Construction Technology of Lightning Protection Devices in Building Electrical Installation Engineering

To better improve the electrical safety of buildings and fulfill the role of lightning protection and grounding,this article combines cases and discusses seven aspects of lightning protection devices’construction technology.These aspects include the lightning protection classification of buildings,air terminals,down conductors,grounding devices,division of lightning protection zones,and lightning electromagnetic pulse shielding.Through the introduction of this article,readers can gain a comprehensive understanding of the application and value of lightning protection grounding construction technology in building electrical installation projects.

Driving and Braking Control of PM Synchronous Motor Based on Low-resolution Hall Sensor for Battery Electric Vehicle

Resolvers are normally employed for rotor positioning in motors for electric vehicles, but resolvers are expensive and vulnerable to vibrations. Hall sensors have the advantages of low cost and high reliability, but the positioning accuracy is low. Motors with Hall sensors are typically controlled by six-step commutation algorithm, which brings high torque ripple. This paper studies the high-performance driving and braking control of the in-wheel permanent magnetic synchronous motor （PMSM） based on low-resolution Hall sensors. Field oriented control （FOC） based on Hall-effect sensors is developed to reduce the torque ripple. The positioning accuracy of the Hall sensors is improved by interpolation between two consecutive Hall signals using the estimated motor speed. The position error from the misalignment of the Hall sensors is compensated by the precise calibration of Hall transition timing. The braking control algorithms based on six-step commutation and FOC are studied. Two variants of the six-step commutation braking control, namely, half-bridge commutation and full-bridge commutation, are discussed and compared, which shows that the full-bridge commutation could better explore the potential of the back electro-motive forces （EMF）, thus can deliver higher efficiency and smaller current ripple. The FOC braking is analyzed with the phasor diagrams. At a given motor speed, the motor turns from the regenerative braking mode into the plug braking mode if the braking torque exceeds a certain limit, which is proportional to the motor speed. Tests in the dynamometer show that a smooth control could be realized by FOC driving control and the highest efficiency and the smallest current ripple could be achieved by FOC braking control, compared to six-step commutation braking control. Therefore, FOC braking is selected as the braking control algorithm for electric vehicles. The proposed research ensures a good motor control performance while maintaining low cost and high reliability.

Sensor Fault Diagnosis and Reconstruction of Engine Control System Based on Autoassociative Neural Network

The topology and property of Autoassociative Neural Networks(AANN) and theAANN's application to sensor fault diagnosis and reconstruction of engine control system arestudied. The key feature of AANN is feature extract and noise filtering. Sensor fault detection isaccomplished by integrating the optimal estimation and fault detection logic. Digital simulationshows that the scheme can detect hard and soft failures of sensors at the absence of models forengines which have performance deteriorate in the service life, and can provide good analyticalredundancy.

STEADY-STATE AND IDLE OPTIMIZA-TION OF INTERNAL COMBUSTION ENGINE CONTROL STRATEGIES FOR HYBRID ELECTRIC VEHICLES

A novel steady-state optimization （SSO） of internal combustion engine （ICE） strategy is proposed to maximize the efficiency of the overall powertrain for hybrid electric vehicles, in which the ICE efficiency, the efficiencies of the electric motor （EM） and the energy storage device are all explicitly taken into account. In addition, a novel idle optimization of ICE strategy is implemented to obtain the optimal idle operating point of the ICE and corresponding optimal parking generation power of the EM using the view of the novel SSO of ICE strategy. Simulations results show that potential fuel economy improvement is achieved relative to the conventional one which only optimized the ICE efficiency by the novel SSO of ICE strategy, and fuel consumption per voltage increment decreases a lot during the parking charge by the novel idle optimization of ICE strategy.

HIGH PERFORMANCE ELECTRIC FIELD MICRO SENSOR WITH COMBINED DIFFERENTIAL STRUCTURE

This paper presents a high performance electric field micro sensor with combined differential structure.The sensor consists of two backward laid micro-machined chips,each packaged by polymer and metal.The novel combined differential structure effectively reduces various environmental affections,such as thermal drift,humidity drift and electrostatic charge accumulation.The sensor is tested in near-ground place as well as balloon-borne sounding.In different weather conditions,the measurement results showed good agreement with those of the commercial electric field mill.

