An automatic method for constructing machining process knowledge base from knowledge graph

2022 ◽  
Vol 73 ◽  
pp. 102222
Author(s):  
Liang Guo ◽  
Fu Yan ◽  
Tian Li ◽  
Tao Yang ◽  
Yuqian Lu
Keyword(s):  
Knowledge Base ◽  
Machining Process ◽  
Knowledge Graph ◽  
Automatic Method ◽  
Process Knowledge

scholarly journals Process Knowledge Graph Modeling Techniques and Application Methods for Ship Heterogeneous Models

2021 ◽  
Author(s):  
Jinfeng Liu ◽  
Jianwei Dong ◽  
Xuwen Jing ◽  
Xuwu Cao ◽  
Chenxiao Du ◽  
...  
Keyword(s):  
Process Design ◽  
Welding Process ◽  
Mapping Method ◽  
Knowledge Graph ◽  
Case Based Reasoning ◽  
Test Model ◽  
Process Knowledge ◽  
Heterogeneous Model ◽  
Heterogeneous Models ◽  
Component Assembly

Abstract In the process design and reuse of marine component products, there are a lot of heterogeneous models, causing the problem that the process knowledge and process design experience contained in them are difficult to express and reuse. Therefore, a process knowledge representation model for ship heterogeneous model is proposed in this paper. Firstly, the multi-element process knowledge graph is constructed, and the heterogeneous ship model is described in a unified way. Then, the multi-strategy ontology mapping method is applied, and the semantic expression between the process knowledge graph and the entity model is realized. Finally, by obtaining implicit semantics based on case-based reasoning and checking the similarity of the matching results, the case knowledge reuse is achieved, to achieve rapid design of the process. This method provides reliable technical support for the design of ship component assembly and welding process, greatly shortens the design cycle, and improves the working efficiency. In addition, a case study of the test model is carried out to verify the feasibility and efficiency of the proposed method.

scholarly journals Extraction of Terms Related to Named Rivers

Languages ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 46
Author(s):  
Juan ◽  
Faber
Keyword(s):  
Knowledge Base ◽  
Mississippi River ◽  
Environmental Science ◽  
Automatic Method ◽  
Statistical Procedures ◽  
Conceptual Structures ◽  
Semantic Models ◽  
Semantic Frames ◽  
Conceptual Network ◽  
Distributional Semantic Models

EcoLexicon is a terminological knowledge base on environmental science, whose design permits the geographic contextualization of data. For the geographic contextualization of landform concepts, this paper presents a semi-automatic method for extracting terms associated with named rivers (e.g., Mississippi River). Terms were extracted from a specialized corpus, where named rivers were automatically identified. Statistical procedures were applied for selecting both terms and rivers in distributional semantic models to construct the conceptual structures underlying the usage of named rivers. The rivers sharing associated terms were also clustered and represented in the same conceptual network. The results showed that the method successfully described the semantic frames of named rivers with explanatory adequacy, according to the premises of Frame-Based Terminology.

Process Fault Diagnosis Based on Process Model Knowledge: Part II—Case Study Experiments

1991 ◽  
Vol 113 (4) ◽  
pp. 627-633 ◽  
Author(s):  
R. Isermann ◽  
B. Freyermuth
Keyword(s):  
Fault Diagnosis ◽  
Knowledge Acquisition ◽  
Knowledge Base ◽  
Process Models ◽  
Normal Operation ◽  
Problem Solution ◽  
Inference Mechanism ◽  
Process Knowledge ◽  
Fault Trees

A computer assisted fault diagnosis system (CAFD) is considered which allows the early detection and localization of process faults during normal operation or on request. It is based on an on-line engineering expert system and consists of an analytical problem solution, a process knowledge base, a knowledge acquisition component and an inference mechanism. The analytic problem solution uses a process parameter estimation, and the detection of process coefficient changes, which are symptoms of process faults. The process knowledge base is comprised of analytical knowledge in the form of process models and heuristic knowledge in the form of fault trees and fault statistics. In the phase of knowledge acquisition the process specific knowledge like theoretical process models, the normal behavior and fault trees is compiled. The inference mechanism performs the fault diagnosis, based on the observed symptoms, the fault trees, fault probabilities and the process history. This is described in Part I. In Part II, case study experiments with a d.c. motor, centrifugal pump, a heat exchanger and an industrial robot show practical results of the model based fault diagnosis.

scholarly journals An Approach to Knowledge Base Completion by a Committee-Based Knowledge Graph Embedding

