<p>The high-precision calculation and measurement of cutting force is a key technology in intelligent manufacturing. The traditional instantaneous rigid force model ignores tool wear and cannot consider factors such as the dynamic characteristics of the process system, resulting in limited solution accuracy. This study innovatively establishes a multi-sensor acquisition system. Leveraging actually collected spindle current and integrating genetic algorithm, the cutting force coefficients are dynamically calibrated. Compared with the calculation error before calibration, the calculation accuracy of the maximum and average cutting force errors has increased by 42.79% and 24.97%, respectively. Meanwhile, the study found a significant linear mapping between cutting force and spindle current after removing no-load current, with a total fitting R² of 0.99 and an average error of 3.62%. This approach effectively simplifies the complex nonlinear model, offering technical support for low-cost, high-precision real-time monitoring of cutting forces in intelligent manufacturing.</p> Graphical abstract <p></p>