TPT May 2022


Thermatool Corp

What about HF welding heat input? Each equation for calculating weld heat input in arc welding and power beam welding processes has something in common: they all take into account voltage and current, as well as travel speed. High frequency electric resistance welding is a multi-physics process where physical, thermal, and electrical aspects are used to control the heat in a non equilibrium solid state welding process. A look at HF induction welding reveals main process parameters: power (volts and amperes), frequency, line speed, vee length, vee angle and forging dynamics. Of course, the role of the impeder also has a big impact on power consumption and heat distribution. Secondary parameters of interest are material properties such as electrical resistivity, magnetic permeability and thermal conductivity, as well as product outer diameter, wall thickness, and heat capacity. The properties and dimensions of the raw material cannot be controlled, but the HF welding frequency can be used to maximise skin and proximity effects to optimise heat input. The effects of Joule heating are controlled by controlling the weld power, vee length and angle, and line speed. The heat generated in the vee can be calculated using the following simple equation:

(wide range of conditions) and under specific R&D conditions. Correlation between frequency and HAZ width has been proven. Conclusion We need a simple way for everyone to make high quality HF welded tube and pipe. Translating theory into practice is always a challenge. Let’s review a few simple and well-known methods for optimising proper quality [5] . The simple process control chart below shows upper control limits (UCL) and lower control limits (LCL) using a yellow limit band. When operating within the process target (green band) the process is centered and under control. If the process begins to experience variation, the yellow band is used to indicate that the probability of reaching the process limit is increasing. The red upper process limit (UPL) and lower process limit (LPL) define the overall process limits. This graphical representation takes a sophisticated statistical process control (SPC) techniques and simplifies it.

Where: Q – heat generated (stored) in the vee (J), I – current passing through edges (A), ρ - resistivity (Ω-m) A – Area (m 2 ) and A= wall thickness x ξ ,

Where ξ is electrical reference depth and can be calculated using following equation

Figure 3: Process control chart

The concept of process control capability is introduced below. Calculated process capability is a measure of how consistently an HF welding process can produce tubes and pipes within specifications. The goal is to control weld quality in a repeatable, yet simple to operate way. The HF welding process should: (1) Be centered over the target weld heat input, as defined by the validated process parameters (2) Have a narrow variation within the process specification (this requires precise heat input control)

Where f- frequency (Hz), μ- magnetic permeability (H/m), ρ- electrical resistivity (Ω-m). The electrical reference depth is inversely proportional with frequency (F), the resistive heating will be increased by the reduced area (A) of the heated “conductor” (with all other variables being the same). Therefore, the inverse relationship with frequency can be related to the resistive heat generation, ie the higher the frequency, the smaller the heated area, hence the more heat is being generated at the same power level. In practical terms this means that with faster mill speeds, heat input will be lower and HAZ width will be narrower. It is important to control all process variables during your HF induction welding process. Power and frequency will be highly dependent on the setup and material being welded, however precise control of both parameters will result in optimised and low heat input resulting in the best HF weld quality. A recent study [4] by Thermatool showed that frequency can be a powerful tool for precise heat input control. The study uses large datasets that have been obtained both in the field

Cp measures whether the process variation is narrower than the process specification.


MAY 2022

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