臭氧生产工艺过程智能测控系统的研究
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摘要
臭氧(03)具有极强的氧化性和杀菌性能,在饮用水、污水处理,食品加工,化工生产及医疗等方面得到了广泛的应用。随着臭氧生产技术的发展及臭氧应用的普及,对臭氧生产工艺过程的自动控制提出了越来越高的要求,而目前臭氧生产过程中测控技术落后、自动化水平低,急待提高。本文在对臭氧生产工艺过程机理深入分析的基础上,提出了应用智能测控技术来实现臭氧生产过程的有效控制和优化控制,研制了整套臭氧生产过程的智能测控系统并成功应用于臭氧生产过程。本文的主要研究内容如下：
(1)在分析臭氧生产过程机理特性及工艺流程的基础上,提出了臭氧生产工艺过程智能测控系统的整体设计方案,采用工控机+嵌入式工控机PC104+单片机组成三层分布式控制系统,实现了臭氧生产过程各关键工艺参数的测控及臭氧生产过程的优化控制,应用结果验证了本设计方案的有效性。
(2)臭氧生产过程中需要监控的工艺参数较多、分布较广,且各种管路交叉,强弱电结合,难以采用有线连接方式,因此本文采用无线传感器网络构建整个智能测控系统,并结合具体应用,对无线传感器网络结构、低功耗及可靠性等方面进行了研究。
(3)设计了气体温度、气体流量以及功率三个关键测控回路,在气体流量测控回路中设计了一种基于浮子流量计的光电式气体流量测量装置,并在实践中对其进行了验证；在功率测控回路中对臭氧生产工艺过程中的功率测量和控制进行了研究,所应用的功率测量方法和控制策略在实践中取得了良好的效果。
(4)在臭氧生产过程中,作为质量指标和控制目标的臭氧浓度目前很难对其进行在线实时测量。本文结合臭氧生产机理,研究了生产工艺过程中对臭氧浓度有直接影响的工艺参量,选择其中六个为辅助变量,应用RBF神经网络建立了臭氧浓度软测量模型,对模型进行了训练、校正以及评价。采用臭氧浓度分析测试仪EG-2001B对臭氧浓度软测量模型进行了实验验证,验证结果表明臭氧浓度软仪表能够很好地实现臭氧浓度的实时在线测量,且具有响应速度快、精度高、适应性好及泛化能力强等优点。
(5)降低臭氧生产的运行成本一直是臭氧技术发展的关键问题之一。本文以单位臭氧生产成本最低为优化目标,基于臭氧生产过程模型获得臭氧生产和应用的最优浓度点,采用优化控制策略对臭氧生产中的各控制量的设定值进行优化,根据工况条件的变化动态地设定各个控制环节的设定值,使臭氧生产过程运行在最优浓度点附近,从而有效地降低臭氧生产的运行成本。
综上,本文对臭氧生产工艺过程智能测控系统进行了比较深入、全面的研究和探讨。实际应用表明：该智能测控系统的设计是成功的,实现了对整个臭氧生产工艺过程的控制和优化,达到了安全、稳定、高效生产的目的。本文的研究也为其他工业生产过程的自动测控系统的研制开发提供了宝贵的设计思路和经验。
Ozone has strong oxidation and sterilization ability. It is widely applied in many fields, such as water and wastewater treatment, food processing, chemical production and medical etc.. With the development of ozone producing technology and the popularization of ozone application, the increasingly higher requirements for the automatic control system of ozone producing system is needed. At present, the measurement and control technology for ozone producing process is outdated and the level of automation is low, so it is anxious for improving the measurement and control system for the ozone producing and application. In this paper, based on analyzing the mechanism of ozone producing process comparatively and deeply, the author proposes intelligent measurement and control system of ozone producing process, and has put it into use successfully. The content of the research in this paper is as follows:
(1) Based on the analysis of the mechanism of ozone producing process and the technological characteristics, the project of the integrated intelligent measurement and control system of ozone producing process are proposed. In this project, the 3-layer distributed control system is presented by assembling industrial PC, PC 104 and microcontroller, and realizes the intelligent measurement and control of ozone producing process. The results of application illustrate the effectiveness of the project.
