煤层气车载钻机电控系统设计

针对传统机械仪表及液控方式不能满足煤层气车载钻机安全、精准、高效的施工需求问题,设计了一种煤层气车载钻机电控系统。该系统由传感器、副控台、控制箱、主控台组成:副控台采集柴油机参数并实现柴油机启停、油门调节和油门切换等控制功能;控制箱通过驱动液压系统电磁阀进行逻辑控制;主控台用于司钻人员观察钻进参数和操作钻进作业。现场应用结果表明,该系统可实时、准确地监测并显示柴油机和钻机钻进参数,实现柴油机运行及钻机钻进逻辑控制,为辅助钻进施工及提升钻进质量提供了保障。     

井涌井漏监测系统设计

在石油勘探开发中,尤其随着欠平衡钻井的推广应用,通过钻井液池相应参数的监测,可指导钻井作业快速、安全、有效地进行。系统采用友好的人机界面,通过对钻井液池出入口密度、温度、电导率、硫化氢气体含量及钻井液总体积的实时测量。可有效地监测各参数的变化,判断可能出现的井漏,井喷等异常工况,并具有报警及历史数据查询等功能。系统宜于井队配备,可与综合录井仪系统无缝连接,实现数据共享;更适于无综合录井仪系统情况下,井队独自完成对井涌井漏的监测。     

实施HSE管理模式建立企业安全生产长效机制

中国石油化工集团公司中原石油勘探局钻井管具工程处始建于1995年,是为国内外石油开发商提供钻井、修井专用管材、工具、井控装备的检测、维修、租赁及现场技术服务;钻头、钻杆、套管及井下工具的加工和销售;欠平衡钻井、下套管油井试压、打捞等石油工程技术服务的专业化石油企业.自2003年3月份以来,为建立安全生产长效机制,引进了HSE管理体系.现就我处建立实施HSE管理体系过程中所取得的一些经验介绍如下:……     

无机械辅助结构自行车机器人控制仿真及实现

为实现自行车机器人的平稳直线行驶,论证了无机械辅助结构、仅靠调整车把维持自平衡的后驱自行车机器人动力学建模、姿态控制、系统仿真及实物样机实验.针对具有典型对称性欠驱动非完整约束的自行车机器人系统难于实现平衡控制问题,首先基于拉格朗日方法分析系统力学机理,建立简化动力学模型.然后基于部分反馈线性化原理,对车体横滚角与转把力矩的欠驱动子系统进行线性化处理及模糊自适应控制.仿真及实验结果表明,有效地实现了自行车机器人直线运动自平衡控制,为进一步开展自行车机器人以及其他欠驱动系统平衡运动控制奠定理论基础.     

近水平孔水力纠偏自动定向方案及其硬件实现

根据煤层气近水平孔钻进的实际需求,结合水力纠偏技术,提出了一种水力纠偏射流自动定向方案,并在此基础上设计了一种纠偏系统。该纠偏系统以单片机为控制核心,采用压力传感器监测钻井液压力的变化以启动或停止整个水力纠偏钻进过程,以倾角传感器和电子罗盘分别采集水平钻孔的倾角和方位角,单片机根据方位角和倾角的值及其互相关系确定射流方向后控制步进电动机调整射流方向。室内调试证明了该射流自动定向方案的可行性。     

油田钻井虚拟仿真系统

利用计算机仿真技术,研究构建一个参数化的油田钻井虚拟仿真系统,对虚拟设备进行参数化的运动控制,逼真地模拟钻井工艺过程。提出了基于数字计算仿真和视景仿真混合技术的虚拟仿真系统架构,分析并建立了井架提升系统和旋转钻进系统的数学模型,利用数学模型控制虚拟钻井设备运动,实现了对缠绕在滑轮组上钢丝绳的实时变形运动控制。最后,能够初始化系统参数、实时显示并控制钻井工艺过程中参数的变化,实现系统的交互性。     

石油钻机新技术探讨

分析了石油勘探开发和工程技术的新发展,特别是针对三大钻机技术(水平井钻井技术、欠平衡钻井技术、深井钻井技术),应运而生的新型石油钻井装备。还阐述了与之相关的新型石油钻井装备,如液压钻机、四象限运行的交流变频电驱钻机、模块钻机、快移快装钻机、钻机智能化、钻机顶驱装置等。     

基于OpenGL的可视化技术在钻井中的应用

在介绍了基于OpenGL的三维可视化技术基本原理和流程的基础上,着重研究了其在钻井工程中的应用.并以中国大陆科学钻探为例,在三维可视化环境中形象直观地展示钻井数据之间的相互关系,在钻前设计、钻进监测及钻后分析中,有效提高地质学家分析复杂数据和提取有效信息的能力,从而提高了钻井效率.     

