Data for the 9 figures contained in the paper, A SOFTWARE FRAMEWORK FOR ASSESSING THE RESILIENCE OF DRINKING WATER SYSTEMS TO DISASTERS WITH AN EXAMPLE EARTHQUAKE CASE STUDY. This dataset is associated with the following publication: Klise, K., M. Bynum, D. Moriarty, and R. Murray. A SOFTWARE FRAMEWORK FOR ASSESSING THE RESILIENCE OF DRINKING WATER SYSTEMS TO DISASTERS WITH AN EXAMPLE EARTHQUAKE CASE STUDY. ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY, 95: 420-431, (2017).

We are pleased to share the dataset SEED-PQD-v1 (SEED Power Quality Distrubance Dataset v1) used in our study titled "XPQRS: Expert power quality recognition system for sensitive load applications," published in Elsevier Journal Measurement. This dataset is invaluable for researchers and practitioners in the field of power quality analysis, especially those focusing on sensitive load applications. This dataset can be used in Python as well as in MATLAB.

Access the published paper:

https://www.sciencedirect.com/science/article/abs/pii/S0263224123004530

Dataset Details:

Fundamental Frequency: 50 Hz

Sampling Rate: 5 kHz

Number of Classes: 17

Signals per Class: 1000

Length of Each Signal (samples): 100

Length of Each Signal (time): 20 ms

Amplitude of Each Signal: Scaled between -1 to 1

Data Format:

The dataset is available in two formats: MATLAB and CSV.

MATLAB File:

Filename: 5Kfs_1Cycle_50f_1000Sam_1A.mat

Structure: A matrix of dimensions (1000 x 100 x 17), where:

1000 = Signals per class

100 = Samples per signal

17 = Number of classes

Class Order:

Pure_Sinusoidal

Sag

Swell

Interruption

Transient

Oscillatory_Transient

Harmonics

Harmonics_with_Sag

Harmonics_with_Swell

Flicker

Flicker_with_Sag

Flicker_with_Swell

Sag_with_Oscillatory_Transient

Swell_with_Oscillatory_Transient

Sag_with_Harmonics

Swell_with_Harmonics

Notch

CSV Files:

Files: 17 CSV files, one for each class.

Structure: Each CSV file has dimensions (1000 x 100), where:

1000 = Signals per class

100 = Samples per signal

Usage:

This dataset is designed to support the development and testing of power quality recognition systems. The 17 classes cover a broad range of power quality disturbances, providing a comprehensive resource for training machine learning models and validating their performance in recognizing various types of power quality issues.

Acknowledgements:

All users of the dataset are advised to cite the following article:

Citation: Muhammad Umar Khan, Sumair Aziz, Adil Usman, XPQRS: Expert power quality recognition system for sensitive load applications, Measurement, Volume 216, 2023, 112889, ISSN 0263-2241, https://doi.org/10.1016/j.measurement.2023.112889. Link to the article

Thank you for your interest in our work. We hope this dataset facilitates further advancements in power quality analysis and related fields.keywords: Power Quality Recognition, Power Quality Classification, Electrical Signal Analysis, Power System Disturbances, Signal Processing, Power Quality Monitoring

Secondary Data from Insights from Publishing Open Data in Industry-Academia Collaboration

Authors

Per Erik Strandberg [1], Philipp Peterseil [2], Julian Karoliny [3], Johanna Kallio [4], and Johannes Peltola [4].

[1] Westermo Network Technologies AB (Sweden).
[2] Johannes Kepler University Linz (Austria)
[3] Silicon Austria Labs GmbH (Austria).
[4] VTT Technical Research Centre of Finland Ltd. (Finland).

Description

This data is to accompany a paper submitted to Elsevier's data in brief in 2024, with the title Insights from Publishing Open Data in Industry-Academia Collaboration.

Tentative Abstract: Effective data management and sharing are critical success factors in industry-academia collaboration. This paper explores the motivations and lessons learned from publishing open data sets in such collaborations. Through a survey of participants in a European research project that published 13 data sets, and an analysis of metadata from almost 281 thousand datasets in Zenodo, we collected qualitative and quantitative results on motivations, achievements, research questions, licences and file types. Through inductive reasoning and statistical analysis we found that planning the data collection is essential, and that only few datasets (2.4%) had accompanying scripts for improved reuse. We also found that authors are not well aware of the importance of licences or which licence to choose. Finally, we found that data with a synthetic origin, collected with simulations and potentially mixed with real measurements, can be very meaningful, as predicted by Gartner and illustrated by many datasets collected in our research project.

