Yarn Diameter Measurements Using Coherent Optical Signal Processing

A method to measure variations in yarn diameter using coherent optical signal processing based on a single photodiode plus additional electronics is described. The approach enables us to quantify yarn irregularities associated with diameter variations which are linearly correlated with yarn mass variations. A robust method of system auto-calibration, eliminating the need for a temperature and humidity controlled environment, is also demonstrated. Two yarns that span the diameter ranges commonly used in the textile industry were used to verify the system linearity and ascertain its resolution. The results obtained have been verified using image analysis. Moreover, a diameter characterization was performed under real-world conditions for three types of yarns and a correlation with capacitive measurements is also presented. The system with sensitivity of 0.034 ${rm V}/{rm mm}^{2}$ is able to detect minute variations of yarn diameter and characterize irregularities starting at very low thresholds (commercial systems generally characterize variations of 30% or greater relative to the average value).      

Yarn Hairiness Characterization Using Two Orthogonal Directions

We demonstrate that one can adequately characterize yarn hairiness by imaging the yarn along a single projection direction using coherent optical processing. A system that simultaneously characterizes the yarn hairiness along two orthogonal projection directions was constructed. Provided that a sufficiently high number of yarn segments are sampled, a strong statistical correlation is obtained between the results in each direction. The resulting images are generated using coherent optical signal processing with a Fourier high-pass spatial filter. This filter blocks the yarn core and produces a signal that highlights the sharp transitions in the transmission of the yarn. Essentially, only the small fibers responsible for the hairiness and the yarn core contours are present. Experimental results are presented for a 62-g/km yarn possessing a high degree of hairiness.      

Yarn Diameter and Linear Mass Correlation

This paper focuses on the determination of the statistical correlation between yarn diameter and yarn linear mass. The experimental methods employed are based on optical analysis and on image processing techniques applied to electron microscope images. Several different cotton yarns were examined over a wide range of yarn linear masses. The results indicate that diameters predicted by the relationship commonly quoted in the literature can be as much as 62% smaller than those experimentally observed.     

Preparation of short submicron-fiber yarn by an annular collector through electrospinning

Electrospinning is known to be a unique method to prepare continuous nanofibers. Its brevity and extensive application in obtaining non-woven membrane, nanofiber bundle or yarn have attracted increasing attention throughout the world. Especially, how to obtain aligned nanofiber array by a modified electrospinning process has been a hot topic in recent years. An annular collector with the cross-section of circle to obtain fibrous yarn through electrospinning, pre-drafting, and subsequent twisting was reported in this investigation. Fiber arrangement in bundle and mechanical properties of the yarn were given by scanning electron microscope and strength tester. Results showed that the pre-drafted bundle consisted of highly-aligned submicron fibers with the diameter from 750 to 1000 nm. In addition, it was found that the yarn is unsuitable for clothing, but may be applied in many other fields, such as composites, tissue engineering, and catalyst materials.     

Consolidation of GF/PP commingled yarn composites

Consolidation quality and corresponding mechanical properties of GF/PP thermoplastic composites manufactured from a commingled yarn system have been investigated. A small compression mould with a laboratory hot press was used to apply the different processing variables (i.e. pressure, holding time and processing temperature). The consolidation quality of finished samples was characterized mainly through (a) microscopic studies of the material's microstructure, (b) density measurements, and (c) evaluations of mechanical properties using a small transverse flexure testing facility. A model for qualitatively describing the impregnation and consolidation processes in commingled yarn based thermoplastic composites was applied to predict variations of void content during consolidation and the time, temperature and pressure required to reach full consolidation. Based on a desired, minimum level of void content (X _v =2.0%), optimum processing windows for manufacturing of GF/PP commingled yarn composites are suggested.     

