scholarly journals A Multi-Sensor Data Fusion System for Laser Welding Process Monitoring

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 147349-147357 ◽  
Author(s):  
Fuqin Deng ◽  
Yongshen Huang ◽  
Song Lu ◽  
Yingying Chen ◽  
Jia Chen ◽  
...  
Keyword(s):  
Data Fusion ◽  
Laser Welding ◽  
Process Monitoring ◽  
Welding Process ◽  
Sensor Data ◽  
Fusion System ◽  
Sensor Data Fusion ◽  
Multi Sensor Data Fusion ◽  
Laser Welding Process

Towards the development of a smart fused filament fabrication system using multi-sensor data fusion for in-process monitoring

2020 ◽  
Vol 26 (7) ◽  
pp. 1249-1261 ◽  
Author(s):  
Michele Moretti ◽  
Federico Bianchi ◽  
Nicola Senin
Keyword(s):  
Data Fusion ◽  
Process Monitoring ◽  
Sensor Data ◽  
Fused Filament Fabrication ◽  
Content Type ◽  
Heterogeneous Sensors ◽  
Sensor Data Fusion ◽  
Part Quality ◽  
Multi Sensor Data Fusion ◽  
Smart Machine

Purpose This paper aims to illustrate the integration of multiple heterogeneous sensors into a fused filament fabrication (FFF) system and the implementation of multi-sensor data fusion technologies to support the development of a “smart” machine capable of monitoring the manufacturing process and part quality as it is being built. Design/methodology/approach Starting from off-the-shelf FFF components, the paper discusses the issues related to how the machine architecture and the FFF process itself must be redesigned to accommodate heterogeneous sensors and how data from such sensors can be integrated. The usefulness of the approach is discussed through illustration of detectable, example defects. Findings Through aggregation of heterogeneous in-process data, a smart FFF system developed upon the architectural choices discussed in this work has the potential to recognise a number of process-related issues leading to defective parts. Research limitations/implications Although the implementation is specific to a type of FFF hardware and type of processed material, the conclusions are of general validity for material extrusion processes of polymers. Practical implications Effective in-process sensing enables timely detection of process or part quality issues, thus allowing for early process termination or application of corrective actions, leading to significant savings for high value-added parts. Originality/value While most current literature on FFF process monitoring has focused on monitoring selected process variables, in this work a wider perspective is gained by aggregation of heterogeneous sensors, with particular focus on achieving co-localisation in space and time of the sensor data acquired within the same fabrication process. This allows for the detection of issues that no sensor alone could reliably detect.

Application and Research of Multi-Sensor Data Fusion for the Earlier Period Diagnosis in Induction Motors

2013 ◽  
Vol 706-708 ◽  
pp. 644-649
Author(s):  
Shu Ying Li ◽  
Mu Qin Tian ◽  
Lei Xue
Keyword(s):  
Data Fusion ◽  
Induction Motors ◽  
Sensor Data ◽  
Fusion System ◽  
Fusion Algorithm ◽  
Sensor Data Fusion ◽  
Multi Sensor Data Fusion ◽  
Recognition Ability ◽  
Single Sensor ◽  
A New Technique

The multi-sensor data fusion widely applied to military and industry areas is a new technique developed in recent years. It can avoid the limitations of a single sensor and obtain more information, improving the recognition ability. This paper analyzes the uncertainties in the traditional earlier period diagnosis in induction motors based on the single parameter and introduces the idea of using multi-sensor data fusion to handle these uncertainties. In a fusion system several parameters will be fused according to the D-S evidential fusion algorithm in order to identify accurately the earlier period faults of the induction motors. Practical diagnostic examples show that the fault diagnostic accuracy and confidence are markedly promoted by using the multi-sensor data fusion.

The Design of Component Level Software Architecture for Multi-Sensor Data Fusion System

2011 ◽  
Vol 58-60 ◽  
pp. 1548-1553
Author(s):  
Ning Ning Qin ◽  
Wen Yi Shen ◽  
Jun Yan ◽  
Bao Guo Xu
Keyword(s):  
Data Fusion ◽  
Software Architecture ◽  
Sensor Data ◽  
Fusion System ◽  
Component Level ◽  
Sensor Data Fusion ◽  
System A ◽  
Object Properties ◽  
Multi Sensor Data Fusion ◽  
Software Reusability

Through investigating the architecture of multi-sensor data fusion system, a universal software architecture which can be used in distributed multi-radar fusion systems is proposed in this paper. In this architecture, functionally independent modules will be extracted from system, it will be standardized as components by object-oriented techniques, and the interface specifications of all the modules are also specified. Aiming at the different objects, system flow and modules can be framed quickly by selecting or expanding proper components based on different scenes feature and object properties. The architecture improves software reusability and scalability, and is propitious to increase software development efficiency.

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