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.

A highly sensitive ratiometric near-infrared nanosensor based on erbium-hyperdoped silicon quantum dots for iron(Ⅲ) detection

Ratiometric fluorescent detection of iron(Ⅲ)(Fe^(3+))offers inherent self-calibration and contactless analytic capabilities.However,realizing a dual-emission near-infrared(NIR)nanosensor with a low limit of detection(LOD)is rather challenging.In this work,we report the synthesis of water-dispersible erbium-hyperdoped silicon quantum dots(Si QDs:Er),which emit NIR light at the wavelengths of 810 and 1540 nm.A dual-emission NIR nanosensor based on water-dispersible Si QDs:Er enables ratiometric Fe^(3+)detection with a very low LOD(0.06μM).The effects of pH,recyclability,and the interplay between static and dynamic quenching mechanisms for Fe^(3+)detection have been systematically studied.In addition,we demonstrate that the nanosensor may be used to construct a sequential logic circuit with memory functions.

Industry-Oriented Detection Method of PCBA Defects Using Semantic Segmentation Models

Automated optical inspection(AOI)is a significant process in printed circuit board assembly(PCBA)production lines which aims to detect tiny defects in PCBAs.Existing AOI equipment has several deficiencies including low throughput,large computation cost,high latency,and poor flexibility,which limits the efficiency of online PCBA inspection.In this paper,a novel PCBA defect detection method based on a lightweight deep convolution neural network is proposed.In this method,the semantic segmentation model is combined with a rule-based defect recognition algorithm to build up a defect detection frame-work.To improve the performance of the model,extensive real PCBA images are collected from production lines as datasets.Some optimization methods have been applied in the model according to production demand and enable integration in lightweight computing devices.Experiment results show that the production line using our method realizes a throughput more than three times higher than traditional methods.Our method can be integrated into a lightweight inference system and pro-mote the flexibility of AOI.The proposed method builds up a general paradigm and excellent example for model design and optimization oriented towards industrial requirements.

Development of an Integrated CMUTs-Based Resonant Biosensor for Label-Free Detection of DNA with Improved Selectivity by Ethylene-Glycol Alkanethiols

Gravimetric resonant-inspired biosensors have attracted increasing attention in industrial and point-ofcare applications,enabling label-free detection of biomarkers such as DNA and antibodies.Capacitive micromachined ultrasonic transducers(CMUTs)are promising tools for developing miniaturized highperformance biosensing complementary metal–oxide–silicon(CMOS)platforms.However,their operability is limited by inefficient functionalization,aggregation,crosstalk in the buffer,and the requirement for an external high-voltage(HV)power supply.In this study,we aimed to propose a CMUTs-based resonant biosensor integrated with a CMOS front–end interface coupled with ethylene–glycol alkanethiols to detect single-stranded DNA oligonucleotides with large specificity.The topography of the functionalized surface was characterized by energy-dispersive X-ray microanalysis.Improved selectivity for onchip hybridization was demonstrated by comparing complementary and non-complementary singlestranded DNA oligonucleotides using fluorescence imaging technology.The sensor array was further characterized using a five-element lumped equivalent model.The 4 mm^(2) application-specific integrated circuit chip was designed and developed through 0.18 lm HV bipolar-CMOS-double diffused metal–oxide–silicon(DMOS)technology(BCD)to generate on-chip 20 V HV boosting and to track feedback frequency under a standard 1.8 V supply,with a total power consumption of 3.8 mW in a continuous mode.The measured results indicated a detection sensitivity of 7.943×10^(-3) lmol·L^(-1)·Hz^(-1) over a concentration range of 1 to 100 lmol·L^(-1).In conclusion,the label-free biosensing of DNA under dry conditions was successfully demonstrated using a microfabricated CMUT array with a 2 MHz frequency on CMOS electronics with an internal HV supplier.Moreover,ethylene–glycol alkanethiols successfully deposited self-assembled monolayers on aluminum electrodes,which has never been attempted thus far on CMUTs,to enhance the selectivity of bio-functionalization.The findings of this study indicate the possibility of full-on-chip DNA biosensing with CMUTs.

