Inverse Model for the Control of Induction Heat Treatments

Abstract

In this work, we present and test an approach based on an inverse model applicable to the control of induction heat treatments. The inverse model is comprised of a simplified analytical forward model trained with experiments to predict and control the temperature of a location in a cylindrical sample starting from any initial temperature. We solve the coupled nonlinear electromagnetic-thermal problem, which contains a temperature dependent parameter α to correct the electromagnetic field on the surface of a cylinder, and as a result effectively the modeled temperature elsewhere in the sample. A calibrated model to the measurement data applied with the process information such as the operating power level, current, frequency, and temperature provides the basic ingredients to construct an inverse model toolbox, which finally enables us to conduct experiments with more specific goals. The input set values of the power supply, i.e., the power levels in the test rig control system, are determined within an iterative framework to reach specific target temperatures in prescribed times. We verify the concept on an induction heating test rig and provide two examples to illustrate the approach. The advantages of the method lie in its simplicity, computationally cost effectiveness and independence of a prior knowledge of the internal structure of power supplies.

Hybrid Neural Network Models for the Optimization of Induction Hardening Processes

“…Our numerical model also allows the operator to enter merely the power level into the control system. So, models that are learned with controlled factors are more useful and can be used in reverse for optimization or smart induction heating [19,20]. Furthermore, because exact material data are sometimes unavailable, it is desirable to train a model without explicitly depending on them.…”

The HCF property research of quenched crankshaft based on the stress field intensity method and the multi-physic field Coupling Numerical simulation approach

“…Compared with other techniques, the strengthening factor of the inductive quenching approach is obviously larger (usually no less than 1.5) than those of the other surface treatment methods. Thus correct design of the manufacturing process parameters becomes necessary to provide the theoretical guidance for the detailed course of working [3] .…”

Data-Driven Inverse Problem for Optimizing the Induction Hardening Process of C45 Spur-Gear

“…In the context of an inverse problem, fewer studies have been conducted for IH. They are related to the estimation of the power levels using the temperature as input in steel cylinders [47] and the heat transfer coefficient using the surface temperature in a steel billet [48]. In industry, solving the inverse problem for IH can have a number of benefits.…”