Design of Cold-Junction Compensation and Disconnection Detection Circuits of Various Thermocouples and Implementation of Multi-Channel Interfaces Using Them-A Secondary Publication

Cold-junction compensation(CJC)and disconnection detection circuit design of various thermocouples(TC)and multi-channel TC interface circuits were designed.The CJC and disconnection detection circuit consists of a CJC semiconductor device,an instrumentation amplifier(IA),two resistors,and a diode for disconnection detection.Based on the basic circuit,a multi-channel interface circuit was also implemented.The CJC was implemented using compensation semiconductor and IA,and disconnection detection was detected by using two resistors and a diode so that IA input voltage became-0.42 V.As a result of the experiment using R-type TC,the error of the designed circuit was reduced from 0.14 mV to 3μV after CJC in the temperature range of 0°C to 1400°C.In addition,it was confirmed that the output voltage of IA was saturated from 88 mV to-14.2 V when TC was disconnected from normal.The output voltage of the designed circuit was 0 V to 10 V in the temperature range of 0°C to 1400°C.The results of the 4-channel interface experiment using R-type TC were almost identical to the CJC and disconnection detection results for each channel.The implemented multi-channel interface has a feature that can be applied equally to E,J,K,T,R,and S-type TCs by changing the terminals of CJC semiconductor devices and adjusting the IA gain.

CLOF Based Outlier Detection Algorithm of Temperature Data for Ethylene Cracking Furnace

The flue temperature is one of the important indicators to characterize the combustion state of an ethylene cracker furnace,the outliers of temperature data can lead to the false alarm.Conventional outlier detection algorithms such as the Isolation Forest algorithm and 3-sigma principle cannot detect the outliers accurately.In order to improve the detection accuracy and reduce the computational complexity,an outlier detection algorithm for flue temperature data based on the CLOF(Clipping Local Outlier Factor,CLOF)algorithm is proposed.The algorithm preprocesses the normalized data using the cluster pruning algorithm,and realizes the high accuracy and high efficiency outlier detection in the outliers candidate set.Using the flue temperature data of an ethylene cracking furnace in a petrochemical plant,the main parameters of the CLOF algorithm are selected according to the experimental results,and the outlier detection effect of the Isolation Forest algorithm,the 3-sigma principle,the conventional LOF algorithm and the CLOF algorithm are compared and analyzed.The results show that the appropriate clipping coefficient in the CLOF algorithm can significantly improve the detection efficiency and detection accuracy.Compared with the outlier detection results of the Isolation Forest algorithm and 3-sigma principle,the accuracy of the CLOF detection results is increased,and the amount of data calculation is significantly reduced.

Detection of the anthropogenic signal and urbanization effects in extreme temperature changes in eastern China

作为中国经济最发达的地区,中国东部受到城市热岛效应和温室气体排放等人类活动的明显影响.本文利用最新的观测和全球气候模式资料,对极端温度强度,频率和持续时间等16个极端温度指数进行了检测归因分析,研究了人为强迫和城市化效应对中国东部极端温度变化的影响.结果表明,近年来极端温度持续增暖,极端暖事件增加,极端冷事件减少.新一代全球气候模式能够合理地反映这些变暖特征,但是部分模式可能高估或低估了观测到的变化.基于最优指纹方法的双信号检测表明,人为信号和城市化效应只能在暖夜和冷夜两个频率指标上同时被检测并分离,其变化约三分之二可归因于人类活动,剩余的三分之一可归因于城市化效应.而在极端温度其他指数的变化中,只有人类活动的影响能够被检测到.

Miniaturized power detection module operating in millimeter wave band

The miniaturized broadband detection module can be embedded into the microwave application system such as the front end of the transmitter to detect the power or other parameters in real time.It is highly prospective in military and scientific research.In this paper,a broadband power detection module operating at 26.5 GHz-40.0 GHz is designed by using low-barrier Schottky diode as the detector and a comparator for threshold output.This module can dynamically detect the power range between-10 dBm and 10 dBm with the detection accuracy of 0.1 dB.Further,the temperature compensation circuit is also applied to improve the measurement error.As a result,the resulted error low to±1 dB in the temperature range of -55℃ to +85℃ is achieved.The designed module is encapsulated by a Kovar alloy with a small volume of 9 mm×6 mm×3 mm.This endows the designed module the advantages of small size,easy integration,and low cost,and even it is applicable to high-reliability environments such as satellites.