Morphological Engineering of Sensing Materials for Flexible Pressure Sensors and Artificial Intelligence Applications

As an indispensable branch of wearable electronics,flexible pressure sensors are gaining tremendous attention due to their extensive applications in health monitoring,human-machine interaction,artificial intelligence,the internet of things,and other fields.In recent years,highly flexible and wearable pressure sensors have been developed using various materials/structures and transduction mechanisms.Morphological engineering of sensing materials at the nanometer and micrometer scales is crucial to obtaining superior sensor performance.This review focuses on the rapid development of morphological engineering technologies for flexible pressure sensors.We discuss different architectures and morphological designs of sensing materials to achieve high performance,including high sensitivity,broad working range,stable sensing,low hysteresis,high transparency,and directional or selective sensing.Additionally,the general fabrication techniques are summarized,including self-assembly,patterning,and auxiliary synthesis methods.Furthermore,we present the emerging applications of high-performing microengineered pressure sensors in healthcare,smart homes,digital sports,security monitoring,and machine learning-enabled computational sensing platform.Finally,the potential challenges and prospects for the future developments of pressure sensors are discussed comprehensively.

An adaptive electrical resistance tomography sensor with flow pattern recognition capability

The all traditional electrical resistance tomography (ERT) sensors have a static structure, which cannot satisfy the intelligent requirements for adaptive optimization to ERT sensors that is subject to flow pattern changes during the real-time detection of two-phase flow. In view of this problem, an adaptive ERT sensor with a dynamic structure is proposed. The electrodes of the ERT sensor are arranged in an array structure, the flow pattern recognition technique is introduced into the ERT sensor design and accordingly an ERT flow pattern recognition method based on signal sparsity is proposed. This method uses the sparse representation of the signal to express the sampling voltage of the ERT system as a sparse combination and find its sparse solution to achieve the classification of different flow patterns. With the introduction of flow identification information, the sensor has an intelligent function of adaptively and dynamically adapting the sensor structure according to the real-time flow pattern change. The experimental results show that the sensor can automatically identify four typical flow patterns: core flow, bubble flow, laminar flow and circulation flow with recognition rates of 91%, 93%, 90% and 88% respectively. For different flow patterns, the dynamically optimized sensor can significantly improve the quality of ERT image reconstruction.

Integration optimization of novel electric power steering system based on quality engineering theory

The dynamic model of a novel electric power steering （EPS） system integrated with active front steering function （the novel EPS system） is built. The concepts and quantitative expressions of the steering road feel, steering sensibility, and steering operation stability are introduced. Based on quality engineering theory, the optimization algorithm is proposed by integrating the Monte Carlo descriptive sampling, elitist non-dominated sorting genetic algorithm （NSGA-II） and 6-sigma design method. With the steering road feel and the steering portability as optimization targets, the system parameters are optimized by the proposed optimization algorithm. The simulation results show that the system optimized based on quality engineering theory can improve the steering road feel, guarantee steering stability and steering portability and thus provide a theoretical basis for the design and optimization of the novel electric power steering system.

Biomimetic Sensors:Active Electrolocation of Weakly Electric Fish as a Model for Active Sensing in Technical Systems

Instead of vision, many nocturnal animals use alternative senses for navigation and object detection in their dark environment. For this purpose, weakly electric mormyrid fish employ active electrolocation, during which they discharge a specialized electric organ in their tail which discharges electrical pulses. Each discharge builds up an electrical field around the fish, which is sensed by cutaneous electroreceptor organs that are distributed over most of the body surface of the fish. Nearby objects distort this electrical field and cause a local alteration in current flow in those electroreceptors that are closest to the object. By constandy monitoring responses of its electroreceptor organs, a fish can detect, localize, and identify environmental objects. Inspired by the remarkable capabilities of weakly electric fish in detecting and recognizing objects, we designed technical sensor systems that can solve similar problems of remote object sensing. We applied the principles of active electrolocation to technical systems by building devices that produce electrical current pulses in a conducting medium （water or ionized gases） and simultaneously sense local current density. Depending on the specific task a sensor was designed for devices could （i） detect an object, （ii） localize it in space, （iii） determine its distance, and （iv） measure properties such as material properties, thickness, or material faults. Our systems proved to be relatively insensitive to environmental disturbances such as heat, pressure, or turbidity. They have a wide range of applications including material identification, quality control, non-contact distance measurements, medical applications and many more. Despite their astonishing capacities, our sensors still lag far behind what electric fish are able to achieve during active electrolocation. The understanding of the neural principles governing electric fish sensory physiology and the corresponding optimization of our sensors to solve certain technical tasks therefore remain ongoing goals of our research.

Study of Pulsed Plasma in a Crossed Flow Dielectric Barrier Discharge Reactor for Improvement of NO_x Removal in Raw Diesel Engine Exhaust

Improved performance of plasma in raw engine exhaust treatment is reported. A new type of reactor referred to as of cross-flow dielectric barrier discharge （DBD） was used, in which the gas flow is perpendicular to the corona electrode. In raw exhaust environment, the cross-flow （radial-flow） reactor exhibits a superior performance with regard to NOx removal when compared to that with axial flow of gas. Experiments were conducted at different flow rates ranging from 2 L/min to 25 L/min. The plasma assisted barrier discharge reactor has shown encouraging results in NOx removal at high flow rates.

