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Land Transport

Pump equipment fault diagnosis system

 

Solution Background

The ship's engine room transmission mechanism refers to the system in a ship used to transmit power and bear loads, mainly composed of components such as thrust bearings, intermediate bearings, and propeller shafts subjected to load.

The bearing status and shaft system installation status directly affect the smooth operation of the shaft system and the navigation performance of the ship. Therefore, health monitoring of the ship's engine room transmission mechanism is of great significance!

Solution Introduction

Solution Overview

Utilizing an external data acquisition mode, a fault analysis and intelligent diagnosis model integrating feature mechanisms and machine learning is established; through iterative optimization of the model with large amounts of data, precise fault identification and localization are achieved; through an application-oriented visual modeling platform, evaluation of equipment fault diagnosis, assessment, and health status trends is realized subjected to load.

Applicable Scenarios

  • Petrochemical Industry: Solving the challenge of high-temperature and high-pressure pump seal failure early warning
  • Municipal Water Affairs: Achieving hierarchical health status management for water intake pump station units
  • Power Energy: Precisely diagnosing early signs of cavitation in boiler feed pumps
  • Smart Manufacturing: Preventing sudden downtime of production line cooling circulation pumps

Core Functions

  • Multi-dimensional Perception Fusion Diagnosis

External vibration/temperature/pressure sensing network compatible with 95% of mainstream pump types

Original "Physical Feature + Deep Feature" fusion analysis framework: The mechanism model library covers 9 major categories of typical fault modes, including centrifugal pumps and plunger pumps

  • Self-Evolving Diagnosis Engine

The diagnostic model automatically iterates every 72 hours, continuously adapting to equipment degradation characteristics

Built-in knowledge graph system automatically consolidates expert diagnostic experience

Solution Benefits

  • Maintenance costs reduced by 40%: Transition from reactive repair to precise maintenance
  • Equipment lifespan extended by 30%: Establishing a scientific health assessment system
  • Production efficiency increased by 25%: Avoiding losses from unplanned downtime
  • Knowledge Digitalization: Building an enterprise-specific fault diagnosis knowledge base

Application Case Examples

Case Study 1: Fault Diagnosis and Health Management of Key Equipment on a Certain Naval Vessel

Pain Point The ship's transmission system is critical equipment; a failure would result in mission termination, leading to significant safety risks and economic losses
Solution Multi-dimensional sensor perception + intelligent algorithm model + visualization platform to achieve equipment fault diagnosis, evaluation, and health status trend assessment
Effect Maintenance costs reduced by 40%: transitioning from reactive repair to precise maintenance; equipment lifespan extended by 30%: establishing a scientific health assessment system

 

 

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Solution Introduction

Application Cases

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