MIMO线性系统输入输出信号统计特征的双谱评定方法

基于高阶统计量具备处理随机信号的特性,提出了一种利用三阶谱(双谱)评定MIMO线性系统时域输入输出信号统计特征的新方法。通过建立线性系统双谱数学模型,根据系统响应、所测得的频响函数以及离散信号的双谱数值估计算法,经逆运算获得系统的双谱驱动信号,随后利用高阶谱对高斯随机信号的盲性判定其输入信号的高斯性。将上述方法与采用传统相位随机化法(对功率谱添加随机相位)所获得的驱动信号分别应用于一悬臂梁模拟控制系统中,通过对输入信号的分析及控制结果的比较,发现基于双谱所生成的时域随机驱动信号呈现出较强的非高斯性且收敛速度更快。对于输出信号统计特征的评定,提出从输入信号与系统频带接近的程度入手,再次利用高阶统计量对高斯随机信号的盲性进行定性判定,对于无法判别满足何种非高斯统计分布特征的,不管是对于输入信号还是输出信号,一律采用绘制信号的概率分布特征曲线进行定量评定。     

SSE- and Noise-Optimized InGaAs Radiation Thermometer

For measurements of radiance temperatures in the range from 150°C to 1,000°C, low uncertainties in the temperature measurements can be achieved by using near-infrared InGaAs radiation thermometers. The design and construction of the NIST near-infrared radiation thermometer (NIRT) that is optimized for low size-of-source effect (SSE) and noise-equivalent temperatures are described. The NIRT utilizes a 50 mm diameter achromatic objective lens with low scatter that images a 4.5 mm diameter spot at a distance of 50 cm from the objective in an on-axis design. A Lyot stop is implemented in the design with the aperture stop placed after the field stop resulting in a collection f/12. A 3 mm diameter InGaAs detector is cooled to − 70°C using a four-stage thermoelectric cooler to obtain high-shunt resistance for linear, low-noise operation at high transimpedance amplifier gains. For thermal and structural stability, the optical components are placed on four, 15 mm diameter graphite-epoxy rods making the optical throughput stable. Optical ray tracing with a commercial program is used to determine the Strehl ratio and other imaging parameters. A possible approach for a detector-based temperature scale in this range which could result in 10 mK (k = 2) thermodynamic temperature uncertainties at the In-point is discussed.     

Studies on the Reduction of Coefficient of Variation: A Case Study

In a spinning mill, yarn is the final product. Linear density expressed in terms of count is one of the important characteristics of yarn. Because variability of textile strands increases as the linear density increases, the variability in the count is often measured in terms of coefficient of variation (CV)%. The yarn with a high CV% of count leads to a higher end breakage rate during the spinning and subsequent weaving/knitting operations, and consequently, results in lesser productivity and poorer appearance quality of the woven/knitted fabric. When this woven/knitted fabric is dyed, uneven shades are generated. Because the production of yarn involves processing of raw cotton in multimachines at multistages, possible sources that lead to a high CV% of count are many. Enrick's (1960) analysis procedure, which is based on the modification of the range method for analysis of variance, is used conventionally for detecting the stages where excessive “between-machine” differences are present. When the CV% of count is inflated due to the generation of systematic variation in any machine or introduction of high variability by any machine, this inflation remains undetected when using Enrick's procedure. The case study presented here demonstrates that a step-by-step analysis of linear densities of different stage-outputs starting from yarn to card sliver, using appropriate nested design models along with Duncan's multiple range test, is very useful in detecting all possible sources of a high CV% of count of yarn.     

Analysis of Barkhausen noise using wavelet-based fractal signal processing for fatigue crack detection

The paper presents new approach to Barkhausen noise signal processing for detection of fatigue crack. Barkhausen noise signal from mild steel samples under axial fatigue is investigated using fractal signal processing, particularly wavelet variance method. Based on repeatability analysis new algorithm is developed and applied to acquired signals. The influence of fatigue on fractal characteristics of Barkhausen noise is analyzed. Signal analysis reveals significant and repeatable changes in wavelet variance, spectral parameter and estimated Hurst exponent just after crack initiation. The results demonstrate high potential of fractal analysis of Surface Barkhausen noise applied to fatigue crack initiation detection.     

On-line tool condition monitoring in face milling using current and power signals

The vast majority of tool condition monitoring systems use the cutting force as the predictor signal. However, due to prohibitive cost to performance ratios and maintenance and operational problems, such methods are not favoured by industries. In this paper, a method for continuous on-line estimation of tool wear, based on the inexpensive spindle motor current and voltage measurements, is proposed for the complex and intermittent cutting face milling operation. Sensors for these signals are free from problems associated with the cutting forces and the vibration signals. Novel signal processing strategies have been proposed for on-line computation of useful features from the measured signals. Feature space filtering is introduced to obtain robust and improved predictors from the extracted features. A multiple linear regression model, built on the filtered features, is then used to estimate tool wear in real-time. Very accurate predictions are achieved for both laboratory and industrial experiments, surpassing earlier results using cutting forces and estimation methods based on complex methodologies such as artificial neural networks.     