ENGINE SENSOR FAULT DIAGNOSIS USING MAIN AND DECENTRALIZED NEURAL NETWORKS

This Paper presents a methodology for solving the sensor failure detection, isolation and accommodation of aeroengine control systems using on line learning neural networks(NN), which has one main NN and a set of decentralized NNs. Changes in the system dynamics are monitored by the on line learning NN. When a failure occurs in some sensor, the sensor failure detection can be accomplished with high precision, and the sensor failure accommodation can be achieved by replacing the value from the failed sensor with its estimate from the decentralized NN. By integrating the optimal estimation and failure logic, this method can detect soft failures. Simulation of one kind of turboshaft engine control system with this multiple neural network architecture shows that the ANN developed can detect and isolate hard and soft sensor failures timely and provide accurate accommodation.

Open-Innovation in the Electrical and Electronic Industries: Engineered Bio-Fluid Compositions Are Paving the Way, and Testing Therewith

Engineered Biofluids are paving the way to industrialized and specifically produced and tailored functional fluids such as coolant and dielectric, high purity traceable media, for the electrical and electronic industries. Dielectric fluid compositions are commonly used in electrical devices, particularly in transformers. These liquids have the aim to isolate the various conductive elements of the device and to limit the heating of the equipment during its operation;in order to minimize, or maintain at higher power, the size of the device and to increase the lifespan of it. Concomitantly a number of bio and traditional processing advancements are made associated with pioneering process technologies which are outlined within the prime context of this paper. Enzyme Engineering and Cocktailing add “A New Dimension to Softer Greener Chem-Bio Approaches” which are referenced beyond curiosity purpose. Some of them are possibly “revolutionary” more than evolutionary. Testing has to evolve accordingly to appreciate the challenges ahead in semi-extreme conditions which are relevant to climate changes as well. A significant part of this orientation work addresses and exemplifies these necessary testing innovations, likely adaptable to smart and responsive connecting, and further down the line bigger data role and learning machine evolutionary concepts. One other innovative part of this exploratory work, is the influence that such illustrative localized testing, with integrated sensors/induced-tracers, and online interpretation, may have on the smart grid developments;whereby production, transmission, distribution and consumption of energy can be made more reliable, more effective and more predictive and can also have an impact on the performance, reliability and sustainability of the equipment itself. Those technologies and associated testing can support environmental, technological and societal awareness;helping to revert some trends being climate changes, fossil fuel preservation and other planetary challenges to maintain the overall and localized fundamental equilibriums.

Key techniques for evaluation of safety monitoring sensors in water conservancy and hydropower engineering

For the evaluation of construction quality and the verification of the design of water conservancy and hydropower engineering projects, and especially for the control of dam safety operation behavior, safety monitoring sensors are employed in a majority of engineering projects. These sensors are used to monitor the project during the dam construction and operation periods, and play an important role in reservoir safety operation and producing benefits. With the changing of operating environments and run-time of projects, there are some factors affecting the operation and management of projects, such as a certain amount of damaged sensors and instability of the measured data. Therefore, it is urgent to evaluate existing safety monitoring sensors in water conservancy and hydropower engineering projects. However, there are neither standards nor evaluation guidelines at present. Based on engineering practice, this study examined some key techniques for the evaluation of safety monitoring sensors, including the evaluation process of the safety monitoring system, on-site detection methods of two typical pieces of equipment, the differential resistor sensor and vibrating wire sensor, the on-site detection methods of communication cable faults, and a validity test of the sensor measured data. These key techniques were applied in the Xiaolangdi Water Control Project and Xiaoxi Hydropower Project. The results show that the measured data of a majority of sensors are reliable and reasonable, and can reasonably reflect the structural change behavior in the project operating process, indicating that the availabilities of the safety monitoring sensors of the two projects are high

NETLAB-An Internet based laboratory for electrical engineering education

This article describes an Internet based laboratory (NETLAB) developed at Zhejiang University for electrical engi- neering education. A key feature of the project is the use of real experimental systems rather than simulation or virtual reality. NELTAB provides remote access to a wide variety of experiments, including not only basic electrical and electronic experiments but also many innovative control experiments. Students can effectively use the laboratory at any time and from anywhere. NETLAB has been in operation since July 2003.