Secondary data from Survey

The file survey.txt contains secondary data from a survey of participants that published open data sets in the 3-year European research project InSecTT.

Secondary data from Zenodo

The file secondary_data_zenodo.json contains secondary data from an analysis of data sets published in Zenodo. It is accompanied with a py-file and a ipynb-file to serve as examples.

License

This data is licenced with the Creative Commons Attribution 4.0 International license. You are free to use the data if you attribute the authors. Read the license text for details.

The advantages of choosing The Lens as an abstract base for identifying relevant publication topics in a given subject area:Open access to data, possibility of simultaneous export of up to 50 thousand bibliometric records, advanced analytics.The data exported from The Lens database can be used in the most commonly utilized programs for bibliometric analysis — VOSviewer and Bibliometrix.The Lens issues — to analyze publication topics (author's interests) in this system, the Keywords and Abstract fields are poorly populated.Characteristics of The Len's base as of September 29, 2024:Scholarly Works (280,455,781) = All Docs; 134M Analytics Set; 41.5M Authors; 1.3M Source Titles; 698K Fields of Study; 353 Journal Subjects; 5.9M Keywords; 254.2K Chemicals; 30.6K MeSH Headings; 41.4M Institutions; 2.6M Funding Organizations; 4.6K Conferences.698K Fields of Study — is a very detailed classification of bibliometric data that can be used similarly to Index Keywords in Scopus and Keywords plus in WoS.The approach proposed in this study is to populate the Keywords and Abstract fields in The Lens with data taken from the bibliometric data of the respective publishers, which are usually very well populated.Taking into account the interests of the author of this paper, the data of Elsevier publisher available in the open ScienceDirect database corresponding to the query are chosen as an example: 'Title, abstract, keywords: digital energy; Article type: Review articles and Research articles; Years: 2020–2024; Subject areas: Engineering, Materials Science and Energy; Languages: English'. Data are current as of September 16, 2024.Omitting the details of data export and preprocessing, the final file used in the VOSviewer and Bibliometrix programs contained 3373 bibliometric records.

Link to the paper. This dataset is associated with the following publication: Naile, J., A.W. Garrison, J. Avants, and J. Washington. Isomers/enantiomers of perfluorocarboxylic acids: Method development and detection in environmental samples. CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 144: 1722-1728, (2016).

Abstract

We developed a methodology to detect the oldest scholarly reference added to Wikipedia articles by which a certain paper is uniquely identifiable as the "first appearance of the scholarly reference." We identified the first appearances of 923,894 scholarly references (611,119 unique DOIs) in180,795 unique pages on English Wikipedia as of March 1, 2017, and stored them in the dataset. Moreover, we assessed the precision of the dataset, which was and it was a high precision regardless of the research field. In this version, it is available not only the dataset of English Wikipedia as of March 1, 2017, but also English Wikipedia as of October 1, 2021, generated by using the same methodology.

Data Records

The data format of the dataset is JSON lines, where each line is a single record. In this dataset, we detected the first appearance of each scholarly reference added to Wikipedia articles. If there are multiple references corresponding to the same paper on the same page, only the oldest one is collected. Sample of the record is the following.

• doi -- DOI corresponding to the paper (String), e.g., "10.1006/anbe.1996.0497"
• paper_type -- Document type of the paper (String), e.g., "journal-article"
• paper_container_title -- Journal title, book title, or proceedings title (Array of String), e.g., ["Animal Behaviour"]
• paper_publisher -- Publisher name (String), e.g., "Elsevier BV"
• paper_title -- Paper title (Array of String), e.g., ["Push or pull: an experimental study on imitation in marmosets"]
• paper_published_year -- Published year (String), e.g., "1997"
• paper_issue -- Issue number (String), e.g., "4"
• paper_volume -- Volume number (String), e.g., "54"
• paper_page -- Page numbers (String), e.g., "817-831"
• paper_author -- Authors information consisted of given and family names, sequences (order in author names), and affiliations (Array of JSON), e.g., [{"given":"THOMAS", "family":"BUGNYAR", "sequence":"first", "affiliation":[]}, {"given":"LUDWIG", "family":"HUBER", "sequence":"additional", "affiliation":[]}]
• issn -- ISSN related to the paper (Array of String), e.g., ["0003-3472"]
• research_field -- Research fields from ESI categories (Array of String), e.g., ["PLANT & ANIMAL SCIENCE"]
• page_id -- Page id (String), e.g., "577858"
• page_title -- Page title (String), e.g., "Imitation"
• revision_id -- Revision id (String), e.g., "203309031"
• revision_timestamp -- Revision timestamp (String), e.g., "2008-04-04 15:54:09 UTC"
• revision_comment -- Revision comment (edit summary) (String), e.g., "/* Animal Behaviour */"
• editor_name -- Wikipedia editor's name (String), e.g., "Nicemr"
• editor_type -- Type of the editor (String), e.g., "User"