(2) The pivotal technological parameters needed to be measured and controlled in ozone producing process are more and located in a large area. And these are various pipelines, the high voltage and low voltage. So it is hard to be connected by wire. In this paper, the wireless sensor network is used to design the intelligent measurement and control system. And combining the practical application, the configuration, low power and the reliability of wireless sensor network are studied.
(3) The three key measurement and control loops of the temperature of gas, the flux of gas and power are designed. A sort of photoelectric measurement equipment for the flux of gas is designed based on the float meter and it is validated in practice. The measurement and control of power in ozone producing process are studied. And the measurement method and control strategy for power obtain a preferable result in practice.
(4) As the production quality index and the control target, the ozone concentration is difficult to real-time measurement on line in ozone producing process at present. In this paper, based on the ozone producing mechanism, the technological parameters which can influence the ozone concentration directly in ozone producing process are studied. Six variables are chosen as the secondary variables and a soft-sensor model of ozone concentration based on RBF neural network is build up. And the soft-sensor model is trained, calibrated and evaluated. The ozone concentration analyzer of EG-2001B is used to verify the precision of the soft-sensor model and the experimental results demonstrated that the soft-sensor model can implement the real-time measurement of ozone concentration on line and has the advantages of fast response time, high precision, good adaptability and strong generalization ability.
(5) One of the key questions in ozone technology development is to reduce the running cost of ozone producing process. In this paper, the unit mass ozone producing cost is chosen as the optimal target, and an optimizing control strategy is introduced to optimize the setting value of the control variables of ozone producing process based on the optimum ozone concentration of ozone production and application obtained by the model of ozone producing process. According to the optimal strategy, the setting values of the control loops are obtained dynamically followed the industrial conditions, and the ozone producing process can be optimized to run at the optimum concentration point and reduce the running cost effectively.
Above all, the intelligent measurement and control system of ozone producing process is investigated comparatively deeply. The intelligent measurement and control system is applied to realize the ozone producing process control and optimization and the practical application demonstrates that the intelligent measurement and control system is successful. All works provide valuable method and experience for other industrial processes.
(1)在分析臭氧生产过程机理特性及工艺流程的基础上,提出了臭氧生产工艺过程智能测控系统的整体设计方案,采用工控机+嵌入式工控机PC104+单片机组成三层分布式控制系统,实现了臭氧生产过程各关键工艺参数的测控及臭氧生产过程的优化控制,应用结果验证了本设计方案的有效性。
(2)臭氧生产过程中需要监控的工艺参数较多、分布较广,且各种管路交叉,强弱电结合,难以采用有线连接方式,因此本文采用无线传感器网络构建整个智能测控系统,并结合具体应用,对无线传感器网络结构、低功耗及可靠性等方面进行了研究。
(3)设计了气体温度、气体流量以及功率三个关键测控回路,在气体流量测控回路中设计了一种基于浮子流量计的光电式气体流量测量装置,并在实践中对其进行了验证；在功率测控回路中对臭氧生产工艺过程中的功率测量和控制进行了研究,所应用的功率测量方法和控制策略在实践中取得了良好的效果。
(4)在臭氧生产过程中,作为质量指标和控制目标的臭氧浓度目前很难对其进行在线实时测量。本文结合臭氧生产机理,研究了生产工艺过程中对臭氧浓度有直接影响的工艺参量,选择其中六个为辅助变量,应用RBF神经网络建立了臭氧浓度软测量模型,对模型进行了训练、校正以及评价。采用臭氧浓度分析测试仪EG-2001B对臭氧浓度软测量模型进行了实验验证,验证结果表明臭氧浓度软仪表能够很好地实现臭氧浓度的实时在线测量,且具有响应速度快、精度高、适应性好及泛化能力强等优点。
(5)降低臭氧生产的运行成本一直是臭氧技术发展的关键问题之一。本文以单位臭氧生产成本最低为优化目标,基于臭氧生产过程模型获得臭氧生产和应用的最优浓度点,采用优化控制策略对臭氧生产中的各控制量的设定值进行优化,根据工况条件的变化动态地设定各个控制环节的设定值,使臭氧生产过程运行在最优浓度点附近,从而有效地降低臭氧生产的运行成本。
综上,本文对臭氧生产工艺过程智能测控系统进行了比较深入、全面的研究和探讨。实际应用表明：该智能测控系统的设计是成功的,实现了对整个臭氧生产工艺过程的控制和优化,达到了安全、稳定、高效生产的目的。本文的研究也为其他工业生产过程的自动测控系统的研制开发提供了宝贵的设计思路和经验。
