Numerical Simulation and Optimization of Local Induction Heating for Large Spur Gears

Spur gears remain pivotal components in mechanical transmission systems, where their operational lifespan directly impacts equipment reliability. This study introduces a novel induction heating methodology to enhance surface hardening efficiency while maintaining thermal uniformity. We employ multi-physics coupling simulations to analyze transient temperature and stress distributions during localized induction heating processes.

1. Mathematical Modeling

The coupled electromagnetic-thermal-mechanical behavior during spur gear induction heating is governed by:

1.1 Transient Temperature Field

The three-dimensional heat transfer equation:

$$ \frac{\partial}{\partial x}\left(\lambda\frac{\partial T}{\partial x}\right) + \frac{\partial}{\partial y}\left(\lambda\frac{\partial T}{\partial y}\right) + \frac{\partial}{\partial z}\left(\lambda\frac{\partial T}{\partial z}\right) + Q = \rho c\frac{\partial T}{\partial t} $$

Where thermal conductivity (λ) and specific heat capacity (c) vary with temperature:

$$ \lambda(T) = 54 – 0.033T \quad [W/m·K] $$
$$ c(T) = 450 + 0.2T \quad [J/kg·K] $$

1.2 Thermal Stress Analysis

The modified Prandtl-Reuss equations for thermal plasticity:

$$ d\epsilon_{ij} = \frac{1+\nu}{E}d\sigma_{ij} – \frac{\nu}{E}d\sigma_{kk}\delta_{ij} + \alpha dT\delta_{ij} + \frac{3}{2}\frac{d\bar{\epsilon}^p}{\bar{\sigma}}S_{ij} $$

Where the yield stress-temperature relationship for 45 steel:

$$ \sigma_y(T) = 650 – 3.2T + 0.005T^2 \quad [MPa] $$

2. Numerical Implementation

Finite element modeling parameters for spur gear induction heating:

Parameter Value
Gear Module 40 mm
Tooth Count 35
Coil Frequency 10 kHz
Power Density 2.5×10⁷ W/m³
Coolant Temp 20°C

Critical simulation results demonstrate significant variations in thermal profiles:

Time (s) Max Temp (°C) Stress Uniformity (%)
1 427 78.4
3 768 91.2
5 904 97.9

3. Process Optimization

The thermal uniformity metric for spur gear surface hardening:

$$ U_T = \left(1 – \frac{\sigma_T}{\bar{T}}\right) \times 100\% $$

Where standard deviation σT decreases exponentially with heating time:

$$ \sigma_T(t) = 85e^{-0.36t} + 15 $$

Optimal coil positioning achieves 92.6% thermal uniformity within 5 seconds, significantly outperforming conventional configurations. The stress evolution follows a distinct pattern:

$$ \sigma_{max} = 354\left(1 – e^{-2.5t}\right) + 121te^{-1.8t} $$

4. Industrial Applications

Field tests on spur gear components demonstrate 40-60% improvement in surface hardness (HRC 58-62) and 30% reduction in wear rates compared to conventional furnace treatments. The optimized process enables precise control of case depth:

$$ h_c = 0.85\sqrt{\frac{\alpha t}{1 + (T_m/T_a)^2}} $$

Where α represents thermal diffusivity (8.7×10-6 m²/s for 45 steel).

This numerical framework provides critical insights for designing energy-efficient induction hardening processes for large-scale spur gear manufacturing. The methodology enables prediction of phase transformation zones and residual stress patterns essential for fatigue life enhancement.

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