References

• Kikkawa, J., Takaku, M. & Yoshikane, F. "Dataset of first appearances of the scholarly bibliographic references on Wikipedia articles", Scientific Data, Vol. 9, Article number 85, pp. 1-11, 2022. https://doi.org/10.1038/s41597-022-01190-z.

FUNDING

• JSPS KAKENHI Grant Number JP20K12543
• JSPS KAKENHI Grant Number JP21K21303

Overview of the quality assurance and quality control that supports the data analysis across all papers.

This dataset is associated with the following publication: Batt , A., E. Furlong, H. Mash , S. Glassmeyer , and D. Kolpin. The importance of quality control in validating concentrations of contaminants of emerging concern in source and treated drinking water samples.. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 579: 1618-1628, (2017).

Food and Energy Security Impact Factor 2024-2025 - ResearchHelpDesk - Food and Energy Security is a high quality and high impact open access journal publishing original research on agricultural crop and forest productivity to improve food and energy security. Aims and Scope Food and Energy Security seeks to publish high quality and high impact original research on agricultural crop and forest productivity to improve food and energy security. It actively seeks submissions from emerging countries with expanding agricultural research communities. Papers from China, other parts of Asia, India and South America are particularly welcome. The Editorial Board, headed by Editor-in-Chief Professor Christine Foyer, is determined to make FES the leading publication in its sector and will be aiming for a top-ranking impact factor. Primary research articles should report hypothesis-driven investigations that provide new insights into mechanisms and processes that determine productivity and properties for exploitation. Review articles are welcome but they must be critical in approach and provide particularly novel and far-reaching insights. Food and Energy Security offers authors a forum for the discussion of the most important advances in this field and promotes an integrative approach of scientific disciplines. Papers must contribute substantially to the advancement of knowledge. Examples of areas covered in Food and Energy Security include: Agronomy Biotechnological Approaches Breeding & Genetics Climate Change Quality and Composition Food Crops and Bioenergy Feedstocks Developmental, Physiology, and Biochemistry Functional Genomics Molecular Biology Pest and Disease Management Political, economic and societal influences on food security and agricultural crop production Post Harvest Biology Soil Science Systems Biology The journal is Open Access and published online. Submission of manuscripts to Food and Energy Security is exclusive via a web-based electronic submission and tracking system enabling rapid submission to first decision times. Before submitting a paper for publication, potential authors should first read the Author Guidelines. Instructions as to how to upload your manuscript can be found on ScholarOne Manuscripts. Keywords Agricultural economics, Agriculture, Bioenergy, Biofuels, Biochemistry, Biotechnology, Breeding, Composition, Development, Diseases, Feedstocks, Food, Food Security, Food Safety, Forestry, Functional Genomics, Genetics, Horticulture, Pests, Phenomics, Plant Architecture, Plant Biotechnology, Plant Science, Quality Traits, Secondary Metabolites, Social policies, Weed Science. Abstracting and Indexing Information Abstracts on Hygiene & Communicable Diseases (CABI) AgBiotechNet (CABI) AGRICOLA Database (National Agricultural Library) Agricultural Economics Database (CABI) Animal Breeding Abstracts (CABI) Animal Production Database (CABI) Animal Science Database (CABI) CAB Abstracts® (CABI) Current Contents: Agriculture, Biology & Environmental Sciences (Clarivate Analytics) Environmental Impact (CABI) Global Health (CABI) Nutrition & Food Sciences Database (CABI) Nutrition Abstracts & Reviews Series A: Human & Experimental (CABI) Plant Breeding Abstracts (CABI) Plant Genetics and Breeding Database (CABI) Plant Protection Database (CABI) Postharvest News & Information (CABI) Science Citation Index Expanded (Clarivate Analytics) SCOPUS (Elsevier) Seed Abstracts (CABI) Soil Science Database (CABI) Soils & Fertilizers Abstracts (CABI) Web of Science (Clarivate Analytics) Weed Abstracts (CABI) Wheat, Barley & Triticale Abstracts (CABI) World Agricultural Economics & Rural Sociology Abstracts (CABI) Society Information The Association of Applied Biologists is a registered charity (No. 275655), that was founded in 1904. The Association's overall aim is: 'To promote the study and advancement of all branches of Biology and in particular (but without prejudice to the generality of the foregoing), to foster the practice, growth, and development of applied biology, including the application of biological sciences for the production and preservation of food, fiber, and other materials and for the maintenance and improvement of earth's physical environment'.

