How to Detect Absorption Refrigerator Absorber Fouling

Overview of Technical Issues:

The absorber's heat exchange surfaces suffer from a harmful blocking and insulating effect caused by fouling deposits, which progressively reduces heat transfer capability and absorption efficiency, but current detection methods provide insufficient monitoring to identify when fouling reaches performance-degrading levels; the goal is to establish reliable detection techniques that enable timely maintenance intervention before significant refrigeration capacity loss occurs.

Solution directions generated for this problem

Problem Direction 1 :

ImproveFouling detection sensitivity
VS
ConstraintDetection system complexity

Inspiration 1 : Cross-domain reference

Application Principle: #26 Copying
Cross-domain applicability Assess applicability
Shuffle trump cards and manufacturing method thereof
Innovative Solution Refine solution

Thermal imaging surface mapping for non-contact fouling detection

Deploy single infrared camera for absorber surface mapping
How to solve :
  • Install fixed-mount thermal imaging camera (8-14μm spectral range, 320×240 resolution, ±0.1°C sensitivity) positioned 1.5-2.0m from absorber tube bundle exterior surface to capture full heat exchange zone
  • Configure automated scanning protocol every 4 hours during operation — camera captures 15-frame sequence over 30 seconds, software averages frames to eliminate noise and generates thermal distribution map with 0.15°C spatial resolution
  • Establish baseline thermal signature database during commissioning with clean tubes — fouling deposits create localized 0.3-0.8°C hot spots due to reduced local heat transfer, algorithm flags regions exceeding baseline by ≥0.25°C as fouling zones and calculates affected surface percentage for maintenance scheduling
Expected Effect : Detect fouling at 5-8% degradation; single camera replaces 20+ thermocouples; system complexity reduced 60%
Risk Control :
  • camera lens fouling from ambient moisture
  • thermal emissivity variation across tube surfaces
  • ambient temperature fluctuations affecting measurement baseline

Problem Direction 2 :

ImproveMeasurement signal resolution
VS
ConstraintMeasurement equipment reliability

Inspiration 1 : Cross-domain reference

Application Principle: #24 Intermediary
Cross-domain applicability Assess applicability
Methods and apparati for nondestructive detection of undissolved particles in a fluid
Innovative Solution Refine solution

Thermal transfer fluid well protection for precision fouling detection

Isolate sensors from corrosive environment using protective wells
How to solve :
  • Install precision RTD sensors (±0.1°C, Pt100 Class AA) inside sealed thermowell tubes filled with high-conductivity thermal transfer fluid (silicone oil ≥200 W/(m·K))
  • thermowell material is 316L stainless steel, wall thickness 0.6mm, immersion depth 80mm into absorber solution flow path
  • thermal fluid ensures <5 second response time while completely isolating sensor from corrosive lithium bromide solution
  • Deploy sensor arrays at 6 strategic locations (solution inlet/outlet, refrigerant inlet/outlet, mid-absorber bundle) to capture differential temperature signatures indicating early fouling (detectable at 5-8% heat transfer degradation vs current 15-20%)
  • Implement automated baseline drift compensation: weekly zero-point calibration using reference junction at stable ambient zone, quarterly verification against traceable standard (±0.05°C bath), sensor replacement only when drift exceeds ±0.15°C over 6 months—expected operational life extends from 6 months to 36+ months without recalibration
Expected Effect : Precision ±0.1°C maintained; sensor life 6× longer; early fouling detection at 5-8% degradation
Risk Control :
  • thermowell thermal resistance accumulation
  • seal integrity degradation
  • thermal fluid contamination over time

Problem Direction 3 :

ImproveHeat transfer monitoring capability
VS
ConstraintMeasurement equipment reliability

Inspiration 1 : Cross-domain reference

Application Principle: #10 Preliminary action
Cross-domain applicability Assess applicability
System and/or method for glucose sensor calibration
Innovative Solution Refine solution

Baseline-referenced continuous fouling detection with periodic high-precision calibration

Establish clean-state baseline during commissioning with high-precision sensors
How to solve :
  • During system commissioning or after cleaning, conduct 48-hour high-precision baseline campaign using protected ±0.1°C sensors in thermowell isolation to map clean heat transfer coefficient (U₀) across all operating loads (20–100% capacity, 10% intervals)
  • archive baseline as reference database
  • Implement continuous monitoring using existing robust sensors (standard ±0.5°C RTDs, solution pump current, refrigerant pressure) already installed for control—no additional hardware in corrosive zone—log data every 5 minutes to calculate operational heat transfer coefficient (U_op)
  • Execute quarterly 48-hour recalibration campaigns using the same protected high-precision sensors
  • compare U_op trends against baseline to detect fouling when (U₀ - U_op)/U₀ exceeds 5%
  • protected sensors operate <1% of time (4 days/year), extending service life from 6 months to 10+ years while maintaining ±0.1°C calibration accuracy
Expected Effect : Fouling detection at 5–7% degradation; sensor life 10× extension; zero added corrosion exposure
Risk Control :
  • baseline drift during quarterly intervals
  • load-dependent U₀ interpolation accuracy
  • existing sensor sampling rate insufficient

Problem Direction 4 :

ImproveMeasurement signal resolution
VS
ConstraintMust not deteriorate

Inspiration 1 : Cross-domain reference

Application Principle: #10 Preliminary action
Cross-domain applicability Assess applicability
Personalized gesture recognition for user interaction with assistant systems
Innovative Solution Refine solution

Baseline-referenced differential measurement with periodic high-precision calibration windows

Establish clean baseline during controlled startup phase with high-precision measurement
How to solve :
  • Perform high-precision baseline scan during system startup under stable no-load conditions (flow variation <2%, load <10%) using ±0.05°C resolution RTD sensors for 30 minutes, capturing clean heat transfer signature across 12 measurement zones
  • Store baseline temperature differentials, flow coefficients, and heat transfer coefficients in system memory as reference dataset
  • During normal operation, switch to robust ±0.3°C filtered measurement at 1-minute intervals, applying 5-point moving average to reject transient noise, then calculate deviation from stored baseline—fouling detected when zone-specific deviation exceeds 0.4°C for 3 consecutive hours
Expected Effect : Detect fouling at 5-8% degradation threshold; false alarm rate <2%; sensor life 36+ months; no additional hardware cost
Risk Control :
  • baseline drift over seasonal temperature changes
  • startup condition variability affecting reference accuracy
  • algorithm threshold tuning for different absorber designs
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