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With the development of autonomous driving technology, it is of great practical and educational significance to consider the ethics in the process of its technology realization. On the one hand, compared with foreign countries, engineering ethics education still needs to be actively promoted and innovated in China. On the other hand, carrying out case study of engineering ethics meets the practical needs of training engineering talents. Based on this, this paper adopts a case study strategy centered on the autonomous driving ethics, and transforms the traditional teacher-centered teaching mode into a student-centered teaching mode in the form of role-playing and collaborative discussion. In addition, a curriculum design framework is proposed, which highlights initiative, participation and self-study guidance. Then, a simulation case of autonomous driving with increasingly complex scenarios is designed, guiding students to consider ethical issues in a deeper and more comprehensive way. As a result, the described teaching plan deepens the ethical awareness of engineering students in the project, and improves their ability to analyze and solve multi-dimensional engineering ethical problems.

With the continuous development and maturity of artificial intelligence, its application in many industries has gradually deepened, which has caused many ethical problems. This paper analyses the engineering ethical dilemma in the development of artificial intelligence from the aspects of intelligent robots, self-driving technology, killer robots and public information security, and further explores the causes of related problems. Finally, the corresponding countermeasures are put forward, including strengthening the supervision of artificial intelligence technology and products, enhancing the moral responsibility of scientists and engineers, strengthening international cooperation and building a human-machine fate community. The analysis of ethical problems and Countermeasures in artificial intelligence technology will help to solve the dilemma faced by AI technology in the development process to a certain extent.

Under the comprehensive background of the development of engineering education in the world today and the promotion of quality education in China, strengthening engineering ethics education of engineering masters meets the needs of engineering technology development, and is also an indispensable part of shaping high-quality engineers. However, engineering ethics awareness cannot be generated spontaneously. It needs to be cultivated and improved through engineering ethics education. Therefore, this paper designs a closed questionnaire from three aspects: school curriculum education, engineering ethics cognition and the application of ethical dilemma of driverless cars. The statistical data of the questionnaire shows that engineering masters do not pay enough attention to the engineering ethics curriculum and it is difficult to use the knowledge of engineering ethics to analyze and solve the actual ethical dilemmas. In addition, it is further found that there is a gap between professional masters and academic masters in the ethical awareness, and the reasons are related to the distribution of engineering ethics education courses offered by the school. This paper proposes three specific recommendations in response to the above problems.

The Energy Internet is a new type of energy utilization system based on power electronic technology and information and communication technologies. It uses energy and information to be closely coupled to achieve safe and efficient coordination and sharing. This paper analyzes the energy Internet basic concept and key technology, combined with the current energy demand of the Internet for information communication system and communication system problems, puts forward the hierarchical network design of energy Internet information communication.

Shape reconstruction of aerospace plate structure is an important issue for safe operation of aerospace vehicles. One way to achieve such reconstruction is by constructing smart fiber Bragg grating (FBG) plate structure with discrete distributed FBG sensor arrays using reconstruction algorithms in which error analysis of reconstruction algorithm is a key link. Considering that traditional error analysis methods can only deal with static data, a new dynamic data error analysis method are proposed based on LMS algorithm for shape reconstruction of smart FBG plate structure. Firstly, smart FBG structure and orthogonal curved network based reconstruction method is introduced. Then, a dynamic error analysis model is proposed for dynamic reconstruction error analysis. Thirdly, the parameter identification is done for the proposed dynamic error analysis model based on least mean square (LMS) algorithm. Finally, an experimental verification platform is constructed and experimental dynamic reconstruction analysis is done. Experimental results show that the dynamic characteristics of the reconstruction performance for plate structure can be obtained accurately based on the proposed dynamic error analysis method. The proposed method can also be used for other data acquisition systems and data processing systems as a general error analysis method.

