Thermal compensation study of a novel electronic pressure scanner based on crested porcupine optimizer combined with deep belief network

The pressure parameters of hypersonic vehicles and their key components, such as engine inlets, are critical to the reliability and stability of the system. Their variations have a direct impact on vehicle performance and flight safety optimization. In order to meet the extreme working conditions in hypersonic environments, a novel high-temperature-resistant electronic pressure scanner is designed in this study, which can be directly integrated into the engine to realize accurate pressure measurement under high-temperature and high-Mach-number conditions. In order to verify the environmental adaptability of this electronic pressure scanner, this paper carries out a high-temperature thermal test and calibration experiment, and obtains high-precision calibration data under different temperature conditions. However, due to the temperature drift effect, measurement errors still exist. To effectively solve this problem, this paper proposes a thermal error compensation method based on CPO-DBN (Crested Porcupine Optimizer-Deep Belief Network), which optimizes the hyperparameters of the deep belief network through the defense mechanism of the crown porcupine, to improve the model’s nonlinear fitting ability and compensation accuracy. The experimental results showed that, compared with the traditional BP (Back Propagation) neural network, DBN and PSO-DBN (Particle Swarm Optimization-DBN) models, the CPO-DBN model had the best performance in thermal error compensation, and the maximum absolute error of pressure measurement was reduced to 1.722 kPa. The compensation accuracy is improved to 0.17 % F.S. with a coefficient of determination of R² = 0.994. This is significantly better than other comparative methods. This study provides an innovative solution for the thermal error compensation of the electronic pressure scanner in high temperature environments, and provides technical support for the performance optimization and system stability improvement of the key components of hypersonic vehicles, which has important engineering application value.