Search

Monitoring health status of equipment is very important for risk avoiding and maintenance decision making, especially for complex safety-critical systems. Most of existing fault diagnosis systems can only generate the state of a specific system level. Models should be developed to assess the health states of the equipment in different hierarchical levels. In this paper, a model based on Bayesian networks is proposed, where determined fault diagnosis result and the fault diagnosis result with uncertainty can all be used. The model structure, how to set uncertain diagnosis result by virtual nodes and how to represent multi-states are formulated and discussed in detail. An application example on a diesel engine combustion system is given, which shows that the method proposed in this paper can realize hierarchical health assessment, including the scenarios that the diagnosis result is uncertain.

In this paper, a waste heat recovery comparison of oxygen and air combustion in a glass melting furnace has been done by using the net present value method. Results show that the optimal numbers of transfer unit are existed both in oxy-fuel and air-fuel combustion systems, which have the same value, to make them get the best economic benefit. At the highest net present value with the number of transfer unit, the oxy-fuel combustion system has less economic benefit but is friendly to the environment than the air-fuel combustion system.

How to operate a BFG/coal co-firing boiler in high efficiency is challenging for a gas/solid multi-fuel combustion system. Taking operation data from a real boiler, this study proposes an operation optimization strategy of BFG/coal co-firing boiler based on deep learning. Firstly, the thermal efficiency model is constructed based on deep learning with all the actual sampling data, which outperform the other modeling methods. Then, the high efficiency data being selected as labeled data, a deep learning-based model of air flow is constructed. It needs to be emphasized that, to take full advantage of all available information and improve the model accuracy, all the labeled and unlabeled data are utilized in auto-coder learning of the air flow modeling. Finally, the constructed air flow model is used for the operation optimization and the thermal efficiency model is used to evaluate the level efficiency improvement. The high accuracy of the proposed modeling approaches makes the implementation of the operation optimization strategy readily practicable.

As a heating equipment, gas boiler is widely used in daily production and life. Considering the security and stability of the control system of gas boiler, this article design a combustion controller based on ARM9. The μCOSII as a real-time operating system is transplanted into nuclear of MCU. For gas boiler is a non-linear, high inertia multivariate and multidisturbance etc, this paper adopts the active disturbance rejection control (ADRC) method. For μCOSII can divide the system into multiple tasks, it can improve security and stability of the system effectively. Besides, ADRC, as a advance control method, can improve the efficiency of system.

According to the combustion control system of industry boiler with large time delay and nonlinear, a kind of combustion system of industry boiler based on PSO-PID neural network controller design method is proposed in this paper. The boiler model is given and the comparison is made between PSO-PID neural network controller and the traditional PID controller. The simulation results indicate that the new controller has good performance of strong robustness and disturbance resisting ability than traditional PID controller.

This paper proposes the application of multi-objective model predictive control to achieve a dynamic optimization of boiler combustion system. The utopia point of the multi-objective model predictive control system is firstly calculated, and the optimal control sequence is then determined by finding the trade-off solution closed to the utopia point. By using this approach, the arbitrary weighting functions, which are generally used in the multi-objective model predictive control approach are not necessary, and moreover, the procedures of pareto front calculation and final solution decision in the conventional multi-objective optimization can be avoided. Simulation results demonstrate the effectiveness of the proposed multi-objective model predictive control.

Aiming at the problems about the drum pressure of the boiler combustion system has the time varying and time delay characteristics, it's difficult for traditional PID (Proportion Integration Differentiation) control to meet the demands of the control problems, a new control algorithm named ITGC (Intelligent Track Guiding Control) was proposed in this paper. Based on traditional PID control algorithm, the set signal was guided by the transition process and the differentiation signal was improved in the ITGC control algorithm. The practical application shown that when the external load, like the main steam flow, has a great change, the drum pressure can still remain near the set value by the use of the ITGC control algorithm, so as to make the boiler combustion system running stable at the automatic control state. The experimental results presented that the ITGC control algorithm is very suitable for the large inertia system like the boiler combustion system. The ITGC control algorithm can be also promoted into the other field of process industry like the chemical industry and metallurgy industry.

Alternative Fuels are successfully used in the Cement Industry in order to reduce production costs, to preserve fossil fuel resources and to minimize anthropogenic CO2 emissions. For co-combustion with standard equipment in cement plants the waste derived fuels have to be prepared in mechanical fuel preparation plants. The fuel must be sized to less than 25/80 mm so that it is entrained in the gas stream or flame and totally burns out within the short retention time in the calciner or in the kiln. To increase the fuel input especially of coarse alternative fuels e.g. tires chips with dimension up to 150 mm, an adapted fuel handling and dosing system is necessary. Alternatively to the direct dosing into the calciner, coarser fuels with dimension of up to 300 mm can be treated in a specialized combustion system that is connected to a standard calciner system. The paper gives insight into the introduction of tire chips to a calciner in Morocco and the arrangement of the first installation of the “Step Combustor” system in Germany.