Parametric study on contact sensors for MASW measurement-based interfacial debonding detection for SCCS

Steel-concrete composite structures(SCCS)have been widely used as primary load-bearing components in large-scale civil infrastructures.As the basis of the co-working ability of steel plate and concrete,the bonding status plays an essential role in guaranteeing the structural performance of SCCS.Accordingly,efficient non-destructive testing(NDT)on interfacial debondings in SCCS has become a prominent research area.Multi-channel analysis of surface waves(MASW)has been validated as an effective NDT technique for interfacial debonding detection for SCCS.However,the feasibility of MASW must be validated using experimental measurements.This study establishes a high-frequency data synchronous acquisition system with 32 channels to perform comparative verification experiments in depth.First,the current sensing approaches for high-frequency vibration and stress waves are summarized.Secondly,three types of contact sensors,namely,piezoelectric lead-zirconate-titanate(PZT)patches,accelerometers,and ultrasonic transducers,are selected for MASW measurement.Then,the selection and optimization of the force hammer head are performed.Comparative experiments are carried out for the optimal selection of ultrasonic transducers,PZT patches,and accelerometers for MASW measurement.In addition,the influence of different pasting methods on the output signal of the sensor array is discussed.Experimental results indicate that optimized PZT patches,acceleration sensors,and ultrasonic transducers can provide efficient data acquisition for MASW-based non-destructive experiments.The research findings in this study lay a solid foundation for analyzing the recognition accuracy of contact MASW measurement using different sensor arrays.

A model of sea surface temperature front detection based on a threshold interval

A model （Bayesian oceanic front detection, BOFD） of sea surface temperature （SST） front detection in satel- lite-derived SST images based on a threshold interval is presented, to be used in different applications such as climatic and environmental studies or fisheries. The model first computes the SST gradient by using a Sobel algorithm template. On the basis of the gradient value, the threshold interval is determined by a gradi- ent cumulative histogram. According to this threshold interval, front candidates can be acquired and prior probability and likelihood can be calculated. Whether or not the candidates are front points can be deter- mined by using the Bayesian decision theory. The model is evaluated on the Advanced Very High-Resolution Radiometer images of part of the Kuroshio front region. Results are compared with those obtained by using several SST front detection methods proposed in the literature. This comparison shows that the BOFD not only suppresses noise and small-scale fronts, but also retains continuous fronts.

Detection of the End Point Temperature of Thermal Denatured Protein in Fish and Chicken Meat Through SDS-PAGE Electrophoresis

Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) was applied in the detection of the end point temperature (EPT) of thermal denatured protein in fish and meat in this study. It was also used in studying the thermal denatured temperature range of proteins in salmon and chicken meat. The results show that the temperature ranges of denatured proteins were from 65 ℃ to 75 ℃ , and these temperature ranges were influenced by the processing methods. Through SDS-PAGE, the features of repeated heating thermal denatured proteins under the same temperature and processing time were studied. The electrophoresis patterns of thermal denatured proteins determined through repeated heating at the same temperature did not exhibit any change. For the detection of cooked fish and meat samples, they were subjected to applying the SDS-PAGE method, which revealed an EPT ranging from 60 ℃ to 80 ℃ .

Preparation of polythiophene/WO_3 organic-inorganic hybrids and their gas sensing properties for NO_2 detection at low temperature

Polythiophene/WO3（PTP/WO3）organic-inorganic hybrids were synthesized by an in situ chemical oxidative polymerization method,and char- acterized by X-ray diffraction（XRD）,transmission electron microscopy（TEM）and thermo-gravimetric analysis（TGA）.The Polythiophene/ WO3 hybrids have higher thermal stability than pure polythiophene,which is beneficial to potential application as chemical sensors.Gas sensing measurements demonstrate that the gas sensor based on the Polythiophene/WO3 hybrids has high response and good selectivity for de- tecting NO2 of ppm level at low temperature.Both the operating temperature and PTP contents have an influence on the response of PTP/WO3 hybrids to NO2.The 10 wt%PTP/WO3 hybrid showed the highest response at low operating temperature of 70-C.It is expected that the PTP/WO3 hybrids can be potentially used as gas sensor material for detecting the low concentration of NO2 at low temperature.

