18 research outputs found
Integrating PLCs with Robot Motion Control in Engineering Capstone Courses
Robotic motion control methods and Programmable Logic Controllers (PLCs) are critical in engineering automation and process control applications. In most manufacturing and automation processes, robots are used for moving parts and are controlled by industrial PLCs. Proper integration of external I/O devices, sensors and actuating motors with PLC input and output cards is very important to run the process smoothly without any faults and/or safety concerns. Most traditional electrical and computer engineering (ECE) programs offer high level of motion theory and controls but little hands-on exposure to PLCs which are the main industrial controllers. This paper provides a framework for a hands-on project to integrate PLCs in robot arm motion control, troubleshooting, and testing the real sensors and motors with PLC experiments which complements the virtual calculations and theory. This PLC with Robot Arm Motion control integration concept idea was introduced and tested in a 600-level graduate capstone project class. By the end of the semester long class, the students used their PLC hardware and software skills to wire a robot arm sensing elements and actuating motors to pick and place objects from one location to a bin. The assessment demonstrated that the course learning objectives were met
Physical Intelligent Sensors
This paper proposes the development of intelligent sensors as part of an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the NASA s Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Integrated Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent Sensors (PIS). The PIS discussed here consists of a thermocouple used to read temperature in an analog form which is then converted into digital values. A microprocessor collects the sensor readings and runs numerous embedded event detection routines on the collected data and if any event is detected, it is reported, stored and sent to a remote system through an Ethernet connection. Hence the output of the PIS is data coupled with confidence factor in the reliability of the data which leads to information on the health of the sensor at all times. All protocols are consistent with IEEE 1451.X standards. This work lays the foundation for the next generation of smart devices that have embedded intelligence for distributed decision making capabilities
Physical Intelligent Sensors
This paper proposes the development of intelligent sensors as part of an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the NASA s Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Integrated Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent Sensors (PIS). The PIS discussed here consists of a thermocouple used to read temperature in an analog form which is then converted into digital values. A microprocessor collects the sensor readings and runs numerous embedded event detection routines on the collected data and if any event is detected, it is reported, stored and sent to a remote system through an Ethernet connection. Hence the output of the PIS is data coupled with confidence factor in the reliability of the data which leads to information on the health of the sensor at all times. All protocols are consistent with IEEE 1451.X standards. This work lays the foundation for the next generation of smart devices that have embedded intelligence for distributed decision making capabilities
Intelligent Sensors: Strategies for an Integrated Systems Approach
This paper proposes the development of intelligent sensors as an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Intelligent Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS)
Introduction of Mechatronics Specialization through Concentration Areas in the Mechanical and Electrical Engineering Technology Programs
The last few decades have experienced an explosion of technology, both in industry and in customer products. A large variety of embedded systems from various areas of applications, digital electronics, internet of things, automatically controlled products, and ultimately mechatronics systems are part of the everyday life. The changes in the industries, consumer markets and implicitly in the job markets, impose changes in the academic programs and curricula. Recently, mechatronics undergraduate programs started being developed in 2 or 4 years colleges across the nation, mainly driven by international companies operating in countries that already offer mechatronics degrees ranging from high school to doctoral programs. Most of the time there are independent mechatronics programs, mainly at the community college level, but mechatronics areas of specialization were also developed under either electrical or mechanical engineering programs, through senior elective courses. In the College of Engineering and Technology at Old Dominion University there are currently well established, accredited electrical and mechanical engineering technology programs, and steps are being taken to introduce the option for mechatronics specialization. A mechatronics concentration area was already introduced under the mechanical engineering technology (MET) program with new courses developed to provide skills in mechatronics, hydraulics, and simulation of mechatronics systems, complementing the existing courses focusing on automation, industrial robotics, computer integrated manufacturing, and computer numerical control. The electrical engineering technology (EET) program, with a current curriculum that includes a large number of courses to provide the foundation for mechatronics, is taking its turn in the development of a mechatronics concentration area. This paper discusses the introduction of mechatronics specialization through concertation areas in the mechanical and electrical engineering technology programs at Old Dominion University, with emphasis on the implementation challenges. This specialization model offers students the choice to incline the balance between the electrical and mechanical components of their mechatronics education through their major and minor selection, and in consonance with their individual strengths and preferences
