•Spectral Kurtosis performance declines as the SNR decreases or in presence of impulsive noise.•New method (Autogram) is proposed to cope with these drawbacks.•Autocorrelation (AC) of the squared ...envelope of the demodulated signal is used for this purpose.•Autogram takes advantage of periodicity of cyclostationarity of bearing defect signals.
Envelope analysis is one of the most advantageous methods for rolling element bearing diagnostics but finding a suitable frequency band for demodulation has been a substantial challenge for a long time. Introduction of the Spectral Kurtosis (SK) and Kurtogram mostly solved this problem but in situations where signal to noise ratio is very low or in presence of non-Gaussian noise these methods will fail. This major drawback may noticeably decrease their effectiveness and goal of this paper is to overcome this problem. Vibration signals from rolling element bearings exhibit high levels of second-order cyclostationarity, especially in the presence of localized faults. The autocovariance function of a 2nd order cyclostationary signal is periodic and the proposed method, named Autogram, takes advantage of this property to enhance the conventional Kurtogram. The method computes the kurtosis of the unbiased Autocorrelation (AC) of the squared envelope of the demodulated signal, rather than the kurtosis of the filtered time signal. Moreover, to take advantage of unique features of the lower and upper portions of the AC, two modified forms of kurtosis are introduced and the resulting colormaps are called Upper and Lower Autogram. In addition, a thresholding method is also proposed to enhance the quality of the frequency spectrum analysis. A new indicator, Combined Squared Envelope Spectrum, is employed to consider all the frequency bands with valuable diagnostic information and to improve the fault detectability of the Autogram. The proposed method is tested on experimental data and compared with literature results so to assess its performances in rolling element bearing diagnostics.
The implementation of condition monitoring and fault diagnosis system (CMFDS) on wind turbine is significant to lower the unscheduled breakdown. Generator is one of the most important components in ...wind turbine, and generator bearing fault identification always draws lots of attention. However, non-stationary vibration signal of weak fault and compound fault with a large amount of background noise makes this task challenging in many cases. So, effective signal processing method is essential in the accurate diagnosis step of CMFDS. As a novel signal processing method, empirical Wavelet Transform (EWT) is used to extract inherent modulation information by decomposing signal into mono-components under an orthogonal basis, which is seen as a powerful tool for mechanical fault diagnosis. Moreover, in order to avoid the inaccurate identification the internal modes caused by the heavy noise, wavelet spatial neighboring coefficient denoising with data-driven threshold is applied to increase Signal to Noise Ratio (SNR) before EWT. The effectiveness of the proposed technique on weak fault and compound fault diagnosis is first validated by two experimental cases. Finally, the proposed method has been applied to identify fault feature of generator bearing on wind turbine in wind farm successfully.
•Condition monitoring system for the wind turbine drivetrain in Nan'ao island wind farm is designed and developed.•Weak fault and compound fault diagnosis method for generator bearing of wind turbine is proposed based on empirical wavelet transform.•Experimental validation and engineering application is carried out to demonstrate the feasibility of the proposed generator bearing fault diagnosis method.
An interactive human‐machine interface (iHMI) enables humans to control hardware and collect feedback information. In particular, wearable iHMI systems have attracted tremendous attention owing to ...their potential for use in personal mobile electronics and the Internet of Things. Although significant progress has been made in the development of iHMI systems, those based on rigid electronics have constraints in terms of wearability, comfortability, signal‐to‐noise ratio (SNR), and aesthetics. Herein the fabrication of a transparent and stretchable iHMI system composed of wearable mechanical sensors and stimulators is reported. The ultrathin and lightweight design of the system allows superior wearability and high SNR. The use of conductive/piezoelectric graphene heterostructures, which consist of poly(l‐lactic acid), single‐walled carbon nanotubes, and silver nanowires, results in high transparency, excellent performance, and low power consumption as well as mechanical deformability. The control of a robot arm for various motions and the feedback stimulation upon successful executions of commands are demonstrated using the wearable iHMI system.
