کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1179638 1491530 2015 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An extensive reference dataset for fault detection and identification in batch processes
ترجمه فارسی عنوان
یک پایگاه داده مرجع گسترده برای تشخیص و شناسایی خطا در فرایندهای دسته ای
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
چکیده انگلیسی


• Extensive benchmark dataset for statistical process monitoring of batch processes
• 4 case studies, each of 400 normal and 22,200 faulty batches
• Processes upsets with of various type, magnitude, and onset time
• Good benchmark owing to range in detection difficulty

Close process monitoring (i.e., detection and identification of disturbances) is important to achieve high process efficiency and safety. The Tennessee Eastman process is an extensive benchmark dataset for fault detection and identification, but it is only representative for continuous processes because it does not contain the inherent non-stationarity that complicates monitoring of batch processes. Nevertheless, batch processes also play an important role in many types of industry. This paper therefore presents an extensive reference dataset for benchmarking data-driven methodologies for fault detection and identification in batch processes.The original Pensim model [10] is expanded with sensor noise. By changing the properties of the initial conditions and/or model parameters, four subsets of different complexity are generated, each containing 400 batches with normal operation. To correctly assess the fault detection and identification in batch processes, 15 faults are simulated with various amplitudes and onset times for a total of 22,200 faulty batches for each subset, or 90,400 batches in total.Analysis of the data indicates that the presented types of process faults and their various amplitudes in each of the four subsets present a suitable benchmark for fault detection and identification in batch processes. The dataset is freely available at http://cit.kuleuven.be/biotec/batchbenchmark.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 148, 15 November 2015, Pages 20–31
نویسندگان
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