Intelligent Sensors: An Integrated Systems Approach
The need for intelligent sensors as a critical component for Integrated System Health Management (ISHM) is fairly well recognized by now. Even the definition of what constitutes an intelligent sensor (or smart sensor) is well documented and stems from an intuitive desire to get the best quality measurement data that forms the basis of any complex health monitoring and/or management system. If the sensors, i.e. the elements closest to the measurand, are unreliable then the whole system works with a tremendous handicap. Hence, there has always been a desire to distribute intelligence down to the sensor level, and give it the ability to assess its own health thereby improving the confidence in the quality of the data at all times. This paper proposes the development of intelligent sensors as an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the NASA Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Intelligent Systems Health Monitoring (ISHM) vision. This paper outlines some fundamental issues in the development of intelligent sensors under the following two categories: Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS)
Integrating Statistical Methods in Engineering Technology Courses
Statistical methods and procedures are very important in engineering applications. In most of the engineering fields electronic devices are used as sensing and controlling components. Lack of proper calibration of these devices and of performance analysis using different statistical methods may lead to erroneous measurements and results. In medical or manufacturing areas such errors in the experimental results could be catastrophic. Applying different statistical tests and procedures enhance the quality of engineering work. Traditionally, most engineering curricula have at least one required course in applied statistics in engineering, but that is not generally the case in engineering technology programs. Most of the engineering technology BS graduates work as field engineers and collect the data from different physical processes and do data analysis to validate the systems performances. Exposure to statistical methods use and data analysis will provide technology graduates with valuable skills in the current high-tech job market. This paper focuses on how statistical analysis and methods using hand calculations and software tools can be integrated in undergraduate engineering technology courses, enhancing the hands-on approach of real engineering projects with software assisted data analysis. Learning the skills of collecting experimental data from real processes and performing statistical analysis on it is the effective approach of solving engineering problems, and it provides higher learning outputs than simulation-based approach. Specifically, integration of statistical analysis was introduced in an industrial instrumentation class, in which the lab component included the use of various sensors and other measurement instruments. By the end of the class, students demonstrated newly acquired statistical skills by performing sensor calibration and they also applied simple linear regression analysis model on the experimental dat
Curriculum Development for Robotics Technology Program
With a growing need for a more skilled workforce, providing industry-driven and employment centric training services is an important national priority. Over 3.4 million manufacturing jobs will need to be filled across the United Sates over the next decade. The skills gap is becoming greater based on the statistics provided by the Global Robotics Technology Market: Forecast, 2014-2020 published by Research and Markets, reporting that the worldwide robotics market is forecast to grow from the 2015 level of 82.78B in 2020. This 11 % compounded average growth in the next five years is unprecedented. Given the anticipated growth of the robotics industry, the number of jobs that will be required to meet the demand will grow exponentially as well. The future is bright for careers in STEM fields; today, the average annual salary for a STEM worker is $33,200 higher than the average of all U.S. workers, making the need for a novel robotics credential imperative. The curriculum development explained in this paper in the area of Advanced Robotics for Manufacturing was carried out broadly in two phases: Phase I of the project focused on investigating and compiling the curricula offered by different community colleges, work force education programs in universities and other industry certificate programs in the Commonwealth of Virginia and then in other states. Phase II of this project focused on curriculum development at CCAM (Commonwealth Center for Manufacturing, VA) that improves/adds the topics, compliments and fills the gap from the data gathered in the first stage. Phase II was not only based on the data generated in Phase I, but also was informed by data gathered from industry needs and new technologies that are required in the manufacturing robotics area. The next phase include implementing the developed curriculum at Community College level and at 4-year degree colleges
An Iterative Kalman Filter for a 3D Ultrasonic Position Estimation System
This paper describes an iterative Kalman Filter to increase the accuracy of a dynamic 3D position estimation system. The novelty of the system lies in the fact that a difference in the time of arrivals is used in conjunction with an estimated speed of sound within the system formulation, and the Kalman Filter is used to further increase the accuracy and robustness of the output. The output is a 3D position of the transmitter obtained from the difference in time of arrivals of the wave burst at multiple receivers fixed within an inertial frame. Results are provided to show the increase in accuracy and robustness along with some limitations of the system. The system has many applications the most significant being image guided surgery