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Utilizing Principal Component Analysis for the Identification of Gas Turbine Defects
This study explores the use of the nonlinear principal component analysis (NLPCA) technique for detecting gas turbine faults. The resurgence of...
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Evaluation of Chinese traditional military settlements’ defensive capabilities via principal component analysis (PCA): a case study of coastal Wei forts in the Ming dynasty
Defensive capability is one of the essential attributes of traditional military settlements. In the Ming dynasty, coastal Wei fort was the one of the...
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Ultrasonic Phased Array Total Focusing Method of Imaging with Rayleigh Waves Based on Principal Component Analysis
AbstractRayleigh waves can be used to detect surface defects effectively. However, the Rayleigh wave imaging quality is often poor due to the low...
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Predicting the alloying element yield in a ladle furnace using principal component analysis and deep neural network
The composition control of molten steel is one of the main functions in the ladle furnace (LF) refining process. In this study, a feasible model was...
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A Hybrid Optimization Approach of Single Point Incremental Sheet Forming of AISI 316L Stainless Steel Using Grey Relation Analysis Coupled with Principal Component Analysiss
We investigated the parametric optimization on incremental sheet forming of stainless steel using Grey Relational Analysis (GRA) coupled with...
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Principal component analysis enables the design of deep learning potential precisely capturing LLZO phase transitions
The development of accurate and efficient interatomic potentials using machine learning has emerged as an important approach in materials simulations...
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Predicting porosity in wire arc additive manufacturing (WAAM) using wavelet scattering networks and sparse principal component analysis
Wire arc additive manufacturing (WAAM) is getting much research attention because of its cost-effectiveness in the metallic production of large and...
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Raw Cellulosic Fibers: Characterization and Classification by FTIR-ATR Spectroscopy and Multivariate Analysis (PCA and LDA)
The textile industry is one of the most pollutants in the world. It is estimated that only 20% of the textiles that become solid waste are recycled....
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Tannin characterization and sourcing in historical leathers through FTIR spectroscopy and PCA analysis
This study aimed to identify and classify the type of plants used for tanning historical leathers using cost-effective Fourier transform infrared...
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Application of Machine Learning Algorithms With and Without Principal Component Analysis for the Design of New Multiphase High Entropy Alloys
The design of high entropy alloys (HEAs) can be accelerated using machine learning (ML) algorithms. In the current study, the design parameter’s...
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Kernel Principal Component Analysis for Structural Health Monitoring and Damage Detection of an Engineering Structure Under Operational Loading Variations
This paper highlights kernel principal component analysis (KPCA) in distinguishing damage-sensitive features from the effects of liquid loading on...
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An electronic nose using conductometric gas sensors based on P3HT doped with triflates for gas detection using computational techniques (PCA, LDA, and kNN)
This study presents the development of an electronic nose comprising eight homemade sensors with pure P3HT and doped with different materials. The...
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Data-driven Search and Selection of Ti-containing Multi-principal Element Alloys for Aeroengine Parts
There is rapidly growing interest in Ti-containing multi-principal element alloysTi-containing multi-principal element alloys (MPEA), due to their...
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Measurement and Multi-response Optimization of Spark Erosion Machining Parameters for Titanium Alloy Using Hybrid Taguchi–Grey Relational Analysis–Principal Component Analysis Approach
This research presents the analysis of parametric optimization of spark erosion machining process of Ti-6Al-4V alloy. In spark erosion machining,...
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NIR spectroscopy in conjunction with multivariate analysis for non-destructive characterization of Xuan paper
In the process of conservation mounting, starch paste made from wheat flour is the glue of choice to paste reinforcing strips and backing papers,...
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A PCA-Integrated OGM (1, N) Predictive Model for In-Process Tool Wear Prediction Based on Continuous Monitoring of Multi-Sensorial Information
In the modern machining process, catastrophic tool failure has become a significant problem because the machining quality and efficiency depend on...
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Machine-learning-assisted analysis of transition metal dichalcogenide thin-film growth
In situ reflective high-energy electron diffraction (RHEED) is widely used to monitor the surface crystalline state during thin-film growth by...
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Rapid, Non-destructive Identification of Iron Ores-Based Random Forest (RF) Using Visible and Near-Infrared Spectroscopy
Visible and near-infrared (Vis–NIR) spectroscopy technology can better meet the needs of identification of mineral differences in iron ores by using...
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Dimensioning a stockpile operation using principal component analysis
Mineral processing plants generally have narrow tolerances for the grades of their input raw materials, so stockpiles are often maintained to reduce...
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Identifying Stochastic Frequency Response Functions Using Real-Time Hybrid Substructuring, Principal Component Analysis, and Kriging Metamodeling
Real-time hybrid substructuring (RTHS) has previously been shown to be an effective tool to quantify the effect of parametric uncertainties on the...
