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The purpose of this paper is to present a doubly fed induction machine (DFIM) operating in motor mode and supplied by two voltage source inverters (in stator and rotor sides).

The aim is to analyze the current sensor fault effects on the stator flux‐oriented control according to the current input‐output decoupling. This justifies the necessity of a reconfiguration control in order to satisfy the system service continuity. Also, a theoretical development of sensitivity coefficients gives an idea about control robustness toward a current sensor fault.

This paper emphasizes the system performance close dependency to the current sensor outputs accuracy. Moreover, simulation results point out the operation system deterioration in case of current sensor fault, which leads in most cases to its shut down in contrast with the industrial expectations. In this paper, the suggested solution is the DFIM speed drive control reconfiguration when a current sensor fault occurs in order to ensure system service continuity. MATLAB‐Simulink simulation results illustrate the system behavior before and after a current sensor fault. System performance preservation is performed after control reconfiguration.

This solution presented in this paper is relevant, especially because of its simplicity.

The aim of this paper is to implement direct teaching of industrial manipulators using current sensors. The traditional way to implement teaching is either to use a teaching pedant, which is time consuming, or use force sensors, which increases system cost. To overcome these disadvantages, a novel method is explored in the paper by using current sensors installed at joints as torque observers.

The method uses current sensors installed at each joint of a manipulator as torque observers and estimates external forces from differences between joint-driven torque computed based on the values of current sensors and commanded values of motor-driven torque. The joint-driven torque is computed by cancelling out both pre-calibrated gravity and friction resistance (compensation). Also, to make the method robust, the paper presents a strategy to detect unexpected slowly drifts and zero external forces and stop the robot in those situations.

Experimental results demonstrated that compensating the joint torques using both pre-calibrated gravity and friction resistance has performance comparable to a force sensor installed on the end effector of a manipulator. It is possible to implement satisfying direct teaching without using force sensors on 7 degree of freedom manipulators with large mass and friction resistance.

The main contribution of the paper is that the authors cancel out both pre-calibrated gravity and friction resistance to improve the direct teaching using only current sensors; they develop methods to avoid unsafe situations like slow drifts. The method will benefit industrial manipulators, especially those with large mass and friction resistance, to realize flexible and reliable direct teaching.

This paper aims to study the influence of different reinforcement methods on crack monitoring characteristics of eddy current array sensors, and the sensors with two different reinforcement methods, SUS304 reinforcement and permalloy reinforcement, are proposed.

First, the finite element model of the sensor is established to analyze the influence of the reinforcement plate’s electromagnetic parameters on the crack identification sensitivity. Then, the crack monitoring accuracy test of sensors with two reinforcement methods is carried out. Finally, the fatigue crack monitoring experiments with bolt tightening torques of 45 and 63 N · m are carried out, respectively.

In this study, it is found that the crack identification sensitivity of the sensor can be improved by increasing the relative permeability of the reinforcement plate. The crack monitoring accuracy of the sensors with two different reinforcement methods is about 1 mm. And the crack identification sensitivity of the sensor reinforced by permalloy reinforcement plate is significantly higher than that of the sensor reinforced by SUS304 reinforcement plate.

The sensor reinforced by reinforcement plate can work normally under the squeezing action of the bolt, and the crack monitoring sensitivity of the sensor can be significantly improved by using the reinforcement plate with high relative permeability.

The purpose of this paper is to investigate the process of rapid prototyping eddy current sensors using 3D printing technology. Making full use of the advantages of 3D printing, the authors study on a new method for fabrication of an eddy current sensor.

In this paper, the authors establish a 3D model using SolidWorks. And the eddy current sensor is printed by the fused deposition modeling method.

Measurement results show that the 3D printing eddy current sensor has a wider linear measurement range and better linearity than the traditional manufacturing sensor. Compared to traditional eddy current sensor fabrication method, this 3D printed sensor can be fabricated at a lower cost, and the fabrication process is more convenient and faster.

This demonstrated 3D printing process can be applied to the 3D printing of sensors of more sophisticated structures that are difficult to fabricate using conventional techniques.

In this work, the process of rapid prototyping eddy current sensors using 3D printing is presented. Sensors fabricated with the 3D printing possess lots of merits than traditional manufactures. 3D printed sensors can be customized according to the configuration of the overall system, thus reducing the demand of sensor's rigid mounting interfaces. The 3D printing also reduce design costs as well as shortens the development cycle. This allows for quick translation of a design from concept to a useful device.

Welding process is a complicated process influenced by many interference factors, a single sensor cannot get information describing welding process roundly. This paper simultaneously uses different sensors to get different information about the welding process, and uses multi‐sensor information fusion technology to fuse the different information. By using multi‐sensors, this paper aims to describe the welding process more precisely.

Electronic and welding pool image information are, respectively, obtained by arc sensor and image sensor, then electronic signal processing and image processing algorithms are used to extract the features of the signals, the features are then fused by neural network to predict the backside width of weld pool.

Comparative experiments show that the multi‐sensor fusion technology can predict the weld pool backside width more precisely.

The multi‐sensor fusion technology is used to fuse the different information obtained by different sensors in a gas tungsten arc welding process. This method gives a new approach to obtaining information and describing the welding process.

