Development of an Intelligent Rotating Machinery Diagnostics Programme

2008 ◽  
Author(s):  
Blazˇ Suhacˇ ◽  
Jozˇe Vizˇintin ◽  
Pavle Bosˇkoski ◽  
Dani Juricˇic´
Keyword(s):  
Early Stage ◽  
Low Cost ◽  
Practical Importance ◽  
Extraction Procedure ◽  
Processing System ◽  
Diagnostic Procedures ◽  
Rotating Machinery ◽  
Lubricating Oil ◽  
Machinery Diagnostics ◽  
Proactive Maintenance

Rotating machines are one of the most wide spread items of equimpnet in the industrial plants; hence the reliable operation is of great practical importance. Analyses show that when a run-to-failure philosophy is adopted in rotating machinery maintenance, their downtime is usually three to four times longer comparing to a periodic or proactive maintenance approach. A successful proactive maintenance program requires an integration of several diagnostic procedures into an intelligent data processing system. Such a system allows detection of a broad range of faults in an early stage. The main aim of this paper is to present current results of our development of an intelligent rotating machinery diagnostics program for detecting a broad range of faults from signals which can be measured non-destructively and on-line. The main motivation is to develop computationally efficient algorithm that can be implemented on a standard (low-cost) platform. In that respect we have developed a test rotating machine equipped with accelerometers, temperature sensors and sensors for lubricating oil characterization. In this paper we focus on gear-box faults and a feature extraction procedure based on non-parametric statistical concepts as suggested and demonstrated on experimental data.

scholarly journals Automation of absolute protein-ligand binding free energy calculations for docking refinement and compound evaluation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Germano Heinzelmann ◽  
Michael K. Gilson
Keyword(s):  
Free Energy ◽  
Early Stage ◽  
Binding Free Energy ◽  
Low Cost ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Drug Candidates ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

AbstractAbsolute binding free energy calculations with explicit solvent molecular simulations can provide estimates of protein-ligand affinities, and thus reduce the time and costs needed to find new drug candidates. However, these calculations can be complex to implement and perform. Here, we introduce the software BAT.py, a Python tool that invokes the AMBER simulation package to automate the calculation of binding free energies for a protein with a series of ligands. The software supports the attach-pull-release (APR) and double decoupling (DD) binding free energy methods, as well as the simultaneous decoupling-recoupling (SDR) method, a variant of double decoupling that avoids numerical artifacts associated with charged ligands. We report encouraging initial test applications of this software both to re-rank docked poses and to estimate overall binding free energies. We also show that it is practical to carry out these calculations cheaply by using graphical processing units in common machines that can be built for this purpose. The combination of automation and low cost positions this procedure to be applied in a relatively high-throughput mode and thus stands to enable new applications in early-stage drug discovery.

Deep Learning Representation from Electroencephalography of Early-Stage Creutzfeldt-Jakob Disease and Features for Differentiation from Rapidly Progressive Dementia

2016 ◽  
Vol 27 (02) ◽  
pp. 1650039 ◽  
Author(s):  
Francesco Carlo Morabito ◽  
Maurizio Campolo ◽  
Nadia Mammone ◽  
Mario Versaci ◽  
Silvana Franceschetti ◽  
...  
Keyword(s):  
Deep Learning ◽  
Supervised Learning ◽  
Early Stage ◽  
Processing System ◽  
Fine Tuning ◽  
Permutation Entropy ◽  
Support Vector ◽  
Progressive Dementia ◽  
Time Frequency ◽  
Jakob Disease

A novel technique of quantitative EEG for differentiating patients with early-stage Creutzfeldt–Jakob disease (CJD) from other forms of rapidly progressive dementia (RPD) is proposed. The discrimination is based on the extraction of suitable features from the time-frequency representation of the EEG signals through continuous wavelet transform (CWT). An average measure of complexity of the EEG signal obtained by permutation entropy (PE) is also included. The dimensionality of the feature space is reduced through a multilayer processing system based on the recently emerged deep learning (DL) concept. The DL processor includes a stacked auto-encoder, trained by unsupervised learning techniques, and a classifier whose parameters are determined in a supervised way by associating the known category labels to the reduced vector of high-level features generated by the previous processing blocks. The supervised learning step is carried out by using either support vector machines (SVM) or multilayer neural networks (MLP-NN). A subset of EEG from patients suffering from Alzheimer’s Disease (AD) and healthy controls (HC) is considered for differentiating CJD patients. When fine-tuning the parameters of the global processing system by a supervised learning procedure, the proposed system is able to achieve an average accuracy of 89%, an average sensitivity of 92%, and an average specificity of 89% in differentiating CJD from RPD. Similar results are obtained for CJD versus AD and CJD versus HC.

scholarly journals A Cotton Module Feeder Plastic Contamination Inspection System

