Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

4.8K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
4.8K
Fault Types01:18

Fault Types

147
When analyzing a single line-to-ground fault from phase A to ground at a three-phase bus, it is important to consider the fault impedance. This impedance is zero for a bolted fault, equal to the arc impedance for an arcing fault, and represents the total fault impedance for a transmission-line insulator flashover. To derive sequence and phase currents, fault conditions are translated from the phase domain to the sequence domain.
For line-to-line faults occurring between phases B and C, the...
147
Root-Locus Method01:19

Root-Locus Method

231
A cruise control system in a car is designed to maintain a specified speed automatically by adjusting the gas pedal. The system continuously measures the vehicle's speed and makes fine adjustments to the pedal to achieve this goal. The root locus method is particularly useful for understanding how the cruise control system's behavior changes under varying conditions, such as when the car goes uphill, downhill, or faces strong wind resistance.
This system can be represented by a block...
231
Plotting and Calibrating the Root Locus01:19

Plotting and Calibrating the Root Locus

201
Root loci often diverge as system poles shift from the real axis to the complex plane. Key points in this transition are the breakaway and break-in points, indicating where the root locus leaves and reenters the real axis. The branches of the root locus form an angle of 180/n degrees with the real axis, where n is the number of branches at a breakaway or break-in point.
The maximum gain occurs at the breakaway points between open-loop poles on the real axis, while the minimum gain is...
201
Properties of the Root Locus01:05

Properties of the Root Locus

175
The root locus method is an invaluable tool for analyzing higher-order systems without needing to factor the denominator of the transfer function. A pole of the system is identified when the characteristic polynomial in the transfer function's denominator equals zero.
To determine if a point lies on the root locus, the criterion involves the sum of angles contributed by all poles and zeros to that point. Specifically, this sum must be an odd multiple of 180 degrees. The gain at any point on...
175
Block Diagram Reduction01:22

Block Diagram Reduction

321
The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
321

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Tumor-Mimic Artificial Cell Integrated With In Situ Synthetic Biology for Testing of Antitumor Drug Sensitivity.

Exploration (Beijing, China)·2026
Same author

Profiling major volatile components in apricot fruit sheds light on the molecular mechanisms underlying low-temperature-mediated volatile release.

Food chemistry. Molecular sciences·2026
Same author

Decitabine inhibits the malignant transformation of oral potentially malignant disorders by upregulating SOX1 expression via demethylation to modulate the wnt pathway in a male rat model.

Archives of oral biology·2026
Same author

The nigrostriatal dopaminergic pathway mediates state-dependent emergence from propofol anesthesia in mice.

Brain research bulletin·2026
Same author

Subthalamic CaMKIIα-expressing neurons facilitate recovery from propofol anesthesia via the STN-ventral pallidum pathway.

Cell biology and toxicology·2026
Same author

The interplay of heatwaves, air pollution, and green space on all-cause mortality in older adults with diabetes mellitus: a national cohort study.

BMC public health·2026
Same journal

Application of ephrin-B2 loaded glycol chitosan-silk fibroin hydrogel in the treatment of diabetic refractory wounds.

Scientific reports·2026
Same journal

International expert Delphi consensus on thromboprophylaxis in metabolic and bariatric surgery.

Scientific reports·2026
Same journal

Assessing the cross-region knowledge transfer capability of selected deep learning building vectorization methods in the context of available training datasets.

Scientific reports·2026
Same journal

Feasibility and preliminary effects of outdoor versus indoor cognitive-motor therapy in women with Alzheimer's disease: A randomized single-blind pilot study.

Scientific reports·2026
Same journal

Hallmarks of social action in the vocal turn-taking of wild common marmosets (Callithrix jacchus).

Scientific reports·2026
Same journal

Role and mechanism of AOPPs-induced NOX4-mediated ferroptosis in intervertebral disc degeneration.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Oct 10, 2025

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.9K

Minimalist module analysis for fault detection and localization.

Zhijiang Lou1, Youqing Wang2, Shan Lu3

  • 1Institute of Intelligence Science and Engineering, Shenzhen Polytechnic, Shenzhen, 518055, China.

Scientific Reports
|December 8, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces minimalist module analysis (MMA), a new method for multivariate statistical-based process monitoring (MSPM). MMA improves fault detection and localization by effectively handling redundant variable correlations in industrial processes.

More Related Videos

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.8K
Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

9.4K

Related Experiment Videos

Last Updated: Oct 10, 2025

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.9K
Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.8K
Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

9.4K

Area of Science:

  • Industrial Process Monitoring
  • Statistical Process Control
  • Data Analytics

Background:

  • Multivariate statistical-based process monitoring (MSPM) methods are widely used for industrial process monitoring.
  • Existing MSPM methods struggle with redundant correlations among process variables, impacting monitoring accuracy.
  • There is a need for advanced methods to enhance fault detection and localization in complex industrial systems.

Purpose of the Study:

  • To propose a novel MSPM method, Minimalist Module Analysis (MMA), to address the limitations of traditional approaches.
  • To develop new monitoring indices and a fault localization strategy specifically for MMA.
  • To evaluate the performance of MMA in fault detection and localization through simulation.

Main Methods:

  • Minimalist Module Analysis (MMA) divides process data into distinct modules with strong internal correlations and minimal redundancy.
  • Each module's independent feature extraction prevents noise interference from other modules.
  • New monitoring indices and a fault localization strategy are developed based on the MMA framework.

Main Results:

  • MMA effectively handles redundant correlations between process variables.
  • Simulation tests show MMA achieves superior performance in fault detection compared to traditional methods.
  • MMA demonstrates enhanced capabilities in accurately localizing process faults.

Conclusions:

  • Minimalist Module Analysis (MMA) offers a significant advancement in multivariate statistical-based process monitoring.
  • The proposed method provides improved accuracy and robustness in identifying and locating process anomalies.
  • MMA is a promising approach for enhancing the reliability and safety of large-scale industrial processes.