数据驱动的设备时变可靠度评价及故障预测

针对化工设备的可靠性随时间或载荷作用次数等寿命指标发生变化这一问题,在传统可靠性模型基础上构造了一种考虑设备运行影响因素的可靠度评价方法,可处理化工设备的运行工况、载荷、应力和强度等参数随时间变化的可靠性计算问题。该方法首先利用传统威布尔分布可靠性模型对设备进行可靠性评价,计算设备的可靠性参数;采用灰色关联分析选择影响威布尔分布模型参数的主要因素,然后应用响应面法,在基于威布尔分布的失效速率模型中引入设备运行的影响因素,建立多变量故障失效速率模型,在此基础上对设备进行时变可靠度评价,并对设备进行简单的故障预测。最后将该方法应用于某化工设备,对其进行时变可靠度评价和设备故障时间预测,验证了该方法的有效性。     

Steady State Permeate Flux Estimation in Cross-Flow Ultrafiltration of Protein Solution

In the membrane separation process, the cross-flow configuration in which the fluid flows parallel to the membrane is widely utilized. Due to the shear stress exerted by the tangential feed flow, the accumulation of the retained species in the membrane is reduced, and the nearly steady state operation can be attained. The determination of steady state permeate flux is significant in the design and optimization problem. Several mechanisms of transport phenomena have been proposed to estimate the steady state permeate flux such as concentration polarization and Brownian diffusion, shear-induced diffusion, inertial lift, and surface transport. Another approach is using dimensional analysis to give the correlation equation with the operating condition instead of a deep focus on mechanism. In this study, we apply the model proposed in our previous study to predict the steady state permeate flux from the experimental data. After that, a new method using dimensional analysis is also developed to predict the steady state permeate flux from the operating conditions such as the trans-membrane pressure, the feed flow rate, and the feed volume fraction in a wide range. The correlation equation provides a good estimation of the experimental results.     

Steady-state multiplicity analysis of two-stage-riser catalytic pyrolysis processes

New two-stage-riser fluidized catalytic pyrolysis (TSRFCP) for maximizing propylene yield technology is considered as an efficient route to moderate the propylene demand/supply gap and to lower the propylene price. The possibility of existence of complex nonlinear behavior associated with the TSRFCP process puts limitations on the supervision of this system. Based on the developed and validated model for the TSRFCP process, this paper focuses on the elucidation of multiple steady states and relevant (in) stability characteristic over a wide range of operating condition. First, graphic analysis of heat generation/removal curves demonstrates that the TSRFCP process has at least one steady state and a maximum of three output steady states under the considered operating conditions and uncertainties such as cooling water flow rates and Conradson carbon residue. Then, operating maps revealing topologies between important input and output variables can disclose detailed nonlinear behavior (input/output multiplicity). Moreover, depending on the choice of the input variable and the relevant operating/design condition, input multiplicity may exist. In short, these results can guide the succeeding control structure selection for realistic TSRFCP processes.     

高纯度精馏过程的集成控制与在线优化策略

For high-purity distillation processes, it is difficult to achieve a good direct product quality control using traditional pro-portional-integral-differential (PID) control or multivariable predictive control technique due to some difficulties, such as long re-sponse time, many un-measurable disturbances, and the reliability and precision issues of product quality soft-sensors. In this paper, based on the first principle analysis and dynamic simulation of a distillation process, a new predictive control scheme is proposed by using the split ratio of distillate flow rate to that of bottoms as an essential controlled variable. Correspondingly, a new strategy with integrated control and on-line optimization is developed, which consists of model predictive control of the split ratio, surrogate model based on radial basis function neural network for optimization, and modified differential evolution optimization algorithm. With the strategy, the process achieves its steady state quickly, so more profit can be obtained. The proposed strategy has been successfully applied to a gas separation plant for more than three years, which shows that the strategy is feasible and effective.     

Globally stable control systems for processes with input multiplicities

A nonlinear process with input multiplicity has two or more input values for a given output at the steady state, and the process steady state gain changes its sign as the operating point changes. A control system with integral action will be unstable when both signs of the process gain and the controller integral gain are different, and its stability region will be limited to the boundary where the process steady state gain is zero. Unlike processes with output multiplicities, feedback controllers cannot be used to correct the sign changes of process gain. To remove such stability limitation, a simple control system with parallel compensator is proposed. The parallel compensator can be easily designed based on the process steady state gain information and tuned in the field. Using the two time scale method, the stability of proposed control systems for processes with input multiplicities can be checked.     

Dynamic modelling and performance optimization of an extractive fermentation

A dynamic model for a continuous extractive fermentation process is proposed. Using this model and the Iterative Dynamic Programming algorithm, optimal operating profiles are identified for process start-up from conventional fermentation operation. Under the optimal operating profile, profit during the transient operation accumulates at a rate approaching that of steady state operation. A sensitivity analysis investigating the effect of economic variations on the overall profit function shows that optimization of manipulated variable profiles primarily reduces the impact of substrate cost, so that the profit function approaches a linear function of the product value.     

