车用柴油机可变截面涡轮增压器控制系统研究

提出了一种以步进电机为执行器、预测函数与增压压力闭不反馈相结合的VGT控制系统，以期对喷嘴环截面积进行有效的控制，综合提高发动机的稳态和动态性能。在自行构建的软硬件系统上进行了试验，结果表明该方案简单易行，实用性很强。     

一种电控柴油机故障诊断系统的开发

针对一种民控管理系统开发了故障诊断模块，相应开发了一种基于计算机的电控柴油机故障诊断系统。该故障诊断模块和故障诊断系统配合使用，可以方便，全面地对柴油机电控系统进行诊断和自诊断，该系统有较好的扩展性，是柴油机电控系统测试，维修及开发的有效工具。     

Seabed scene simulation and its realization in extending Vega

Realistic simulation of underwater scene is always difficult because of the special and complex vision effects in underwater space. Seabed is an important part of underwater environment. This paper describes the methods for seabed scene simulation based on OpenGL. It includes construction of fluetuant terrain based on the random sinusoidal algorithm, simulation of seabed flicker effect by means of circular texture mapping and generation of turbidity effect by using fog techniques. For the application based on the leading high level 3D development environment-Vega, underwater scene simulation is still a difficulty since there is no module for it. Based on the analysis of Vega software and the research on seabed scene simulation methods, a Vega extending module named “Underwater Space” was created through developing module class and extending lynx interface. The module class was designed through developing DLL written in C . The Lynx was extended through developing keyword configure file, GUI configure file and lynx plug-in DLL. The problem that Vega can‘t simulate underwater space, is elementarily resolved. The results show that this module is efficient, easy using, and the seabed scene images am vivid.     

Identity-based threshold decryption on access structure

For the applied limitation of the existing threshold decryption schemes based on the (t, n) structure, an identity-based threshold decryption scheme which can be applied on the access structure is proposed through designing a special distribution algorithm of the private key shares. The generation and distribution of private key shares, the encryption, the decryption and the combination are introduced in detail. The validity and security of the scheme are proved and analyzed. Comparisons with the existing schemes show that the proposed scheme is more flexible.     

Tool sequence optimization based on three logical modes of robot control via CPLEX optimization

Cluster tools have advantages of shorter cycle times, faster process development, and better yield for less contamination. The sequence of dual-arm cluster tools is a complex logistics process during the semiconductor production. Efficient use of cluster tools is naturally very significant to competitive fab operations. Generating an optimized sequence in a computationally efficient manner and assessing the quality of the requirements to improve the fab production are the key factors for semiconductor manufacturing productivity. The Petri net modeling is introduced to minimize the makespan of the process for the three different logical modes and select a better mode after comparing the makespan among the three logical modes. The tool sequence optimization problem is formulated as optimization firing transition sequences based on the Petri net and then the formulation is converted to be linearly solved by the branch-and-cut method in the standard commercial solver CPLEX. Special methods for the linear conversion are highlighted. Due to the limited calculation time requirement for the real production and the large scale of the problem, special methods for the efficiency tuning are applied according to the characteristics of the problem. Numerical testing is supported by one of the most advanced semiconductor enterprises and the computational results show significant improvement compared with the traditional manual sequence results.     

Poisson noise removal based on nonlocal total variation with Euler’s elastica pre-processing

An enhancement-based Poisson denoising method for photon-limited images is presented. The noisy image is firstly pre-processed for enhancing incomplete object information, and then it is denoised while preserving the restored structural details. A variational regularization model based on Euler’s elastica (EE) is proposed for image enhancement pre-processing. A nonlocal total variation (NLTV) regularization model is then employed in the second stage of image denoising. The above two optimization problems are solved by the alternating direction method of multipliers (ADMM). For Poissonian images with low image peak values, experiments demonstrate the validity and efficiency of the proposed method for both restoring geometric structure and removing noise.     

Semiparametric specification of the utility function in a travel mode choice model

We propose a semiparametric approach that can capture the nonlinearity of deterministic components of the utility functions in discrete choice models and demonstrate it by analyzing travel mode choice behaviour for an interregional trip. The proposed smoothing spline-based specification method can be used to make ex ante evaluations regarding the parametric specifications of the deterministic utility functions in discrete choice models.     

Effective method for knock signal denoising in internal combustion engine

Uncontrolled expansion of combustion wave in spark ignited internal combustion engine causes knock effect which seriously degrades efficiency and lifetime of the engine. Thus, accurate knock detection and control are essential for obtaining a desired performance from the engine. Usually, knock sensor is used to detect this phenomenon but it has limited accuracy especially at engine high-speed rotations because of natural vibration and external noises. In this study an effective method based on Non-Local Mean (NLM) algorithm has been proposed to improve the knock detection accuracy. This method is evaluated based on four different indicators and four engine cylinders. The results show 52.9 % improvement in knock detection. Also feasibility of real time execution of this method based on embedded hardware has been studied.     

Origin–destination table disaggregation using biproportional least squares estimation

This paper describes a group of techniques for disaggregating origin–destination tables for travel forecasting that makes explicit use of observed traffic on a network. Five models within the group are presented, each of which uses nonlinear least-squares estimation to obtain row and column factors for splitting trip totals from and to larger geographical areas into smaller ones. The techniques are philosophically similar to Fratar factoring, although the solution method is quite different. The techniques are tested on a full-sized network for Northfield, MN and are found to work effectively.