中医熏蒸温度系统建模与控制研究
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摘要
腰椎间盘突出症是骨科多发病，中医熏蒸是治疗腰椎间盘突出症的常用方法，因其疗效显著、费用低以及副作用小而在临床中广泛应用。然而，临床信息采集、存储技术落后，临床经验利用率低等因素是制约其数字化发展与完善的主要瓶颈。
温度是能量传递的宏观表达形式，患者体征、室外温度以及熏蒸方剂等因素与熏蒸温度相互作用，彼此影响，至今尚无统一的科学规范与之对应。基于以上研究背景建立中医熏蒸温度系统模型，深度分析挖掘与利用临床资源，不仅对于继承和发扬中医具有重要的研究价值，而且对提升人类的健康水平具有广阔的应用前景。
温度是中医熏蒸的关键治疗参数，复杂的生理现象与物理现象并存，导致了常规的温度建模与控制方法无法适用于此类系统，针对这一问题利用智能控制理论与生物医学机理，对中医熏蒸温度系统进行建模与控制，是中医熏蒸现代化发展的必经之路。主要研究内容如下：
1.建立基于传热学的温度机理模型。中医熏蒸温度系统是一个大滞后、时变的非线性系统，各个变量之间存在强耦合作用，通过分析热源的热传导、对流过程以及通风窗通风对流过程，利用传热学理论及质能平衡方衡，建立熏蒸舱内热环境模型，为后续的温度控制提供模型支持。
2.研究变论域模糊控制器。分析指数型伸缩因子函数特征，基于中医熏蒸临床信息，构建患者年龄、病程、热源温度、熏蒸时间、室外平均温度及疗效分级6簇隶属度函数。在此基础上设计变论域模糊控制器并对其数学特性及临床应用进行研究。
3.提出变结构动态模糊神经网络的颖学习算法。利用数学分析方法中Stone-weierstrass定理，对变结构动态模糊神经网络通用逼近性能进行分析，借鉴矩阵分解及概率论中正态分布的数学特性建立规则学习算法及规则修剪算法，借鉴数据挖掘理论，建立样本空间学习算法，并完成网络稳定性分析。
4.建立中医熏蒸温度系统仿真模型。在有限元工具箱PDE中建立热源模型、功率模型、方剂扩散模型以及控制器模型。用所建立的模型对不同症型治疗过程的温度进行预测，预测值和实测值的拟合关系较好。说明YL-DFNN对熏蒸空间的非线性系统辨识有效。对不同症型的温度进行优化控制，仿真结果表明YL-DFNN能够实现节能降耗的控制要求。
At present, Traditional Chinese Drug Fumigation has become a common treatmentfor Lumbar disc herniation due to its significant effects, low costs and fewer sideeffects. However, its further development and improvement in terms of digitization arelargely constrained by the backward technology for the collection and storage ofclinical information and the low utilization of clinical experience.
Temperature is a macro way of showing the transmission of energy. The factors,such as physical signs of the patients, outdoor temperature and fumigation prescription,interact with the temperature during the course of fumigation. However, up to nowthere is no uniform scientific criterion for it. Under this circumstances, setting up aTraditional Chinese Drug Fumigation temperature model and analysis of deepexcavation of the clinical resources will be of significant value, and helpful forimproving people’s health conditions.
Temperature is the key to Chinese medicine fumigation treatment parameters andthere are complex physiological phenomena and physical phenomena in this course oftreatment. This lead to a normal temperature modeling and control methods can notapply to such systems. In order to solve this problem, using the intelligent control withbiomedical knowledge to traditional Chinese medicine fumigation temperature systemmodeling and control is the only way of traditional Chinese medicine fumigationmodernization development.
The study of this paper as follows:
Firstly, establish the mechanism of temperature based on heat transfer model.Chinese medicine fumigation temperature system is a big lag, strong coupling, andtime varying nonlinear systems. The fumigation cabin thermal environment model hasbeen established based on the analysis of the heat source heat conduction, convection,and the windows ventilation convection process.
Secondly，research on variable universe fuzzy controller. a new-type function ofcontraction-expansion factor is established in this paper，which can be realized easilyto optimize the controller of complicated control system based on based on traditionalChinese medicine fumigation constructing clinical information, patient age, duration,temperature of heat source, the steaming time, outdoor mean air temperature and effectgrade. Fuzzy control is one of intelligent control methods which is based on fuzzy theory and interpolation mechanism, so the structure analysis of typical fuzzycontroller can offer important guidance for fuzzy controller design.
Thirdly，variable structure dynamic fuzzy neural network Ying learning algorithmis proposed. Use the Stone-Weierstrass theorem in mathematical analysis to analyzethe variable structure dynamic neural network universal approximation capability,draw on the mathematical properties of the normal distribution in the matrixdecomposition and probability theory to create a rule learning algorithm for rulepruning algorithm, establish the sample space learning algorithms, and completenetwork stability analysis.
Finally，establish of Chinese medicine fumigation temperature system simulationmodel. In the finite element toolbox PDE establishment heat source model, powermodel, diffusion model and controller model of prescription. Forecast the temperatureof different disease treatment process of the model, forecast values and measure valuesfitting relationship is good and the YL-DFNN on fumigation space for nonlinearsystem identification is effective. Simulation results show that YL-DFNN can achieveenergy saving control requirements on the different disease type temperature optimizedcontrol.