Food and Energy Security - ResearchHelpDesk - Food and Energy Security is a high quality and high impact open access journal publishing original research on agricultural crop and forest productivity to improve food and energy security. Aims and Scope Food and Energy Security seeks to publish high quality and high impact original research on agricultural crop and forest productivity to improve food and energy security. It actively seeks submissions from emerging countries with expanding agricultural research communities. Papers from China, other parts of Asia, India and South America are particularly welcome. The Editorial Board, headed by Editor-in-Chief Professor Christine Foyer, is determined to make FES the leading publication in its sector and will be aiming for a top-ranking impact factor. Primary research articles should report hypothesis-driven investigations that provide new insights into mechanisms and processes that determine productivity and properties for exploitation. Review articles are welcome but they must be critical in approach and provide particularly novel and far-reaching insights. Food and Energy Security offers authors a forum for the discussion of the most important advances in this field and promotes an integrative approach of scientific disciplines. Papers must contribute substantially to the advancement of knowledge. Examples of areas covered in Food and Energy Security include: Agronomy Biotechnological Approaches Breeding & Genetics Climate Change Quality and Composition Food Crops and Bioenergy Feedstocks Developmental, Physiology, and Biochemistry Functional Genomics Molecular Biology Pest and Disease Management Political, economic and societal influences on food security and agricultural crop production Post Harvest Biology Soil Science Systems Biology The journal is Open Access and published online. Submission of manuscripts to Food and Energy Security is exclusive via a web-based electronic submission and tracking system enabling rapid submission to first decision times. Before submitting a paper for publication, potential authors should first read the Author Guidelines. Instructions as to how to upload your manuscript can be found on ScholarOne Manuscripts. Keywords Agricultural economics, Agriculture, Bioenergy, Biofuels, Biochemistry, Biotechnology, Breeding, Composition, Development, Diseases, Feedstocks, Food, Food Security, Food Safety, Forestry, Functional Genomics, Genetics, Horticulture, Pests, Phenomics, Plant Architecture, Plant Biotechnology, Plant Science, Quality Traits, Secondary Metabolites, Social policies, Weed Science. Abstracting and Indexing Information Abstracts on Hygiene & Communicable Diseases (CABI) AgBiotechNet (CABI) AGRICOLA Database (National Agricultural Library) Agricultural Economics Database (CABI) Animal Breeding Abstracts (CABI) Animal Production Database (CABI) Animal Science Database (CABI) CAB Abstracts® (CABI) Current Contents: Agriculture, Biology & Environmental Sciences (Clarivate Analytics) Environmental Impact (CABI) Global Health (CABI) Nutrition & Food Sciences Database (CABI) Nutrition Abstracts & Reviews Series A: Human & Experimental (CABI) Plant Breeding Abstracts (CABI) Plant Genetics and Breeding Database (CABI) Plant Protection Database (CABI) Postharvest News & Information (CABI) Science Citation Index Expanded (Clarivate Analytics) SCOPUS (Elsevier) Seed Abstracts (CABI) Soil Science Database (CABI) Soils & Fertilizers Abstracts (CABI) Web of Science (Clarivate Analytics) Weed Abstracts (CABI) Wheat, Barley & Triticale Abstracts (CABI) World Agricultural Economics & Rural Sociology Abstracts (CABI) Society Information The Association of Applied Biologists is a registered charity (No. 275655), that was founded in 1904. The Association's overall aim is: 'To promote the study and advancement of all branches of Biology and in particular (but without prejudice to the generality of the foregoing), to foster the practice, growth, and development of applied biology, including the application of biological sciences for the production and preservation of food, fiber, and other materials and for the maintenance and improvement of earth's physical environment'.