基于OpenGL的可视化技术在钻井中的应用

在介绍了基于OpenGL的三维可视化技术基本原理和流程的基础上,着重研究了其在钻井工程中的应用。并以中国大陆科学钻探为例、在三维可视化环境中形象直观地展示钻井数据之间的相互关系．在钻前设计、钻进监测及钻后分析中,有效提高地质学家分析复杂数据和提取有效信息的能力,从而提高了钻井效率。     

AGP风力发电测量保护模块通过型式试验

2012年7月18日,上海安科瑞电气股份有限公司自主研发的AGP风力发电测量保护模块,在国家继电保护及自动化设备质量监督检验中心测试,其电气安全、电磁兼容、通信规约、动模及系统等项目检测通过,并获得合格检验报告,报告编号:NoJW120666。AGP300测量保护模块具有电网解列的监测功能,丰富的保护功能,最多可达4路保护继电器输出。过频/欠频、过压/欠压、电压/电流不平衡、过载/欠载     

集成状态监测和故障诊断的设备管理平台的建立

针对目前设备状态维修中故障诊断和维修管理相互脱节的问题，在状态维修思想的指导下，构建了实施状态维修的设备管理平台，给出了系统平台的集成架构。结合发电企业设备维修的实际，提出了状态维修实施的信息模型。运用IDEF方法对整个设备管理平台的总体功能进行了详细分析，建立了系统的功能模型。在构建系统模型的基础上，综合采用网络技术、计算机技术和数据库技术等开发出了集成状态监测和故障诊断的设备管理系统，为企业成功开展状态维修提供了有效的管理平台。     

Application of the condition based maintenance checking system for aircrafts

Condition Based Maintenance (CBM) systems have evolved as an effective health and usage monitoring mechanism in aircrafts by reducing the costs associated with unscheduled maintenance. CBM systems help maintainers to detect and manage the condition of aviation system components and take maintenance actions when there is evidence of need. In this paper we describe the application of a software prototype, which is an automation of the CBM practices. We briefly explain the novel framework on which it is built. We illustrate the building of the configuration information, required to generate the maintenance reports that are deemed essential for continuous improvement under CBM, using a markup language called XML. We explain the procedure in generating the reports using the developed prototype. We demonstrate that the developed prototype has the functional capabilities essential to implement CBM on any aircraft and is valuable in cutting down the software maintenance costs as it can perform new operations without having to modify the existing source codes.     

A decision support system for real-time monitoring and control of dynamical processes

This article presents the concept and development of a prototype diagnostic decision support system for real-time control and monitoring of dynamical processes. This decision support system, known as Diagnostic Evaluation and Corrective Action (DECA), employs qualitative reasoning, in conjunction with quantitative models, for monitoring and diagnosis of malfunctions in dynamical processes under routine operations and emergency situations. DECA is especially suited for application to time-constrained environments where an immediate action is needed to avoid catastrophic failure(s). DECA is written in common Lisp and has been implemented on a Symbolics 3670 machine; its efficacy has been verified using the data from the Three Mile Island No. 2 Nuclear Reactor Accident.     

未来智能钻井系统

展望了未来智能钻井技术的系统组成、功能及其运行方式.智能钻井新技术是钻井技术、新材料技术、检测控制、微电子技术、通信和计算机、机器人和超微加工技术等的集成.未来的智能钻井将采用轻便车载连续油管全自动钻机,钻井作业中,安置在钻头上的智能机器人将观测和检测到的所有井下参数上传到地面,在钻井的同时完成测井工作;地面人员通过控制钻头运动轨迹和转速,实现遥控智能钻井;起下钻等钻井作业均由地面机器人按指令自动完成;通过通信网络技术,实现全球钻井协同工作.因此,智能钻井将大幅度降低钻井成本,大大提高钻井速度,减少钻井事故的产生,实现井眼轨迹的精确控制,进一步提高石油天然气勘探开发技术水平.     