2020 ◽  
Vol 10 (8) ◽  
pp. 2651
Author(s):  
Su Jeong Choi ◽  
Hyun-Je Song ◽  
Seong-Bae Park
Keyword(s):  
Knowledge Base ◽  
Language Processing ◽  
Graph Embedding ◽  
Knowledge Bases ◽  
Knowledge Graph ◽  
Data Sets ◽  
Complete Knowledge ◽  
Proposed Model ◽  
Ranking Task ◽  
Low Dimensional

Knowledge bases such as Freebase, YAGO, DBPedia, and Nell contain a number of facts with various entities and relations. Since they store many facts, they are regarded as core resources for many natural language processing tasks. Nevertheless, they are not normally complete and have many missing facts. Such missing facts keep them from being used in diverse applications in spite of their usefulness. Therefore, it is significant to complete knowledge bases. Knowledge graph embedding is one of the promising approaches to completing a knowledge base and thus many variants of knowledge graph embedding have been proposed. It maps all entities and relations in knowledge base onto a low dimensional vector space. Then, candidate facts that are plausible in the space are determined as missing facts. However, any single knowledge graph embedding is insufficient to complete a knowledge base. As a solution to this problem, this paper defines knowledge base completion as a ranking task and proposes a committee-based knowledge graph embedding model for improving the performance of knowledge base completion. Since each knowledge graph embedding has its own idiosyncrasy, we make up a committee of various knowledge graph embeddings to reflect various perspectives. After ranking all candidate facts according to their plausibility computed by the committee, the top-k facts are chosen as missing facts. Our experimental results on two data sets show that the proposed model achieves higher performance than any single knowledge graph embedding and shows robust performances regardless of k. These results prove that the proposed model considers various perspectives in measuring the plausibility of candidate facts.

Assembly Process Knowledge Graph for Digital Twin

2021 ◽  
Author(s):  
Yukun Jiang ◽  
Changjiang Chen ◽  
Xiaojun Liu
Keyword(s):  
Knowledge Graph ◽  
Assembly Process ◽  
Process Knowledge ◽  
Digital Twin

Application of AI in Optimization of Machining Conditions

1991 ◽  
Author(s):  
Tongjian Chen ◽  
Weiping Wang ◽  
Xiaofang Wang
Keyword(s):  
Expert System ◽  
Knowledge Base ◽  
Optimization Method ◽  
Machining Process ◽  
Effective Algorithm ◽  
Machining Processes ◽  
Machining Conditions

Abstract In these days researchers have been attempting to build up a versatile optimization method which is adaptable for all the purposes but no ideal one has been appeared. The paper proposes a new consideration for practising the optimization of machining conditions in various machining processes on workshop scenes. The optimizing strategy is through an expert system of selection to determine a most effective algorithm from the current sophiticated optimizing algorithms collected in the knowledge base as subroutines, then to run the algorithem program and obtain the optimized results by means of the interactive function of expert system. The method not only has the versatile property to be used in various sorts of machining easily but also keeps the completeness of each sophiticated optimizing method developed for a special machining process without compromise.

A Knowledge Base for Non-Traditional Machining Process Selection

2008 ◽  
Vol 4 (4) ◽  
pp. 37-46 ◽  
Author(s):  
Edison Chandraseelan.R. ◽  
Jehadeesan R. Jehadeesan R. ◽  
Raajenthiren M. Raajenthiren M.
Keyword(s):  
Knowledge Base ◽  
Machining Process ◽  
Process Selection

Research on Fault Knowledge Base Technology of High-End CNC Machining System

2011 ◽  
Vol 308-310 ◽  
pp. 35-40
Author(s):  
Xiao Li Xu ◽  
Bin Ren ◽  
Yun Bo Zuo ◽  
Guo Xin Wu
Keyword(s):  
Knowledge Base ◽  
Cutting Tool ◽  
Cnc Machining ◽  
Machining Process ◽  
Cnc Machine Tools ◽  
Machining Accuracy ◽  
Construction Technology ◽  
Test Platform ◽  
Machining System ◽  
Wear Condition

In the high-end CNC machining process, the stability and reliability of the running state of the machining system directly affects the machining accuracy and work-piece quality. In order to effectively ensure the reliable, stable, safe operation of the high-end CNC machining system, the fault knowledge base technology construction for the cutting tool system is carried out. It focuses on the high-end CNC machine tools, and build the condition monitoring system test platform with cutting tool system as the core; the fault sample acquisition method based on the rough set theory is proposed; a knowledge base model construction technology is conducted; and the network-based sample acquisition test platform is established, so as to provide users with data information on the operation of cutting tool system, and provide the key test techniques for the generation mechanism of the dynamic performance and wear condition of the operation of cutting tool system and for the analysis of the intrinsic correlation between the characteristic parameters and wear condition of cutting tools.

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