Highly sensitive curvature sensor based on an asymmetrical Mach–Zehnder interferometer

Mach–Zehnder interferometers have attracted attention due to their flexible structures and extensive applications. In this study, a simple and highly sensitive curvature sensor based on an asymmetrical Mach–Zehnder interferometer comprising an up-taper and a peanut-like section was theoretically and experimentally characterized. A simulation was conducted to investigate the influence of structural parameters on the interference spectrum. Experimental measurements show that a high curvature sensitivity of ?35.3?nm/m^?1 from 1.35 to 2.20?m^?1 was obtained and high mechanical strength was demonstrated. The temperature–curvature cross-sensitivity of 4.44?×?10^?4?m^?1/°C was lower than the curvature resolution. The high curvature sensitivity and low temperature cross-sensitivity make this sensor a candidate for practical applications.     

Sensitivity-enhanced single-mode fiber-tapered hollow core fiber-single-mode fiber Mach–Zehnder interferometer for refractive index measurements

In this paper, a sensitive-enhanced single-mode fiber—tapered hollow core fiber—single-mode fiber Mach–Zehnder interferometer is demonstrated for refractive index sensing. The sensitivity was improved by forming an up-taper at the two splicing joints and concave cone in hollow core fiber. The up-tapered regions served as a more effective mode splitter/combiner, and the tapered hollow core fiber was used to generate a stronger evanescent field to enhance the interaction of light with the analyte. According to the principles of interference between the cladding and fundamental modes, we performed refractive index measurements. The experiments indicated that the proposed sensor has a high refractive index sensitivity of 214.97?nm/RIU in the refractive index range of 1.333–1.379, with a minimum refractive index measurement resolution of 9.3?×?10^?5. In addition, the sensor had a low temperature response of 2.96?pm/°C in the range from 50 to 85°C and a low cross sensitivity of 1.377?×?10^?5 RIU/°C. The proposed sensor is attractive for its high refractive index sensitivity, easy fabrication, low cross sensitivity, and good mechanical strength, making it of potential value for refractive index measurements for chemical and biological sensing.     

A 1.8-µm multiwavelength thulium-doped fiber laser based on a hybrid interference filter

A 1.8-µm tunable multiwavelength thulium-doped fiber laser based on a hybrid filter is proposed. In the designed ring-cavity fiber laser, the filter consists of one Sagnac loop and one dual-pass Mach–Zehnder filter. In the experiment, the lasing threshold is 155?mW, and a continuously tunable and stable single-wavelength laser could be realized with a minimum tuning interval of 2.1?nm within a scope of 22.5?nm. When an 1858-nm laser is obtained, the peak power fluctuation is less than 0.83?dB within 20 minutes at room temperature. By adjusting the polarization controller, stable dual-wavelength lasers are simultaneously achieved, and the peak power shift is less than 1.24?dB within a scan time of 20 minutes at room temperature. By changing the polarization state, stable triple-wavelength lasing is obtained, and the power fluctuation is less than 1.95?nm. In the experiment, the 3-dB linewidth of the laser is less than 0.4?nm.     

Fiber optic pressure sensor based on a single-mode fiber F–P cavity

In this paper, we propose and experimentally demonstrate a pressure sensor based on birefringent single-mode fiber F–P cavity using optical heterodyne. The proof of concept device consists of a light source, a polarizer controller, a modulator, a RF generator, a single-mode fiber Fabry–Perot cavity, a strain inspector, an erbium doped fiber amplifier, a filter, a polarizer, an optical spectrum analyzer, and a digital communication analyzer. The dynamic range of the proposed sensor is explored. The results demonstrate the new concept of fiber pressure sensors and the technical feasibility for pressure measurements.     

Roller bearing safety region estimation and state identification based on LMD–PCA–LSSVM

The basic idea of safety region is introduced into roller bearing condition monitoring. Local mean decomposition (LMD), principal component analysis (PCA) and least square support vector machine (LSSVM) are used comprehensively for the estimation of the safety region and the identification of normal state and faulty state for the roller bearing operational status. First, the vibration acceleration data was segmented according to a certain time interval and then Product Functions (PFs) of each piece of the data were obtained by LMD. Based on this, statistics control limits T² and SPE were extracted by PCA as roller bearings’ state characteristics. Finally, LSSVM was used for the estimation of the safety region of the roller bearing operation state, and multi-class LSSVM was used for the identification of the four normal, ball fault, inner race fault and outer race fault states. The results show that both the safety region estimation and state identification are accurate, and confirm the validity of the LMD–PCA–LSSVM method.     