集成状态监测和故障诊断的设备管理系统

提出了离线和在线监测诊断相结合的状态维修策略,在状态维修思想的指导下,建立了系统的工作模型和功能模型。综合采用网络技术、计算机技术和数据库技术等开发出了集成状态监测和故障诊断的设备管理系统,为企业开展状态维修提供了有效的管理工具。     

钻井燃油罐液位自动监测系统

首先对钻井燃油罐液位自动监测系统进行了总体结构设计,然后以STC单片机为主控制器,通过GPS卫星定位器进行井场位置定位,利用温度监测模块对各个箱体的温度进行实时测量,另外通过液位监测模块实时监控油罐液位的高度值,出现异常情况时,及时报警.所有数据信息通过GPRS通讯模块实时传至控制中心,由此实现油罐液位监测功能.     

复杂系统维护策略最新研究进展: 从视情维护到预测性维护

对于复杂、可修复的工程系统, 设备维护是确保系统安全性、可靠性、可用性的重要手段之一. 系统维护策略已经历修复性维护、定时维护、视情维护等多种维护策略. 其中, 视情维护是目前最受关注的维护策略, 它通过收集和评估系统的实时状态信息进行维护决策, 具有全寿命周期内系统可靠性高、运营维护成本低等优点. 近年来, 随着物联网技术、信息技术和人工智能的快速发展, 一种更新颖的视情维护策略——预测性维护逐渐成为领域研究热点. 本文首先简要回顾了系统维护策略的发展历程; 然后, 重点介绍了视情维护的研究进展, 根据决策支持技术的不同, 将视情维护划分为基于随机退化模型的视情维护和基于数据驱动的预测性维护, 对每类技术的发展分支与研究现状进行了疏理、分析和总结; 最后, 探讨了当前复杂系统维护策略面临的挑战性问题和可能的未来研究方向.     

基于KingSCADA加气混凝土生产监控系统的设计与实现

针对加气混凝土生产与管理自动化的需要,开发设计了一种基于KingSCADA的混凝土生产监控系统。该系统提高了加气混凝土生产的自动化程度及控制精度。介绍了基于KingSCADA的加气混凝土生产系统的总体结构和实现功能。     

Flexible job shop scheduling under condition-based maintenance: Improved version of imperialist competitive algorithm

Maintenance activities have been ignored in many studies on scheduling problems where all machines are assumed to be available without interruption in the planning horizon. However, in realistic situations, they might be unavailable due to preventive maintenance, basic maintenance or unforeseen breakdowns. In this paper, we simulate a condition-based maintenance (CBM) for flexible job shop scheduling problem (FJSP) and consider the combination of Sigmoid function and Gaussian distribution to improve the CBM simulation. This study proposes an improved imperialist competitive algorithm (ICA) for the FJSP scheduling problem with the objective of the makespan minimization. The performance of the proposed algorithm is enhanced with a hybridization of ICA with simulated annealing (SA), after diagnosing standard ICA disadvantages and shortcomings. This ICA also includes a simulation part to handle CBM requirements. Various parameters of the novel ICA are reviewed to calibrate the algorithm with the help of the Taguchi experimental design. Experimental results show the high performance of the novel ICA in comparison with the standard ICA. The obtained results demonstrate that the novel ICA is an effective algorithm for FJSP under CBM. Finally, the performance of ICA is evaluated compared to other popular algorithms.     

Condition based maintenance of the two-beam laser welding in high volume manufacturing of piezoelectric pressure sensor

Two-beam laser welding (TBLW) is an advanced process for precise, low distortion joining of cylindrical miniature parts. The process is composed of a laser source, optics and various actuators, which form a sophisticated system for control and maintenance in high volume manufacturing. A well-established method for identifying welding defects and ensuring welding quality is the monitoring of plasma light emission in TBLW. Although such monitoring systems can detect a change in process status, they are not able to diagnose the nature of the fault. The main challenge in this research was to extend the use of quality-based monitoring systems to measure additional deterioration-related parameters and to estimate system deterioration from them by using expert knowledge.This paper shows a novel condition-based maintenance (CBM) for the TBLW system, which performs condition identification using online monitoring of plasma light emission in combination with offline inspection of the seam macrographs. A combination of quality parameters derived from seam macrographs of defective parts is used to identify process deterioration, such as contamination of the optics, misalignment of the optomechanical system, or reduced laser power. The information obtained is used to make predefined process adjustments based on expert domain knowledge. The implementation of the developed CBM in high volume manufacturing of piezoelectric pressure sensors resulted in more predictable TBLW by reducing system failures as well as shorter diagnosis times.