Detection of Land-Use and Surface Temperature Change at Different Resolutions

Understanding the relationship between land-use/land-cover change (LULCC) and environment is seriously important to manage arid land. However, information on how environmental factors influence the LULCC patterns at different scales in arid area is lacking. This paper investigates the application of RS/GIS for detecting LULCC and assessing its impact on surface temperature in the Ismailia Governorate, Egypt. Landsat images have been utilized to quantify the changes from 1984 to 2011. The images were pre-processed using calibration techniques and the geometric and atmos- pheric corrections were performed. Different ratios, indices, and optimized index factor were implemented to decide the best band combination. Supervised classification using Maximum Likelihood technique and spatial reclassification have been employed. Six land-use/land-cover categories (urban, vegetation, waterlogged 1 and 2, bare land, and water) were identified. The highest overall accuracy and Kappa coefficient is 93.04% and 80.65%, respectively. The integration of RS and GIS was further applied to examine the impact of land-use change on surface temperatures. The results revealed a notable land-use change in the study area. The Built-up area has rapidly increased in Ismailia during the 27 years pe- riod. The built-up area (37.65?C in 1984 and 43.876?C in 2011) and Barren land (37.34?C in 1984 and 42.801?C in 2011) exhibit the highest surface radiant temperature, while vegetated surfaces (28.73?C in 1984 and 32.96?C in 2011), water (25.94?C in 1984 and 27.32?C in 2011), waterlogged1 (34.54?C in 1984 and 35.60?C in 2011) recorded low radiant temperature respectively. Waterlogged2 is the class that shows an unexpected radiant temperature (26.38?C in 1984 and 27.75?C in 2011). The urban development between 1984 and 2011 has given rise to an average of 6.23?C in surface radiant temperature. During 27 years, the change rate of land-use types which are decreased are barren land (1.12% an- nually) and waterlogged1 and 2 (0.76 and 6.61% annually). The area of vegetation, water, and built-up are increased by 0.98%, 0.82%, and 0.61% per year, respectively.

Performance Analysis of Temperature and Strain Simultaneous Measurement System Based on Heterodyne Detection of Brillouin Scattering

Microwave heterodyne detection can be used to measure the temperature and strain distribution along a fiber with high accuracy in a Brillouin optical time domain reflectometry （BOTDR） system. This method involves simultaneous measurement of Brillouin scattering and Rayleigh scattering in fiber, and scanning of Brillouin spectrum to obtain the desired information. This paper presents a simultaneous measurement system of temperature and strain based on microwave detection and analyzed the system performances such as measurement accuracy, dynamic range, and spatial resolution theoretically. The analysis shows that the system can achieve a temperature resolution of 1°C and a strain resolution of 100 μs.

Gold Nanoparticles/Thermochromic Composite Film on Screen-Printed Electrodes for Simultaneous Detection of Protein and Temperature

In this study, gold nanoparticles and thermochromic composite films modified screen-printed carbon electrodes (TM-AuNPsSPCEs) were developed as a platform for the simultaneous detection of protein and temperature. The TM-AuNPs composited film had better sensitivity resulting from the gold nanoparticles amplification effect. A phase transition model analysis of TM-AuNPs films found that the TM-AuNPs films had three-phase transition intervals (<45℃, 45℃ to 80℃ and >80℃) which accommodated the temperature requirements for protein denaturation. When used to detect different concentrations of haemoglobin (Hb) solution, the TM-AuNPs modified SPCEs had a better sensitivity in detecting the different concentrations in comparison to TM and AuNP modified SPCEs which showed no clear sensitivity towards the different Hb concentrations. The dual detection and excellent sensitivity show a good application prospect for the study of the TM-AuNPs composite film.

