螺杆钻具性能试验自动测试系统研究

发布时间：2018-01-17 03:08

本文关键词：螺杆钻具性能试验自动测试系统研究　出处：《西安电子科技大学》2015年硕士论文　论文类型：学位论文

【摘要】：随着螺杆钻井技术的不断更新与发展,新型螺杆钻具性能测试试验台的研究也应与之相匹配。目前,螺杆钻具试验台存在人力投入多、试验操作过程复杂、试验时间长、自动化智能化程度不高等问题。为解决这些弊端,设计了基于虚拟仪器的螺杆钻具性能试验自动测试系统。其能够在保证螺杆钻具性能测试试验台基本功能的前提下,不断提高螺杆钻具试验台的性能,减少人力物力的投入,缩短试验时间,提高试验台的使用效率和可靠性。该系统在综合考虑螺杆钻具机械特征和工作性能,以及电气控制技术、数据采集处理技术以及通信技术的基础上,将工控机、数据采集器、智能传感器以及虚拟仪器软件相结合,并应用数据库技术和智能控制技术,实现了螺杆钻具性能参数的自动测试。综合分析本文设计的螺杆钻具性能试验自动测试系统,可知其有如下特点:(1)在硬件方面,设计了以工控机为核心的分布式数据采集与管理系统。该系统由工控机、数据采集器、智能传感器以及电动调节阀等组成,实现了螺杆钻具性能试验中的自动数据采集与存储功能,有效减少了试验过程中人力物力的投入,缩短了试验时间,提高了试验台的使用效率、可靠性和自动化程度。(2)在软件方面,开发了基于Lab Windows/CVI的螺杆钻具性能试验数据管理与分析软件。该软件系统有效解决了数据采集、数据实时存储的问题,并可自动分析了启动压力等性能参数,提高了螺杆钻具试验的效率。软件采用多线程技术来实现实时数据采集与存储,采用Activex技术实现报表的输出,使得系统操作更为简单、方便。(3)针对流量自动控调节存在时滞、不稳定的问题,提出了基于参数自适应模糊PID控制的流量自动控调节算法。仿真与试验结果表明,基于参数自适应模糊PID控制算法的流量控制方法,缩小了超调量,减少了调节时间,节约了成本。实验结果表明,该系统在保证螺杆钻具性能测试试验台基本功能的前提下,减少了人力物力的投入,缩短了试验时间,提高了试验台的使用效率和可靠性,达到了系统设计的要求。
[Abstract]:With the continuous renewal and development of screw drilling technology, the research of new screw drilling tool performance test bench should be matched with it. At present, the screw drilling tool test rig has more manpower input and complex operation process. The test time is long, the automation intelligence degree is not high and so on. In order to solve these disadvantages. An automatic testing system of screw drill tool performance based on virtual instrument is designed, which can continuously improve the performance of screw drill tool test rig on the premise of guaranteeing the basic function of screw drill tool performance test rig. It reduces the input of manpower and material resources, shortens the test time, and improves the efficiency and reliability of the test bed. The system takes into account the mechanical characteristics and working performance of the screw drill tool, as well as the electrical control technology. On the basis of data acquisition and processing technology and communication technology, this paper combines industrial computer, data collector, intelligent sensor and virtual instrument software, and applies database technology and intelligent control technology. The automatic testing system of screw drill tool performance parameters is realized. The system designed in this paper has the following characteristics: 1) in the hardware aspect. A distributed data acquisition and management system based on industrial control computer is designed, which is composed of industrial control computer, data collector, intelligent sensor and electric control valve. The function of automatic data acquisition and storage is realized in the performance test of screw drill, which effectively reduces the input of manpower and material resources, shortens the test time and improves the efficiency of the test rig. Reliability and automation. 2) in software. The data management and analysis software of screw drill tool performance test based on Lab Windows/CVI is developed, which effectively solves the problems of data acquisition and real-time data storage. The performance parameters such as starting pressure can be analyzed automatically, and the efficiency of screw drill tool test is improved. The software adopts multi-thread technology to realize real-time data acquisition and storage. The Activex technology is used to realize the output of the report form, which makes the operation of the system more simple and convenient. (3) aiming at the problem of time delay and instability in the automatic flow control and adjustment. An automatic flow control algorithm based on parameter adaptive fuzzy PID control is proposed. The simulation and experimental results show that the flow control method based on parameter adaptive fuzzy PID control algorithm reduces the overshoot. The experimental results show that the system can reduce the input of manpower and material resources and shorten the test time on the premise of guaranteeing the basic function of the test rig. It improves the efficiency and reliability of the test bed and meets the requirements of the system design.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TE921

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