节点文献
基于光纤传感器的深孔内表面粗糙度测量方法研究
Research on Detection Method of Inner Surface Roughness for Deep Hole Based on Fiber Optical Sensor
【作者】 徐伟;
【导师】 宋寿鹏;
【作者基本信息】 江苏大学 , 仪器仪表工程(专业学位), 2018, 硕士
【摘要】 表面粗糙度作为表征表面加工质量的主要参数,很大程度上影响着工件的性能。因此,表面粗糙度的测量与评定是生产过程控制和产品质量控制的重要依据。尽管目前测量工件表面粗糙度的方法很多,有的已经比较成熟,但是针对深孔内表面的全深度多母线粗糙度检测技术因其深径比大和内部空间小,发展还远远不够,依然存在测量效率低、操作难度大以及测量精度低等问题。针对上述问题,本文提出了一种基于光纤传感器阵列的深孔内表面粗糙度检测方法,实现了深孔内表面的全深度多母线粗糙度测量。首先推导了单光纤对结构的反射式强度调制型光纤传感器(Reflective Intensity Modulated Fiber Optical Sensor,RIM-FOS)的光强调制函数,然后通过计算机仿真了传感器特征参数对光强调制特性的影响,结合内表面粗糙度测量要求,确定了单路RIM-FOS的设计。并设计了基于RIM-FOS的光纤传感阵列,以及相应的光电检测电路,制定了传感器阵列的布设方案,在制作的孔状零件粗糙度试样上进行了传感器的标定试验,建立了标度转换关系曲线,并在搭建的试验平台上实现了粗糙度的全深度测量。论文的主要研究内容和结论如下:(1)理论分析了理想条件下单光纤对特征参数对光强调制特性的影响规律,结合内表面粗糙度测量要求,进行了单路RIM-FOS原理设计。(2)提出了光纤传感阵列方案,进行了阵列结构设计,并确定了光纤传感阵列的布设方案。(3)建立了单路RIM-FOS系统测量粗糙度值的数学模型。(4)设计了深孔内表面粗糙度测量系统硬件和软件。硬件部分包括:单光源驱动的光纤传感阵列,低噪声的光电检测电路等;软件部分包括:基于STM32开发板的多路信号采集、处理、存储、显示以及数据查询软件。(5)首先,搭建了特性测试平台,验证了各路RIM-FOS实际光强调制特性的一致性;然后,搭建了标定试验平台,进行了标定试验,拟合了不同孔径下具体的电压与粗糙度值换算公式;最后,搭建了深孔内表面粗糙度系统试验平台,试验得到了全深度、多母线测量性能,试验结果表明该系统粗糙度测量相对误差小于8%。
【Abstract】 Surface roughness,as the main parameter to characterize the surface quality,affects the performance of the workpiece to a large extent.Therefore,the measurement and evaluation of surface roughness is an important basis for production process control and product quality control.Although there are many methods to measure the surface roughness of the workpiece,some of them are already mature,but the development of the full depth and multi bus roughness detection technology for the deep hole surface is still far from enough because of its large depth-diameter ratio and small internal space.It still has the problems of low measurement efficiency,large operation difficulty and low measurement precision.In view of the above problems,a method based on optical fiber sensor array is proposed to detect the inner surface roughness of the deep hole,and the function of the full depth multi bus roughness measurement is implemented.First,the intensity modulation function of Reflective Intensity Modulated Fiber Optical Sensor,RIM-FOS is derived from single sensor structure.Then the influence of the characteristic parameters of the sensor is simulated by computer.Combined with the measurement requirements of inner surface roughness,the design of single sensor is determined.The optical fiber sensor array based on single RIM-FOS and the corresponding photoelectric detection circuit were designed.The layout scheme of the sensor array was set up.The calibration test of the sensor was carried out on the made parts roughness sample,and the scale conversion relation curve was established,and the roughness full depth measurement was realized on the test platform.The main contents and conclusions of this thesis are as follows:(1)The influence of the characteristic parameters on the intensity modulation characteristic under the ideal condition is analyzed theoretically,and the single RIMFOS principle is designed according to the requirement of the inner surface roughness measurement.(2)The optical fiber sensor array is proposed,and the array structure is designed.The layout scheme of optical fiber sensor array is determined.(3)A mathematical model for measuring roughness of single RIM-FOS system is established.(4)The hardware and software of deep hole inner surface roughness measurement system are designed.The hardware includes a fiber optic array driven by a single light source,a low noise photoelectric detection circuit,and so on.The software part includes the multi-channel signal acquisition,processing,storage,display and data query software based on the STM32 board.(5)First,a characteristic test platform was built to verify the consistency of the actual intensity modulation characteristics of all RIM-FOS.Then,the calibration test platform was built,and the calibration test was carried out.The calculation formula of the specific voltage values and roughness values under different aperture was fitted.Finally,the deep hole surface roughness system test platform was built.The test results show that the relative error of the roughness measurement is less than 8%.
【Key words】 deep hole; inner surface roughness; full depth; optical fiber sensor; array;