Measure Non-Uniform Corrosion Using Fiber-Optic Sensing
Overview of Technical Issues:
The fiber-optic sensing element insufficiently detects non-uniform corrosion patterns because localized pitting and crevice corrosion create highly variable spatial damage that the sensing system cannot resolve with adequate precision, resulting in missed detection of critical localized corrosion zones and undetected structural failure risks; the goal is to achieve reliable measurement of spatially varying corrosion across the metal structure.
Problem Direction 1 :
ImproveSpatial sampling density
VSConstraintSystem complexity
Inspiration 1 : Cross-domain reference
Application Principle: #1 Segmentation
Cross-domain Case Inspiration
This patent improves data processing quantity (throughput) by [segmenting] the datapath into offloadable stages and distributing workload selectively, while preventing system complexity deterioration through modular isolation and shared memory coordination. It demonstrates how [segmentation] enables scalable resource allocation—high-density processing where needed, standard processing elsewhere—directly paralleling the contradiction of increasing spatial sampling density without proportionally increasing fiber-optic system complexity.
Edge datapath using user space network stack
Innovative Solution View detail
Adaptive zone-partitioned fiber-optic corrosion sensing with dynamic resolution allocation
Partition structure into risk zones with adaptive sensor density allocation
How to solve :
- Divide metal structure into three corrosion risk zones: Zone A (welds, crevices, joints — 15–20% area) deploys 1–2mm spacing fiber sensors
- Zone B (moderate-risk surfaces — 25–30% area) uses 5mm spacing
- Zone C (low-risk flat areas — 50–60% area) maintains 20–50mm spacing, reducing total sensor count by 65–75%
- Install modular fiber cassettes with pre-calibrated spacing (1mm, 5mm, 20mm) using snap-fit mounting brackets
- each cassette contains integrated wavelength-division multiplexed (WDM) fiber Bragg gratings interrogated by single optical channel per zone, avoiding channel multiplication
- Implement dynamic reallocation protocol: when Zone B/C sensors detect corrosion indicators (strain change ≥50 με or temperature anomaly ≥2°C), temporarily deploy portable 1mm-resolution inspection modules to affected 100×100mm sub-areas within 24 hours, then return to standard monitoring — concentrates high-resolution capacity on active sites without permanent deployment
Expected Effect : Sensor count reduced 70%, 1–3mm pitting detection maintained, system complexity equivalent to 15mm uniform spacing
Risk Control :
- risk zone mapping accuracy insufficient
- modular cassette optical coupling loss ≥0.5dB
- dynamic reallocation response delay exceeds corrosion progression rate
Inspiration 2 : Technology in this field
Search: High spatial resolution fiber optic sensing, Localized pitting corrosion detection, Enhanced spatial sampling techniques, Optical surface monitoring systems, Multi-point fiber sensor arrays
Existing SolutionView detail
Distributed Fiber-Optic Sensing with Algorithmic Spatial Interpolation for Sub-5mm Corrosion Detection
Use distributed fiber sensors with algorithmic spatial filtering to achieve effective sub-5mm corrosion resolution
How to solve :
- Deploy side-illuminated fiber-optic sensors at 5-10mm physical spacing using distributed sensing architecture (Reference 6 methodology), achieving baseline spatial sampling while maintaining single-fiber simplicity
- Apply pattern recognition algorithms adapted from Reference 1 profilometry methods to interpolate between physical sensing points, filtering surface roughness (threshold ≥20μm noise suppression) and identifying clustered corrosion signatures indicative of 1-3mm localized pitting through moving-average windowing (7-pixel kernel) and statistical clustering
- Integrate white light interferometry principles (Reference 1) with fiber Bragg grating strain sensing to detect depth variations of 0.01-0.1mm resolution, correlating spectral shifts with localized metal loss and distinguishing pitting (isolated deep events) from general corrosion (uniform shallow loss) via cumulative distribution function analysis of depth data
Expected Effect : Effective 1-3mm corrosion detection resolution with 5-10mm physical sensor spacing; 60-80% reduction in optical channel requirements versus direct 1-3mm spacing
Risk Control :
- Algorithm accuracy in distinguishing pitting from surface roughness on curved structures
- Fiber alignment precision maintenance under thermal cycling and mechanical vibration
- Computational processing latency for real-time monitoring applications
Problem Direction 2 :
ImproveSpatial sampling density
VSConstraintData processing burden
Inspiration 1 : Cross-domain reference
Application Principle: #10 Preliminary action
Cross-domain Case Inspiration
This patent improves information quantity and quality (analogous to 'Quantity of substance') by resolving and fusing entity records from multiple sources through [preliminary deduplication, attribute fusion, and classification], while avoiding processing time deterioration ('Loss of time') by reducing downstream computational load—directly paralleling the need to handle increased corrosion scan data volume without extending processing cycles.
