scholarly journals On-Line Interpretation and Real-Time Diagnosis of Rocket’s Single Equipment

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Erbao Xu ◽  
Yan Li ◽  
Lining Peng ◽  
Yuxi Li ◽  
Mingshun Yang
Keyword(s):  
Real Time ◽  
Launch Vehicle ◽  
The Real ◽  
Abnormal State ◽  
Proposed Model ◽  
Single Vehicle ◽  
On Line ◽  
Edge Layer ◽  
Time Diagnosis ◽  
Sheer Number

The work state of a launch vehicle is generally interpreted automatically on software. However, the sheer number of target parameters makes it difficult to realize real-time interpretation, and abnormal interpretation result does not necessarily mean that the vehicle is in abnormal state. This paper introduces the edge computing to achieve on-line interpretation and real-time diagnosis of a single launch vehicle. Firstly, the parameters to be interpreted were subjected to thresholding, leaving only those with high interpretation value. Next, the interpretation server layer of the real-time diagnosis model was built based on the attribute and value reduction algorithm of variable precision rough set (VPRS). Moreover, the higher-grade criteria were written in criterion modeling language (CML) and used to interpret the various higher-grade interpretation data pushed by the edge layer in real time. On this basis, the outputs of the edge layer and interpretation server layer were integrated to achieve the real-time diagnosis of single vehicle faults. Finally, the proposed model was proved feasible through the application in a launch vehicle.

The Real-Time Prediction of Surface Roughness Based on Genetic Wavelet Network

2010 ◽  
Vol 102-104 ◽  
pp. 610-614 ◽  
Author(s):  
Jun Chi ◽  
Lian Qing Chen
Keyword(s):  
Surface Roughness ◽  
Real Time ◽  
Back Propagation ◽  
Cutting Parameters ◽  
Wavelet Network ◽  
Back Propagation Algorithm ◽  
The Real ◽  
Roughness Model ◽  
On Line ◽  
Artificial Network

A methodology based on relax-type wavelet network was proposed for predicting surface roughness. After the influencing factors of roughness model were analyzed and the modified wavelet pack algorithm for signal filtering was discussed, the structure of artificial network for prediction was developed. The real-time forecast on line was achieved by the nonlinear mapping and learning mechanism in Elman algorithm based on the vibration acceleration and cutting parameters. The weights in network were optimized using genetic algorithm before back-propagation algorithm to reduce learning time.The validation of this methodology is carried out for turning aluminum and steel in the experiments and its prediction error is measured less than 3%.

Contingent Rule: Information Aesthetic, Performance and Hypermediacy

Leonardo ◽  
2011 ◽  
Vol 44 (3) ◽  
pp. 286-287 ◽  
Author(s):  
Eung Suk Kim ◽  
Joonsung Yoon
Keyword(s):  
Stock Market ◽  
Real Time ◽  
Information Visualization ◽  
Market Data ◽  
The Real ◽  
Proposed Model ◽  
Aesthetic Performance

This paper proposes a model of information aesthetic performance in the context of hypermediacy. It addresses the need to consider the features of performance in recently emerging information visualization artwork. By analyzing an artwork, the real-time stock market data-based Contingent Rule, the authors discuss aesthetic effects of performance as well as information visualization. The proposed model could contribute to a better understanding of information visualization in terms of Jay David Bolter and Richard Grusin's ‘hypermediacy.’ This research provides a new guideline for reviewing information visualization.

Use of a spectrophotometric intracutaneous analysis device in the real-time diagnosis of melanoma

2007 ◽  
Vol 158 (2) ◽  
pp. 420-422 ◽  
Author(s):  
P.N. Hall ◽  
J.E. Hunter ◽  
F.M. Walter ◽  
P. Norris
Keyword(s):  
Real Time ◽  
The Real ◽  
Time Diagnosis

Interactive Two-Stage Rendering Technique of Deformable Part Through Haptic Interface

2011 ◽  
Author(s):  
Zhaoguang Wang ◽  
Georges Dumont
Keyword(s):  
Real Time ◽  
Degrees Of Freedom ◽  
Rigid Body Dynamics ◽  
Haptic Interaction ◽  
Two Stage ◽  
Deformation Spaces ◽  
The Real ◽  
Time Deformation ◽  
Main Challenge ◽  
On Line

Virtual Reality technology has been widely applied in the background of industrial evaluation applications. However, a large majority of these applications are focusing on haptics-based assemblies which mainly deal with rigid-body dynamics. Here we concern the real-time haptic interaction with deformable mock-ups aiming at the industrial design evaluation of mechanical parts. The main challenge of this application is that a tradeoff between the deformation accuracy and the interaction performance has to be achieved. In this paper, we propose a two-stage method for a real-time deformation modelling by combining an off-line pre-computation phase and an on-line deformation interaction phase. The key contributions of this paper lie on two aspects. First, during off-line phase, we propose a mesh analysis method which allows us to pre-compute different deformation spaces by anticipating the evaluation scenarios. Moreover, a real-time switch among different deformation spaces is developed so that the on-line deformation computation can focus on degrees of freedom where necessary with respect to users’ interactions. Second, during on-line phase, we apply a division scheme to divide the deformation process into two separate modules which are implemented on different threads to ensure the haptic interaction performance. Experiments are carried out based on a prototype implementation concerning different models of growing complexity. The deformation accuracy and the real-time performance are discussed.

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