电梯多参数安全检测装置的设计
发布时间：2019-07-03 09:24
【摘要】：伴随着高层建筑的兴建,电梯使用范围越来越广,而且电梯安全问题也日渐严重,加强电梯安全检测成为了当务之急。因此,设计一台便携、多参数的电梯安全检测装置具有重要的现实意义。本文在查阅了国内外电梯安全检测相关产品的基础上,结合项目需求,设计了一台电梯多参数安全检测装置,完成了原理样机的制作与测试。本文主要工作和特色如下:(1)所设计的电梯多参数安全检测装置由上下位机组成。下位机使用嵌入式系统设计,负责采集和处理电梯的三轴加速度、运行速度、位移、振动、轿门速度、噪声和电机功率等数据;上位机采用平板电脑,负责显示、存储测量结果以及与远程服务器通信。整套装置实现了多参数在线检测,且灵活便携,人机交互友好。(2)装置集成了平衡系数测量功能和故障诊断功能,一机多用。(3)对装置的原理样机进行了实验室测试与现场测试,结果表明各功能模块运行正常,达到了设计要求。(4)介绍了基于贝叶斯网络的故障诊断方法,重点研究了贝叶斯网络的推理和参数学习过程,并结合电梯加速度故障诊断实例进行说明,最后以仿真实验验证。
[Abstract]:With the construction of high-rise buildings, elevators are used more and more widely, and elevator safety problems are becoming more and more serious, so it is urgent to strengthen elevator safety detection. Therefore, it is of great practical significance to design a portable and multi-parameter elevator safety detection device. In this paper, on the basis of consulting the related products of elevator safety testing at home and abroad, combined with the requirements of the project, a multi-parameter safety detection device of elevator is designed, and the manufacture and test of the prototype are completed. The main work and characteristics of this paper are as follows: (1) the designed elevator multi-parameter safety detection device is composed of upper and lower computers. The lower computer is designed by embedded system, which is responsible for collecting and processing the data of elevator triaxial acceleration, running speed, displacement, vibration, sedan chair door speed, noise and motor power. The upper computer adopts tablet computer, which is responsible for displaying, storing the measurement results and communicating with the remote server. The whole device realizes multi-parameter on-line detection, flexible and portable, human-computer interaction friendly. (2) the device integrates balance coefficient measurement function and fault diagnosis function, one machine is multi-purpose. (3) the prototype of the device is tested in laboratory and tested on the spot. The results show that each functional module runs normally and meets the design requirements. (4) the fault diagnosis method based on Bayesian network is introduced. The reasoning and parameter learning process of Bayesian network are studied in detail, and the example of elevator acceleration fault diagnosis is given to illustrate it. Finally, the simulation experiment is used to verify it.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU857
[Abstract]:With the construction of high-rise buildings, elevators are used more and more widely, and elevator safety problems are becoming more and more serious, so it is urgent to strengthen elevator safety detection. Therefore, it is of great practical significance to design a portable and multi-parameter elevator safety detection device. In this paper, on the basis of consulting the related products of elevator safety testing at home and abroad, combined with the requirements of the project, a multi-parameter safety detection device of elevator is designed, and the manufacture and test of the prototype are completed. The main work and characteristics of this paper are as follows: (1) the designed elevator multi-parameter safety detection device is composed of upper and lower computers. The lower computer is designed by embedded system, which is responsible for collecting and processing the data of elevator triaxial acceleration, running speed, displacement, vibration, sedan chair door speed, noise and motor power. The upper computer adopts tablet computer, which is responsible for displaying, storing the measurement results and communicating with the remote server. The whole device realizes multi-parameter on-line detection, flexible and portable, human-computer interaction friendly. (2) the device integrates balance coefficient measurement function and fault diagnosis function, one machine is multi-purpose. (3) the prototype of the device is tested in laboratory and tested on the spot. The results show that each functional module runs normally and meets the design requirements. (4) the fault diagnosis method based on Bayesian network is introduced. The reasoning and parameter learning process of Bayesian network are studied in detail, and the example of elevator acceleration fault diagnosis is given to illustrate it. Finally, the simulation experiment is used to verify it.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU857
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