Search results

This study presents a new method for the detection of faults in large transformer cores. It is based on the analysis of leakage flux components in the vicinity of the sheet stack. The purpose of this study is to provide a nondestructive analysis tool for transformer cores during the assembly process to detect accidental defects such as inter-laminar short circuits.

The different components of the leakage flux allow localization of the fault in the stack and also permit to assess its severity. Out of the many kinds of defects which may appear in a transformer core, this method only detects those which actually cause an increase in the transformer’s global iron losses, which are thus the most detrimental.

The proposed method allows a more efficient control of the quality of the cores during their manufacturing process. Until now, it was only possible to know the quality of the core when the transformer was fully assembled.

The accuracy of the method depends on the size of the defect and may request many measurements to give usable information.

Controlling iron losses in a core during its construction avoids heavy dismantling operations, both financially and temporally.

This method can help transformer manufacturers optimize their building process. In addition, the method remains effective regardless of the size of the core considered.

This paper aims to improve the general circuit of driving and protection based on insulated gate bipolar transistor (IGBT) in dielectric barrier discharge power supply by designing a novel half-bridge inverter circuit with discrete components.

With one SG3524 chip, the structure based on discrete components is used to design the IGBT drive circuit. The driving waveform is isolated and sent out by photo-coupler 6N137. The protection circuit is realized by Hall sensor directly detecting the main circuit current, supplemented by a few components, including diodes, resistors, capacitors and triodes. It improves the reliability of the protection circuit.

In the driving circuit, the phase difference of signals from two channels are 180°. Moreover, when the duty cycle is set at 40%, it can ensure sufficient pulse width modulation response time. In the protection circuit, when over-current occurs, an intermittent output signal is automatically sent out. Furthermore, the over-current response time can be controlled independently. The peak voltage can be adjusted continuously from 0 to 30 kV with its frequency from 8 to 25 kHz and the power output up to 150 W.

The novel circuit of driving and protection makes not only its structure simpler and easier to be realized but also key parameters, such as frequency, the duty cycle and the driving voltage, continuously adjustable. Moreover, the power supply is suitable for other discharges such as corona discharge and jet discharge.

Power converters are an integral part of the energy conversion process in solar photovoltaic (PV) systems which is used to match the solar PV generation with the load requirements. The increased penetration of renewable invokes intermittency in the generated power affecting the reliability and continuous energy supply of such converters. DC-DC converters deployed in solar PV systems impose stringent restrictions on supplied power, continuous operation and fault prediction scenarios by continuously observing state variables to ensure continuous operation of the converter.

A converter deployed for a mission-critical application has to ensure continuous regulated output for which the converter has to ensure fault-free operation. The fault diagnostic algorithm relies on the measurement of a state variable to assess the type of fault. In the same line, a predictive controller depends on the measurement of a state variable to predict the control variable of a converter system to regulate the converter output around a fixed or a variable reference. Consequently, both the fault diagnosis and the predictive control algorithms depend on the measurement of a state variable. Once measured, the available data can be used for both algorithms interchangeably.

The objective of this work is to integrate the fault diagnostic and the predictive control algorithms while sharing the measurement requirements of both these control algorithms. The integrated algorithms thus proposed could be applied to any converter with a single inductor in its energy buffer stage.

laboratory prototype is created to verify the feasibility of the integrated predictive control and fault diagnosis algorithm. As the proposed method combine the fault detection algorithm along with predictive control, a load step variation and manual fault creation methods are used to verify the feasibility of the converter as with the simulation analysis. The value for the capacitors and inductors were chosen based on the charge-second and volt-second balance equations obtained from the steady-state analysis of boost converter.

The purpose of this paper is to present a new approach to edge detection using semiconductor flash memory networks having scalable and parallel hardware architecture.

A flash cell can store multiple states by controlling its voltage threshold. The equivalent resistance of the operation states controlled by threshold voltage of flash cell gives out different combinations of logic 0 and 1 states. The paper explores this basic feature of flash memory in designing a resistance change memory network for implementing novel edge detector hardware. This approach of detecting the edges is inspired from the spatial change detection ability of the human visual system.