Assimilation of FY-3D MWTS-Ⅱ Radiance with 3D Precipitation Detection and the Impacts on Typhoon Forecasts

Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors.The traditional precipitation detection method for microwave only detects clouds and precipitation horizontally,without considering the three-dimensional distribution of clouds.Extending precipitation detection from 2D to 3D is expected to bring more useful information to the data assimilation without using the all-sky approach.In this study,the 3D precipitation detection method is adopted to assimilate Microwave Temperature Sounder-2(MWTS-Ⅱ)onboard the Fengyun-3D,which can dynamically detect the channels above precipitating clouds by considering the near-real-time cloud parameters.Cycling data assimilation and forecasting experiments for Typhoons Lekima(2019)and Mitag(2019)are carried out.Compared with the control experiment,the quantity of assimilated data with the 3D precipitation detection increases by approximately 23%.The quality of the additional MWTS-Ⅱradiance data is close to the clear-sky data.The case studies show that the average root-mean-square errors(RMSE)of prognostic variables are reduced by 1.7%in the upper troposphere,leading to an average reduction of4.53%in typhoon track forecasts.The detailed diagnoses of Typhoon Lekima(2019)further show that the additional MWTS-Ⅱradiances brought by the 3D precipitation detection facilitate portraying a more reasonable circulation situation,thus providing more precise structures.This paper preliminarily proves that 3D precipitation detection has potential added value for increasing satellite data utilization and improving typhoon forecasts.

Detection and characteristics analysis of the western subarctic front using the high-resolution SST product

Oceanic front plays a significant role in the ocean vertical mixing and the regulation of air-sea interaction,among others.The western branch of the subarctic front(WSAF)located in the Northwest Pacific has attained lots of attention given its strong intensity and widespread influence on this region.In this study,we take advantage of the merged sea surface temperature(SST)at a high spatial resolution of 0.05°to investigate the characteristics of WSAF.The front detection algorithm that combines the Sobel operator and histogram analysis is adopted.It is advantageous in both preserving the front intensity represented by the SST gradient as well as reducing the detection noise level.We systematically applied this algorithm to the daily SST products for front detection,based on which the WSAF characteristics including its intensity,occurrence of frequency,latitudinal position and coverage area are then extracted.WSAF is mostly located within a small latitude range between 40°N and 41°N with a clear seasonal trend in its intensity that peaks in the winter and troughs in the summer.The seasonal variation of WSAF intensity is almost consistent throughout the temporal period of interest from 2010 to 2018.Similar seasonality is observed for its occurrence of frequency with the winter-summer contrast reaching up to5%.The findings presented here shall help better interpret the WSAF characteristics in the long-term run as well as their impact on the regional weather and climate patterns at high spatial resolution.

Improving tree health assessment accuracy at low temperatures:considering the effect of trunk ice content on electrical resistance and stress wave tomography

Accurate decay detection and health assessment of trees at low temperatures is an important issue for forest management and ecology in cold areas.Low temperature ice formation on tree health assessment is unknown.Because electric resistance tomography and stress wave tomography are two widely used methods for the detection of tree decay,this study investigated the effect of ice content on trunk electrical resistance and stress wave velocity to improve tree health assessment accuracy.Moisture content,trunk electrical resistance and stress wave velocity using time domain reflectometry were carried out on Larix gmelinii and Populus simonii.Ice content is based on moisture content data.The ice content of both species showed a trend of increasing and then decreasing.This was opposite with ambient temperatures.With the decrease of temperatures,daily average ice content increased,but the range narrowed gradually and both electrical resistance and stress wave velocity increased.Both increased rapidly near 0℃,mainly caused by ice formation(phase change and freezing of free water)in live trees.In addition,both are positively correlated with ice content.The results suggest that ice content should be considered for improving the accuracy of tree decay detection and health evaluation using electric resistance tomography and stress wave velocity methods under low temperatures.

A New Dual-electrode and Multi-channel Electrochemical Detection System for Capillary Electrophoresis

A new type of dual-electrode and multi-channel electrochemical detection technology for capillary electrophoresis is described in this paper. Two detectors(the amperometric detector and the conductometric detector) or two conductometric detectors are connected to the same capillary electrophoresis system. The whole system possesses the advantages of the two electrochemical detectors including sparing time, improving the analytical speed and expanding the sample range. The working electrode and detector cell are handled easily. The system was applied to sample detection with satisfactory results.

Research of multi-channel impulse noise detection algorithms based on template

Attenuating the undesired audio noise generated by impulse noise,such as shot and scream of brakes,is specially useful for real-time audio recording of TV or broadcasting live report.On the basis of impulse noise detection algorithms based on template,this paper improves the method of establishing the template by using multiple microphones to pick up noise corrupted signals and impulse noises in the environment.The universal of thresholds is found and a detection algorithm with slope as the characteristic is proposed by comparing a variety of feature extraction algorithms.The proposed algorithm gets a significant improvement in testing speed and accuracy,which means it is suitable for real-time processing of audio signals.