An optimization method based on mode approach and improved genetic algorithms is developed for optimal FBG sensors placement in health monitoring and reconstruction of flexible thin-plate structure. The optimization objective is to obtain a kind of placement of FBG sensors which has the best reconstruction effects. The structure is modeled using Finite Element methods and modal analysis is carried out to create a modal space which provides data for both shape-reconstruction and error-calculation. The optimization is performed by improved genetic algorithm that uses the mean square error of reconstruction for the comparison of different optimal solution candidates. FBG sensors were arranged on the structural surface and experiment with an optimized sensor placement were performed to verify the effectiveness of the method and the simulation results.

It is of great significance to perform FBG sensor calibration in shape reconstruction for a board. It impacts on the shape reconstruction accuracy directly. Aiming at the deficiencies of traditional off-line calibration method, an online calibration for FBG networks based on improved particle swarm optimization algorithm was put forward, optimization model was established, and fitness function was given. The optimal goal is to obtain the minimum of fitness function. Improved particle swarm optimization algorithm was used to obtain the optimal solution, ie. strain-curvature coefficients of FBG networks. The simulation experiments verified the effectiveness of the method. Finally, experimental platform was built for experimental verification and analysis of the results of calibration. Experimental results showed that high reconstruction accuracy can be obtained by this calibration method, while the measurement characteristics of the FBG sensors can be reflected more accurately.

The control of a flexible transmission system under various conditions with various loads is an important challenge. This paper proposes a multiple-model adaptive control algorithm as a solution for the flexible transmission benchmark problem. Switching strategies and controller design methods are described in detail by means of the results of a stability analysis of the controller. To verify the effectiveness of the proposed algorithm, a flexible transmission experimental platform was employed to carry out comparison experiments using a robust controller, an adaptive controller, and the proposed controller. The experimental results showed that the proposed algorithm performed much better than the other controllers because in actual experiments, the other controllers failed under many conditions. The experimental parameter analysis of the proposed algorithm shows that the influence of parameters in the case of the proposed system is not significant when there is a sufficient number of models and reasonable dwell time. This means that the proposed algorithm can always guarantee stability control for flexible industrial transmission systems, and can quickly and stably track and adjust the target.

A transfer transistor structure achieving complete charge transfer in a CMOS image sensor pixel is proposed to eliminate image lag. This structure adopted double N implants for photodiode to ensure a wide channel of charge transfer, a surface P type preventing from dark current and especially a non-uniform doped poly-silicon gate to adjust the potential profile in channel. The simulation results show that if a light pulse of 10000lux illuminates for one integration cycle, the signal voltage of the following frame drops to 1/50000 of the first one. The electron density in N buried layer after charge transfer is around 108/cm3, far below the intrinsic value.

As the accuracy of the control channel model directly affects the stability and the convergence of the active vibration controller for smart flexible structures, offline identification of the control channel model is inappropriate for a vibration system whose characteristic and parameter is time-varying. To solve the problem of the control channel model identification, an active vibration control algorithm based on online control channel identification is proposed in this paper. Adopting a noise signal as the input identification signal, the FIR filter structure as the system model structure, and FxLMS algorithm as the control algorithm, the detailed derivation of the algorithm is presented. To test and verify the feasibility and priority of the proposed algorithm, simulation analysis is done by Matlab, while the actual experiment is done on the experimental active vibration control platform. The experiment results show that the proposed algorithm is feasible with good control performance and rapid convergence.

Taking the piezoelectric flexible plate as research object, this paper presents an efficient method to simulate and analyze intelligent structures with MATLAB and ANSYS applied. Firstly, this paper focuses on the development of modeling method for intelligent structures with distributed sensors and actuators. Modal analysis and transient analysis were done by using ANSYS 11.0 software, with the finite model of the intelligent plate constructed. Then based on an APDL (the design language of ANSYS) program, the vibration control experiments were done. By analyzing different control performance of different actuator assign position, the optimization criterion suggested by NASA for piezoelectric sensors and actuators arrangement was verified. While the optimal configuration was chosen, the control channel and primary path model of the vibration control system were obtained with MATLAB system identification toolbox employed. Finally according to the identified model an iterative learning control system was developed. The analysis and experimental results show that the analysis method for intelligent structures proposed in this paper is economical and effective and the designed controller has a good vibration suppression performance.