ABSTRACT Background: Dystonia is a heterogeneous disorder that, when refractory to medical treatment, may have a favorable response to deep brain stimulation (DBS). A practical way to have an overview of a research domain is through a bibliometric analysis, as it makes it more accessible for researchers and others outside the field to have an idea of its directions and needs. Objective: To analyze the 100 most cited articles in the use of DBS for dystonia treatment in the last 30 years. Methods: The research protocol was performed in June 2019 in Elsevier’s Scopus database, by retrieving the most cited articles regarding DBS in dystonia. We analyzed authors, year of publication, country, affiliation, and targets of DBS. Results: Articles are mainly published in Movement Disorders (19%), Journal of Neurosurgery (9%), and Neurology (9%). European countries offer significant contributions (57% of our sample). France (192.5 citations/paper) and Germany (144.1 citations/paper) have the highest citation rates of all countries. The United States contributes with 31% of the articles, with 129.8 citations/paper. The publications are focused on General outcomes (46%), followed by Long-term outcomes (12.5%), and Complications (11%), and the leading type of dystonia researched is idiopathic or inherited, isolated, segmental or generalized dystonia, with 27% of articles and 204.3 citations/paper. Conclusions: DBS in dystonia research is mainly published in a handful of scientific journals and focused on the outcomes of the surgery in idiopathic or inherited, isolated, segmental or generalized dystonia, and with globus pallidus internus as the main DBS target.

This dataset contains NO "numeric" digital data, only scanned field log sheets, and hydrological sampling results sheets. The paper records have now been destroyed. The hydrological samples were collected at the wharf beside CSIRO Marine Laboratories, Castray Esplanade, Hobart, Tasmania between November 1984 and December 1986. Sampling was undertaken to determine if the water quality off the wharf was suitable for use in a planned for aquarium facility (This was not built). Sampling was …Show full descriptionThis dataset contains NO "numeric" digital data, only scanned field log sheets, and hydrological sampling results sheets. The paper records have now been destroyed. The hydrological samples were collected at the wharf beside CSIRO Marine Laboratories, Castray Esplanade, Hobart, Tasmania between November 1984 and December 1986. Sampling was undertaken to determine if the water quality off the wharf was suitable for use in a planned for aquarium facility (This was not built). Sampling was conducted approximately daily at 2m, and weekly at 1m, 3m, 5m and 7m. Samples were analysed for temperature, salinity, dissolved oxygen, phosphate and nitrate. This "Coastal Station" was not part of the national coastal station scheme. - Although the links below are labeled "Graphic", as they are scanned images of the log sheets rather than "numbers", the sheets contain the values of analysed parameters. The PDF files are supplied individually, rather than as a single ZIP archive due to the large file size. Read Notes_on_CL_Logs.txt for a brief description of the contents of each PDF file. Note: Gustaaf M. Hallegraeff (CSIRO)joined by taking weekly phytoplankton water samples 1986-87 with a focus on quantitatively monitoring the toxic dinoflagellate Gymnodinium catenatum . A brief account appeared in: G.M. HALLEGRAEFF, S.O. STANLEY, C.J. BOLCH & S.I. BLACKBURN (1989). Gymnodinium catenatum blooms and shellfish toxicity in Southern Tasmania, Australia. In:T.Okaichi, D.M.Anderson & T.Nemoto (eds), Red tides: Biology, Environmental Science and Toxicology, pp.75-78. Elsevier - The Data Centre does NOT hold a copy of the phytoplankton data.

Context

Flenley et al. stated the problem of automatic pollen images recognition more than 50 years ago. It requires solving two tasks: detection and classification. Nowadays, both tasks can be successfully handled using computer vision (CV) methods. However, the main obstacle in these tasks solving is the absence of big open datasets for benchmarking. Existing open datasets for pollen classification task (POLEN23E, POLLEN73S) are quite small and represent different domains, thus, their merging is not straightforward. Moreover, there is no open pollen dataset annotated for the detection task.