Nanopore-based molecular sensing and measurement, specifically DNA sequencing, is advancing at a fast pace. Some embodiments have matured from coarse particle counters to enabling full human genome assembly. This evolution has been powered not only by improvements in the sensors themselves, but also in the assisting microelectronic CMOS readout circuitry closely interfaced to them. In this light, this paper aims to review established and emerging nanopore-based sensing modalities considered for DNA sequencing and CMOS microelectronic methods currently being used.

Readout and amplifier circuits, which are potentially appropriate for conditioning and conversion of nanopore signals for downstream processing, are studied. Furthermore, arrayed CMOS readout implementations are focused on and the relevant status of the nanopore sensor technology is reviewed as well.

Ion channel nanopore devices have unique properties compared with other electrochemical cells. Currently biological nanopores are the only variants reported which can be used for actual DNA sequencing. The translocation rate of DNA through such pores, the current range at which these cells operate on and the cell capacitance effect, all impose the necessity of using low-noise circuits in the process of signal detection. The requirement of using in-pixel low-noise circuits in turn tends to impose challenges in the implementation of large size arrays.

The study presents an overview on the readout circuits used for signal acquisition in electrochemical cell arrays and investigates the specific requirements necessary for implementation of nanopore-type electrochemical cell amplifiers and their associated readout electronics.

The purpose of this paper is to suggest a novel current sensor-less drive system for a novel axial flux-switching permanent-magnet motor drive to reduce the costs and avoid problems caused by faults of the current sensors.

Commonly, a conventional controller needs at least two current sensors; in this paper, the current sensors are removed by replacing estimated stator current with the extended Kalman filter.

A prototype of the novel axial flux-switching permanent-magnet motor is fabricated and tested. It is found that the experimental results confirm the proposed method and show that the control has almost the same performance and ability as the conventional control.

The axial flux-switching permanent-magnet motor is one of the most efficient motors, but current sensor-less control of an axial flux-switching permanent-magnet motor with a sandwiched permanent magnet and a unity displacement winding factor has not been specially reported to date. Thus, in this paper, the authors report on current sensor-less control based on the extended Kalman filter for electric vehicles.

This paper aims to propose a low-power complementary MOS (CMOS) current sensor for control circuit in an integrated DC-DC buck converter.

The integrated DC-DC converter, which is composed of feedback control circuit and power block, is designed with 0.35-µm CMOS process. Current sensor in the control circuit is integrated with sense-FET and voltage-follower circuits to reduce power consumption and improve its sensing accuracy. In the current-sensing circuit, the size ratio of the power metal oxide semiconductor field effect transistor (MOSFET) to the sensing transistor (K) is 1,000, and a current-mirror is used for a voltage follower. N-channel MOS acts as a switching device in the current-sensing circuit, where the sensing FET is in parallel with the power MOSFET. The amplifier and comparator are designed to obtain a high gain and a fast transient time.

Experiment shows that the current sensor is operated with accuracy of more than 85 per cent, and the transient time of the error amplifier is controlled within 100 µs. The sensing current is in the range of a few hundred µA at a frequency of 0.6-2 MHz and an input voltage of 3-5 V. The output voltage is obtained as expected with the ripple ratio within 5 per cent.

The proposed current sensor in DC-DC converter provides an accurately sensed inductor current with a significant reduction in power consumption in the range of 0.2 mW. High-accuracy regulation is obtained using the proposed current sensor. As the sensor utilizes simple switch-type voltage follower and sense-FET, it can be widely applied to other low-power applications such as high-frequency oscillator and over-current protection circuit.

The overall performance of an electronic nose system will depend on the individual performance of its constituent elements. Although often overlooked, it is clear that careful design/selection of the front‐end signal conditioning circuit is of critical importance if optimal performance of the odour sensing system is to be achieved. In this paper circuits are reviewed, which have been employed as front‐end signal conditioners for resistance‐based sensors in electronic nose systems, with many of the conclusions drawn being equally applicable to other resistor sensors. The relevant equations governing the behaviour of each circuit methodology are derived and advantages and disadvantages are discussed. The performance of the circuit is then quantitatively assessed in a specific test case, in which the maximum sensitivity of the circuit is calculated in relation to the task of interfacing to a theoretical thin‐film conducting‐polymer sensor.

The status of welding process is difficult to monitor because of the intense disturbance during the process. The purpose of this paper is to use multiple sensors to obtain information about the process from different aspects and use multi‐sensor information fusion technology to fuse the information, to obtain more precise information about the process than using a single sensor alone.

Arc sensor, visual sensor, and sound sensor were used simultaneously to obtain weld current, weld voltage, weld pool's image, and weld sound about the pulsed gas tungsten‐arc welding (GTAW) process. Then special algorithms were used to extract the signal features of different information. Fuzzy measure and fuzzy integral method were used to fuse the extracted signal features to predict the penetration status about the welding process.

Experiment results show that fuzzy measure and fuzzy integral method can effectively utilize the information obtained by different sensors and obtain better prediction results than a single sensor.

Arc sensor, visual sensor, and sound sensor are used in pulsed GTAW at the same time to obtain information, and fuzzy measure and fuzzy integral method are used to fuse the different features in welding process for the first time; experiment results show that multi‐sensor information can obtain better results than single sensor, this provides a new method for monitoring welding status and to control the welding process more precisely.