Crimp Force Curve Dataset
Raw data from measurements or recordings
2025
Subject: Time Series; Manufacturing; Quality Control; Crimping
DOI: 10.7910/DVN/WBDKN6
Details
Description
The "Crimp Force Curve Dataset" is a comprehensive collection of univariate time series data representing crimp force curves recorded during the manufacturing process of crimp connections. This dataset has been designed to support a variety of applications, including anomaly detection, fault diagnosis, and research in data-driven quality assurance.
A salient feature of this dataset is the presence of high-quality labels. Each crimp force curve is annotated both by a state-of-the-art crimp force monitoring system - capable of binary anomaly detection - and by domain experts who manually classified the curves into detailed quality classes. The expert annotations provide a valuable ground truth for training and benchmarking machine learning models beyond anomaly detection.
The dataset is particularly well-suited for tasks involving time series analysis, such as training and evaluating of machine learning algorithms for quality control and fault detection. It provides a substantial foundation for the development of generalisable, yet domain-specific (crimping), data-driven quality control systems.
The data is stored in a Python pickle file crimp_force_curves.pkl, which is a binary format used to serialize and deserialize Python objects. It can be conveniently loaded into a pandas DataFrame for exploration and analysis using the following command:
df = pd.read_pickle("crimp_force_curves.pkl")
This dataset is a valuable resource for researchers and practitioners in manufacturing engineering, computer science, and data science who are working at the intersection of quality control in manufacturing and machine learning.
Creators/Owners
Debug: Alles
Autoren: Hofmann B
Datum: None
Year: 2025
Beschreibung: The "Crimp Force Curve Dataset" is a comprehensive collection of univariate time series data representing crimp force curves recorded during the manufacturing process of crimp connections. This dataset has been designed to support a variety of applications, including anomaly detection, fault diagnosis, and research in data-driven quality assurance.
A salient feature of this dataset is the presence of high-quality labels. Each crimp force curve is annotated both by a state-of-the-art crimp force monitoring system - capable of binary anomaly detection - and by domain experts who manually classified the curves into detailed quality classes. The expert annotations provide a valuable ground truth for training and benchmarking machine learning models beyond anomaly detection.
The dataset is particularly well-suited for tasks involving time series analysis, such as training and evaluating of machine learning algorithms for quality control and fault detection. It provides a substantial foundation for the development of generalisable, yet domain-specific (crimping), data-driven quality control systems.
The data is stored in a Python pickle file crimp_force_curves.pkl, which is a binary format used to serialize and deserialize Python objects. It can be conveniently loaded into a pandas DataFrame for exploration and analysis using the following command:
df = pd.read_pickle("crimp_force_curves.pkl")
This dataset is a valuable resource for researchers and practitioners in manufacturing engineering, computer science, and data science who are working at the intersection of quality control in manufacturing and machine learning.
Subject: Time Series; Manufacturing; Quality Control; Crimping
Verf: 320704969
Publ-Datum: None
Datentyp: 234405601
Anderer Datentyp:
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Groesse: 0
Einheit: 0
EOrgs: <QuerySet []>
FOBE: <QuerySet []>
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