温度是能量传递的宏观表达形式，患者体征、室外温度以及熏蒸方剂等因素与熏蒸温度相互作用，彼此影响，至今尚无统一的科学规范与之对应。基于以上研究背景建立中医熏蒸温度系统模型，深度分析挖掘与利用临床资源，不仅对于继承和发扬中医具有重要的研究价值，而且对提升人类的健康水平具有广阔的应用前景。
温度是中医熏蒸的关键治疗参数，复杂的生理现象与物理现象并存，导致了常规的温度建模与控制方法无法适用于此类系统，针对这一问题利用智能控制理论与生物医学机理，对中医熏蒸温度系统进行建模与控制，是中医熏蒸现代化发展的必经之路。主要研究内容如下：
1.建立基于传热学的温度机理模型。中医熏蒸温度系统是一个大滞后、时变的非线性系统，各个变量之间存在强耦合作用，通过分析热源的热传导、对流过程以及通风窗通风对流过程，利用传热学理论及质能平衡方衡，建立熏蒸舱内热环境模型，为后续的温度控制提供模型支持。
2.研究变论域模糊控制器。分析指数型伸缩因子函数特征，基于中医熏蒸临床信息，构建患者年龄、病程、热源温度、熏蒸时间、室外平均温度及疗效分级6簇隶属度函数。在此基础上设计变论域模糊控制器并对其数学特性及临床应用进行研究。
3.提出变结构动态模糊神经网络的颖学习算法。利用数学分析方法中Stone-weierstrass定理，对变结构动态模糊神经网络通用逼近性能进行分析，借鉴矩阵分解及概率论中正态分布的数学特性建立规则学习算法及规则修剪算法，借鉴数据挖掘理论，建立样本空间学习算法，并完成网络稳定性分析。
4.建立中医熏蒸温度系统仿真模型。在有限元工具箱PDE中建立热源模型、功率模型、方剂扩散模型以及控制器模型。用所建立的模型对不同症型治疗过程的温度进行预测，预测值和实测值的拟合关系较好。说明YL-DFNN对熏蒸空间的非线性系统辨识有效。对不同症型的温度进行优化控制，仿真结果表明YL-DFNN能够实现节能降耗的控制要求。
At present, Traditional Chinese Drug Fumigation has become a common treatmentfor Lumbar disc herniation due to its significant effects, low costs and fewer sideeffects. However, its further development and improvement in terms of digitization arelargely constrained by the backward technology for the collection and storage ofclinical information and the low utilization of clinical experience.
Temperature is a macro way of showing the transmission of energy. The factors,such as physical signs of the patients, outdoor temperature and fumigation prescription,interact with the temperature during the course of fumigation. However, up to nowthere is no uniform scientific criterion for it. Under this circumstances, setting up aTraditional Chinese Drug Fumigation temperature model and analysis of deepexcavation of the clinical resources will be of significant value, and helpful forimproving people’s health conditions.
Temperature is the key to Chinese medicine fumigation treatment parameters andthere are complex physiological phenomena and physical phenomena in this course oftreatment. This lead to a normal temperature modeling and control methods can notapply to such systems. In order to solve this problem, using the intelligent control withbiomedical knowledge to traditional Chinese medicine fumigation temperature systemmodeling and control is the only way of traditional Chinese medicine fumigationmodernization development.
The study of this paper as follows:
Firstly, establish the mechanism of temperature based on heat transfer model.Chinese medicine fumigation temperature system is a big lag, strong coupling, andtime varying nonlinear systems. The fumigation cabin thermal environment model hasbeen established based on the analysis of the heat source heat conduction, convection,and the windows ventilation convection process.
Secondly，research on variable universe fuzzy controller. a new-type function ofcontraction-expansion factor is established in this paper，which can be realized easilyto optimize the controller of complicated control system based on based on traditionalChinese medicine fumigation constructing clinical information, patient age, duration,temperature of heat source, the steaming time, outdoor mean air temperature and effectgrade. Fuzzy control is one of intelligent control methods which is based on fuzzy theory and interpolation mechanism, so the structure analysis of typical fuzzycontroller can offer important guidance for fuzzy controller design.
Thirdly，variable structure dynamic fuzzy neural network Ying learning algorithmis proposed. Use the Stone-Weierstrass theorem in mathematical analysis to analyzethe variable structure dynamic neural network universal approximation capability,draw on the mathematical properties of the normal distribution in the matrixdecomposition and probability theory to create a rule learning algorithm for rulepruning algorithm, establish the sample space learning algorithms, and completenetwork stability analysis.
Finally，establish of Chinese medicine fumigation temperature system simulationmodel. In the finite element toolbox PDE establishment heat source model, powermodel, diffusion model and controller model of prescription. Forecast the temperatureof different disease treatment process of the model, forecast values and measure valuesfitting relationship is good and the YL-DFNN on fumigation space for nonlinearsystem identification is effective. Simulation results show that YL-DFNN can achieveenergy saving control requirements on the different disease type temperature optimizedcontrol.
引文
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