W.A. Deabes

Characterization of Capacitive Sensors and Monitoring of Metal Fill in Lost Foam Casting

The filling characteristics in lost foam casting need to be monitored to minimize the fill-related defects. Capacitive sensors, based on the change in the coupling capacitance with the presence of grounded metal in its proximity, provide a simple nondestructive method of acquiring filling information. In the current work, the previously proposed capacitive sensor design is optimized for response sensitivity for metal fill in simple and complex foam patterns. The response from the multi-electrode sensor is determined for various locations of the metal piece. An ANFIS (artificial neural fuzzy inference system) numerical model is developed for the nonlinear sensor response and used to find the sensor responses for various metal fill conditions. Further, a least square error approach is suggested to estimate the sensor response for multiple pieces in front of the sensor.

Reliable Metal-Fill Monitoring System Using Wireless Sensor Networks

Among the wide range of wireless sensor networks (WSN) applications, some require reliable data communications such that data packets can be delivered to the destination without any losses. This paper is focused on one such application, namely a metal-fill monitoring system for the lost foam casting process implemented using capacitive sensors and wireless sensor networks. The problem of packet losses associated with wireless transmission of data using WSN with emphasis on the foundry environment has been explored and a method of delayed retransmission has been tested for offline monitoring. The delayed retransmission technique can be used in applications where the completeness of the data collected is more critical than the time taken to collect it The entire system from sensing to data transmission provides a flexible and cost effective method to monitor the metal fill process. Another technique that is more suitable for online applications is also briefly presented.

A Feature-Based Solution to Forward Problem in Electrical Capacitance Tomography of Conductive Materials

A new feature-based technique is introduced to solve the nonlinear Forward Problem (FP) of the Electrical Capacitance Tomography (ECT) with the target application of monitoring the metal-fill profile in Lost Foam Casting (LFC) process. The new technique to solve the FP is based on key features extracted from the metal distributions and the Correction Factor (CF). The CF is predicted by an Artificial Neural Network (ANN) based on key distribution features. The CF adjusts the linear solution of the FP for nonlinear effects. The data for the ANN training was generated through ANSYS finite element analysis and the codes written in MATLAB. The ANN was implemented using MATLAB Neural Network Toolbox. This approach shows promising results. The ANN was able to learn the effect of these features on the CF with the % RMS error of 2.21 for training data. For the previously unseen test metal distributions, the average RMS error was 2.2%.

Reconfigurable wireless stand-alone platform for Electrical Capacitance Tomography

This paper presents the assessment of using Field Programmable Gate Arrays (FPGA) technology to design a stand-alone Electrical Capacitance Tomography (ECT) system. ECT application is manifested by computationally intensive image reconstruction algorithms requiring fast processing of large amounts of data. To date, reconfigurable hardware has not been used in the area of electrical tomography. Furthermore, the experimental results show that using the FPGA as a hardware platform to realize ECT system achieves superior performance in terms of speed and design compactness compared to DSP implementation.

Fuzzy sliding motion controller for six-degree-of-freedom robotic manipulator

Sliding mode control and fuzzy tuning techniques are combined to generate a robust and an accurate fuzzy sliding controller for non-linear systems. The control law consisting of equivalent control, robust control, and fuzzy control is designed such that the equivalent control satisfies desirable dynamics. Reaching the sliding surface is guaranteed by the robust control term even in the presence of parameter and disturbance uncertainties. Fuzzy tuning schemes are employed to reduce the chattering problem around the sliding surface. The method is applied to the control of a six-degree-of-freedom robotic manipulator. Simulation results verify the validity of the proposed approach.

