectral correlation analysis. On this base, MSB is introduced to suppress these influences for accurately extracting equally spaced harmonics in the squared envelope and is then integrated to isolate fault signatures, allowing effective fault detection and diagnosis of epicyclic gearboxes, which lead to novel contributions of an MSB Enhanced Squared Envelope (MSB-ESE) approach. An experimental study of compound epicyclic gear faults was conducted to demonstrate the superior performance of MSB-ESE along with the special ORS technique in detecting and diagnosing the compound faults on sun and planet gears.
This paper proposes a novel multiple amplitude modulation and frequency modulation (AM–FM) demodulation method based on local modulation signal bispectrum (LMSB), which can demodulate the fault ...features of different components from the gearbox signal with multi-mesh frequency bands and multi-modulation components. Firstly, the collected measurement signal is decomposed into a series of sub-band signals, and the generated sub-band signals are demodulated by modulation signal bispectrum (MSB), which realizes the simultaneous demodulation of multi-mesh frequency bands and multi-modulation components. Subsequently, each sub-band signal resulting from MSB demodulation is synchronously averaged to generate the LMSB, which removes random noise and interference frequencies from the sub-band signals. Finally, the periodic modulation intensity (PMI) is utilized to evaluate the ability of the LMSB to demodulate multi-component signals with AM–FM components. The effectiveness of LMSB in processing multi-component signals with AM–FM components is demonstrated by numerical simulation signals and experimental analysis. Analysis results demonstrate the superiority of LMSB in multiple AM–FM demodulation compared with MSB, envelope analysis (EA) and Teager energy operator (TEO). This research provides a novel perspective for gearbox fault detection.
Transient impulses caused by local defects are critical for the fault detection of rotating machines. However, they are extremely weak and overwhelmed in the strong noise and harmonic components, ...making the transient features are very difficult to be extracted. This paper proposes an adaptive multi-scale improved differential filter (AMIDIF) to enhance the identification of transient impulses for rotating machine fault diagnosis. In this scheme, firstly, the AMIDIF is performed to decompose the measured signal of rotating machine into a series of multi-scale improved differential filter (MIDIF) filtered signals. Subsequently, in view of the MIDIF filtered signals exhibit varying extents of validity in revealing fault features, a weighted reconstruction method using correlation analysis is proposed in which the weighted coefficients are counted and distributed to the corresponding MIDIF filtered signals to highlight the effective MIDIF filtered signals and weaken the invalid ones. Finally, the transient impulse components of rotating machinery are obtained by multiplying the weighted coefficients and the MIDIF filtered signals under different scales. Furthermore, the fault types of rotating machines are inferred from the fault defect frequencies in the envelope spectrum of the transient impulses. Simulation analysis and experimental studies are implemented to verify the performance of the AMIDIF compared with the state-of-the-art methods including spectral kurtosis (SK), multi-scale average combination different morphological filter (ACDIF) and multi-scale morphology gradient product operation (MGPO). The results prove that the AMIDIF has excellent performance in extracting transient features for rotating machines fault diagnosis.
•An AMIDIF is developed for transient impulse enhancement.•AMIDIF can extract the bidirectional impulses in the signal at the same time.•Correlation coefficient is used to optimize the weighted coefficient in AMIDIF.•Performance of the AMIDIF is validated by simulation and experimental cases.
Weak fault feature extraction is of great significance to the fault diagnosis of rolling bearing. At the early stage of defects, fault features are usually weak and easily submerged in strong ...background noise, which makes feature information extremely difficult to be excavated. This paper proposes an iterative morphological difference product wavelet (MDPW) to address this issue. In this scheme, firstly, the morphological difference product filter (MDPF) is developed using the combination morphological filter-hat transform operator and difference operator. The MDPF is then incorporated into a morphological undecimated wavelet to construct the MDPW, which can achieve noise suppression and fault feature enhancement. Subsequently, the optimal iteration numbers that influence the performance of MDPW is determined using the fault severity indicator, which effectively extracts periodic impulse related to the failure of rolling bearing. Finally, the fault identification is inferred by the occurrence of fault defect frequencies in the MDPW spectrum with the optimal iteration numbers. The validity of the iterative MDPW is evaluated through numerical simulations and experiment cases. The analysis results demonstrate that the iterative MDPW has higher diagnosis accuracy than existing algorithms (e.g., adaptive single-scale morphological wavelet and weighted multi-scale morphological wavelet). This research provides a new perspective for improving the weak fault feature extraction of rolling bearing.
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