A method for root cause diagnosis with picture fuzzy sets based dynamic uncertain causality graph

2021 ◽  
pp. 1-11
Author(s):  
Li Li ◽  
Yongfang Xie ◽  
Xiaofang Chen

Root cause diagnosis is of great significance to make efficient decisions in industrial production processes. It is a procedure of fusing knowledge, such as empirical knowledge, process knowledge, and mechanism knowledge. However, it is insufficient and low reliability of cause analysis methods by using crisp values or fuzzy numbers to represent uncertain knowledge. Therefore, a dynamic uncertain causality graph model (DUCG) based on picture fuzzy set (PFS) is proposed to address the problem of uncertain knowledge representation and reasoning. It combines the PFS with DUCG model to express expert doubtful ideas in a complex system. Then, a new PFS operator is introduced to characterize the importance of factors and connections among various information. Moreover, an enhanced knowledge reasoning algorithm is developed based on the PFS operators to resolve causal inference problems. Finally, a numerical example illustrates the effectiveness of the method, and the results show that the proposed model is more reliable and flexible than the existing models.

Author(s):  
Alessandro Umbrico ◽  
Gabriella Cortellessa ◽  
Andrea Orlandini ◽  
Amedeo Cesta

A key aspect of robotic assistants is their ability to contextualize their behavior according to different needs of assistive scenarios. This work presents an ontology-based knowledge representation and reasoning approach supporting the synthesis of personalized behavior of robotic assistants. It introduces an ontological model of health state and functioning of persons based on the International Classification of Functioning, Disability and Health. Moreover, it borrows the concepts of affordance and function from the literature of robotics and manufacturing and adapts them to robotic (physical and cognitive) assistance domain. Knowledge reasoning mechanisms are developed on top of the resulting ontological model to reason about stimulation capabilities of a robot and health state of a person in order to identify action opportunities and achieve personalized assistance. Experimental tests assess the performance of the proposed approach and its capability of dealing with different profiles and stimuli.


2021 ◽  
Vol 40 (1) ◽  
pp. 1107-1128
Author(s):  
Peide Liu ◽  
Muhammad Akram ◽  
Ayesha Bashir

This article puts forward an innovative notion of complex picture fuzzy set (CPFS) which is particularly an extension and a generalization of picture fuzzy sets (PFSs) by the addition of phase term in the description of PFSs. The uniqueness of CPFS lies in the capability to manage the uncertainty and periodicity, simultaneously, due to the presence of phase term which broadens the range of CPFS from a real plane to the complex plane of unit disk. We describe and verify the fundamental operations and properties of CPFSs. We introduce the aggregation operators, namely; complex picture fuzzy power averaging and complex picture fuzzy power geometric operators in CPFSs environment, based on weighted and ordered weighted averaging and geometric operators. We construct multi-criteria decision making (MCDM) problem, using these operators and describe a numerical example to illustrate the validity and competence of this article. Finally, we discuss the advantages of this generalized concept of aggregation technique and analyze a comparative study to demonstrate the superiority and consistency of our model.


2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Dliouah Ahmed ◽  
Binxiang Dai

The major concern of this article is to propose the notion of picture fuzzy rough sets (PFRSs) over two different universes which depend on δ , ζ , ϑ -cut of picture fuzzy relation ℛ on two different universes (i.e., by combining picture fuzzy sets (PFSs) with rough sets (RSs)). Then, we discuss several interesting properties and related results on the PFRSs. Furthermore, we define some notions related to PFRSs such as (Type-I/Type-II) graded PFRSs, the degree α and β with respect to ℛ δ , ζ , ϑ on PFRSs, and (Type-I/Type-II) generalized PFRSs based on the degree α and β with respect to ℛ δ , ζ , ϑ and investigate the basic properties of above notions. Finally, an approach based on the rough picture fuzzy approximation operators on two different universes in decision-making problem is introduced, and we give an example to show the validity of this approach.


Author(s):  
Nguyen Van Dinh ◽  
Nguyen Xuan Thao

To measure the difference of two fuzzy sets (FSs) / intuitionistic sets (IFSs), we can use the distance measure and dissimilarity measure between fuzzy sets/intuitionistic fuzzy set. Characterization of distance/dissimilarity measure between fuzzy sets/intuitionistic fuzzy set is important as it has application in different areas: pattern recognition, image segmentation, and decision making. Picture fuzzy set (PFS) is a generalization of fuzzy set and intuitionistic set, so that it have many application. In this paper, we introduce concepts: difference between PFS-sets, distance measure and dissimilarity measure between picture fuzzy sets, and also provide  the formulas for determining these values. We also present an application of dissimilarity measures in the sample recognition problems, can also be considered a decision-making problem.


Author(s):  
Ehsan Mollasalehi ◽  
Seyed Abdolali Zareian Jahromi ◽  
Mario Forcinito ◽  
Wei Hu ◽  
Qiao Sun

Condition monitoring and fault diagnosis of operating machinery have been of the main interests for many years. Existing systems employ data driven models which has limited prediction capability. On the contrary, a physics based model can predict phenomena that the system has not seen before. It also provides a means for root cause analysis. However, major obstacles include the complexity involved and real-time feasibility. In this paper, we use the bond graph technique to construct an analytical, physics-based model. We use a reciprocating compressor as an example since it is a good representation of multi-domain processes with a variety of possible failure modes. The bond graph model is cross examined with a finite element model and ultimately validated. To show how one can benefit from this approach, cracked piston rod is simulated to generate vibration signals that can potentially be picked up from accelerometers mounted on the exterior surface of the compressor.


2017 ◽  
Vol 18 (5) ◽  
pp. 393-401 ◽  
Author(s):  
Shao-rui Hao ◽  
Shi-chao Geng ◽  
Lin-xiao Fan ◽  
Jia-jia Chen ◽  
Qin Zhang ◽  
...  

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