scholarly journals A Dynamic Model Incorporated with Delay Estimation and Variable Selection for Control of SCR De-NOx Process

Catalysts ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1364
Author(s):  
Ze Dong ◽  
Ling Li ◽  
Laiqing Yan ◽  
Ming Sun ◽  
Jinsong Li
Keyword(s):  
Variable Selection ◽  
Nearest Neighbor ◽  
Catalytic Reduction ◽  
Nox Emission ◽  
Delay Estimation ◽  
Nox Emissions ◽  
Emission Model ◽  
K Nearest Neighbor ◽  
Bidirectional Search ◽  
Selection For

In order to control NH3 injection for the selective catalytic reduction of nitrogen oxide (NOx) denitration (SCR de-NOx) process, a model that can accurately and quickly predict outlet NOx emissions is required. This paper presents a dynamic kernel partial least squares (KPLS) model incorporated with delay estimation and variable selection for outlet NOx emission and investigated control strategy for NH3 injection. First, k-nearest neighbor mutual information (KNN_MI) was used for delay estimation, and the effect of historical data lengths on KNN_MI was taken into account. Bidirectional search based on the change rate of KNN_MI (KNN_MI_CR) was used for variable selection. Delay–time difference update algorithm and feedback correction strategy were proposed. Second, the NH3 injection compensator (NIC) and the outlet NOx emission model constituted a correction controller. Then, its output and the output of the existing controller are added up to suitable NH3 injection. Finally, the KNN_MI_CR method was compared with different algorithms by benchmark dataset. The field data results showed that the KNN_MI_CR method could improve model accuracy for reconstructed samples. The final model can predict outlet NOx emissions in different operating states accurately. The control result not only meets the NOx emissions standard (50 mg/m3) but also keeps high de-NOx efficiency (80%). NH3 injection and NH3 escape are reduced by 11% and 39%.

FASICA Framework: Service Selection Using K-d Tree and Cache

2015 ◽  
Vol 25 (05) ◽  
pp. 807-828
Author(s):  
Aimrudee Jongtaveesataporn ◽  
Shingo Takada
Keyword(s):  
Nearest Neighbor ◽  
Service Oriented Architecture ◽  
Service Selection ◽  
K Nearest Neighbor ◽  
Search Results ◽  
Key Points ◽  
Service Oriented ◽  
Selection For ◽  
Selection Of

The selection of services is a key part of Service Oriented Architecture (SOA). Services are primarily selected based on function, but Quality of Service (QoS) is an important factor when choosing among several services with the same function. But current service selection approaches often takes time to unnecessarily recompute requests. Furthermore, if the same service is chosen as having the "best" QoS for multiple selections, this may result in that service having too much load. We thus propose the FASICA (FAst service selection for SImilar constraints with CAche) Framework which chooses a service with satisfactory QoS as quickly as possible. The key points are (1) to use a cache which stores previous search results, (2) to use K-Nearest Neighbor (K-NN) algorithm with K-d tree when a satisfactory service does not exist in the cache, and (3) to distribute the service request according to a distribution policy. Results of simulations show that our framework can rapidly select a service compared to a conventional approach.

Feature Selection for Helicopter Swashplate Bearing Fault Diagnosis

2017 ◽  
Author(s):  
Yong Wang ◽  
Lin Li
Keyword(s):  
Nearest Neighbor ◽  
Ball Bearing ◽  
K Nearest Neighbor ◽  
Time Frequency ◽  
Bearing Fault Diagnosis ◽  
Feature Extraction And Selection ◽  
Frequency Domains ◽  
Selection For ◽  
Selection Of

This paper provides a case study of diagnosing helicopter swashplate ball bearing faults using vibration signals. We develop and apply feature extraction and selection techniques in the time, frequency, and joint time-frequency domains to differentiate six types of swashplate bearing conditions: low-time, to-be-overhauled, corroded, cage-popping, spalled, and case-overlapping. With proper selection of the features, it is shown that even the simple k-nearest neighbor (k-NN) algorithm is able to correctly identify these six types of conditions on the tested data. The developed method is useful for helicopter swashplate condition monitoring and maintenance scheduling. It is also helpful for testing the manufactured swashplate ball bearings for quality control purposes.

scholarly journals An Experimentally Verified NOx Emission Model for Gas Turbine Combustors

1975 ◽  
Author(s):  
W. S. Y. Hung
Keyword(s):  
Gas Turbine ◽  
Analytical Model ◽  
Field Data ◽  
Experimental Testing ◽  
A Priori ◽  
Water Injection ◽  
Nox Emission ◽  
Nox Emissions ◽  
Emission Model ◽  
Gas Turbine Combustors

An analytical model has been developed to simulate the thermal NOx emission processes in various gas turbine combustors for a variety of fuels. The NOx emissions predicted by the model are in excellent agreement with available laboratory and field data. Its capability to simulate the water injection process accurately has been demonstrated previously. Comprehensive understanding of the NOx emission processes in gas turbine combustors has been gained through the current analytical studies. NOx emissions as influenced by ambient humidity, changes in combustor geometry, type of fuel used and changes in operating parameters can now be evaluated quantitatively through a priori prediction and have been verified by available laboratory and field data. The analytical model has also been demonstrated to be a powerful guidance tool in directing the experimental testing program in an effort to reduce NOx emissions from gas turbine combustors.

Sign in / Sign up

Export Citation Format

Share Document