人工神经网络在舰船火灾探测中的应用

舰船火灾探测系统的目的是能及时、准确地探测到舰船上发生的火灾。提出一种利用人工神经网络的舰船火灾探测方法，通过设计三层反向传播（BP）人工神经网络模型，使用改进的BP算法——LM算法，对多传感器（温度传感器、烟雾传感器和CO传感器）同时探测到的数据进行智能化处理。仿真结果表明：基于人工神经网络的舰船火灾探测系统能及时、准确地识别各种火灾信号。     

提速客车盘形制动轮对轮座镶入部超声波探伤工艺探讨

介绍了提速客车盘形制动轮对轮座镶入部超声波探伤工艺,分析了探伤过程中存在的实际问题,并提出了相应的改进措施与建议。     

铁路车辆轮对自动检测系统的研制

介绍一种可自动测量铁路货车轮对参数并实现计算机自动化管理的系统，对其结构和一些关键技术作了较详细的分析。分析表明，该系统采用工业控制计算机、精密传感器、摄像机以及各种先进的测试和控制技术，对包括轮对外形尺寸、轮对踏面擦伤、剥离以及车轴、轮对和标志板的标记等20多个参数实现动态在线测量，大大提高了工作效率和检测精度，解决了目前轮对测量手段落后、测量误差大、劳动强度高等问题。     

荧光磁粉探伤法在船舶检验中的应用

阐述了荧光磁粉探伤法在船舶检验中的应用经验，介绍了该探伤法的特点、常用设备和材料、以及操作中应注意的事项。对荧光磁粉探伤法及普通磁粉探伤法进行了对比试验，介绍了其试验结果，证明前述探伤法的灵敏度优于后者。并列举了一些应用实例，以证明在船舶检验中应用荧光磁粉法探伤的有效性。     

Multimode trip information detection using personal trajectory data

Handheld global positioning system (GPS) devices can serve as a new tool to collect an individual's trip information with advantages of low cost, accurate data, and intensive spatial coverage. Various machine learning algorithms have been explored to detected trip train information in previous studies; however, few of them focused on the evaluation and comparison of the performance and applicability of different models. Meanwhile, according to previous studies, car and bus mode detection is a thorny issue due to their similar travel characteristics, and algorithms still need to be well explored and improved to solve this problem. In this article, an innovative method is proposed to detect trip information, including trip modes, mode-changing time and location, and other attributes, from personal trajectory data. The method is a two-step process. A machine learning algorith-based module (including artificial neural network, support vector machine, random forests, and Bayesian network) is firstly used to identify walk, bicycle, and motorized trip modes (bus or car); we thoroughly compared the performance of these four algorithms. Then a second module, using critical points on the GPS trajectories, is further developed to distinguish car and bus mode, incorporated with GIS map information. Field test results show that the proposed machine learning models can all be applied for walk, bicycle, and motorized mode detection with high detection rates exceeding 90%; however, the algorithms work relatively poorly for bus and car mode detection, with results mostly below 75%. The proposed two-step method can greatly improve bus and car mode detection accuracy by 14–30%. As a result, the average mode detection rates for all the four modes are above 90%. Compared with mode detection results by using only the machine learning algorithm, the proposed two-step method has much better performance in both accuracy and consistency.     

基于道路标线的交通事故现场摄影测量研究

论述了基于普通相机的交通事故现场测量技术基本理论,提出了一种利用道路标线作为标定参考物的新的标定方法,在小波多尺度边缘检测基础上,利用Harris角点提取对图像进行分析处理,对影响摄影测量精度的有关参数进行了简要描述,对一个实际事故现场的部分数据进行了分析,验证了设计的算法。     

既有多梁式桥梁的损伤识别

讨论了利用量测的柔度矩阵定位损伤的方法。分别选用模态柔度和模态柔度曲率两种方法对多梁式T型梁桥的损伤识别进行研究;并定性分析了测试噪声对损伤识别结果的影响。为反映实际多梁式桥梁的损伤识别情况,采用符合实际多梁式桥梁结构构形的计算模型模拟结构损伤。通过一个简支多梁式T梁桥的数值试验验证了所提方法的可行性。结果表明在量测模态与频率数不多的情况下,所讨论的方法可用于识别多梁式桥梁的损伤。     

锚拉板区域焊缝消除应力后性能试验分析

基于重庆江津观音岩长江大桥的斜拉索和主梁的锚固采用拉板式的锚固方式,大部分板件为厚钢板,锚拉板各板件之间各焊缝进行了焊接应力消除工艺,对消除应力后的焊缝进行了各项试验检测。应用数理统计分析理论及SPSS分析软件,判断焊缝的试验检测结果是否符合正态分布规律;采用概率的置信区判断焊缝是否达到相关的力学性能要求,确保斜拉桥主梁与锚拉板焊缝连接的安全和传力的可靠。     

水下爆炸声源对抗低频声呐干扰效果研究

在分析水下爆炸声源声学特性的基础上,研究了水下爆炸噪声对低频被动声呐的对抗机理,以圆柱形基阵为例,对不同水声干扰弹装药量、干扰弹到潜艇距离以及海况等级条件下对声呐主瓣、旁瓣的压制干扰效果进行仿真分析。结果表明,与传统噪声干扰器相比,水下爆炸声源对声呐的干扰效果更为明显,能显著降低声呐的探测距离,可为己方舰艇的机动规避和后续对抗创造有利条件。     

坝陵河大桥基础工程施工岩溶地质探测及预报

坝陵河大桥基础工程岩溶非常发育.针对东索塔、东锚碇基底及西锚洞工程岩溶发育情况,分别采用高密度电法、地质雷达和HSP声波反射法进行岩溶探测.实践表明,以上几种方法的综合应用效果较好,对工程施工起到了指导作用.