Ozone has strong oxidation and sterilization ability. It is widely applied in many fields, such as water and wastewater treatment, food processing, chemical production and medical etc.. With the development of ozone producing technology and the popularization of ozone application, the increasingly higher requirements for the automatic control system of ozone producing system is needed. At present, the measurement and control technology for ozone producing process is outdated and the level of automation is low, so it is anxious for improving the measurement and control system for the ozone producing and application. In this paper, based on analyzing the mechanism of ozone producing process comparatively and deeply, the author proposes intelligent measurement and control system of ozone producing process, and has put it into use successfully. The content of the research in this paper is as follows:
(1) Based on the analysis of the mechanism of ozone producing process and the technological characteristics, the project of the integrated intelligent measurement and control system of ozone producing process are proposed. In this project, the 3-layer distributed control system is presented by assembling industrial PC, PC 104 and microcontroller, and realizes the intelligent measurement and control of ozone producing process. The results of application illustrate the effectiveness of the project.
(2) The pivotal technological parameters needed to be measured and controlled in ozone producing process are more and located in a large area. And these are various pipelines, the high voltage and low voltage. So it is hard to be connected by wire. In this paper, the wireless sensor network is used to design the intelligent measurement and control system. And combining the practical application, the configuration, low power and the reliability of wireless sensor network are studied.
(3) The three key measurement and control loops of the temperature of gas, the flux of gas and power are designed. A sort of photoelectric measurement equipment for the flux of gas is designed based on the float meter and it is validated in practice. The measurement and control of power in ozone producing process are studied. And the measurement method and control strategy for power obtain a preferable result in practice.
(4) As the production quality index and the control target, the ozone concentration is difficult to real-time measurement on line in ozone producing process at present. In this paper, based on the ozone producing mechanism, the technological parameters which can influence the ozone concentration directly in ozone producing process are studied. Six variables are chosen as the secondary variables and a soft-sensor model of ozone concentration based on RBF neural network is build up. And the soft-sensor model is trained, calibrated and evaluated. The ozone concentration analyzer of EG-2001B is used to verify the precision of the soft-sensor model and the experimental results demonstrated that the soft-sensor model can implement the real-time measurement of ozone concentration on line and has the advantages of fast response time, high precision, good adaptability and strong generalization ability.
(5) One of the key questions in ozone technology development is to reduce the running cost of ozone producing process. In this paper, the unit mass ozone producing cost is chosen as the optimal target, and an optimizing control strategy is introduced to optimize the setting value of the control variables of ozone producing process based on the optimum ozone concentration of ozone production and application obtained by the model of ozone producing process. According to the optimal strategy, the setting values of the control loops are obtained dynamically followed the industrial conditions, and the ozone producing process can be optimized to run at the optimum concentration point and reduce the running cost effectively.
Above all, the intelligent measurement and control system of ozone producing process is investigated comparatively deeply. The intelligent measurement and control system is applied to realize the ozone producing process control and optimization and the practical application demonstrates that the intelligent measurement and control system is successful. All works provide valuable method and experience for other industrial processes.
引文
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