The proposed approach consumes less number of electronic components for its implementation, and outperforms the conventional approaches of edge detection with respect to the processing speed, scalability and ease of design. It is also demonstrated to provide edges invariant to changes in the direction of the spatial change in the images.

This research brings about a new direction in the development of edge detection, in terms of developing high-speed parallel processing edge detection and imaging circuits.

The proposed approach reduces the implementation complexity by removing the need to have convolution operations for spatial edge filtering.

This paper presents one of the first edge detection approaches that is purely a hardware oriented design, uses resistance of flash memory to form edge detector cells, and one that does not use computational operations such as additions or multiplications for its implementation.

This study aims to present a novel technique to localize the human position in a room, to manage people in a specified space.

In this study, a real-time human sensing detection and smart lighting control was designed within a single silicon core. The chip has been successfully realized within 1.5 mm² silicon area using TSMC 0.25 um process.

This chip can read the weak signal of pyroelectric infrared (PIR) sensor to find the position of human body in a dark room and then help control the smart lighting system for an intelligent surveillance system.

This chip presented the retriggering delay control to expand the LED lighting time infinitely to avoid lighting-off suddenly while users stay on a space. This function is very useful in a practical intelligent surveillance system that is mainly based on human detection to better reduce power dissipation and memory space.

This work encompasses the various laboratory-based and portable methods evolved in recent times for sensitive and selective detection of ethylene for fruit-ripening application. The role of ethylene in natural and artificial fruit ripening and the associated health hazards are well known. So there is a growing need for ethylene detection. This paper aims to highlight potential methods developed for ethylene detection by various researchers, including ours. Intense efforts by various researchers have been on since 2014 for societal benefits.

The paper focuses on types of sensors, fabrication methods and signal conditioning circuits for ethylene detection in ppm levels for various applications. The authors have already designed, developed a laboratory-based set-up belonging to the electrochemical and optical methods for detection of ethylene.

The authors have developed a carbon nanotube (CNT)-based chemical sensor whose performance is higher than the reported sensor in terms of material, sensitivity and response, the sensor element being multi-walled carbon nanotube (MWCNT) in comparison to single-walled carbon nanotube (SWCNT). Also the authors have developed infrared (IR)-based physical sensor for the first time based on the strong IR absorption of ethylene at 10.6 µm. These methods have been compared with literature based on comparable parameters. The review highlights the potential possibilities for development of portable device for field applications.

The authors have reported new chemical and physical sensors for ethylene detection and quantification. It is demonstrated that it could be used for fruit-ripening applications A comparison of reported methods and potential opportunities is discussed.

With the widespread use and development of automobile, much attention has been paid to its security issues. So to ensure the driving safety, the automobile must be equipped with good braking performance. In the process of braking, the friction from friction pair causes continuous wear and tear of the surface of brake lining and increases the gap between break pairs, until the lining is not being used (Belhocinea et al., 2014); thus, it is very important to detect the lining wear rate.

This paper designed the automobile brake friction test wear rate detection system based on Labview.

Through the detect data, we find that the automobile brake lining wear rate detection system has higher detect accuracy, in the process of detection, the brake lining without the defects such as cracks and bulges, which shall effect the normal use, the lining has no remarkable scratch to disk friction surface, can completed meet the requirements of users.

The automobile brake friction test wear rate detecting system adopts the components of USB-9211 DAQ, optoNCDT1700 non-contract high accuracy displacement sensor, in addition the Labview software to complete the functions such as lining wear rate real time detection, data multichannel real time acquisition, display, and storage record, etc., and uses LabSQL to import the detecting data to Microsoft Access database, which can satisfy the demands of various customers. Moreover, the wear rate real time detection can reflect the lining’s wear regulation of different manufacturers and different material and provide a reliable basis for selecting the appropriate lining material and predicting the lining’s lifetime.