Detection Algorithm of Surface Defect Word on Printed Circuit Board

For Printed Circuit Board(PCB)surface defect detection,traditional detection methods mostly focus on template matching-based reference method and manual detections,which have the disadvantages of low defect detection efficiency,large errors in defect identification and localization,and low versatility of detectionmethods.In order to furthermeet the requirements of high detection accuracy,real-time and interactivity required by the PCB industry in actual production life.In the current work,we improve the Youonly-look-once(YOLOv4)defect detection method to train and detect six types of PCB small target defects.Firstly,the original Cross Stage Partial Darknet53(CSPDarknet53)backbone network is preserved for PCB defect feature information extraction,and secondly,the original multi-layer cascade fusion method is changed to a single-layer feature layer structure to greatly avoid the problem of uneven distribution of priori anchor boxes size in PCB defect detection process.Then,the K-means++clustering method is used to accurately cluster the anchor boxes to obtain the required size requirements for the defect detection,which further improves the recognition and localization of small PCB defects.Finally,the improved YOLOv4 defect detection model is compared and analyzed on PCB dataset with multi-class algorithms.The experimental results show that the average detection accuracy value of the improved defect detection model reaches 99.34%,which has better detection capability,lower leakage rate and false detection rate for PCB defects in comparison with similar defect detection algorithms.

Fifth-order phase-sensitive detection of ultrafast polarization beats in cascade four-level system

We study the colour-locked twin-noisy-field correlation effects in the fifth-order nonlinear susceptibility of ultrafast polarization beats in a cascade four-level system. More importantly, the fifth-order phase-sensitive heterodyne detection of ultrafast polarization beats has been exploited. The fifth-order nonlinear optical response can be controlled and modified through the colour-locked correlation of twin noisy fields. Thus, this method with the phase dispersion information is a good way to measure the real and imaginary parts of the fifth-order nonlinear susceptibility.

Design of multilayer cellular neural network based on memristor crossbar and its application to edge detection

Memristor with memory properties can be applied to connection points(synapses)between cells in a cellular neural network(CNN).This paper highlights memristor crossbar-based multilayer CNN(MCM-CNN)and its application to edge detection.An MCM-CNN is designed by adopting a memristor crossbar composed of a pair of memristors.MCM-CNN based on the memristor crossbar with changeable weight is suitable for edge detection of a binary image and a color image considering its characteristics of programmablization and compactation.Figure of merit(FOM)is introduced to evaluate the proposed structure and several traditional edge detection operators for edge detection results.Experiment results show that the FOM of MCM-CNN is three times more than that of the traditional edge detection operators.

A New Method of Early Short Circuit Detection

To reduce the pressure on contacts and circuit breaker and realize the zone selective interlocking (ZSI) function above the instantaneous protection threshold (e.g., >10In), the short circuit current needs to be early detected. The state-of–art of early short circuit detection (ESCD) method is reviewed. Based on the equivalent model of the short circuit, a new method based on the current and its integration is proposed. The prospective current value can be detected in the early stage of the short circuit. According to the evaluation result, the short circuit current can be early forecasted with the proposed method.

FAULT DETECTION FOR MULTIPLE-VALUED LOGIC CIRCUITS WITH FANOUT-FREE

The single fault and multiple fault detections for multiple-valued logic circuits are studied in this paper. Firstly, it is shown that the cardinality of optimal single fault test set for fanout-free m-valued circuits with n primary inputs is not more than n + 1, for linear tree circuits is two, and for multiplication modulo circuits is two if n is an odd number or if n is an even number and m ＞ 3, where the optimal test set of a circuit has minimal number of test vectors. Secondly,it is indicated that the cardinality of optimal multiple fault test set for linear tree circuits with n primary inputs is 1 + [n/(m - 1)], for multiplication modulo circuits is n+ 1, for fanout-free circuits that consist of 2-input linear tree circuits and 2-input multiplication modulo circuits is not greater than n+ 1, where [x] denotes the smallest integer greater than or equal to x. Finally,the single fault location approaches of linear tree circuits and multiplication modulo circuits are presented, and all faults in the two types of circuits can be located by using a test set with n + 1 vectors.

A FAULT DETECTION SENSOR FOR CIRCUIT AGING USING DOUBLE-EDGE-TRIGGERED FLIP-FLOP

In nanoscale technology, transistor aging is one of the most critical problems that impact on the reliability of circuits. Aging sensor is a good online way to detect the circuit aging, which performs during the operating time with no influence of the normal operation of circuits. In this paper, a Dou- ble-edge-triggered Detection Sensor for circuit Aging （DSDA） is proposed, which employs data signal of logic circuits as its clock to control the sampling process. The simulation is done by Hspice using 45 nm technology. The results show that this technique is not case of the detection precision is more than 80% under aging fault effectively with the 8% power cost and 30% sensitive to the process variations. The worst the different process variations. It can detect performance cost.