Based on localization of single synthetic intelligent fault diagnosis method that applies to construction machinery, Traits of neural network theory and fuzzy Logic method are discussed. A method of the further fusion diagnosis using neural network and fuzzy measurement is proposed. The method uses observational data, integrates diagnosis methods with subjective and impersonal information, which can identify fault more comprehensive and objective, and efficiently improve the fault location capability. This article discusses idea of design, framework and functions, steps of diagnosis. Furthermore, it is proved that the fault diagnosis system is feasible and superior through a real example of combustion system of a certain diesel engine.

The combustion control of circulating fluidized bed boiler (CFBB) is an important but difficult link of its control system. An algorithm is introduced here, in which parameters of the PID controller are optimized online by BP neural networks and the programming steps are described. The mathematical models of combustion system of CFBB are analyzed. And both the simulation of conventional PID and BP-PID control algorithm are carried out in the combustion system of CFBB, it proved that this algorithm is valid and feasible.

Experiments were conducted to investigate dynamic characteristic of a novel reciprocal porous media combustion system with heat recirculation. Dynamic temperatures in different position of system and distribution in periods were analyzed in details, in addition to dynamic emissions. The results showed that temperatures in different position of system vary periodically while the system operated steadily and periodically. Phase difference of temperature dynamic variation is just right 180 degree between two sides of system. Temperature distribution has two temperature peak zones liking an i°Mi± Maximum temperature fluctuation appears in combustion zones of both sides, more near to combustion zone, higher fluctuation is. It also increases with the half period increasing. Combustion emissions are low, and vary periodically as the system operated steadily and periodically. A fluctuation of emissions lies during the switching, especially for the CO and NOx.

Double swirl combustion system, which is abbreviated to DSCS, is a new combustion system. For its noticeable effect on improving the fuel-air mixing process and reducing raw emissions, it has been accepted and applied widely. Double swirl combustion chamber, as one of the most important components of the DSCS, plays an important role to affect the fuel-air mixing processes and the fuel-air mixture quality which controls the combustion processes. Hence, make the further researches on the DS combustion chamber and design an optimized DS combustion chamber is very necessary and important. However, there has no reports about the researches on the configuration parameters of DS chamber have been published. Therefore, the authors make the research on parametric design of DS combustion chamber, to find out the main configuration parameters of DS chamber, and then explore how those configuration parameters affect the performance of DS chamber. In this paper, the authors make analysis on the configuration structure detailedly, and determine the crucial configuration parameters of DS chamber, and then, the authors make series of simulation researches on those parameters to reveal their effect rules, and indicate the design direction of DS chamber based on those results.

Wireless surface acoustic wave sensors are attractive in harsh environment applications, for example for temperature and gas sensing in combustion system exhausts. Pulse-mode sensing separates the stimulus and response signals temporally, increasing the allowable separation between antennas. Previous researchers have typically used custom electronics for extraction of the phase shift between two reflections. We describe a flexible laboratory system for accurate measurements of the phase shift, and demonstrate its application. We report on wired and wireless temperature measurements up to 900 and 700 C, respectively using langasite surface acoustic wave devices.

The fuel lean reburning system is considered for reducing NOX emission by using numerical approach. Liquefied Petroleum Gas (LPG) is used as the main and reburn fuel. The fuel lean reburning system has to operate in a fuel lean condition in order to achieve complete combustion, since additional air is not used anymore in fuel lean reburn technology. The goal of this work is to obtain the most optimal combustion system by employing the fuel lean reburning system to reduce pollutions. Furthermore, there are very few studies that have focused on how the reburning process is affected by changes in the flow field that are induced by combustion. It is important to study the effect of the combustion condition on the reburning process in order to control fuel lean reburning. The results show that the fuel lean reburning method leads to 45% NOX reduction by using 0.13 of the reburn fuel fraction and by achieving complete combustion without any additional oxidizer. Furthermore, the importance of the recirculation flow into the furnace region is verified by the measuring and predicting methods.

In order to achieve energy saving and environmental protection, indicators of boiler must be controlled within an appropriate range. For 35T / H boiler of a winery factory, a set of intelligent control system is designed; the control model is established and solved through an advanced genetic algorithm to realize intelligent control of the system. The application results show that the system has perfect functions, energy-saving effect obviously and environment requirements friendly.

In order to achieve energy saving and environmental protection requirements, indicators of industrial boiler must be controlled within an appropriate range. For a winery 35T / H boilers, after the establishment of mathematical model and solving, the implementation method is designed and then PLC is used to realize the intelligent control of system. After field application, the system achieves the design purpose, realizes perfect function and obvious energy-saving effect, but also to reach environmental requirements.