2020 ◽  
Vol 2 (2) ◽  
pp. 280-293
Author(s):  
Mathew G. Pelletier ◽  
Greg A. Holt ◽  
John D. Wanjura
Keyword(s):  
Mechanical Design ◽  
Low Cost ◽  
Processing System ◽  
Technical Note ◽  
Inspection System ◽  
Learning Program ◽  
Cotton Lint ◽  
Cotton Industry ◽  
Bill Of Materials ◽  
The U.S

The removal of plastic contamination in cotton lint is an issue of top priority to the U.S. cotton industry. One of the main sources of plastic contamination showing up in marketable cotton bales, at the U.S. Department of Agriculture’s classing office, is plastic from the module wrap used to wrap cotton modules produced by the new John Deere round module harvesters. Despite diligent efforts by cotton ginning personnel to remove all plastic encountered during unwrapping of the seed cotton modules, plastic still finds a way into the cotton gin’s processing system. To help mitigate plastic contamination at the gin; an inspection system was developed that utilized low-cost color cameras to see plastic on the module feeder’s dispersing cylinders, that are normally hidden from view by the incoming feed of cotton modules. This technical note presents the design of an automated intelligent machine-vision guided cotton module-feeder inspection system. The system includes a machine-learning program that automatically detects plastic contamination in order to alert the cotton gin personnel as to the presence of plastic contamination on the module feeder’s dispersing cylinders. The system was tested throughout the entire 2019 cotton ginning season at two commercial cotton gins and at one gin in the 2018 ginning season. This note describes the over-all system and mechanical design and provides an over-view and coverage of key relevant issues. Included as an attachment to this technical note are all the mechanical engineering design files as well as the bill-of-materials part source list. A discussion of the observational impact the system had on reduction of plastic contamination is also addressed.

The Development of an Electronically Controlled Petrol Injection System

1970 ◽  
Vol 185 (1) ◽  
pp. 95-107
Author(s):  
B. H. Croft
Keyword(s):  
Early Stage ◽  
Low Cost ◽  
High Standard ◽  
Original System ◽  
Injection System ◽  
Specific Power ◽  
Exhaust Emission ◽  
Development Effort ◽  
Electronic Control ◽  
Wide Range

The requirements of the modern automotive petrol engine in relation to higher specific power outputs while retaining good driveability and satisfying the impending exhaust emission control regulations, motivated an investigation into the potential of petrol injection. Consideration of the control requirements and accuracy necessary led, at an early stage, to the selection of electronic control on the basis of control capability, long term reliability, relatively low cost and the potential for future development. The fuel system was designed round the electronic control, manifold injection being used instead of direct injection on the basis of simplicity, lower cost and greater installation flexibility. The original system concept has changed only in detail, development effort being applied to the refinement of the system components to achieve a high standard of performance and the facility to apply the system with minimal modification to a wide range of engine types. The system is described in some detail and typical examples of the system performance on vehicles are presented.

scholarly journals An Affordable Knee Arthroscopy Simulator

2020 ◽  
Vol 44 (1) ◽  
Author(s):  
Paul André Alain Milcent ◽  
Alexandre Roberto Roman Coelho ◽  
Sthéphano Pellizzaro Rosa ◽  
Ygor Luiz Degraf da Fonseca ◽  
Andressa Zabudovski Schroeder ◽  
...  
Keyword(s):  
Knee Arthroscopy ◽  
Articular Surface ◽  
Low Cost ◽  
Diagnostic Procedures ◽  
The Body ◽  
Knee Model ◽  
Intercondylar Eminence ◽  
Pvc Pipe ◽  
Training Methodologies ◽  
Modeling Clay

Abstract: Introduction: The objective of this study is to describe a model of knee arthroscopy simulator that is affordable, low-cost and easily reproducible, aiming to enable the diffusion of more effective active teaching and training methodologies. Methods: For the creation of the arthroscopic camera, an endoscopic camera for mobile phones and computers model SXT-5.0M manufactured by KKMOON were used. The camera was introduced in a metal tube, which was coupled to a set of three 20 mm PVC hydraulic connectors to simulate the handle and sleeve of the arthroscope. The camera has a resolution of 1280 x 720 pixels and is equipped with six built-in white LED lamps, simulating and eliminating the need to use an additional light source. The knee model was developed using a PVC pipe fixed on a wooden support, to which synthetic femur and tibia models were affixed. Four three-centimeter diameter holes, compatible with the standard arthroscopic portals, were made in the body of the PVC pipe. For the menisci, a model was made out of modeling clay (Corfix®), until the anatomical structures were close to the real ones. The model consists of both menisci and the intercondylar eminence, simulating the proximal tibial articular surface. The model made out of modeling clay was the basis for the production of a thin Crystal Polyester Resin mold. Using the resin mold, the meniscal models were made of Silicone Rubber Type II, widely used in industry and crafts. Results: A functional and reproducible simulator was obtained, consisting of a knee model and an arthroscopic camera. The simulator works adequately adapted to a TV, monitor or computer, and allows the simulation of diagnostic procedures, meniscectomy and meniscoplasty. Conclusion: It is possible to develop a knee arthroscopy simulator, with components available in local and electronic commerce, at a cost of approximately R$ 300.

