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

Distribution Reliability and Automation01:25

Distribution Reliability and Automation

Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
Three-Phase Short Circuit—Unloaded Synchronous Machine01:21

Three-Phase Short Circuit—Unloaded Synchronous Machine

Conducting a three-phase short circuit test on an unloaded synchronous machine helps understand its impact on the system. The AC fault current's oscillogram, with the DC offset removed, reveals that the waveform amplitude decreases from an initially high value to a steady-state level for one phase of the machine.
This behavior occurs due to the magnetic flux produced by the short-circuit armature currents. Initially, these currents follow high-reluctance paths but eventually shift to...
Automated Microbial Diagnostics01:24

Automated Microbial Diagnostics

Automated diagnostic analyzers have transformed clinical microbiology by providing rapid and reliable methods for pathogen identification and antibiotic susceptibility testing. Among these systems, the Vitek 2 is widely used because it automates the traditionally labor-intensive processes of microbial identification (ID) and antibiotic susceptibility testing (AST), delivering standardized and timely results that are essential for effective patient care.Microbial Identification with ID CardsThe...

You might also read

Related Articles

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

Sort by
Same author

Macrophage-Dependent Intercellular Crosstalk in Multiphenotypic Heart Failure With Preserved Ejection Fraction.

Journal of the American Heart Association·2026
Same author

The relationship between vulnerable narcissism and body dissatisfaction among cosplayers: the serial mediating mechanisms of self-objectification and rumination.

Frontiers in psychology·2026
Same author

Single-nucleus RNA sequencing reveals the underlying roadmap of early gonadal differentiation in teleost.

Science China. Life sciences·2025
Same author

State of Health for Lithium-Ion Batteries Based on Explainable Feature Fragments via Graph Attention Network and Bi-Directional Gated Recurrent Unit.

Sensors (Basel, Switzerland)·2025
Same author

Reveals meat quality and muscle metabolism characteristics in naturally grazed Sunit sheep at different ages.

Food chemistry: X·2025
Same author

A novel splicing variant in TECTA associated with prelingual autosomal dominant nonsyndromic hearing loss via dominant-negative effect.

Human molecular genetics·2025

Related Experiment Video

Updated: Jul 7, 2026

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

A Data-Driven Loose Contact Diagnosis Method for Smart Meters.

Wenpeng Luan1, Yajuan Huang1, Bochao Zhao1

  • 1School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China.

Sensors (Basel, Switzerland)
|June 27, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a data-driven framework using Local Outlier Factor (LOF) and Multiple Linear Regression (MLR) for early detection of smart meter terminal faults, preventing fire hazards.

Keywords:
LOF methodMLR methodarc faultloose contactscrew terminalsmart metersvoltage differentials

More Related Videos

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
11:21

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

8.3K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

650

Related Experiment Videos

Last Updated: Jul 7, 2026

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
Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
11:21

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

8.3K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

650

Area of Science:

  • Electrical Engineering
  • Data Science
  • Predictive Maintenance

Background:

  • Loose screw terminals in smart meters cause overheating and arcing, leading to fire risks.
  • Early fault detection is crucial for mitigating these hazards and ensuring grid safety.

Purpose of the Study:

  • To propose a novel data-driven framework for early fault detection in smart meter terminals.
  • To accurately diagnose terminal contact degradation and associated fire hazards.

Main Methods:

  • Utilized voltage differentials from simulated smart meter data.
  • Integrated Local Outlier Factor (LOF) for arc fault detection (outlier identification).
  • Employed Multiple Linear Regression (MLR) for loose contact quantification (resistance analysis).

Main Results:

  • The LOF-MLR framework successfully identified arc faults and quantified loose contact resistance.
  • Demonstrated superior diagnostic accuracy and adaptability compared to traditional methods.
  • Validated robustness across diverse load conditions.

Conclusions:

  • The proposed data-driven framework effectively detects smart meter terminal faults, enhancing safety.
  • LOF and MLR integration offers a reliable solution for predictive maintenance in smart metering infrastructure.