查看更多>>摘要：A novel dew point measurement method has been developed by using a temperature sensor covered by humidity sensitive thin film (referred as HSTF). The measurement mechanism is that the mutation of the temperature-time curve caused by the thermal effect of the HSTF can be used to detect dew points. The automatic measurement system of dew point and relative humidity (RH) based on LabVIEW is built. Compared with the existing dew point detection methods, the technique has the advantages of simple device and anti-interference. The experimental data were compared with the reference values with the satisfactory results, relative humidity deviations are less than 1%, the working range is 0-30 degrees C within 25-85% humidity environment and the maximum response time are less than 65 s which can be further shortened by software. The research provides an effective way for the construction of a simple and automatic dew point measurement system.
Ye, ChaofengLaureti, StefanoMalekmohammadi, HamedWang, Yang...
10页
查看更多>>摘要：Eddy current testing (ECT) is a widely used non-destructive testing (NDT) method in many industrial applications, which has been developed and advanced significantly in the past few decades. However, there are still challenges to overcome, such as the need for scanning and imaging large surfaces, improving the defect detection and classification capability. In this work, these have been addressed using tunnelling magnetoresistance (TMR) sensor array and a swept-frequency chirp excitation signal, together with the pulse-compression algorithm. Conventionally, time domain analysis is used in pulsed eddy current to gather info about any defects. Here the time domain analysis is implemented on the output of the pulse-compression procedure applied to the sweptfrequency chirp response, which is also processed via frequency domain analysis. The results showed larger SNR values for time domain images and a better clustering of the SNR values compared to the frequency domain, facilitating the defect depth estimation and classification.
Topsoy, Oguz KaganMuhammad, FakhriyKolak, SedaUlu, Ahmet...
12页
查看更多>>摘要：In the present study, a screen-printed electrode for Diazinon (DZN) detection was modified with nanofibers prepared via electrospinning technique. The chemical structure, morphology, and crystallinity of the nanofibers were characterized in detail. The electrochemical behaviors of the modified screen-printed electrode were evaluated by cyclic voltammetry, differential pulse voltammetry, and electrochemical impedance spectroscopy. The spinning time, pH value and scan rates were optimized at 6 min, 5.25, and 50 mVs(-1), respectively. The limit of detection as 2.888 nM was obtained over a linear concentration range (3 nM-100 nM). Besides, DZN selectivity, repeatability, and storage stabilities of the developed sensor were proven. Meanwhile, the sensor was successfully applied for the determination of DZN in the tomato juice sample with recovery values in the range of 93.27-108.30%. The developed sensor could be a promising candidate to detect the presence and level of DZN in real samples.
查看更多>>摘要：An online double-sided identification and eliminating system based on machine vision was developed to identify the unclosed-glumes rice seed by analyzing its double-sided image simultaneously. The vibrating plate and linear vibration conveyor achieved the transfer of rice seed from disordering to spacing, and the identified unclosedglumes rice seed was eliminated by the blowing jet. Hough linear detection and extracted feature were used to identify the unclosed-glumes rice seeds. The algorithm achieved the accuracy of 88.1% for normal seeds and 87.7% for unclosed-glumes seeds when using double-sided image acquired online. Multi-thread processing was used for double-sided images to shorten the code execution time. The online double-sided identification and eliminating system achieved the average accuracy of 83.7% for normal seeds and 83.3% for unclosed-glumes seeds. Results show that the system has a good adaptation of different rice seed varieties and achieved desired accuracy for online identification and eliminating of unclosed-glumes rice seed.
查看更多>>摘要：A differential luminescent imaging method is applied to a pressure-sensitive paint (PSP) measurement to capture a quasi-steady acoustic pressure field. Conventionally, PSP measurements capture an absolute luminescent intensity and convert it to pressure. When the mean component of the absolute luminescent intensity occupies a substantial portion of the dynamic range of the image acquisition device, it leads to a coarse signal resolution. Differential luminescent imaging, utilizing two-color luminescent intensities and a differential amplifier, extracts the fluctuation component from the absolute luminescent intensity. The developed differential luminescent imaging system gives a point-wise pressure measurement. These measurements are combined to produce a spatially resolved image. It is capable of resolving the periodic pressure wave over the acoustic field where the resolution of a conventional PSP measurement falls into one digital count. This comparison to a conventional PSP measurement is given as a reference by which to evaluate the spatiotemporal resolution of the differential luminescent imaging method.
Gibiino, Gian PieroAngelotti, Alberto M.Santarelli, AlbertoTraverso, Pier Andrea...