A transparent and stretchable interactive human machine interface (iHMI) based on patterned graphene (GP) heterostructures is developed. The conductive/piezoelectric GP heterostructures enable the iHMI to have high transparency, excellent performance, low power consumption, and superb mechanical deformability. The control of a robot arm for various motions and feedback stimulation upon successful executions of commands are demonstrated using the wearable iHMI system.
This paper outlines a simple label-free sensor system for the sensitive, real time measurement of an important protein biomarker of sepsis, using a novel microelectrode integrated onto a needle ...shaped substrate. Sepsis is a life threatening condition with a high mortality rate, which is characterised by dysregulation of the immune response following infection, leading to organ failure and cardiovascular collapse if untreated. Currently, sepsis testing is typically carried out by taking blood samples which are sent to a central laboratory for processing. Analysis times can be between 12 and 72 h making it notoriously difficult to diagnose and treat patients in a timely manner. The pathobiology of sepsis is becoming increasingly well understood and clinically relevant biomarkers are emerging, which could be used in conjunction with a biosensor to support real time diagnosis of sepsis. In this context, microelectrodes have the analytical advantages of reduced iR drop, enhanced signal to noise ratio, simplified quantification and the ability to measure in hydrodynamic situations, such as the bloodstream. In this study, arrays of eight (r = 25 µm) microelectrodes were fabricated onto needle shaped silicon substrates and electrochemically characterised in order to confirm successful sensor production and to verify whether the observed behaviour agreed with established theory. After this, the electrodes were functionalised with an antibody for interleukin-6 (IL-6) which is a protein involved in the immune response to infection and whose levels in the blood increase during progression of sepsis. The results show that IL-6 is detectable at physiologically relevant levels (pg/mL) with incubation times as short as 2.5 min. Electrochemical impedance spectroscopy (EIS) and differential pulse voltammetry (DPV) measurements were taken and DPV was concluded to be the more suitable form of measurement. In contrast to the accepted view for macro electrodes that the impedance increases upon antigen bind, we report herein a decrease in the micro electrode impedance upon binding. The small size of the fabricated devices and their needle shape make them ideal for either point of care testing or insertion into blood vessels for continuous sepsis monitoring.
•An array of 8 × 50 µm gold electrodes were fabricated onto a needle shaped substrate.•The device was electrochemically characterised to confirm successful fabrication and demonstrate microelectrode behaviour.•Interleukin 6 (IL-6) antibody was immobilised onto the electrode surface.•EIS & DPV measurements were demonstrated as effective methods for detection of antibody- antigen binding.•A dose response curve was established showing IL-6 could be measured at normal and elevated levels using DPV.
In this research, the operating parameters of proton exchange membrane (PEM) electrolyzer are optimized in order to decrease the required input voltage using Taguchi method. The considered parameters ...include the operating temperature, the pressure of cathode and anode, membrane water content, membrane thickness, and cathode and anode exchange current density. First, a thermodynamic model is developed for the PEM electrolyzer, and then the Taguchi method is applied for optimization of the electrolyzer performance. The signal to noise ratio (SNR) and the analysis of variance (ANOVA) method are also performed to determine the contribution ratio of effective parameters. The results reveal that the optimal condition is achieved at maximum working temperature, membrane water content, and cathode and anode exchange current density and at minimum membrane thickness, cathode pressure, and anode pressure. The anode exchange current density has considerable effect on the electrolyzer voltage with contribution of 67.15% while the membrane water content and the anode pressure have a minor influence with contribution of 1.1% and 0.42%, respectively.
•Optimization of working parameters of PEM electrolyzer.•Using of Taguchi algorithm for optimization.•Determining the contribution ratio of the effective parameters on the PEM electrolyzer performance.•ANOVA method is used to determine the contribution of effective parameters of PEM electrolyzer.