The purpose of this paper is to prevent the destruction of other parts of a wind energy conversion system because of faults, the diagnosis of insulated-gate bipolar transistor (IGBT) faults has become an essential topic of study. Demand for sustainable energy sources has been prompted by rising environmental pollution and energy requirements. Renewable energy has been identified as a viable substitute for conventional fossil fuel energy generation. Because of its rapid installation time and adaptable expenditure for construction scale, wind energy has emerged as a great energy resource. Power converter failure is particularly significant for the reliable operation of wind power conversion systems because it not only has a high yearly fault rate but also a prolonged downtime. The power converters will continue to operate even after the failure, especially the open-circuit fault, endangering their other parts and impairing their functionality.

The most widely used signal processing methods for locating open-switch faults in power devices are the short-time Fourier transform and wavelet transform (WT) – based on time–frequency analysis. To increase their effectiveness, these methods necessitate the intensive use of computational resources. This study suggests a fault detection technique using empirical mode decomposition (EMD) that examines the phase currents from a power inverter. Furthermore, the intrinsic mode function’s relative energy entropy (REE) and simple logical operations are used to locate IGBT open switch failures.

The presented scheme successfully locates and detects 21 various classes of IGBT faults that could arise in a two-level three-phase voltage source inverter (VSI). To verify the efficacy of the proposed fault diagnosis (FD) scheme, the test is performed under various operating conditions of the power converter and induction motor load. The proposed method outperforms existing FD schemes in the literature in terms of fault coverage and robustness.

This study introduces an EMD–IMF–REE-based FD method for VSIs in wind turbine systems, which enhances the effectiveness and robustness of the FD method.

The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation methods of the system.

A multi-channel data acquisition scheme based on PCI-E (rapid interconnection of peripheral components) was proposed. The flexible biosensor is integrated with the flexible data acquisition card with monitoring capability, and the embedded (device that can operate independently) chip STM32F103VET6 is used to realize the simultaneous processing of multi-channel human health parameters. The human health parameters were transferred to the upper computer LabVIEW by intelligent clothing through USB or wireless Bluetooth to complete the transmission and processing of clinical data, which facilitates the analysis of medical data.

The smart clothing provides a mobile medical cloud platform for wearable medical through cloud computing, which can continuously monitor the body's wrist movement, body temperature and perspiration for 24 h. The result shows that each channel is completely accurate to the top computer display, which can meet the expected requirements, and the wearable instant care system can be applied to healthcare.

The smart clothing in this study is based on the monitoring and diagnosis of textiles, and the electronic communication devices can cooperate and interact to form a wearable textile system that provides medical monitoring and prevention services to individuals in the fastest and most accurate way. Each channel of the system is precisely matched to the display screen of the host computer and meets the expected requirements. As a real-time human health protection platform technology, continuous monitoring of human vital signs can complete the application of human motion detection, medical health monitoring and human–computer interaction. Ultimately, such an intelligent garment will become an integral part of our everyday clothing.

The purpose of this paper is to develop a method for multiple soft fault diagnosis of nonlinear circuits including fault detection, identification of faulty elements and estimation of their values in real circumstances.

The method for fault diagnosis proposed here uses a measurement test leading to a system of nonlinear equations expressing the measured quantities in terms of the circuit parameters. Nonlinear functions, which appear in these equations are not given in explicit analytical form. The equations are solved using a homotopy concept. A key problem of the solvability of the equations is considered locally while tracing the solution path. Actual faults are selected on the basis of the observation that the probability of faults in fewer number of elements is greater than in a larger number of elements.

The results indicate that the method is an effective tool for testing nonlinear circuits including bipolar junction transistors and junction field effect transistors.

The homotopy method is generalized and associated with a restart procedure and a numerical algorithm for solving differential equations. Testable sets of elements are found using the singular value decomposition. The procedure for selecting faulty elements, based on the minimal fault number rule, is developed. The method comprises both theoretical and practical aspects of fault diagnosis.