An Improved Randomized Circle Detection Algorithm Using in Printed Circuit Board Locating Mark

This paper presents an improved Randomized Circle Detection (RCD) algorithm with the characteristic of circularity to detect randomized circle in images with complex background, which is not based on the Hough Transform. The experimental results denote that this algorithm can locate the circular mark of Printed Circuit Board (PCB).

Image boundary extraction based on island model genetic algorithms for integrated circuit defect detection

The integrated circuit chip with high performance has a high sensitivity to the defects in manufacturing environments.When there are defects on a wafer,the defects may lead to the degradation of chip performance.It is necessary to design effective detection approaches for the defects in order to ensure the reliability of wafer.In this paper,a new method based on image boundary extraction is presented for the detection of defects on a wafer.The method uses island model genetic algorithms to perform the segmentation of wafer images,and gets the optimal threshold values.The island model genetic algorithm uses two distinct subpopulations,it is a coarse grain parallel model.The individuals migration can occur between the two subpopulations to share genetic materials.A lot of experimental results show that the defect detection method proposed in this paper can obtain the features of defects effectively.

Micro capacitance detection circuit for MEMS capacitive sensor

With the development of micro-electr o-mechanical system(MEMS) technolog y,the MEMS-based capacitive sensor has been widely applied in the field of ele ctron components.However,the capacitance of the micromachined sensor is so sma ll that the detection of the smaller value change of the capacitance is a great challenge.Based on the principle of charging and discharging of the capacitor,a kind of pulse width modulated differential circuit is introduced in this paper.For subsequent amplification,a modified amplifier is presented.The different ial circuit converts the weak capacitance change to the change of the pulse widt h of the output voltage,and the linear relationship can be obtained.And the mo dified amplifier implements the processes of amplification and filtering synchro nously,and a large DC output voltage can be obtained by the lo w-pass filter.T he designed circuits have advantages as simplified circuit,high voltage stabili ty,perfect linearity and resolution.Besides,it is feasible to be integrated w ith the sensor to largely reduce the transmission error and interference.

The Detection of Inter-Turn Short Circuits in the Stator Windings of Sensorless Operating Induction Motors

This work proposes an alternative strategy to the use of a speed sensor in the implementation of active and reactive power based model reference adaptive system (PQ-MRAS) estimator in order to calculate the rotor and stator resistances of an induction motor (IM) and the use of these parameters for the detection of inter-turn short circuits (ITSC) faults in the stator of this motor. The rotor and stator resistance estimation part of the IM is performed by the PQ-MRAS method in which the rotor angular velocity is reconstructed from the interconnected high gain observer (IHGO). The ITSC fault detection part is done by the derivation of stator resistance estimated by the PQ-MRAS estimator. In addition to the speed sensorless detection of ITSC faults of the IM, an approach to determine the number of shorted turns based on the difference between the phase current of the healthy and faulty machine is proposed. Simulation results obtained from the MATLAB/Simulink platform have shown that the PQ-MRAS estimator using an interconnected high-gain observer gives very similar results to those using the speed sensor. The estimation errors in the cases of speed variation and load torque are almost identical. Variations in stator and rotor resistances influence the performance of the observer and lead to poor estimation of the rotor resistance. The results of ITSC fault detection using IHGO are very similar to the results in the literature using the same diagnostic approach with a speed sensor.

Cycle life prediction and match detection in retired electric vehicle batteries

The lifespan models of commercial 18650-type lithium ion batteries （nominal capacity of 1150 mA-h） were presented. The lifespan was extrapolated based on this model. The results indicate that the relationship of capacity retention and cycle number can be expressed by Gaussian function. The selecting function and optimal precision were verified through actual match detection and a range of alternating current impedance testing. The cycle life model with high precision （〉99%） is beneficial to shortening the orediction time and cutting the prediction cost.