A Multi-Channel Fusion Based Newborn Seizure Detection

We propose and compare two multi-channel fusion schemes to utilize the information extracted from simultaneously recorded multiple newborn electroencephalogram (EEG) channels for seizure detection. The first approach is known as the multi-channel feature fusion. It involves concatenating EEG feature vectors independently obtained from the different EEG channels to form a single feature vector. The second approach, called the multi-channel decision/classifier fusion, is achieved by combining the independent decisions of the different EEG channels to form an overall decision as to the existence of a newborn EEG seizure. The first approach suffers from the large dimensionality problem. In order to overcome this problem, three different dimensionality reduction techniques based on the sum, Fisher’s linear discriminant and symmetrical uncertainty (SU) were considered. It was found that feature fusion based on SU technique outperformed the other two techniques. It was also shown that feature fusion, which was developed on the basis that there was inter-dependence between recorded EEG channels, was superior to the independent decision fusion.

Damage warning of suspension bridges based on neural networks under changing temperature conditions

This paper aims at successive structural damage detection of long-span bridges under changing temperature conditions.First,the frequency-temperature correlation models of bridges are formulated by means of artificial neural network techniques to eliminate the temperature effects on the measured modal frequencies.Then,the measured modal frequencies under various temperatures are normalized to a reference temperature,based on which the auto-associative network is trained to monitor signal damage occurrences by means of neural-network-based novelty detection techniques.The effectiveness of the proposed approach is examined in the Runyang Suspension Bridge using 236-day health monitoring data.The results reveal that the seasonal change of environmental temperature accounts for variations in the measured modal frequencies with averaged variances of 2.0%.And the approach exhibits good capability for detecting the damage-induced 0.1% variance of modal frequencies and it is suitable for online condition monitoring of suspension bridges.

Temperature effect on the structural strains of an ancient Tibetan building based on long-term monitoring data

Many studies have indicated that structural strain will be significantly influenced by temperature variations,and a good understanding of the effect of temperature on structural strain is essential.A structural health monitoring system has been installed in a typical Tibetan timber building to measure the structural strains and ambient temperature since 2012.This paper presents the correlation between temperature and strain data from the monitored structure.A method combining singular spectrum analysis and polynomial regression is proposed for modeling the temperature induced strains in the structure.Singular spectrum analysis is applied to smooth the temperature data,and the correlation between the resulting temperature time series and the measured strains is obtained by polynomial regression.Parameters of the singular spectrum analysis and the regression model are selected to have the least regression error.Results show that the proposed method has both good reproduction and prediction capabilities for temperature induced strains,and that the method is accurate and effective for eliminating the effect of temperature from the measured strain.A standardized Novelty Index based on the residual strain is also used for the condition assessment of the structure.

A multi-channel chemical sensor and its application in detecting hydrothermal vents

There are well-established chemical and turbidity anomalies in the plumes occurring vicinity of hydrothermal vents, which are used to indicate their existence and locations. We here develop a small, accurate multi-channel chemical sensor to detect such anomalies which can be used in deep-sea at depths of more than 4 000 m. The design allowed five all-solid-state electrodes to be mounted on it and each (apart from one reference electrode) could be changed according to chemicals to be measured. Two experiments were conducted using the chemical sensors. The first was a shallow-sea trial which included sample measurements and in situ monitoring. pH, Eh, CO3^2- and SO4^2- electrodes were utilized to demonstrate that the chemical sensor was accurate and stable outside the laboratory. In the second experiment, the chemical sensor was integrated with pH, Eh, CO3^2- and H2S electrodes, and was used in 29 scans of the seabed along the Southwest Indian Ridge (SWIR) to detect hydrothermal vents, from which 27 sets of valid data were obtained. Hydrothermal vents were identified by analyzing the chemical anomalies, the primary judging criteria were decreasing voltages of Eh and H2S, matched by increasing voltages of pH and CO3^2- . We proposed that simultaneous detection of changes in these parameters will indicate a hydrothermal vent. Amongst the 27 valid sets of data, five potential hydrothermal vents were targeted using the proposed method. We suggest that our sensors could be widely employed by marine scientists.