10页
查看更多>>摘要：The Error Vector Magnitude (EVM) is a fundamental metric used in communications to quantify the wideband distortion generated by a non-linear device subject to modulated excitation. While typically adopted for impedance-matched devices, the EVM is here investigated for the performance assessment of mismatched power amplifiers (PAs) across wide modulation bandwidths (BWs). A system-level analysis is developed to characterize the EVM for a non-linear device cascaded with a generic linear network. To study particular operating regimes of interest under wideband load mismatch, the EVM measurement process is here applied together with a novel wideband active load-pull technique, leading to a newly implemented frequency-domain characterization platform based on classical relative measurements from a Vector Network Analyzer (VNA). The experimental results ultimately show that the analyzed EVM measurement method can be consistently and effectively combined with load-pull techniques in realistic application cases, enabling improved wideband radio-frequency (RF) PA design and characterization.
查看更多>>摘要：Now-a-days inductor-capacitor (LC) resonator based sensors are widely used in the field of measurement for the measurement of different parameters like pressure, humidity, strain, temperature, pH etc. The basic principle of the sensor is inductive coupling between two loosely coupled inductors in sensing side and reading side. It has the facility of the passive, non-contact and wireless sensing which makes it very advantageous in various field where direct contact with the measurand body is difficult like furnaces, automobile engines, rotating objects, human body etc. In the case of temperature measurement, the LC sensor really plays a crucial role as it helps to measure temperature in inaccessible areas like any harsh and sealed temperature system. A lot of research works are carried out by different researchers for many practical applications. In this paper, a review has been done for a number of recent works on the temperature measurement techniques using LC sensors, which explores the key technologies, different design considerations and methods for assisting the development of LC sensors and configurations and modifications adopted for the respective researches for different future applications.
查看更多>>摘要：Light scattering is used for remote diagnostics of certain physical properties of particulate systems. The main purpose of this review is to coherently present an updated theoretical background of forward and inverse analysis for particle size distribution measurements of disperse samples. In particular, both well-tried and recent methods for analytical and numerical treatment of measurement data inversion are examined. An extensive bibliography is included for further study.
查看更多>>摘要：Health services for rotating machinery are essential to ensure safe industrial production. In recent years, deep learning (DL) methods based on vibration analysis have been continuously developed in rotating mechanical fault diagnosis (MFD). However, current diagnostic models based on DL facing three major challenges: (1) Convolutional neural network (CNN)-based DL algorithms lose spatial information of features, which may inevitably cause recognition errors; (2) Sufficient faulty training samples must be required to guarantee the learning capability of DL models, which may not be satisfied in actual engineering; (3) The poor generality of existing DL-based models make it difficult for different rotating machines or even different components of a mechanical device for diagnostic tasks. Toward the above problems, a revised DL model, namely dual convolution-capsule network (DC-CN), is introduced to diagnose rotating machinery faults under minor sample conditions. The DC-CN well merits the advantages of CNN and the capsule network (CN), which fully retains spatial information while digging in-depth fault features. Therefore, DC-CN achieves an ideal balance between diagnostic effectiveness and data amount. Experiments including different rotating machinery and different fault components are conducted to validate the diagnostic performance of the proposed model, and the tSNE dimensionality reduction algorithm is introduced to visualize the extracted features. The proposed DC-CN demonstrated the best diagnostic capability than other DL models in different rotating machinery: 1. For rolling bearing, DC-CN achieved 99.78%, 98.22%, 100%, and 100% under 4 different loading conditions; 2. For the planetary gearbox, DC-CN reached 96.91% and 98.22% under different rotational conditions, including 8 health scenarios of different gear types; 3. DC-CN has excellent performance under small sample conditions.
查看更多>>摘要：Aiming at the problem of rock mass structure fine detection, a solution idea of synchronous data acquisition based on acoustic scanning technology and borehole panoramic image technology is proposed. Based on the omni-directional acoustic pulse reflection sequence data and panoramic optical borehole image, the problem of difficult calculation of typical borehole structure scale and extended azimuth positioning is solved. A 3D modeling and data visualization optimization scheme of borehole rock mass structure based on full pulse acoustic scanning data and forward-looking borehole optical image is formed. By combining the acoustic scanning characteristics of section and the optical image characteristics of rock wall, the extraction technology of borehole rock mass structural characteristic parameters is formed. The 3D imaging and characteristic parameter extraction technology system of borehole rock mass structure is formed, which is applied to the actual borehole rock mass structure detection. The detection results are consistent with the actual characteristics.
NSTL
Elsevier