ISO 13379-2:2015 PDF

Name: ISO 13379-2:2015 — Condition monitoring and diagnostics of machines — Data interpretation and diagnostics techniques — Part 2: Data-driven applications
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Condition monitoring and diagnostics of machines — Data interpretation and diagnostics techniques — Part 2: Data-driven applications

Название (английский):

ISO 13379-2:2015

Condition monitoring and diagnostics of machines — Data interpretation and diagnostics techniques — Part 2: Data-driven applications

Статус документа:: Действующий
Формат:: Электронный (PDF)
Количество страниц:: 12
Дата публикации:: 8 апреля 2015 г.
Издание:: ISO IS 13379 edition 1 version 1
ICS:: 17.160

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Описание (английский):

ISO 13379-2:2015 gives procedures to implement data-driven monitoring and diagnostic methods to facilitate the work of analysis carried out by specialist staff typically located in a monitoring centre.

Abstract

Похожие стандарты

Стандарты, упомянутые в описании

Overview

ISO 13379-2:2015 - "Condition monitoring and diagnostics of machines - Data interpretation and diagnostics techniques - Part 2: Data‑driven applications" provides procedures for implementing data‑driven monitoring and diagnostic methods. It is focused on methods and workflows used by specialist staff (typically in a monitoring centre) to detect anomalies and identify faults by comparing observed process data to models of normal behaviour. Data sources include DCS/data historians and specialised monitoring systems.

Key topics and technical requirements

Scope and purpose

Procedures to build, initialize, tune and apply data‑driven models for condition monitoring and diagnostics.
Training approaches for monitoring (trained on normal behaviour) and diagnosis (trained on normal and fault conditions).

Data preparation

Data cleaning: identify and handle missing, noisy, out‑of‑range or stuck data; warning to exercise caution before deleting historical records.
Interpolation issues: beware of historian compression/linear interpolation that can distort correlations.
Resampling: resample data to appropriate rates (retain timestamps for transients; coarser sampling under steady state).

Model development

Select relevant features (raw or derived), grouped by function (mechanical, electrical, thermal).
Train models using data covering all expected operating conditions; build separate models for distinct operational modes where required.
Prepare and execute model tests; evaluate model performance and set alarms based on residuals (differences between observed and expected values).

Diagnostic methods

Pattern recognition and classification approaches for fault identification.
Examples of data‑driven algorithms noted: AAKR, PLS, SVM, Mahalanobis‑Taguchi (MT).

Practical recommendations

Competence needed to build and maintain models (deep statistical knowledge not mandatory, but practical experience is).
Consider additional sensors if existing data do not cover critical failure modes.

Applications

Predictive maintenance and anomaly detection for rotating equipment (e.g., turbines, pumps), process plants, HVAC and electrical systems.

Integration with plant historians, SCADA or specialised vibration/monitoring systems to detect abnormal behaviour and trigger alarms.

Use cases include online monitoring centres, condition monitoring programs, reliability and criticality analyses, and root‑cause diagnostics.

Related standards

ISO 13379-1 (General guidelines)

ISO 13379-3 (Knowledge‑based applications)

ISO 13372 (Vocabulary)

ISO 17359 (Implementation procedures and audits)

Keywords: ISO 13379-2, condition monitoring, data-driven monitoring, machine diagnostics, predictive maintenance, data cleaning, model development, anomaly detection, pattern recognition.

ISO 13379-2:2015 PDF

Abstract

Похожие стандарты

Overview

Key topics and technical requirements

Applications

Who should use this standard

Related standards

Технические детали

BS ISO 13379-1:2025

Condition monitoring and diagnostics of machine systems. Data interpretation and diagnostics techniques. Gene…

ISO 13372:2004

Condition monitoring and diagnostics of machines — Vocabulary

ISO 17359:2011

Condition monitoring and diagnostics of machines — General guidelines

ISO 13379:2003

Condition monitoring and diagnostics of machines — General guidelines on data interpretation and diagnostics…