Chicago, Illinois
June 18, 2006
June 18, 2006
June 21, 2006
2153-5965
Instrumentation
12
11.1196.1 - 11.1196.12
10.18260/1-2--324
https://peer.asee.org/324
1644
Terrance D. Lovell is an electrical engineering student at Penn State Berks in Reading, PA where he has completed his associate’s degree in electrical engineering technology. He is a research assistant in the EET department. Prior to his academic pursuits he was an electronics countermeasures technician for the U. S. Marine Corps.
Dale H. Litwhiler is an Assistant Professor at Penn State Berks-Lehigh Valley College in Reading, PA. He received his B.S. from Penn State University, his M.S. from Syracuse University and his Ph.D. from Lehigh University all in electrical engineering. Prior to beginning his academic career in 2002, he worked with IBM Federal Systems and Lockheed Martin Commercial Space Systems as a hardware and software design engineer.
Teaching a Computer to Read: Image Analysis of Electrical Meters
Abstract
There exists a vast infrastructure of heritage analog and digital meters installed in commercial and industrial applications. These devices typically have no built-in means of automated reading. Modifying the equipment is not a viable option in many applications. With the low cost of USB digital cameras and the availability of LabVIEW™ VISION, a cost-effective method of reading multiple meters of assorted types can be created. Duplicating the process that a human performs while reading a meter display is daunting. However, this process is simplified by using virtual instruments (VIs), which perform essential functions such as edge, pattern and rotation detection. As part of an undergraduate research project, a computer, using LabVIEW™ Vision, together with a USB digital camera is used to read a digital multimeter (DMM) and an analog watt-hour meter. Circular edge detection, pattern searches, and rotation detection are used to locate dials and segments and to determine their values. Horizontal and vertical edge detection and region of interests (ROI) are used to identify and determine the values of a DMM’s display. The ability to read meters with only minimal human interaction increases accuracy and speed. This feature and the ability to create visual data logging have many uses in educational and industrial applications. This paper presents techniques for identifying and reading meter data. The basics of reference images and their use in image analysis are explored in reading legacy DMM and analog watt-hour meters.
Introduction and Motivation
Various types of electrical meters are required and utilized to take many types of measurements in commercial and industrial applications. There exists a wide range of installed legacy meters which are capable of performing these measurements. The vast majority of these devices lack the ability to be remotely or locally monitored by computers. The ability to be monitored by a computer is becoming increasingly important as the convenience of remotely monitoring equipment outweighs the cost of visiting each piece of equipment. Modern measurement equipment is certainly capable of transmitting its acquired data either through wires of wirelessly. The infrastructure of existing equipment is slowly being replaced with this type of devices. However, the replacement of the installed base of legacy equipment is a costly and daunting task and may not be practical in many instances.
The use of cameras in manufacturing automation is well published and very successful. Most systems employ sophisticated and expensive vision equipment for the control of robotic equipment.1,2 With the recent popularity of the universal serial bus (USB), a plethora of formidable image capturing devices have emerged. These devices have very high resolution and very low cost. These features make them very attractive for many data acquisition applications as well. Together with sophisticated yet simple to use LabVIEW software, powerful and elegant instrumentation systems can be created.3
Lovell, T., & Litwhiler, D. (2006, June), Teaching A Computer To Read: Image Analysis Of Electrical Meters Paper presented at 2006 Annual Conference & Exposition, Chicago, Illinois. 10.18260/1-2--324
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