MODELING AND IMPLEMENTATION OF SPEED GOVERNOR FOR THE HYBRID ELECTRIC VEHICLE ENGINE

A speed control analysis for an in-line gasoline fueled internal combustion （IC） engine is presented for the purpose of alleviation of high frequency oscillations in engine revolutions. A dynamic cylinder-by-cylinder model is proposed, base on slider-crank mechanism, which is extended to develop a digital governor providing a high fidelity estimation of rotary speed oscillation for hybrid vehicle engines. A modified PID controller that P and I gain is placed in feedback path is also described for hybrid electric vehicle （HEV） engine speed regulation, By comparison between measured and estimated signals, it is demonstrated that a good agreement has been achieved and the governor behaves an excellent damping speed ripple.

Progress of Journal 'Advanced Technology of Electrical Engineering and Energy'

The paper has introduced the Journal 'Advanced Technology of Electrical Engineering and Energy',presented its main journal evaluation indexes. The result indicates that the journal has made great progress in recent years. It gives much info. about the journal to authors.

Effect of Fluid Electrical Property Changes on Surface Transverse Wave Sensors

A fluid sensor based on the surface transverse wave (STW) delay line on ST-cut quartz has been developed and tested in a large number of fluids with different viscosity and permittivity levels.Influence of fluid mechanical and electrical properties on the sensor's response has been determined and the sensor's performance has been compared with a bulk acoustic wave (BAW) viscosity sensor.The result shows that the viscosity sensitivity of the developed STW sensor represented by the signal to noise ratio is lower than that of a 5 MHz BAW sensor.Applications of the sensor in detecting the quality of industrial fluids are discussed.

Design of Engine-Generator Work Mode for Hybrid Electric Vehicle

From electric circuit theory view, a system model of series hybrid electric vehicle was built which uses engine-generator and battery pack as its on-board energy source in this paper. Based on the analysis for the constant power work mode and constant bus voltage work mode of engine-generator, a third work mode was put forward which combined the advantages of constant power and constant bus voltage work modes. The new work mode is reasonable to keep the battery in good working conditions and to extend its life. Also the working conditions of engine can be bettered to get low pollution and high efficiency.

A BPR-CNN Based Hand Motion Classifier Using Electric Field Sensors

In this paper,we propose a BPR-CNN(Biometric Pattern Recognition-Convolution Neural Network)classifier for hand motion classification as well as a dynamic threshold algorithm for motion signal detection and extraction by EF(Electric Field)sensors.Currently,an EF sensor or EPS(Electric Potential Sensor)system is attracting attention as a next-generationmotion sensing technology due to low computation and price,high sensitivity and recognition speed compared to other sensor systems.However,it remains as a challenging problem to accurately detect and locate the authentic motion signal frame automatically in real-time when sensing body-motions such as hand motion,due to the variance of the electric-charge state by heterogeneous surroundings and operational conditions.This hinders the further utilization of the EF sensing;thus,it is critical to design the robust and credible methodology for detecting and extracting signals derived from the motion movement in order to make use and apply the EF sensor technology to electric consumer products such as mobile devices.In this study,we propose a motion detection algorithm using a dynamic offset-threshold method to overcome uncertainty in the initial electrostatic charge state of the sensor affected by a user and the surrounding environment of the subject.This method is designed to detect hand motions and extract its genuine motion signal frame successfully with high accuracy.After setting motion frames,we normalize the signals and then apply them to our proposed BPR-CNN motion classifier to recognize their motion types.Conducted experiment and analysis show that our proposed dynamic threshold method combined with a BPR-CNN classifier can detect the hand motions and extract the actual frames effectively with 97.1%accuracy,99.25%detection rate,98.4%motion frame matching rate and 97.7%detection&extraction success rate.

Ecosystem Service Value of Jingtaichuan Electric Power Irrigation Engineering

The ecosystem service value of Jingtaichuan electric power irrigation engineering( referred to as Jingdian engineering) was divided into internal value( the value of farmland system,shelter forest system outside of farmland and wetland waters) and external value( the ecological service value of ecological migration to the vegetation restoration of the Qilian Mountains) firstly,and then it was analyzed by using the model method and the factor equivalent method. The results showed that the internal ecological service value of Jingdian engineering was 36. 3 ×10~8 yuan,which was 25. 0 times larger than the total annual cost. The external ecological service value was 40. 05 ×10~8 yuan,which was 27. 6 times larger than the total annual cost. Among the three functional systems,the ecological service value of farmland system was the largest. The ecological service value of farmland system was mainly reflected in waste disposal,wind prevention and sand fixation,and food production. The external ecological service value was mainly the ecological service value of migration to vegetation restoration in the Qilian Mountains. Jingdian engineering is the only highlifting project that raises water to the desert in China. It transfers water from outer basins to control desertification and provides a successful road for ecological migration and desertification control in arid areas.