Fault Diagnosis for High-Level Applications Based on Dynamic Bayesian Network

2009 ◽  
pp. 61-70 ◽  
Author(s):  
Zhiqing Li ◽  
Lu Cheng ◽  
Xue-song Qiu ◽  
Li Wu
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Dynamic Bayesian Network ◽  
High Level

Fault Diagnosis System Based on Dynamic Bayesian Network

2011 ◽  
Vol 55-57 ◽  
pp. 1824-1829
Author(s):  
Hong Bo Wang ◽  
Zhong Gui Ma ◽  
Xu Yan Tu
Keyword(s):  
Fault Diagnosis ◽  
Natural Gas ◽  
Bayesian Network ◽  
Distribution Network ◽  
Dynamic Bayesian Network ◽  
Start Time ◽  
Inference System ◽  
Basic Model ◽  
Natural Gas Transmission ◽  
Transmission And Distribution

The paper focus on dynamic bayesian network (DBN) inference system and its application on the natural gas transmission and distribution network for the system fault diagnosis which is including time restriction (that is the earliest start time and the latest end time) for task. DBN is a graphic model which can describe the relationships between variable data, and used for reasoning. After we research the basic model of DBN, and the maximum depend algorithm is improved which which can increase the feasibility of natural gas transmission and distribution network system. we can see the new model is more accuracy than the traditional technical fault diagnosis clearly. Also, simulation result can verify the design of DBN is effectively and valuable.

scholarly journals INCREASING EFFECTIVENESS OF MODEL-BASED FAULT DIAGNOSIS: A DYNAMIC BAYESIAN NETWORK DESIGN FOR DECISION MAKING

2006 ◽  
Vol 39 (13) ◽  
pp. 90-95 ◽  
Author(s):  
Philippe WEBER° ◽  
Didier THEILLIOL° ◽  
Christophe AUBRUN° ◽  
Alexandre EVSUKOFF
Keyword(s):  
Decision Making ◽  
Fault Diagnosis ◽  
Bayesian Network ◽  
Network Design ◽  
Dynamic Bayesian Network ◽  
Model Based

Dynamic bayesian network-based fault diagnosis for ASHRAE guideline 36

2021 ◽  
Author(s):  
Ojas Pradhan ◽  
Jin Wen ◽  
Yimin Chen ◽  
Xing Lu ◽  
Mengyuan Chu ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Dynamic Bayesian Network

A dynamic Bayesian network based methodology for fault diagnosis of subsea Christmas tree

2020 ◽  
Vol 94 ◽  
pp. 101990
Author(s):  
Peng Liu ◽  
Yonghong Liu ◽  
Baoping Cai ◽  
Xinlei Wu ◽  
Ke Wang ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Dynamic Bayesian Network ◽  
Christmas Tree

scholarly journals A Multidisciplinary Artificial Intelligence Model of an Affective Robot

10.5772/45662 ◽  
2012 ◽  
Vol 9 (1) ◽  
pp. 6 ◽  
Author(s):  
Hooman Aghaebrahimi Samani ◽  
Elham Saadatian
Keyword(s):  
Artificial Intelligence ◽  
Bayesian Network ◽  
Multidisciplinary Approach ◽  
Affective State ◽  
Dynamic Bayesian Network ◽  
Endocrine System ◽  
Affective States ◽  
Intelligence System ◽  
Human Love ◽  
High Level

A multidisciplinary approach to a novel artificial intelligence system for an affective robot is presented in this paper. The general objective of the system is to develop a robotic system which strives to achieve a high level of emotional bond between humans and robot by exploring human love. Such a relationship is a contingent process of attraction, affection and attachment from humans towards robots, and the belief of the vice versa from robots to humans. The advanced artificial intelligence of the system includes three modules, namely Probabilistic Love Assembly (PLA), based on the psychology of love, Artificial Endocrine System (AES), based on the physiology of love, and Affective State Transition (AST), based on emotions. The PLA module employs a Bayesian network to incorporate psychological parameters of affection in the robot. The AES module employs artificial emotional and biological hormones via a Dynamic Bayesian Network (DBN). The AST module uses a novel transition method for handling affective states of the robot. These three modules work together to manage emotional behaviours of the robot.

Sign in / Sign up

Export Citation Format

Share Document