The interest for robust automatic modal parameter extraction techniques has increased significantly over the last years, together with the rising demand for continuous health monitoring of critical ...infrastructure like bridges, buildings and wind turbine blades. In this study a novel, multi-stage clustering approach for Automated Operational Modal Analysis (AOMA) is introduced. In contrast to existing approaches, the procedure works without any user-provided thresholds, is applicable within large system order ranges, can be used with very small sensor numbers and does not place any limitations on the damping ratio or the complexity of the system under investigation. The approach works with any parametric system identification algorithm that uses the system order n as sole parameter. Here a data-driven Stochastic Subspace Identification (SSI) method is used. Measurements from a wind tunnel investigation with a composite cantilever equipped with Fiber Bragg Grating Sensors (FBGSs) and piezoelectric sensors are used to assess the performance of the algorithm with a highly damped structure and low signal to noise ratio conditions. The proposed method was able to identify all physical system modes in the investigated frequency range from over 1000 individual datasets using FBGSs under challenging signal to noise ratio conditions and under better signal conditions but from only two sensors.
•Automated OMA methodology that does not require any user-defined thresholds.•System may have modes with arbitrary large damping ratios and mode shape complexities.•Method can be used with any parametric system identification algorithm.•Internal thresholds adapt to varying number of sensors and signal-to-noise ratios.
Graphene and the flexible Ni foam substrate are used in a facile hydrothermal process to control the formation of MoSe2-graphene composites. The effects of the content of graphene on the structure of ...MoSe2-graphene composites are investigated and the results indicate a suitable proportion of MoSe2 and graphene (7:1) is more beneficial to the charge transport and ion transfer owing to formation of unique porous layered structure. In this composite, abundant graphene nanosheets cover on the surface and interspace of MoSe2 bars homogeneously, leading to large specific surface area and plenty of macropores. As the electrode material of supercapacitors, the composites display a high specific capacitance of 1422Fg−1 and retain the specific capacitance of 100.7% after 1500 cycles. As expected, after charged at a current density of 5Ag−1, the composites can light up a miniature bulb for more than 70seconds. Moreover, the as-prepared materials exhibit a good catalytic activity toward the electrochemical oxidation of dopamine with a linear range of 0.01-10μM and the detection limit of 1.0nM in terms of the role of signal to noise ratio of 3:1 (S/N=3). These results indicate that the porous layered MoSe2-graphene composite in situ prepared on Ni foam can be applied for high-performance supercapacitors and electrochemical sensors.
We report the facile electrochemical fabrication of NiO nanoparticles (NPs)/Pt NPs/electrochemically reduced graphene oxide (NiO/Pt/ERGO) ternary composite modified electrode. The NiO/Pt/ERGO film ...was characterized by scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectrometry (EDS), atomic force microscopy (AFM), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). Cyclic voltammetry (CV) measurements reveal that NiO/Pt/ERGO can directly catalyze the oxidation of glucose and display enhanced current responses. This nonenzymatic sensor shows an excellent sensitivity of 668.2μAmM−1cm−2 (476mM−1cm−2), a linear range of 0.05–5.66mM (R=0.9996), a fast response time (2.5s), and a low detection limit (S/N ratio=3) of 0.2μM in alkaline medium. The nonenzymatic glucose sensor also exhibits superior stability and good anti-interference properties. The electrochemical detection results demonstrate that NiO/Pt/ERGO/GCE is a good candidate for glucose quantification.
In this study, the metal matrix composite materials were produced by hot press with various production parameters. The drilling experiments were performed on computer numerical control vertical ...machining centre without cutting fluid. Analysis of variance (ANOVA) was carried out in order to determine the effects of the production parameters on thrust force and surface roughness of metal matrix composites drilled with different feed rate. The effect of production parameters such as temperature, pressure and reinforcement ratio were investigated, and their effects were presented. The optimal level for each production parameters was determined by ‘Maximize the S/N ratio approach with a Taguchi design’. The test results revealed that the reinforcement ratio was the main factor affecting the surface roughness of the metal matrix composites for both feed rate. However, same singularity was not matter on thrust force due to close contribution rates of production parameters and high error rates of analysis. In literature, an increase on the thrust force and the surface roughness values was reported as the feed rate increased during machining. Nevertheless, in our MMCs system, the thrust force and the surface roughness values were in tendency of declination as the feed rate increased which makes this study more novel research.
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