Application of an FFT-based algorithm to signal processing of LVDTposition sensors

This paper presents a new method for signal processing of linear variable differential transformer (LVDT) position sensors. Based on a spectral estimation of the differential secondary signal, the method has been implemented using a floating-point digital signal processor (DSP) and a 14-bit analog interface circuit (AIC) to generate the primary signal and to process the primary and the secondary signals. Compared with the classic solution based on synchronous demodulation the resulting accuracy is improved. Heavy filtering is not required, except for the anti-aliasing function. The algorithm decreases the measuring time and offers diagnostic capability     

Discrete Wavelet Transform Based Measurement of Inner Race Defect Width in Taper Roller Bearing

Local bearing defect monitoring and measurement has been a challenging area of research for profitable use of motion. A technique based on decomposition using Symlet wavelet is implemented for measuring inner race defect width in a taper roller bearing. It is difficult to estimate the defect width in inner race because defect moves continuously with respect to accelerometer. The bursts are selected from the signal for measuring the defect width on the basis of their amplitude. The degree of ambiguity in detecting the entry point in the groove gets reduced by using Symlet5 wavelet based decomposition which is almost linear phase nature and hence, sharpness in the signal gets maintained even in case of sudden change induced in raw signal. The technique has been successfully implemented for measuring defect width ranging from 0.4714 to 1.8145 mm. The measurement of defect width has also been verified by image analysis. Maximum difference in measurements has been found to be 6.68 % for the defect width of 0.4714 mm at no load condition and this gets reduced to 1.21 % with increase in load. This method has also potential in dimension measurement of surfaces having dissimilar and uneven surface characteristics.     

Oxidation kinetics of metallic inclusions in a composite with an Al2O3‐ZrO2 matrix

Many studies have been conducted to obtain toughness in ceramic‐ceramic and metal‐ceramic composites, using new processing techniques or by addition of metallic inclusions in the ceramic matrix. The oxidation behavior of metallic inclusions, niobium and nickel metallic particles embedded in an Al₂O₃‐ZrO₂ matrix, was measured through thermogravimetric analysis. In this work oxidation mechanisms were proposed and kinetic parameters defined using a software module for the kinetic analysis of thermal measurements by means of multiple linear or non‐linear regression. The morphology of the oxidized surfaces of the samples was examined by using scanning electron microscopy. Oxides were identified by X‐ray diffraction. The oxidation kinetics of metallic particles of niobium and nickel are highly complex, for they depend on various factors, i.e., metal’s characteristics, processing of the composite, oxygen diffusion through the matrix, grain boundaries, and heating rate applied to the material.     

The Effectiveness of Multichannel Electrodes on Drilling Blind Holes on Inconel 718 by EDM Process

This study presents an experimental study on making through and blind holes on Inconel 718 by hole drilling electrical discharge machining process. Several holes of Ø2 mm were drilled at specific levels of process parameters using tubular brass electrodes having different channel configurations. Machining performances were analyzed on the basis of material removal and electrode wear. Measurements of depth, diameter, overcut, and taper of holes were performed based on scanning electron microscope photographs to evaluate geometrical and dimensional accuracies of drilled holes. Surface roughness measurements as well as energy-dispersive X-ray analyses were conducted to examine characteristics of machined hole surfaces. The research reveals that drilling holes using multichannel electrodes exhibit superior results in aspects of lower drilling time, better dimensional accuracy, and improved surface quality.     