Gear fault identification based on Hilbert–Huang transform and SOM neural network

Gear vibration signals always display non-stationary behavior. HHT (Hilbert–Huang transform) is a method for adaptive analysis of non-linear and non-stationary signals, but it can only distinguish conspicuous faults. SOM (self-organizing feature map) neural network is a network learning with no instructors which has self-adaptive and self-learning features and can compensate for the disadvantage of HHT. This paper proposed a new gear fault identification method based on HHT and SOM neural network. Firstly, the frequency families of gear vibration signals were separated effectively by EMD (empirical mode decomposition). Then Hilbert spectrum and Hilbert marginal spectrum were obtained by Hilbert transform of IMFs (intrinsic mode functions). The amplitude changes of gear vibration signals along with time and frequency had been displayed respectively. After HHT, the energy percentage of the first six IMFs were chosen as input vectors of SOM neural network for fault classification. The analysis results showed that the fault features of these signals can be accurately extracted and distinguished with the proposed approach.     

Brittle–ductile mode cutting of glass based on controlling cracks initiation and propagation

Owing to brittleness and hardness, functional glass is one of the most difficult to cut materials. This paper proposes a new machining method—brittle–ductile mode machining combining both properties of brittle breakage and plastic flow of glass. Edge-indention experiments are first conducted in order to deduce the laws of crack initiation and propagation in the process of glass cutting, then a single-straight tool with big inclination angle is designed for glass cutting based on the laws of crack initiation and propagation and properties of plastic flow. With this new tool, the lateral and subsurface cracks initiation can be suppressed, and media cracks propagate away from machined surface. At the same time, the requirements for machining glass in ductile manner can be fulfilled. Validation experiments show that highly efficient and precise glass cutting can be achieved at the cutting depth of sub-millimeter level, and an integral and crack-free surface with good finish can be obtained. This method overcomes the process restriction on critical cutting depth and tool feed for ductile regime turning technology and can be transferred to mass production.     

Phasor measurement based on IEC 61850-9-2 and Kalman–Filtering

This paper proposes a new technique for estimating phasors during the transient phenomena in the electrical power systems. Unlike traditional Phasor Measurement Units (PMUs) that estimates phasors at process level, the proposed technique estimates phasors at bay level. The estimation technique relies on a robust recursive Kalman–Filtering, which is employed for computing the phasors based on the time-critical IEC 61850-9-2 Sampled Measured Values casted by the substation Merging Units (MUs). Many evolution tests of the proposed technique have been carried out for both stationary and transient phenomena in power systems to determine the accuracy of the measurements obtained at various conditions. The proposed estimator can produce phasors at bay level with reporting rate of 100 frames per second, which is encouraged in IEEE Std C37.118 and can satisfy higher accuracies than provided by the traditional Phasor Measurement Units, which are 0.01 degree and 0.01% for phase and magnitude, respectively.     

Bearing remaining useful life estimation based on time–frequency representation and supervised dimensionality reduction

The extraction of ideal age feature is a challenging task in vibration-based bearing remaining useful life (RUL) estimation. Aiming at this problem, a new approach is proposed on the basis of time–frequency representation (TFR) and supervised dimensionality reduction. Firstly, S transform and Gaussian pyramid are employed to obtain TFRs at multiple scales. Textural features of TFRs are used as the high-dimensional features. Then, a two-step supervised dimensionality reduction technique, i.e. principal component analysis (PCA) plus linear discriminant analysis, is employed to reduce the dimensionality, in which the target dimension and number of classes are taken as variable parameters. Finally, the simple multiple linear regression model is utilized to estimate the RUL. Experimental results indicate that the proposed approach outperforms the methods using traditional statistical features and/or PCA. Additionally, variable conditions of load and speed should be considered in the future to further improve the proposed approach.     

High GVF and low pressure gas–liquid two-phase flow measurement based on dual-cone flowmeter

Parameter measurement of gas–liquid two-phase flows with a high gas volume fraction (GVF) has received great attention in the research field of multiphase flow. The cone meter, as a new proposed differential pressure (DP) meter, is increasingly being applied in flowrate measurement of gas–liquid two-phase flow. A dual-parameter measurement method of gas–liquid two-phase flow based on a dual-cone meter is proposed. The two-phase flow is investigated in a horizontal pipeline with high GVF and low pressure, and exists in the form of annular flow. By adding a second cone meter, both gas mass fraction (GMF) and mass flowrate are measured. The pressure drop performances of five different sized cones have been discussed to make a cooperating cone selection and efficiently position the dual-cone in the pipe. Dual-cone flowmeter experiments of 0.45 and 0.65 equivalent diameter ratio combination, and 0.65 and 0.85 equivalent diameter ratio combination are respectively carried out to analyze the linearity of two-phase flow multiplier with Lockhart–Martinelli parameter and obtain the dual-parameter measurement results. The relative experiment error of GMF, gas mass flowrate and total mass flowrate are respectively within ±7%, ±5% and ±10%. The relative error of the liquid phase is within ±10% when the liquid mass fraction is beyond 40%. The experimental results show that it is efficient to utilize this dual-cone method for high GVF and low pressure gas–liquid two-phase flow measurement.     

