Application of boiler combustion optimization control technology

2015 ◽  
pp. 719-722
Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-24
Author(s):  
Baoping Zou ◽  
Jianxiu Wang ◽  
Zhanyou Luo ◽  
Lisheng Hu

The construction quality of tunnel smooth blasting is difficult to control and fluctuates greatly. Moreover, the existing technology, which relies on the visual observation, empirical judgment, and artificial control, has difficulty meeting the requirements of tunnel smooth blasting construction quality control. This paper presents the construction principle of a tunnel smooth blasting quality control system, introduces a process quality control technology into quality control of tunnel smooth blasting construction, designs a framework for the tunnel smooth blasting quality control system, and collects control index data based on field investigation, expert consultation, and experimental research. By using the methods of index utilization rate statistics, gray correlation analysis, and principal component analysis, this paper primarily elects and selects the control indexes; establishes the tunnel smooth blasting quality control index system; constructs a comprehensive optimization control model of tunnel smooth blasting quality using back propagation artificial neural network (BP-ANN), Elman neural network (ENN), and adaptive neuro fuzzy inference systems (ANFIS); and studies the tunnel smooth blasting quality control system. The following are the conclusions of this study: (1) This paper presented a method of constructing a tunnel smooth blasting quality control index system and established this system with seven criteria layers, namely, geological conditions, explosive properties, borehole parameters, charge parameters, method of initiation, tunnel parameters, and construction factors, as well as a total of nine indexes. (2) The comprehensive optimization control model of BP-ANN, ANFIS, and ENN for tunnel smooth blasting quality was established. (3) The uniform design method was used to optimize the blasting parameters of the tunnel section, which needs to be controlled, and verify that the construction of these comprehensive optimization control models can change the focus of tunnel smooth blasting quality control from the traditional single index control method into a dynamic, intelligent, pluralistic, and integrated control technology.


2014 ◽  
Vol 587-589 ◽  
pp. 1892-1896
Author(s):  
Yong Xiang Chen ◽  
Xiang Jie Dong ◽  
Jie Sun

This study focuses on Network optimization of Cluster Supply Chain and the reliability of evolution control technology. We adopt the method of dynamic simulation and a series of model construction and statistical validation of Dynamic Control Technology to carry on analytical investigation, to split apart the statistics and the separation degree polymerization of the supply chain network in the evolutionary process, to put forward a kind of practical application requirement which is based on SOA framework and meet the limit of radiation area of industrial cluster and to integrate optimization control technology of intersecting resources in the cluster.


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