A Temperature-Autocompensated Detecting Circuit for the Capacitance Fuze

In view of drastic possible changes in fuze environment tempera- ture,a kind of temperature autocompensated detecting circuit for the capaci- tance fuze is proposed.It provides a steady detected output when the envi- ronment temperature varies from-50℃ to 65℃ and keeps a stable detecting sensitivity.Based on an analysis of the circuit,influence of the major param- eters of the oscillating circuit on the amplitude are explored.A few impor- tant controllable parameters affecting the circuit feature are found out.A parameter-control method is given in order to improve the circuit perfor- mance.

A Novel System for Moving Object Detection Using Bionic Compound Eyes

Conventional moving target detection focuses on algorithms to improve detection efficiency. These algorithms pay less attention to the image acquisition means, and usually solve specific problems. This often results in poor flexibility and reus- ability. Insect compound eyes offer unique advantages for moving target detection and these advantages have attracted the attention of many researchers in recent years. In this paper we proposed a new system for moving target detection. We used the detection mechanism of insect compound eyes for the simulation of the characteristics of structure, control, and function. We discussed the design scheme of the system, the development of the bionic control circuit, and introduced the proposed mathe- matical model of bionic cqmpound eyes for data acquisition and object detection. After this the integrated system was described and discussed. Our paper presents a novel approach for moving target detection. This approach effectively tackles some of the well-known problems in the field of view, resolution, and real-time processing problems in moving target detection.

Data-Driven Fault Detection of Multiple Open-Circuit Faults for MMC Systems Based on Long Short-Term Memory Networks

This paper presents a long short-term memory(LSTM)-based fault detection method to detect the multiple open-circuit switch faults of modular multilevel converter(MMC)systems with full-bridge sub-modules(FB-SMs).Eighteen sensor signals of grid voltages,grid currents and capacitance voltages of MMC for single and multi-switch faults are collected as sampling data.The output signal characteristics of four types of single switch faults of FB-SM,as well as double switch faults in the same and different phases of MMC,are analyzed under the conditions of load variations and control command changes.A multi-layer LSTM network is devised to deeply extract the fault characteristics of MMC under different faults and operation conditions,and a Softmax layer detects the fault types.Simulation results have confirmed that the proposed LSTM-based method has better detection performance compared with three other methods:K-nearest neighbor(KNN),naive bayes(NB)and recurrent neural network(RNN).In addition,it is highly robust to model uncertainties and Gaussian noise.The validity of the proposed method is further demonstrated by experiment studies conducted on a hardware-in-the-loop(HIL)testing platform.

Current Technologies of Synthetic Biosensors for Disease Detection:Design,Classification and Future Perspectives

Synthetic biology aims to endow living cells with new functions by incorporating functional gene networks into them.By overexpressing,blocking and rewiring native gene pathways,synthetic biologists have harnessed this promising technology to reprogram cells to perform diverse tasks such as drug discovery,biopharmaceutical manufacturing,gene therapy and tissue engineering,etc.In this review,we focus on current technologies of synthetic biosensors for disease detection.We start with the design principle of synthetic biosensors.Then we move towards the characteristics of simple synthetic biosensors,which can respond to a single input signal,and complex synthetic biosensors including Boolean gate biosensors,cascade biosensors,time-delay biosensors,oscillator biosensors and hysteretic biosensors,which can respond to more than two input signals and perform complex tasks.Synthetic biosensor has showed great potential in disease detection,but it is still in its infancy stage.More efforts should be made in identifying and constructing clinically relevant regulation systems.Computational tools are also needed in the design process in order to guarantee the precision of the synthetic biosensor.The ultimate goal of a synthetic biosensor is to act as a therapeutic sensor-effector device that connects diagnostic input with therapeutic output and therefore provides all-in-one diagnostic and therapeutic solutions for future gene-and cell-based therapies.

A New Method for the Detections of Multiple Faults Using Binary Decision Diagrams

With the complexity of integrated circuits is continually increasing, a local defect in circuits may cause multiple faults. The behavior of a digital circuit with a multiple fault may significantly differ from that of a single fault. A new method for the detection of multiple faults in digital circuits is presented in this paper, the method is based on binary decision diagram （BDD）. First of all, the BDDs for the normal circuit and faulty circuit are built respectively. Secondly, a test BDD is obtained by the XOR operation of the BDDs corresponds to normal circuit and faulty circuit. In the test BDD, each input assignment that leads to the leaf node labeled 1 is a test vector of multiple faults. Therefore, the test set of multiple faults is generated by searching for the type of input assignments in the test BDD. Experimental results on some digital circuits show the feasibility of the approach presented in this paper.