Study of elastic waves of acoustic frequencies generated by surface partial discharges of solid insulators in vacuum

The paper presents studies on the electrical properties of cylindrical shape samples of insulators made from polyamide, epoxy resin, polymethyl methacrylate, and electrical porcelain, located in vacuum at a pressure of 0.1 mPa. The insulator samples had a diameter of 20 mm and a height of 1-10 mm. The study was performed with an alternating voltage of 50 Hz in the range up to 70 kV (peak). The examination has shown that partial discharges on the surface of the insulator generate elastic waves of acoustic frequency. The waves may be used to locate the position of the partial discharges by means of suitably sensitive equipment. During the measurements the following parameters of the acoustic signals have been recorded: the largest amplitude of signal, the number of signal amplitudes exceeding the discrimination level, the rate of signals, the number of events the envelopes of which exceed the discrimination level, the rate of events and the root mean square value of signal. It was found that for purposes of determining the voltage threshold necessary for occurrence of acoustic activity, a measurement of the largest amplitude of a given acoustic signal is the most appropriate. Nevertheless, for forecasting a flashover occurrence of examined insulators a measurement of the root mean square value of acoustic emission signal may be also effectively used. Values of both of these parameters significantly increased just before an instance of surface flashover.     

空气中PM2．5颗粒形成过程初探

文章主要研究了黑色金属冶炼及压延加工业PM2．5的排放特征,采用ELPI（Electrical Low Pressure Impactor）静电低压撞击器对烟气中的颗粒的粒数分布及质量浓度分布进行在线分析,通过自动烟尘测试仪采集样品,并对颗粒物的形貌、聚集特性、化学组分及物相组成等进行了深入研究,为中国工业排放PM2．5颗粒的来源分析及PM2．5对健康、气候的影响提供了有力的数据依据。     

Adaptive ultrasonic measurement of blood vessel diameter and wall thickness: theory and experimental results

An adaptive ultrasonic technique for measuring blood vessel diameter and wall thickness is presented. This technique allows one to use a target-specific transmitted waveform/receiver filter to obtain a larger signal-to-noise ratio (SNR) in the received signal than conventional techniques. Generally, SNR of a received wave increases as the intensity of the transmit wave increases; however, because of the FDA limitations placed on the amount of transmit energy, it is important to be able to make the most efficient use of the energy that is available to obtain the best possible SNR in the received signal. Adaptive ultrasonic measurement makes the most efficient use of the energy that is available by placing the maximum amount of energy in the largest target scattering mode. This results in more energy backscatter from a given target, which leads to a higher SNR in the received waveform. Computer simulations of adaptive ultrasonic measurement of blood vessel diameter show that for a SNR of 0 dB in the transmitted waveform, the standard deviation of the diameter measurements for a custom-designed transmitted waveform is about two orders of magnitude less than the standard deviation of the diameter measurements using more conventional waveforms. Diameter and wall thickness measurement experiments were performed on a latex tube and a bovine blood vessel using both custom-made and conventionally used transmitted waveforms. Results show that the adaptively designed waveform gives a smaller uncertainty in the measurements. The adaptive ultrasonic blood vessel diameter and wall thickness measuring technique has potential applications in examining vessels which are either too deep inside the body or too small for conventional techniques to be used, because of the low SNR in the received signal.     

Signal processing for in-line inspection of gas transmission pipelines

Gas transmission pipelines in the United States are primarily inspected using the magnetic flux leakage (MFL) nondestructive evaluation (NDE) technique. However, accurate analysis of the NDE signals in terms of the underlying defects requires a thorough knowledge of various operational parameters such as B-H characteristics of the pipe wall, the velocity of the scanning tool, etc. In certain situations, information about such operational parameters is either absent or hard to obtain. Appropriate signal processing techniques can be applied to the raw MFL signals to ensure that defect characterization is possible in spite of local variations in the test situation. This paper presents two such signal processing methods—one, to compensate the MFL signal for variations in pipe-material grade, and the other to remove the effects of signal distortion that occur due to the velocity of the scanning device.     

Ultrasonic densitometer using a multiple reflection technique

This work presents recent improvements in a density measurement cell with a double-element transducer that can eliminate diffraction effects. A new mechanical design combined with the use of more appropriate materials has resulted in better parallelism between interfaces, more robust assembly, and chemical resistance. A novel method of signal processing, named the energy method, is introduced to obtain the reflection coefficient, reducing sensitivity to noise and improving accuracy. The measurement cell operation is verified both theoretically, using an acoustic wave propagation model, and experimentally, using homogeneous liquids with different densities. The accuracy in the density measurement is 0.2% when compared with the measurements made with a pycnometer.