An assessment of dynamic operability measures

By using the local condition numbers, which are also measures of the conditioning of a nonlinear mapping of both transfer function and state space matrices, we investigate the way in which the system controllability varies across the anticipated range of operating conditions for two common process systems with nonlinearities. Linear techniques can lead to erroneous conclusions, shown here for a CSTR. It is also shown that the condition of the scaled state space matrix is not a reliable indication of the controllability of the system. The dynamic characteristics of a CSTR and a heat exchanger are investigated by obtaining the sensitivity indices from the model linearized at several steady states over a range of frequencies.     

固体发动机失效率优化模型的建立及应用

通过对固体火箭发动机贮存失效规律分析,将指数分布和威布尔分布结合,建立了一种新的失效率优化模型,并对实际贮存发动机的寿命可靠性进行了计算。计算结果表明,用失效率优化模型计算的寿命较好地反映了发动机实际贮存的真实情况,从而为贮存发动机寿命可靠性计算提供了一种新的实用计算方法。     

鲁棒PPLS模型及其在过程监控中的应用

概率偏最小二乘（PPLS）模型建立的条件是主元和误差都服从高斯分布,但是高斯分布的期望和方差容易受到离群点的影响,导致模型的鲁棒性较差。针对PPLS模型的不足,提出一种鲁棒概率偏最小二乘（RPPLS）方法,用拖尾更宽的T分布代替高斯分布,通过调整自由度参数,使模型对含离群点数据的拟合效果更好。更进一步,将RPPLS引入过程监控中,提出GT²和GSPE两个监控指标,分别监控过程的受控状态以及模型关系的变化。PPLS和RPPLS在TE过程监控的应用结果表明RPPLS不仅能更准确检测故障的产生,而且能更有效降低故障的漏报率。     

Fundamentals of plasticating extrusion. I. A theoretical model for melting

A steady state model for melting in a screw extruder has been developed based on the assumption that a stable solid bed of polymer granules is melted by heat that is conducted from a hot barrel and heat that is generated by viscous dissipation in the film that separates the solid bed and the surface of the barrel. The solid bed gradually decreases in width, as it proceeds in the channel, until it disappears at which point the melting is terminated. The model predicts the solid bed width profile and the required length of melting in terms of physical properties, operating conditions, and geometry of the screw. The model has been tested based on experimental data.     

Optimization of circulating cooling water systems based on chance constrained programming

Recent research on deterministic methods for circulating cooling water systems optimization has been well developed. However, the actual operating conditions of the system are mostly variable, so the system obtained under deterministic conditions may not be stable and economical. This paper studies the optimization of circulating cooling water systems under uncertain circumstance. To improve the reliability of the system and reduce the water and energy consumption, the influence of different uncertain parameters is taken into consideration. The chance constrained programming method is used to build a model under uncertain conditions, where the confidence level indicates the degree of constraint violation. Probability distribution functions are used to describe the form of uncertain parameters. The objective is to minimize the total cost and obtain the optimal cooling network configuration simultaneously. An algorithm based on Monte Carlo method is proposed, and GAMS software is used to solve the mixed integer nonlinear programming model. A case is optimized to verify the validity of the model. Compared with the deterministic optimization method, the results show that when considering the different types of uncertain parameters, a system with better economy and reliability can be obtained (total cost can be reduced at least 2%).     

Concurrent monitoring of operating condition deviations and process dynamics anomalies with slow feature analysis

Latent variable (LV) models have been widely used in multivariate statistical process monitoring. However, whatever deviation from nominal operating condition is detected, an alarm is triggered based on classical monitoring methods. Therefore, they fail to distinguish real faults incurring dynamics anomalies from normal deviations in operating conditions. A new process monitoring strategy based on slow feature analysis (SFA) is proposed for the concurrent monitoring of operating point deviations and process dynamics anomalies. Slow features as LVs are developed to describe slowly varying dynamics, yielding improved physical interpretation. In addition to classical statistics for monitoring deviation from design conditions, two novel indices are proposed to detect anomalies in process dynamics through the slowness of LVs. The proposed approach can distinguish whether the changes in operating conditions are normal or real faults occur. Two case studies show the validity of the SFA‐based process monitoring approach. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3666–3682, 2015     

Modelling of a clinker rotary kiln using operating functions concept

Modelling and parameter identification of complex dynamic systems/processes is one of the main challenging problems in control engineering. An example of such a process is clinker rotary kiln (CRK) in cement industry. In the prevailing models independently of which structure is used to describe the kiln's dynamics and the identification algorithm, parameters are assumed to be centralised and constant while the CRK is well known as a distributed parameter system with a strongly varying dynamic through time. In this work, the kiln's dynamic is described in the form of a state‐space representation with three state variables using a system of partial differential equations (PDE). The structure is chosen so that it can easily be embedded in classical state‐space control algorithms. The parameters of the PDE system are called operating functions since their numerical values vary with respect to different operating conditions of the kiln, to their position in the kiln, and through time. A phenomenological approach is also proposed in this paper to identify the operating functions for a given steady‐state operation of the kiln. The model is then used to perform a semi‐dynamic simulation of the process through manipulating main process variables.     

