scholarly journals A New Approach to Assess the Quality of Small High-Speed Centrifugal Fans Using Noise Measurement

1999 ◽  
Vol 5 (2) ◽  
pp. 147-153 ◽  
Author(s):  
Dingjun Cui ◽  
Ian A. Craighead
Keyword(s):  
Signal Processing ◽  
Quality Assessment ◽  
Condition Monitoring ◽  
High Speed ◽  
Noise Levels ◽  
New Approach ◽  
Commercial Market ◽  
Centrifugal Fans ◽  
Special Approach

The requirements for a special approach for the quality assessment of small high-speed centrifugal fans are outlined and a new parameter designating the noise levels from the product in comprehensive form will be discussed and described as a criterion for such quality assessment.By applying techniques of signal processing and condition monitoring, the sources of the vibration and noise in different sections of the product can be identified, then the noise from each source from different components can be determined. Using this criterion, more aspects of the quality of the products can be assessed and suggestions to improve the quality of the products can be made. Finally, the assessment of a number ofvacuum cleaner motor/fan units available in the commercial market will be presented and compared with conventional specifications. It will be shown that the new parameter provides a more useful indication of appliance quality.

Application of FPGAs to High-Speed Condition Based Maintenance of Rolling Element Bearings

Volume 3 ◽  
2004 ◽  
Author(s):  
Mark Harriman ◽  
Farbod Zorriassatine ◽  
Rob Parkin ◽  
Mike Jackson ◽  
Jo Coy
Keyword(s):  
Signal Processing ◽  
Condition Monitoring ◽  
Execution Time ◽  
Field Programmable Gate Array ◽  
High Speed ◽  
Mechanical Engineering ◽  
Electronic Engineering ◽  
Bearing Condition Monitoring ◽  
Field Programmable ◽  
Gate Array

Field-Programmable Gate Array (FPGA) technology has been applied widely in electronic engineering and computing industries, but it has not had the same level of reception in other disciplines including mechanical engineering [1]. The purpose of this paper is to examine FPGA implementations of signal processing techniques that are used in the context of bearing condition monitoring. As the number of bearings can be large sparse sensor arrays are used to locate and detect their condition. The demands of realtime process monitoring [2] [3] can place a heavy burden upon the monitoring system. Field-Programmable Gate Array (FPGA) technology [4] in this application makes it possible to implement more sophisticated algorithms. These exploit its high-speed, parallel, reconfigurable architecture. Bring forth the advantages of FPGA technology to condition monitoring. The techniques covered are: cross-correlation, digital signal processing (DSP) Infinite Impulse Response (IIR) filters, neural networks and signature matching. The implemented designs are optimised for both execution time and the amount of logic area consumed. Results were obtained from each technique and were assessed and compared in terms of execution time and also the amount of logic consumed on the FPGA. Over the past 15 years FPGA technology has been applied extensively in electronic engineering but its scope has not been as vastly in mechanical engineering. The objective of this paper was to examine an application in mechanical engineering. Ideally this would be done with a mechanical engineering compatible approach, giving rise to a methodology, which would allow FPGA programming [5] to become a transferable skill.

scholarly journals Identifying Mislabeled Training Data

1999 ◽  
Vol 11 ◽  
pp. 131-167 ◽  
Author(s):  
C. E. Brodley ◽  
M. A. Friedl
Keyword(s):  
Classification Accuracy ◽  
Majority Vote ◽  
Learning Algorithms ◽  
Empirical Evaluation ◽  
Training Data ◽  
Noise Levels ◽  
New Approach ◽  
Good Data ◽  
Bad Data

This paper presents a new approach to identifying and eliminating mislabeled training instances for supervised learning. The goal of this approach is to improve classification accuracies produced by learning algorithms by improving the quality of the training data. Our approach uses a set of learning algorithms to create classifiers that serve as noise filters for the training data. We evaluate single algorithm, majority vote and consensus filters on five datasets that are prone to labeling errors. Our experiments illustrate that filtering significantly improves classification accuracy for noise levels up to 30 percent. An analytical and empirical evaluation of the precision of our approach shows that consensus filters are conservative at throwing away good data at the expense of retaining bad data and that majority filters are better at detecting bad data at the expense of throwing away good data. This suggests that for situations in which there is a paucity of data, consensus filters are preferable, whereas majority vote filters are preferable for situations with an abundance of data.

scholarly journals Measuring the reproducibility and quality of Hi-C data

2017 ◽  
Author(s):  
Galip Gürkan Yardımcı ◽  
Hakan Ozadam ◽  
Michael E.G. Sauria ◽  
Oana Ursu ◽  
Koon-Kiu Yan ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Best Practices ◽  
Correlation Analysis ◽  
Quality Assessment ◽  
Simulated Data ◽  
Depth Resolution ◽  
Quality Measures ◽  
Noise Levels ◽  
Simple Correlation

