基于自适应深度置信网络的压力变送器温度补偿方法研究  

Temperature Compensation Method of Pressure Sensor Based on Adaptive Deep Belief Network

作　　者：高彬彬[1] 顾幸生[1] 王鑫 GAO Binbin;GU Xingsheng;WANG Xin(Key Laboratory of Smart Manufacturing in Energy Chemical Process,Ministry of Education,East China University of Science and Technology,Shanghai 200237,China;Research&Development Center,Shanghai Automation Instrumentation Co.Ltd,Shanghai 200072,China)

机构地区：[1]华东理工大学能源化工过程智能制造教育部重点实验室,上海200237 [2]上海自动化仪表有限公司技术中心,上海200072

出　　处：《华东理工大学学报（自然科学版）》2024年第2期238-246,共9页Journal of East China University of Science and Technology

基　　金：国家自然科学基金(61973120)。

摘　　要：随着压力变送器检测技术和人工智能技术的不断发展,在航空航天、石化、核电等领域人们对压力变送器的稳定性、实时性、测量精度等方面有了更严格的要求。而工作环境的温度会对设备精度造成巨大影响,导致变送器测量值出现偏移。针对此问题,本文提出了基于自适应深度置信网络的高精度压力变送器温度补偿方法。深度置信网络(Deep Belief Networks,DBN)在无监督学习阶段提取数据的特征,然后在有监督阶段使用少量的数据对网络参数进行微调;利用白鲸优化算法(Beluga Whale Optimization,BWO)在全局搜索和局部寻优之间达到平衡,有效地提高DBN网络的优化效果;引入Metropolis准则和适应度平衡因子,进一步提高算法的全局寻优能力以及模型收敛速度。实验拟合后的数据精度可达0.0048%,远高于现有的最高标准0.05级。经过一系列对比分析,验证了补偿算法的准确性和实用性。With the development of modern pressure transmitter detection technology and artificial intelligence technology,stricter requirements are made on the stability,real-time performance and measurement accuracy of pressure transmitter in aerospace,petrochemical,nuclear power and other fields.The temperature of working environment may greatly affect the accuracy of equipment,leading to offset in the measured values of the transmitter.Aiming at these problems,this paper proposes a temperature compensation method for highprecision pressure transmitters based on adaptive DBN(Deep Belief Network).DBN extracts features from data in the unsupervised learning phase,and then fine tunes network parameters using a small amount of data in the supervised phase;Utilizing the BWO(Beluga whale optimization)algorithm to achieve a balance between global search and local optimization,effectively improving the optimization performance of DBN networks;Introducing the Metropolis criterion and fitness balance factor to further improve the algorithm’s global search capability and model convergence speed.The experimental results show that the data accuracy after fitting can reach 0.0048%,much higher than the existing highest standard of 0.05 level.By comparative analysis,the accuracy and practicability of the compensation algorithm are verified.

关 键 词：温度补偿 深度置信网络 启发式算法 压力变送器 白鲸优化算法 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]