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Related Concept Videos

Bus Impedance Matrix01:24

Bus Impedance Matrix

454
Calculating subtransient fault currents for three-phase faults in an N-bus power system involves using the positive-sequence network. When a three-phase short circuit occurs at a specific bus, the analysis uses the superposition method to evaluate two separate circuits.
In the first circuit, all machine voltage sources are short-circuited, leaving only the prefault voltage source at the fault location. The positive-sequence bus impedance matrix can be determined by solving the nodal equations,...
454
Multimachine Stability01:25

Multimachine Stability

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Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
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Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

660
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
660
Power System Three-Phase Short Circuits01:21

Power System Three-Phase Short Circuits

473
Determining the subtransient fault current in a power system involves representing transformers by their leakage reactances, transmission lines by their equivalent series reactances, and synchronous machines as constant voltage sources behind their subtransient reactances. In this analysis, certain elements are excluded, such as winding resistances, series resistances, shunt admittances, delta-Y phase shifts, armature resistance, saturation, saliency, non-rotating impedance loads, and small...
473

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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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An early fault detection method for induced draft fans based on MSET with informative memory matrix selection.

You Lv1, Fang Fang1, Tingting Yang1

  • 1Key Laboratory of Power Station Energy Transfer Conversion and System, North China Electric Power University, Changping District, Beijing 102206, China; School of Control and Computer Engineering, North China Electric Power University, Changping District, Beijing 102206, China.

ISA Transactions
|February 29, 2020
PubMed
Summary

This study introduces an early fault detection method for induced draft (ID) fans using Multivariate State Estimation Technique (MSET) and discrete particle swarm optimization (DPSO). The method enhances predictive maintenance and reduces unexpected shutdowns in industrial equipment.

Keywords:
Discrete particle swarm optimizationEarly fault detectionInduced draft fansMemory matrixMultivariate state estimation technique

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Area of Science:

  • Mechanical Engineering
  • Industrial Monitoring
  • Predictive Maintenance

Background:

  • Early fault detection in induced draft (ID) fans is crucial for industrial reliability.
  • Unscheduled shutdowns of ID fans lead to significant operational and economic losses.
  • Existing methods may lack the sensitivity for detecting incipient faults.

Purpose of the Study:

  • To develop an effective early fault detection method for ID fans.
  • To improve the reliability of ID fans through predictive maintenance.
  • To reduce unscheduled downtime in coal-fired power plants.

Main Methods:

  • Utilized discrete particle swarm optimization (DPSO) for informative memory matrix selection.
  • Developed a Multivariate State Estimation Technique (MSET) model using the selected memory matrix.
  • Defined a similarity index to assess equipment health status and provide early fault warnings.

Main Results:

  • The proposed MSET-based method with DPSO successfully identified early faults in an ID fan.
  • The informative memory matrix selection enhanced the accuracy of the MSET model.
  • The similarity index effectively indicated the health status of the ID fan.

Conclusions:

  • The proposed method offers a reliable approach for early fault detection in ID fans.
  • This technique can significantly improve the operational reliability of industrial equipment.
  • The application in a coal-fired power plant validates the method's effectiveness.