AbstractHi-C is currently the most widely used assay to investigate the 3D organization of the genome and to study its role in gene regulation, DNA replication, and disease. However, Hi-C experiments are costly to perform and involve multiple complex experimental steps; thus, accurate methods for measuring the quality and reproducibility of Hi-C data are essential to determine whether the output should be used further in a study. Using real and simulated data, we profile the performance of several recently proposed methods for assessing reproducibility of population Hi-C data, including HiCRep, GenomeDISCO, HiC-Spector and QuASAR-Rep. By explicitly controlling noise and sparsity through simulations, we demonstrate the deficiencies of performing simple correlation analysis on pairs of matrices, and we show that methods developed specifically for Hi-C data produce better measures of reproducibility. We also show how to use established (e.g., ratio of intra to interchromosomal interactions) and novel (e.g., QuASAR-QC) measures to identify low quality experiments. In this work, we assess reproducibility and quality measures by varying sequencing depth, resolution and noise levels in Hi-C data from 13 cell lines, with two biological replicates each, as well as 176 simulated matrices. Through this extensive validation and benchmarking of Hi-C data, we describe best practices for reproducibility and quality assessment of Hi-C experiments. We make all software publicly available at http://github.com/kundajelab/3DChromatin_ReplicateQC to facilitate adoption in the community.

Based on Signal Processing and Diagnosis for Large Port Crane Condition Monitoring System Vibration Detection of High Speed Heavy-Duty Crane

2014 ◽  
Vol 494-495 ◽  
pp. 825-829
Author(s):  
Min Hui Tong ◽  
Hui Qing Qiu ◽  
Yue Min Wang
Keyword(s):  
Signal Processing ◽  
Condition Monitoring ◽  
High Speed ◽  
Heavy Duty ◽  
Monitoring And Diagnosis ◽  
Sensing System ◽  
Vibration Detection ◽  
System Vibration ◽  
Condition Monitoring System ◽  
Operation Status

In order to master the safety status of the large port crane and diagnosis and predict the fault in advance for alerting, the condition monitoring and diagnosis & sensing system is used in this paper. By using sorts of sensors and accelerate meters installing on the crane, acquire all kind of signals of the machine, then put the data to the signal processing and diagnosis sensing system, the operation status of the crane can be found out, and the potential fault or failure can be diagnosis and detected in advance. The condition monitoring and diagnosis & sensing sys-tem can acquired the condition status from the large port crane and diagnosis the potential fault or failure for the machine. Thus, the problem how to master the condition of the large crane port crane and provided the safety alerting for the huge machine is solved.

Expert System for Quality Assessment of Electronic Book Exhibitions

2013 ◽  
pp. 32-39
Author(s):  
Svetlana V. Savkina
Keyword(s):  
Expert System ◽  
Quality Assessment ◽  
Electronic Book ◽  
Electronic Books ◽  
Comparison Of The Results

The article presents the results of testing the complex methodology of assessment of quality of electronic books exhibitions (EBE). The author describes the project of the expert system, allowing to implement the EBE assessment without the experts’ participation. There is given the comparison of the results of assessments, carried out by experts and by the expert system.

Quality of cytogenetic investigations: problems and ways for improvement

2020 ◽  
pp. 22-24
Author(s):  
В.Г. Антоненко ◽  
Н.В. Шилова ◽  
Е.Н. Лукаш ◽  
Э.Р. Бабкеева ◽  
В.Н. Малахов
Keyword(s):  
Quality Assessment ◽  
Russian Federation ◽  
Chromosomal Analysis ◽  
Common Causes

Представлены результаты экспертной оценки качества цитогенетических исследований в лабораториях РФ в системе межлабораторных сличительных испытаний «ФСВОК» в 2018-2019 гг. Обсуждаются наиболее частые причины неудовлетворительных результатов экспертизы и возможные пути улучшения качества цитогенетических исследований. We report the results of quality assessment for preparation of cytogenetic slides and chromosomal analysis in the laboratories of Russian Federation in the system of the interlaboratory comparative examinations “FSVOK” in 2018-2019. Common causes of poor results of assessment and the ways for improvement of quality for cytogenetic investigations are discussed.

ABOUT NECESSITY OF MATHEMATICAL MODELING OF THE BUSINESS PROCESS OF COST ESTIMATE CALCULATIONS IN THE CONSTRUCTION OF OIL AND GAS FACILITIES

2017 ◽  
pp. 139-145
Author(s):  
R. I. Hamidullin ◽  
L. B. Senkevich
Keyword(s):  
Mathematical Modeling ◽  
Quality Assessment ◽  
Business Process ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Gas Industry ◽  
Construction Organizations ◽  
The Cost ◽  
Cost Of Construction

A study of the quality of the development of estimate documentation on the cost of construction at all stages of the implementation of large projects in the oil and gas industry is conducted. The main problems that arise in construction organizations are indicated. The analysis of the choice of the perfect methodology of mathematical modeling of the investigated business process for improving the activity of budget calculations, conducting quality assessment of estimates and criteria for automation of design estimates is performed.

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