scholarly journals Detection & Classification of Cardiac Arrhythmia

2017 ◽  
Vol 6 (1) ◽  
pp. 31
Author(s):  
Chetan M. Jadhav ◽  
V. K. Bairagi
Keyword(s):  
Cardiac Arrhythmia ◽  
Early Stage ◽  
Low Cost ◽  
Simple Method ◽  
Arrhythmia Detection ◽  
Ecg Signals ◽  
Electrocardiogram Signals ◽  
Electrical Impulses ◽  
Very High

<p>The term Arrhythmia refers to any change from the normal sequence in the electrical impulses. It is also treated as abnormal heart rhythms or irregular heartbeats. The rate of growth of Cardiac Arrhythmia disease is very high &amp; its effects can be observed in any age group in society. Arrhythmia detection can be done in many ways but effective &amp; simple method for detection &amp; diagnosis of  Cardiac Arrhythmia is by doing analysis of Electrocardiogram signals from ECG sensors. ECG signal can give us the detail information of heart activities, so we can use ECG signals to detect the rhythm &amp; behaviour of heart beats resulting into detection &amp; diagnosis of Cardiac Arrhythmia. In this paper new &amp; improved methodology for early Detection &amp; Classification of Cardiac Arrhythmia has been proposed. In this paper ECG signals are captured using ECG sensors &amp; this ECG signals are used &amp; processed to get the required data regarding heart beats of the human being &amp; then proposed methodology applies for Detection &amp; Classification of Cardiac Arrhythmia. Detection of Cardiac Arrhythmia using ECG signals allows us for easy &amp; reliable way with low cost solution to diagnose Arrhythmia in its prior early stage.</p>

scholarly journals Valproic Acid-Like Compounds Enhance and Prolong the Radiotherapy Effect on Breast Cancer by Activating and Maintaining Anti-Tumor Immune Function

2021 ◽  
Vol 12 ◽  
Author(s):  
Zuchao Cai ◽  
David Lim ◽  
Guochao Liu ◽  
Chen Chen ◽  
Liya Jin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Valproic Acid ◽  
Tumor Recurrence ◽  
Early Stage ◽  
Low Cost ◽  
Inhibit Tumor Growth ◽  
Tnf Α ◽  
M1 Phenotype ◽  
Ifn Γ ◽  
Concurrent Cancer

Inadequate sustained immune activation and tumor recurrence are major limitations of radiotherapy (RT), sustained and targeted activation of the tumor microenvironment can overcome this obstacle. Here, by two models of a primary rat breast cancer and cell co-culture, we demonstrated that valproic acid (VPA) and its derivative (HPTA) are effective immune activators for RT to inhibit tumor growth by inducing myeloid-derived macrophages and polarizing them toward the M1 phenotype, thus elevate the expression of cytokines such as IL-12, IL-6, IFN-γ and TNF-α during the early stage of the combination treatment. Meanwhile, activated CD8+ T cells increased, angiogenesis of tumors is inhibited, and the vasculature becomes sparse. Furthermore, it was suggested that VPA/HPTA can enhance the effects of RT via macrophage-mediated and macrophage-CD8+ T cell-mediated anti-tumor immunity. The combination of VPA/HPTA and RT treatment slowed the growth of tumors and prolong the anti-tumor effect by continuously maintaining the activated immune response. These are promising findings for the development of new effective, low-cost concurrent cancer therapy.

scholarly journals A Natural Language Processing System for Extracting Evidence of Drug Repurposing from Scientific Publications

2020 ◽  
Vol 34 (08) ◽  
pp. 13369-13381
Author(s):  
Shivashankar Subramanian ◽  
Ioana Baldini ◽  
Sushma Ravichandran ◽  
Dmitriy A. Katz-Rogozhnikov ◽  
Karthikeyan Natesan Ramamurthy ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Generic Drugs ◽  
Low Cost ◽  
Processing System ◽  
Drug Repurposing ◽  
Cancer Type ◽  
Entity Extraction ◽  
Scientific Publications

More than 200 generic drugs approved by the U.S. Food and Drug Administration for non-cancer indications have shown promise for treating cancer. Due to their long history of safe patient use, low cost, and widespread availability, repurposing of these drugs represents a major opportunity to rapidly improve outcomes for cancer patients and reduce healthcare costs. In many cases, there is already evidence of efficacy for cancer, but trying to manually extract such evidence from the scientific literature is intractable. In this emerging applications paper, we introduce a system to automate non-cancer generic drug evidence extraction from PubMed abstracts. Our primary contribution is to define the natural language processing pipeline required to obtain such evidence, comprising the following modules: querying, filtering, cancer type entity extraction, therapeutic association classification, and study type classification. Using the subject matter expertise on our team, we create our own datasets for these specialized domain-specific tasks. We obtain promising performance in each of the modules by utilizing modern language processing techniques and plan to treat them as baseline approaches for future improvement of individual components.

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