Reliability analysis based on the principle of maximum entropy and Dempster–Shafer evidence theory

The Probability density functions (PDFs) of some uncertain parameters are difficult to determine precisely due to insufficient information. Only the varying intervals of such parameters can be obtained. A method of reliability analysis based on the principle of maximum entropy and evidence theory was proposed to address the reliability problems of random and interval parameters. First, the PDFs and cumulative distribution functions of interval parameters were obtained on the basis of the principle of maximum entropy and Dempster–Shafer evidence theory. Second, the normalized means and standard deviations of interval parameters were obtained using the equivalent normalization method. Third, two explicit iteration algorithms of reliability analysis were proposed on the basis of the advanced firstorder and second-moment method to avoid solving the limit state function and obtain the reliability index. Finally, the accuracy and efficiency of the proposed methods were verified through a numerical example and an engineering case.     

Discrete-time direct adaptive control for robotic systems based on model-free and if–then rules operation

An adaptive controller for a class of nonlinear discrete-time systems is proposed for robotic systems under the assumption that the parameters and structure of system dynamics are all unknown. This controller is designed with the concept of model-free adaptive control requiring only the input–output of the unknown plant. The robotic system has been generalized to be a nonaffine discrete-time system under reasonable assumptions. The adaptive scheme called fuzzy rules emulated network (FREN) is implemented as a direct controller. The IF–THEN rules for FREN have been defined by the knowledge according to the relation between input and output of the robotic system without any compensator for the unknown mathematical model or nonlinearities. The underlying physical specifications of robotic system such as the operating range, maximum joint velocity, and so on have been considered to initialize the membership functions and adjustable parameters of FREN. The adaptation scheme is developed according to convergence analysis established for both adjustable parameters and the tracking error. The performance of the proposed controller is validated by the experimental system with a 7-degrees-of-freedom robotic arm operated in velocity-mode control.     

Identification of oil–gas two-phase flow pattern based on SVM and electrical capacitance tomography technique

The correct identification of two-phase flow patterns is the basis for the accurate measurement of other flow parameters in two-phase flow measurement. Electrical capacitance tomography (ECT) is a new visualization measurement technique for two-phase/multi-phase flows. The capacitance measurements obtained from the ECT system contain flow pattern information, and then six feature parameters are extracted. The support vector machine (SVM) has a desirable classification ability with fewer training samples. The inputs of the SVM are extracted feature parameters of different flow patterns. Simulation and static experiments were carried out for typical flow patterns. Results showed that this method is fast in speed and can identify these flow patterns correctly.     

Five-axis tool path and feed rate optimization based on the cutting force–area quotient potential field

Feed rate assignment in five-axis surface machining is constrained by many factors, among which a particularly critical one is the deflection cutting force on the tool: while a larger feed rate increases the machining productivity by shortening the total machining time, it nevertheless inevitably enlarges the deflection cutting force as well, which will cause the tool to be more prone to bending and the machine more prone to vibration, thus adversely degrading the surface finish quality. In this paper, we present a new five-axis tool path generation algorithm that strives to globally maximize feed rate for an arbitrary free-form surface while respecting a given deflection cutting force threshold. The crux of the algorithm is a new concept of the (cutting) force–area quotient function—at any cutter contact point on the surface, the maximal effective material removal rate (with respect to the deflection cutting force threshold) is a continuous function of the feed direction. This function induces a potential field on the surface and based on which an efficient tool path generation algorithm is designed. Preliminary experiments show that substantial reduction in total machining time can often be achieved by the proposed algorithm.     