A fuzzy-based reconstruction algorithm for estimating metal fill profile in lost foam casting

Lost foam casting (LFC) process is one of the most energy efficient casting methods in the industry. The metal-fill profile is an important factor that affects casting quality. Hence the characterization and the control of the metal fill, if possible, are essential in LFC. Electrical capacitive tomography (ECT) sensors, based on measuring the change in the coupling capacitance with the presence of grounded metal in its proximity, provide a simple non-intrusive visualization technique of acquiring the metal profile. The principle of ECT is to use a rugged and noninvasive array of capacitive electrodes mounted around a target area and measure the changes in inter-electrode capacitance caused by variations of the grounded metal inside the target area. Cross-sectional images of the metal distribution are then reconstructed from the measured data. Deducing the metal fill distribution from the capacitance measurements is a difficult problem. A novel technique for solving the inverse problem in the electrical capacitance tomography is introduced. The new technique is based on Fuzzy Inference Systems (FIS) to predict the molten metal profile from the capacitance measurements. The developed system is intended to be utilized on the foundry floor and hence a limited number of measurements are utilized. The proposed technique is able to detect the position of the metal by using just eight measurements from the sensors.

Analysis, design and application of a capacitance measurement circuit with wide operating frequency range

A novel high frequency, low cost circuit for measuring capacitance is proposed in this paper. This new capacitance measuring circuit is able to measure small coupling capacitance variations with high stray-immunity. Hence, it could be used in many potential applications such as measuring a metal fill time in the lost foam casting (LFC) process and electrical capacitive tomography (ECT) system. The proposed circuit is based on differential charging/discharging method using current feedback amplifier and a synchronous demodulation stage. The circuit has a wide high frequency operating range with zero phase shift; hence multiple circuits can work at different frequencies simultaneously to measure the capacitance. The non-ideal characteristics of the circuit has been analyzed and verified through LTSpice simulation. Results from the tests on a prototype and a simulation elucidate the practicality of the proposed circuit.

Design and Implementation of a Control System for a Counter Gravity Casting Machine

In counter-gravity casting, pressure is used to draw molten metal, against gravity, into the flask in order to replace the foam pattern and form the final product. The performance of the current pressure controller needs improvement to increase the quality and repeatability of the final product. There are two major hardware difficulties that needed to be compensated for. The first is the nonlinear behavior of valves (hysteresis nonlinearity), which is addressed using a gain scheduling approach by decomposing the nonlinear system into approximate linear subsystems. Consequently, each linear sub-system is controlled using a PID controller. The second difficulty is the decrease of the plenum pressure responsible for creating the vacuum, which requires a new control approach. A PID controller with a gain scheduling scheme and a feed forward term was developed to overcome the nonlinear characteristic of the valves and to compensate for variation of the pressure inside the plenum. The new controller showed considerable performance improvements. Furthermore, the experimental results show how the control is robust in the presence of significant dynamic variations in the input profile.

A confidence prediction system for metal fill visualization using Electrical Capacitance Tomography

Electrical Capacitance Tomography systems have gained increasing acceptance, though there are some problems associated with ECT systems. The mathematical complexity of image reconstruction makes visualization of the metal fill difficult. This paper focuses on the design and analysis of a system that uses information from the electrical capacitance tomography system to produce confidence values for the metal distribution that is being monitored. The confidence values produced by the system were found to be 84% reliable.

Metal fill profile detection in Lost Foam Casting process using capacitive sensors

Electrical capacitive tomography (ECT) provides a simple noninvasive and ruggedized visualization technique for acquiring the metal fill profile in lost foam casting process (LFC) process. The mutual capacitance change caused by variation of the grounded metal inside the target area is measured by using an array of capacitive electrodes mounted around a target area. This paper implements a new technique for determining the metal fill profile. The proposed system has been made wireless and using a limited number of measurements which lower the cost of the hardware. An iterative linear back projection (ILBP) technique for reconstructing the metal images is adapted. Experiments are carried using a LFC simulated environment to test the performance of the system. The proposed method is able to detect the position of the metal using only 6 measurements from the sensors. Reconstructed images for the metal profile show the ability of the proposed system to identify the location and amount of the metal inside the foam pattern.