基于距离测度法的中枢神经系统损伤检测

基于AR模型的EEG信号距离测度方法可以较好地表征中枢神经系统损伤的情况。主要探讨在这种方法中利用不同的定阶准则建立相应的AR模型及其对距离测度结果的影响。同时，使用自适应滤波器对原始信号进行滤波，将分离后的平稳和非平衡成分再进行距离测度法的研究。对滤波器的参数分析表明，这种方法可以很好地消除EEG信号中可能混有的不同程度的噪声，得到的距离测度结果也能更好地表示损伤的变化情况。     

动态台车吸能装置的试验调试与研究

汽车的被动安全越来越受到人们的关注。安全带动态试验中,机械缓冲吸能装置的钢条排布方式决定了减速度曲线的最终波形,直接关系到试验结果是否满足标准要求。本文针对机械式缓冲吸能装置,采用试验验证的方法,研究钢条的排布方式,并对台车的减速度曲线进行调试与修正,获得了满足法规要求的曲线。大量实际试验表明:通过试验方法获取钢条的排布方式,吸能装置的减速度曲线稳定,可以满足检测和试验需求。     

The lateral stability of train suspension systems employing inerters

This paper investigates the benefits of lateral stability of train suspension systems employing a newly developed mechanical network element known as an inerter. An inerter was proposed as an ideal mechanical two-port element to substitute for the mass element in the mechanical/electrical analogy. As of now, inerters have been successfully applied to car and motorcycle suspension systems, for which significant performance benefits were reported. This paper discusses the improvements on lateral stability of train suspension systems employing inerters. The study was carried out in three parts. First, an existing 12 degrees-of-freedom (DOF) train model was built and verified by a multi-body-builder, AutoSim^TM. Second, inerters were applied to the train suspension system to increase the critical speed. Finally, the discussion was extended to a 16-DOF model to demonstrate the performance improvement by inerters. From the results, inerters were deemed effective in improving the lateral stability of train suspension systems.     

密闭舱室挥发性有机化合物被动式采集与非靶向测试

本文建立了密闭舱室挥发性有机化合物(VOCs)被动式采集与非靶向测试方法。采用极性和非极性填料进行被动式采样,分析结果可互相对比且互为补充,采样方式简单、便携、稳定。运用目前先进的气相色谱-高分辨质谱(GC-HRMS)分析方法可高灵敏度、高分辨率鉴别采样中的VOCs组分,8个舱室采样位点共筛查出70种低浓度VOCs污染物。在得到的各类VOCs含量数据中,以多环芳烃(PAHs)这一类致癌性和致突变性污染物为例,根据含量热图分析获取多环芳烃在舱室中的分布规律,并推测其主要来源于机舱和设备舱中油料挥发以及厨房烹饪油烟。该方法的建立将更加高效、准确筛查舱室VOCs组分并进行污染源解析,有助于舱室大气环境质量提升和舰艇战斗力生成。     

Literature review and fundamental approaches for vehicle and tire state estimation*

ABSTRACT

Most modern day automotive chassis control systems employ a feedback control structure. Therefore, real-time estimates of the vehicle dynamic states and tire-road contact parameters are invaluable for enhancing the performance of vehicle control systems, such as anti-lock brake system (ABS) and electronic stability program (ESP). Today's production vehicles are equipped with onboard sensors (e.g. a 3-axis accelerometer, 3-axis gyroscope, steering wheel angle sensor, and wheel speed sensors), which when used in conjunction with certain model-based or kinematics-based observers can be used to identify relevant tire and vehicle states for optimal control of comfort, stability and handling. Vehicle state estimation is becoming ever more relevant with the increased sophistication of chassis control systems. This paper presents a comprehensive overview of the state-of-the-art in the field of vehicle and tire state estimation. It is expected to serve as a resource for researchers interested in developing vehicle state estimation algorithms for usage in advanced vehicle control and safety systems.     

单ESM传感器对运动目标的快速定位方法

研究了机载单ESM传感器对运动目标的定位问题．建立了单ESM传感器平台作航向机动时对运动目标定位的数学模型以及相应的求解方法，克服了单ESM传感器平台做直线运动时对运动目标观测存在不可观测的局限性，对于ESM平台作航向机动和匀速直线运动情况具有普遍适用性．理论分析和仿真结果表明：文中提出的算法，能够迅速有效地对运动目标进行定位，并具有较高的定位和跟踪精度，航向机动量越大，对目标的定位精度越高．     

Study on real-time estimation of the ship motion cross spectra

 Time-varying coefficient vector autoregressive (T-VVAR) modeling with instantaneous responses is applied to spectrum analysis based on the nonstationary motion data of ships. Because of the ship's maneuvers, changes such as course and speed, the ship motions in waves are regarded as a nonstationary random process, although the seaway can be considered as a stationary stochastic process. The T-VVAR model is transformed into a state space model, and the time-varying coefficients can be evaluated by using the Kalman filter algorithm. Using the estimated time-varying coefficients, the instantaneous cross spectra of the ship motions can be calculated at every moment. In order to examine the reliability of the proposed procedure, on-board tests were carried out. Under stationary conditions, at a constant speed and course, the proposed method shows good agreement with stationary vector autoregressive (SVAR) modeling analysis. Moreover, it is confirmed that the proposed method can estimate the instantaneous cross spectra of the ship motions even under nonstationary conditions, showing that this is a powerful tool for on-line analysis of the nonstationary motion data of ships. Received: August 2, 2002 / Accepted: November 28, 2002 Acknowledgments. The authors thank the captain and crew of the training ship Shioji Maru, Tokyo University of Mercantile Marine. Address correspondence to: T. Iseki (iseki@ipc.tosho-u.ac.jp) Updated from the Japanese original, which won the 2002 SNAJ prize (J Soc Nav Archit Jpn 2001;190:161–168)     

基于AT89C52的PDT模拟器及实现

分析利用实际装备进行电子对抗训练的不足，介绍了用模拟器进行电子对抗仿真训练的实现方法，给出一个以AT89C52作为单片机系统的核心的PDT模拟器予系统设计，分析其中的软硬件关键技术．     

Development and validation of a Kalman filter-based model for vehicle slip angle estimation

It is well known that vehicle slip angle is one of the most difficult parameters to measure on a vehicle during testing or racing activities. Moreover, the appropriate sensor is very expensive and it is often difficult to fit to a car, especially on race cars. We propose here a strategy to eliminate the need for this sensor by using a mathematical tool which gives a good estimation of the vehicle slip angle. A single-track car model, coupled with an extended Kalman filter, was used in order to achieve the result. Moreover, a tuning procedure is proposed that takes into consideration both nonlinear and saturation characteristics typical of vehicle lateral dynamics. The effectiveness of the proposed algorithm has been proven by both simulation results and real-world data.     

Identifying tyre models directly from vehicle test data using an extended Kalman filter

Individual tyre models are traditionally derived from component tests, with their parameters matched to force and slip measurements. They are imported into vehicle models which should, but do not always properly provide suspension geometry interaction. Recent advances in Global Positioning System (GPS)/inertia vehicle instrumentation now make full state measurement viable in test vehicles, so tyre slip behaviour is directly measurable. This paper uses an extended Kalman filter for system identification, to derive individual load-dependent tyre models directly from these test vehicle state measurements. The resulting model therefore implicitly compensates for suspension geometry and compliance. The paper looks at two variants of the tyre model, and also considers real-time adaptation of the model to road surface friction variations. Test vehicle results are used exclusively, and the results show successful tyre model identification, improved vehicle model state prediction – particularly in lateral velocity reproduction – and an effective real-time solution for road friction estimation.