一种机械故障监测的信息融合

在叶片振动故障监测过程中，单传感器的间断相位法只能测得叶片振幅值信息，本文应用两个传感器的信息融合技术，通过多源信息的综合、分析和推理，得出了叶片振动频率信息，提高了传感器系统的有效性，消除了单个传感器的局限性。     

Source code size estimation approaches for object-oriented systems from UML class diagrams: A comparative study

BackgroundSource code size in terms of SLOC (source lines of code) is the input of many parametric software effort estimation models. However, it is unavailable at the early phase of software development.ObjectiveWe investigate the accuracy of early SLOC estimation approaches for an object-oriented system using the information collected from its UML class diagram available at the early software development phase.MethodWe use different modeling techniques to build the prediction models for investigating the accuracy of six types of metrics to estimate SLOC. The used techniques include linear models, non-linear models, rule/tree-based models, and instance-based models. The investigated metrics are class diagram metrics, predictive object points, object-oriented project size metric, fast&&serious class points, objective class points, and object-oriented function points.ResultsBased on 100 open-source Java systems, we find that the prediction model built using object-oriented project size metric and ordinary least square regression with a logarithmic transformation achieves the highest accuracy (mean MMRE = 0.19 and mean Pred(25) = 0.74).ConclusionWe should use object-oriented project size metric and ordinary least square regression with a logarithmic transformation to build a simple, accurate, and comprehensible SLOC estimation model.     

Betting system for formative code review in educational competitions

Using competitions to motivate students is a well-known practice that has proved to be successful. Nevertheless, grading students only through their results in the competition could unfairly limit the range of grades that each student can get: regardless of the quality of the different teams participating, one student must necessarily win the tournament, another must be second, and so on until the last place. In fact, player rankings are relative assessments that are conditioned by the performance of every student. In this paper, we propose solving this issue by making students do a code review before betting on the competition. By betting, the grade of students depends both on the performance of their own solution and the one they bet on. This way, grades represent not only coding skills, but also code analysis skills, widening the attainable range of grades and allowing for a fairer grade distribution. As a result, students that are not so proficient in coding are rewarded if they demonstrate they can do a good analysis of the source code written by others, which is a very valuable skill in the professional world. We provide a case study in an undergraduate course, showing positive results.     

Efficient fault-tolerant collision-free data aggregation scheduling for wireless sensor networks

This paper investigates the design of fault-tolerant TDMA-based data aggregation scheduling (DAS) protocols for wireless sensor networks (WSNs). DAS is a fundamental pattern of communication in wireless sensor networks where sensor nodes aggregate and relay data to a sink node. However, any such DAS protocol needs to be cognisant of the fact that crash failures can occur. We make the following contributions: (i) we identify a necessary condition to solve the DAS problem, (ii) we introduce a strong and weak version of the DAS problem, (iii) we show several impossibility results due to the crash failures, (iv) we develop a modular local algorithm that solves stabilising weak DAS and (v) we show, through simulations and an actual deployment on a small testbed, how specific instantiations of parameters can lead to the algorithm achieving very efficient stabilisation.     

复杂断块油田特高含水期实现持续稳产的做法

胜利油田临盘采油厂目前开发动用临盘、商河、临南三个油田,区域构造位于渤海湾盆地济阳坳陷惠民凹陷中央隆起带。“九五”末期由于油田相继进入特高含水期,剩余油分布复杂、断块破碎、油水井套损严重、注采完善程度低,造成油田产量连续三年下降。针对严峻的开发形势,进入“十五”以后,通过深化油藏构造、储层、剩余油潜力的研究,强化注采井网的完善。提高了水驱控制程度,增强油田稳产基础,提高采收率。全厂连续三年原油年产量连续稳定在163×104t,取得较好的开发效果和经济效益。     

A virtual actuator and sensor approach for fault tolerant control of LPV systems

In this paper, a fault tolerant control (FTC) strategy using virtual actuators and sensors for linear parameter varying (LPV) systems is proposed. The main idea of this FTC method, initially developed for LTI systems, is to reconfigure the control loop such that the nominal controller could still be used without need of retuning it. The plant with the faulty actuator/sensor is modified adding the virtual actuator/sensor block that masks the actuator/sensor fault. The suggested technique is an active FTC strategy that reconfigures the virtual actuator/sensor on-line taking into account faults and operating point changes. The stability of the reconfigured control loop is guaranteed if the faulty plant is stabilizable/detectable. The LPV virtual actuator/sensor is designed using polytopic LPV techniques and linear matrix inequalities (LMIs). A two-tank system simulator is used to assess the performance of the proposed method. In particular, it is shown that the application of the proposed technique results in an improvement, in terms of performance, with respect to the LTI counterpart.     

Particle filtering for sensor fault diagnosis and identification in nonlinear plants

We propose a novel method for sensor monitoring and fault-tolerant estimation in systems described by general stochastic nonlinear and/or non-Gaussian state-space models. Faults are defined as abruptly occurring calibration errors, causing the sensor readings to be biased or scaled. Actuators and the process itself are assumed to be fault free. The main novelty of the work is an adaptive particle filter, whose configuration changes in order to diagnose sensor faults and to compensate for their effects. The presence, type and magnitude of sensor faults are determined through hypothesis testing and maximum likelihood estimation, based on the difference between the measurements and the particle filter estimates. The validity of the proposed approach was demonstrated through simulations on a drum-boiler model, although its effectiveness is not conditioned on any particular feature of the considered example.     

Fault identification for process monitoring using kernel principal component analysis

In this research, we develop a new fault identification method for kernel principal component analysis (kernel PCA). Although it has been proved that kernel PCA is superior to linear PCA for fault detection, the fault identification method theoretically derived from the kernel PCA has not been found anywhere. Using the gradient of kernel function, we define two new statistics which represent the contribution of each variable to the monitoring statistics, Hotelling's T²and squared prediction error (SPE) of kernel PCA, respectively. The proposed statistics which have similar concept to contributions in linear PCA are directly derived from the mathematical formulation of kernel PCA and thus they are straightforward to understand. The main contribution of this work is that we firstly suggest a fault identification method especially applicable to process monitoring using kernel PCA. To demonstrate the performance, the proposed method is applied to two simulated processes, one is a simple nonlinear process and the other is a non-isothermal CSTR process. The simulation results show that the proposed method effectively identifies the source of various types of faults.     

基于自相关算法的 TOA 估计方法研究

TOA（脉冲到达时间）估计是检测和截获非合作突发通信信号的关键,在通信对抗中至关重要。在介绍基于自相关（AC）算法 TOA 估计原理的基础上,讨论了在低信噪比情况下自相关算法的门限设置问题。采用双门限方法对门限设置进行了改进,并通过计算机进行了仿真分析和验证。