Thus, here we present the largest open pollen dataset obtained from the bright-field microscope, including 20 plant species, 2413 images containing 7745 single pollen grains, annotated for the classification and detection tasks.

Content

The images in the dataset are obtained using lighting microscope Olympus BX51. Pollen is stained with Fuchsin. The dataset is made using the Olympus DP71 image viewing system. All the pollen species were collected from Perm Krai, Russia, but typical for Europe in common.

The dataset is related to two domains: allergenic-specific palynology and mellisopalynology. Hence, it contains 13 taxa of allergenic plants (willow, linden, alder, birch, nettle, pigweed, plantain, sorrel, grass, pine, maple, hazel, mugwort) and 8 taxa of honey plants (linden, buckwheat, clover, angelica wild, angelica garden, hill mustard, meadow pink, fireweed).

The allergenic dataset we call POLLEN13L-det. We set the baseline for the detection and recognition on this dataset, see the paper [link to be provided]. We achieved 96.3% of average precision for the detection task and 98.34% of F1 measure for the classification task.

Cite

To cite our dataset, please use Khanzhina, Natalia, et al. "Combating data incompetence in pollen images detection and classification for pollinosis prevention." Computers in biology and medicine 140 (2022): 105064.

or

@article{khanzhina2022combating, title={Combating data incompetence in pollen images detection and classification for pollinosis prevention}, author={Khanzhina, Natalia and Filchenkov, Andrey and Minaeva, Natalia and Novoselova, Larisa and Petukhov, Maxim and Kharisova, Irina and Pinaeva, Julia and Zamorin, Georgiy and Putin, Evgeny and Zamyatina, Elena and others}, journal={Computers in biology and medicine}, volume={140}, pages={105064}, year={2022}, publisher={Elsevier} }

Acknowledgements

This dataset is collected with the great help of Larisa Novoselova, Irina Kharisova, Julia Pinaeva and Georgiy Zamorin.

Inspiration

Researchers are welcome to solve the detection and classification tasks :) Although we set relatively high baseline scores on these tasks, there is still the room for improvement. For example, there are two species that belong to one genus - angelica wild and angelica garden - its shape is almost the same even to most of palynologists, which significantly complicates the recognition.

Make pollen recognition great again!

Context

This dataset contains the machine data of a degrading component recorded over the duration of 12 month total. It was initiated in the European research and innovation project IMPROVE.

Content

The Vega shrink-wrapper from OCME is deployed in large production lines in the food and beverage industry. The machine groups loose bottles or cans into set package sizes, wraps them in plastic film and then heat-shrinks the plastic film to combine them into a package. The plastic film is fed into the machine from large spools and is then cut to the length needed to wrap the film around a pack of goods. The cutting assembly is an important component of the machine to meet the high availability target. Therefore, the blade needs to be set-up and maintained properly. Furthermore, the blade can not be inspected visually during operation due to the blade being enclosed in a metal housing and its fast rotation speed. Monitoring the cutting blades degradation will increase the machines reliability and reduce unexpected downtime caused by failed cuts.

For more information see also this new vs worn blade data.

The 519 files in the dataset are of the format MM-DDTHHMMSS_NUM_modeX.csv, where MM is the month ranging from 1-12 (not calendar month), DD is the day of the month, HHMMSS is the start time of day of recording, NUM is the sample number and X is a mode ranging from 1-8. Each file is a ~8 second sample with a time resolution of 4ms that totals 2048 time-samples for every file.

Acknowledgements

This dataset is publicly available for anyone to use under the following terms.

von Birgelen, Alexander; Buratti, Davide; Mager, Jens; Niggemann, Oliver: Self-Organizing Maps for Anomaly Localization and Predictive Maintenance in Cyber-Physical Production Systems. In: 51st CIRP Conference on Manufacturing Systems (CIRP CMS 2018) CIRP-CMS, May 2018.

Paper available open access: https://authors.elsevier.com/sd/article/S221282711830307X

IMPROVE has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 678867

Inspiration

Show the degradation of the component over the course of the year. Has the component been replaced at some point? If the wear can be predicted accurately, a remaining useful life prediction can be made in order to determine maintenance windows (predictive maintenance).

There are 8 different modes and several different speeds that the machine can be operated in. Is it possible to infer such modes by time series analysis?