Optimization of a reaction and heat exchange system with recycle

Data obtained from an operating plant involving a gas phase reaction and heat exchange system has been correlated using a multiple regression program. The results of the regression analysis have been incorporated in a mathematical model of the plant which can determine the steady state optimum conditions for the major process variables. This approach to optimization has been successfully employed on an existing vinyl chloride plant where significant gains in production have been obtained, and a more thorough understanding of process variables has been acquired.     

AN ALGORITHM FOR SUPERVISORY MULTIVARIABLE CONSTRAINED OPTIMIZATION OF INDUSTRIAL PROCESSES

An algorithm is presented for supervisory optimization of industrial processes that integrates the minimization of operating costs with process operating constraints. It is assumed that the supervisory algorithm manipulates the set points of a lower-level control system and that the set points are updated at long enough intervals of time so that the process reaches steady state between set point updates. This steady state assumption greatly simplifies the algorithm computations and, more importantly, significantly reduces the effort required for process identification. This article develops the algorithm and then presents results from its application to a simulated distillation train. The simulation parallels an application of the algorithm to an actual industrial train on a commercial distributed control system.     

Finite-Element Analysis of Ceramic Multilayer Capacitors: Failure Probability Caused by Wave Soldering and Bending Loads

A two-dimensional numerical model that predicts the reliability of multilayer capacitors (MLCs) during soldering and bending is presented. The Weibull parameters used in the model are based on measurements of soldered MLC devices. The preheating and soldering temperatures have a dominant impact on the failure probability, in comparison to the thickness of the nickel layer, the soft solder geometry, and the number of inner electrodes. Comparison of calculated and measured reliability of three MLC sizes leads to the assumption that residual stresses due to the manufacturing process or size-related microstructure are important.     

A pseudo‐steady state model of the kinetics of laccase‐catalysed oxidation of aqueous phenol

A model has been developed to describe the kinetics of the oxidation of phenol by oxygen using laccase (EC 1.10.3.2) from Trametes versicolor as catalyst. The model incorporates an assumption, referred to as the pseudo‐steady state assumption, that at any instant during the reaction the enzyme achieves an approximate steady state distribution of its various forms around the catalytic cycle. The model was validated by comparing model predictions with experimental observations of phenol transformation and oxygen consumption over time. Excellent agreement was found between experimental data and model predictions. The pseudo‐steady state assumption had the advantage of reducing the complexity of the model equations to be solved while simultaneously maintaining the model's predictive ability. The pseudo‐steady state model was further simplified in accordance with specific initial conditions to provide a simplified method for the estimation of the model constants. Copyright © 2006 Society of Chemical Industry     

气相卧式搅拌釜聚丙烯反应器的模拟及多稳态分析

聚合过程是强放热的非线性过程,这类过程一般存在多稳态现象,且不同的稳态具有不同的局部稳定性.采用气相卧式搅拌釜聚丙烯反应器的Innovene工艺是目前生产聚丙烯最先进的工艺之一.本文开展了该反应器的稳态模拟与多稳态分析研究,对平稳生产、新牌号开发都有着重要的意义.利用Polymer Plus建立了更符合实际且适用于稳定性研究的气相卧式搅拌釜聚丙烯反应器非等温模型,以GPC数据进行聚丙烯反应网络的参数反演.通过灵敏度分析求解系统的多稳态解,通过推理分析的方式判断各个反应区域的稳定性,解决了该问题多稳态研究中的稳定性判断问题,并通过稳定性分析,从本质安全角度出发识别出适于操作的稳态点范围.     

基于图像空间结构统计分布的浮选泡沫状态识别

通过泡沫图像统计建模,实现了基于图像空间结构感知的浮选泡沫状态自动识别与客观评价。首先,采用Weibull分布建立了泡沫图像各方向边缘响应结构的统计分布模型,有效获取了泡沫图像空间结构的统计分布细节;然后,通过统计学习获得各典型工况状态下的泡沫图像边缘响应统计分布的混合高斯（MoG）模型;最后,通过简单的贝叶斯推理推断出测试泡沫图像对应的工况状态。结果表明：所提出的方法因有效获取了与浮选生产性能直接相关的泡沫空间结构的统计分布特征,可以实时监视泡沫空间结构的变化情况,泡沫生产状态识别准确率高。     

An experimental study of steady-state multiplicity features of two parallel catalytic reactions

A study of the multiplicity features of a single catalytic pellet on which either ethane, carbon monoxide or both reactants were oxidized revealed several new features such as: four different stable states during the co-oxidation of both reactants and three states during the oxidation of carbon monoxide. Very intricate bifurcation diagrams, which describe the dependence of a state variable on an operating condition, were found.It was shown that the experimental finding of a cross-section of the bifurcation set is the rational approach of studying the multiplicity features of systems characterized by a large number of parameters and for which no exact mathematical model is available. Recent theoretical results provide useful guidance in selecting the operating conditions so that all the possible multiplicity features are found. These theoretical results may be used to place constraints on the functional form of any proposed reaction rate expression.