Taking the piezoelectric flexible beam as the research object, this paper proposed a FXLMS algorithm based MIMO adaptive vibration control method to attenuate the oscillations of flexible structures at low frequency. By introducing the piezoelectric constitutive equations and analyzing the multi-channel adaptive filtered feedforward control algorithm and its FXLMS algorithm process, the model parameter identification strategy for the controlled structure as well as the controller design structure diagram are given in this paper. Structure modal characteristic analysis was done to determine the optimal configuration of piezoelectric sensors and actuators. Active vibration control experimental platform was established to verify the effectiveness of the FXLMS control scheme. The vibration control experiment was done after the control channel model was obtained. The experimental results show that the MIMO adaptive vibration controller proposed in this paper has a good control performance, with low order model and rapid convergence.

Taking the piezoelectric beam as research object, filtered-U least mean square (FULMS) control algorithm for feed-forward adaptive control is analyzed and compared with filtered-x least mean square (FXLMS) feed-forward control algorithm, which can solve the problem that the vibration feedback may affect the measuring of the reference signal in FXLMS. By introducing FXLMS and FULMS control algorithm, this paper gives the controller design structure, while structure modal analysis to determine the optimal placement of piezoelectric sensors and actuators and model parameter identification for the controlled structure are done. Then the active vibration control experimental platform is established to verify the effectiveness of FULMS control scheme as well as FXLMS control scheme. Meanwhile the experimental results of FXLMS and FULMS are compared. The performance comparison shows that the FULMS adaptive vibration controller has a better control performance, with more rapid convergence than FXLMS controller.

To improve the full well capacity (FWC) of a small size backside illuminated (BSI) CMOS image sensor (CIS), the effect of photodiode capacitance (CPD) on FWC is studied, and a reformed pinned photodiode (PPD) structure is proposed. Two procedures are implemented for the optimization. The first is to form a varying doping concentration and depth stretched new N region, which is implemented by an additional higher-energy and lower-dose N type implant beneath the original N region. The FWC of this structure is increased by extending the side wall junctions in the substrate. Secondly, in order to help the enlarged well capacity achieve full depletion, two step P-type implants with different implant energies are introduced to form a P-type insertion region in the interior of the stretched N region. This vertical inserted P region guarantees that the proposed new PD structure achieves full depletion in the reset period. The simulation results show that the FWC can be improved from 1289e− to 6390e−, and this improvement does not sacrifice any image lag performance. Additionally, quantum efficiency (QE) is enhanced in the full wavelength range, especially 6.3% at 520 nm wavelength. This technique can not only be used in such BSI structures, but also adopted in an FSI pixel with any photodiode-type readout scheme.

The charge transfer efficiency improvement method is introduced by optimizing the electrical potential distribution under the transfer gate along the charge transfer path. A non-uniform doped transfer transistor channel is introduced to provide an ascending electrical potential gradient in the transfer transistor channel. With the adjustments to the overlap length between the R1 region and the transfer gate, the doping dose of the R1 region, and the overlap length between the anti-punch-through (APT) implantations and transfer gate, the potential barrier and potential pocket in the connecting region of transfer transistor channel and the pinned photodiode (PPD) are reduced to improve the electrical potential connection. The simulation results show that the percentage of residual charges to total charges drops from 1/104 to 1/107, and the transfer time is reduced from 500 to 110 ns. This means the charge transfer efficiency is improved.

This paper has made a study of the scheduling and the allocation of the byproduct gases in a large scale steel works. In order to realize the optimal utilization and allocation of these gases with a micro-computer, the paper introduces the model of multi-objective optimization and proposed a new decomposition-coordination method, called Constraint coordination method, which is simpler and more effective than Dantzig Wolfe decomposition method. In the last part of tho paper, the method has been successfully used in the computation of optimal allocation of the gas resources in the steel works.