Inverse determination of Johnson–Cook model constants of ultra-fine-grained titanium based on chip formation model and iterative gradient search

In this paper, a systematic approach on how to predict kinematic errors based on tolerance of machine tools’ guideways is introduced. Firstly, the truncated Fourier series function is applied to fit curve of guideways surface. Since geometric profile errors are regarded as a bridge between tolerance and kinematic errors of machine tools’ guideways, the mapping relationship between tolerance and geometric profile errors of machine tools’ guideways is formulated, and the mapping relationship between geometric profile errors and kinematic errors of guideways is established. Then, kinematic errors prediction model based on tolerance of guideways is subsequently proposed. Finally, simulation verification is conducted with this method. Simulation results show the range of the predicted kinematic errors (positioning error, y direction and z direction straightness error, roll error, pitch error, and yaw error) is 17.12 μm, 56.57 μm, 70.71 μm, 28.28 μrad, 141.42 μrad, and 113.14 μrad, respectively. In order to verify the feasibility and effectiveness of the presented method, a measuring experiment is carried out on guideways of a gantry-type five-axis milling machine tools by using a dual-frequency laser interferometer. The measured and identified discrete data can be fitted precisely by Fourier curve fitting method. The fitting results show the range of the measured kinematic errors is 16.96 μm, 59.43 μm, 68.63 μm, 28.65 μrad, 135.40 μrad, and 111.58 μrad, respectively. The maximum residual errors between the predicted and measured values of kinematic errors are 1.67 μm, 5.19 μm, 5.50 μm, 1.87 μrad, 9.81 μrad, and 7.07μrad, respectively. Comparing with the measured results of kinematic errors, residual errors are considerably small and can be neglected. Therefore, there is no doubt that this method is effective enough for predicting kinematic errors and can be used to replace the measurement of kinematic errors. In the design stage of machine tools, this approach is convenient for engineers to derive the distribution of kinematic errors. And its basic idea can be applied to other type of machine tools’ guideways.     

Effect of VC and (Ta,Nb)C on wear of WC–10Co based cemented carbides

Abstract

WC–Co cemented carbides, including small angular tungsten carbides particles, are used extensively to improve wear resistance. Some additives can affect mechanical and wear properties of these materials. In this study, the effect of VC and (Ta, Nb)C content on wear of WC–10Co were considered. The tests were performed at normal load of 230 N and sliding distance of 800 m up to 3200 m. Wear tests were carried out using dry sand/rubber wheel apparatus. Wear rate, standard and modified wear coefficients were calculated. The microstructures of prepared specimens were examined by optical microscopy. The morphological analysis of the worn surfaces was made by SEM. The results show that VC content has more effect than (Ta, Nb)C content on wear behaviour. Wear mechanism is different in the specimens, but removal of cobalt rich phase and fracture of carbide grains is clear in all of specimens. Abrasive wear is prevailing in all specimens.     

Non-stationary signal analysis based on general parameterized time–frequency transform and its application in the feature extraction of a rotary machine

With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time–frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.     

The influence of friction and wear on the generation of surface microprofile of steel–sintered friction powder based on copper in the course of operation in lubricated medium

The development of new compositions of sintered friction powders based on copper that operate in lubricated states should be based on deep knowledge of peculiar features of break-in and wear mechanisms of both counterbody and friction material. The obtained data have enabled the determination of the existence of the transferred bronze layer of friction material, the peculiarities of the generation of the surface microprofile of the counterbody during operation, these data can be useful upon assessing the thermal loading of the friction zone.     

Development of a high-voltage waveguide photodetector comprised of Schottky diodes and based on the Ge–Si structure with Ge quantum dots for portable thermophotovoltaic converters

This paper demontstrates the possibility of developing a high-voltage waveguide photodetector comprised of Schottky diodes and based on a Au/Ge — Si structure with Ge quantum dots pseudomorphic to a silicon matrix, which ensures an increase in the external quantum yield and open-circuit voltage. It is shown on this photodetector that there is a great increase and broadening in sensitivity up to λ = 2.1 μm, which coincides with the main radiation range of a black (gray) body at the emitter temperatures from 1200 to 1700 °C, practically used in thermophotovoltaic converters. This state of the ensemble of Ge quantum dots by means of molecular beam epitaxy can be obtained only under the condition of low growth temperature (250–300 °C). It is established that, below the Si absorption edge, photoresponse on the photodetectors under consideration is determined by two main mechanisms: absorption on the ensemble of Ge quantum dots and Fowler emission. It is shown by the analysis of the Raman scattering spectra on the optical photons of Ge–Si structures that the quantum efficiency of photodetectors based on them in the first case is due to the degree of nonuniform stress relaxation in the array of Ge quantum dots. The photoresponse directly associated with the Ge quantum dots is manifested on Schottky diodes with a superthin intermediate oxide layer SiO₂, which eliminates the second mechanism. In further development, the proposed photodetector architecture with pseudomorphic Ge quantum dots can be used both for portable thermophotovoltaic converters and fiber-optic data transmission systems at wavelengths corresponding to basic telecommunication standards (λ = 0.85, 1.3 and 1.55, 1.3, and 1.55 μm) on the basis of silicon technologies.