RGD\∂VEXVLQHVVHQYLURQPHQWIRUWKHF HPHQWSURGXFHUVLVEHFRPL QJPRUHFKDOOHQJLQJ�� 5LVLQJ� production costs and environmental regulations are only two of the main limiting factors. One proven solution is the use of alternative fuels, whereby especially the influence of such fuels to the production-process and pyro-process needs to be evaluated. This is very important in order to achieve the goal of a highly efficient combustion of alternative fuel with a minimal environmental impact. Starting with sampling and analysis of the fuels, proper pyro-process investigation often indicates some necessary modifications of the existing equipment to avoid, or at least minimize bottlenecks. The data from the pyro-process investigation is the basis for the design of the alternative fuel preparation plant. Due to the development of modular preparation systems, high flexibility for different requirements can be attained. Dosing and combustion of the alternative fuel are an equally important factor. Unique feeding systems to the various areas of the calciner, including feeding to the tertiary air duct, and proper design of the combustion system ensure to reach the required goals. The potential of fuel cost reduction through alternative fuel substitution depends on many different parameters and have to be considered case-by-case.

The furnace combustion system of circulating fluidized bed boiler (CFBB) must ensure the steam pressure as a constant via controlling the coal quantity and wind flow. Another important role is to avoid the temperature varying excessively which will result in the high temperature agglomeration or low temperature agglomeration in boiler. Based on the model and characteristic analysis of combustion system, this paper presents an override control solution which can satisfy the various control tasks requirement. In this design, the control strategy is selected automatically according to the furnace temperature value. When the temperature is normal, abnormal or unsafe, the conventional control, limiting control or shut-down devices with warning will be triggered respectively. The dynamic control process is simulated on an object model, and the quiver phenomenon that often occurs in override control is analyzed and improved. The simulation result shows that this design can deal with the control task of both steam pressure and the agglomeration at the same time, and ensure the device safety and system continuous. Whatpsilas more, the design is proved to be effective in the Wangjiazhai power plant, mining bureau of Shuichen, Guizhou province.

This paper presents fundamental dust collector principles and how they apply to practical design features included in modern dust collector design. In applications where the dust is combustible, as in coal handling and pulverizing operations, special design features must be incorporated. The recent 2007 edition of the National Fire Protection Association NFPA 85 - Boiler And Combustion System Hazards Code has brought a renewed interest in the safety features of solid fuel pulverizing and firing systems. The updated code requirements for dust collectors used in indirect firing systems is discussed along with requirements for inerting the dust collector in the event of a suspected fire.

A system of two coupled Van der Pol equations is considered as a model for combustion instability. This system is analyzed using the Krylov-Bogoliubov method. The results of the analysis are compared with simulation results and with data obtained from a combustion system.

We have developed a neural-network based on fault diagnostic system for diesel engine combustion system. Grounded on the presented evolutionary algorithm, neural networks automatically adjust the network parameters (connection weights and bias terms). Computer simulation experimental results confirm that the proposed method has high diagnostically accuracy.

It is difficult to have good performance for chain boiler combustion control system due to large delay time, varying coal's quality and steam load. A neural network identification method for nonlinear system's delay time is discussed. Using the abrupt mutation resulted from the training error sum square of the real output and the expected output of the network, this method changes the input sample period of the neural network so that it can discriminate the delay time of the nonlinear model. Combining the discrimination of neural network system with long time delay and the control method based on model reference, it can be applied to control the nonlinear long delay time system with variable parameters or unknown delay time. Simulating with a 10t/h chain boiler model, the results show it has much better advantage of celerity and robustness.

Coal-fired boiler combustion system is a complex multiinput and multioutput plant with strong nonlinear and large time-delay. What's more, it is difficult to establish accurate mathematical model. Because the oxygen content signal has large time-delay and air leak exists, traditional combustion control method that uses oxygen meter to decide air flow is inefficient. Aiming at common problems in the boiler combustion process and based on heat balance principle, this paper adopts the variable oxygen content correction project which sets optimal excess air ratio according to current combustion thermal efficiency and dynamic self-optimizing control which can self-search optimal combustion state. The air/fuel ratio can be adjusted on-line to maintain the optimal combustion condition. Local experiment proves that adopting dynamic self-optimizing control to search optimal air/fuel ratio in combustion process can improve boiler's thermal efficiency and achieve the goal of optimal combustion.

The paper introduced the engineering modular modeling method, and developed process simulation algorithms of CFBB (circulating fluidized bed boiler) combustion system with the support of STAR-90 simulation software. The paper also developed a simulation model of DG450t/h CFBB combustion system. The simulation results showed that the model could correctly reflect property of the working process.

An intelligent algorithm is proposed for an industrial boiler control system. By intelligently reforming a classical PID control algorithm, a better static and dynamic performance is achieved. Based on human knowledge, taking in human experience about the ratio of air to coal consumed, by adjusting and calculating the set value, and through computer self learning, the good performance of overall smooth optimization of combustion efficiency is obtained.

This paper discusses specialized coal and pet-coke-firing, viewing the design of customized combustion systems in order to meet client's specific requirements. This is an approach to combustion subject that is becoming well known and widely accepted all over the world, fitting particularly well when the combustion takes place inside a clinker rotary kiln. The best way to perform this approach is by means of dimensionless indexes, which characterize macroscopically the result of a wide variety of simultaneous chemical reactions, and phenomena of heat, mass and momentum transfer. The most significant dimensionless indexes, which help tremendously in the combustion system design, are presented and discussed.