Resolving entities from multiple data sources for assistant systems
Innovative Solution View detail
Hierarchical edge-computing architecture with adaptive corrosion feature extraction for real-time high-density fiber-optic monitoring
Deploy edge processors at fiber interrogators to extract corrosion features before central transmission
How to solve :
- Install FPGA-based edge processors at each fiber interrogator unit (every 10-20m of fiber) to perform real-time signal filtering, corrosion signature extraction, and anomaly classification before data transmission—reduces central processing load by 85-92%
- Apply trained convolutional neural network models (CNN) at edge nodes to identify corrosion-specific spectral patterns (strain rate >50 με/day, temperature gradient >2°C/m) and transmit only 8-15% flagged anomaly data plus compressed baseline snapshots (JPEG2000, compression ratio 20:1) to central system
- Implement hierarchical processing protocol—edge nodes execute fast Fourier transform and wavelet decomposition (processing time <500ms per 1000 data points), extract 12-18 key features (peak amplitude, frequency centroid, kurtosis), central system performs correlation analysis and predictive modeling only on pre-filtered datasets, maintaining total scan cycle <8 minutes for 100× data volume increase
Expected Effect : Processing time maintained at 5-8 min despite 100× data increase; corrosion detection latency <10 min; false negative rate <3%
Risk Control :
- edge processor synchronization drift across distributed nodes
- CNN model accuracy degradation under environmental noise (temperature variation ±15°C, vibration 0-50Hz)
- network bandwidth bottleneck during simultaneous multi-zone anomaly events
Inspiration 2 : Technology in this field
Search: Real-time data processing algorithms, High-frequency data acquisition, Web-based remote monitoring, Process control integration, Digital signal processing
Existing SolutionView detail
Hierarchical Edge Computing with Adaptive Spatial Filtering for High-Density Fiber-Optic Corrosion Data Processing
Implement distributed edge computing architecture with real-time corrosion data processing at sensor level to enable continuous trending within same time frame as process parameters
How to solve :
- Deploy edge processors at fiber-optic interrogator units performing real-time pattern recognition using digital signal processing techniques to identify corrosion signatures, filtering out non-corrosive baseline data and reducing transmission volume by 70-85%
- Implement hierarchical data aggregation where edge nodes pre-classify spatial regions into high-risk (active corrosion), medium-risk (trending), and low-risk (stable) zones using residue analysis and threshold detection, transmitting only anomalous data and statistical summaries for stable regions
- Apply adaptive sampling algorithms that dynamically adjust measurement frequency based on detected corrosion rates—increasing to 1-3mm resolution in active zones while maintaining 10-20mm spacing in stable areas, using forgetting factors (λ=0.92-0.997) to weight recent data appropriately for varying corrosion rates
Expected Effect : Processing time maintained under 5 minutes for 100× data volume; 75% reduction in central processing load
Risk Control :
- Edge processor reliability in harsh environments
- Algorithm accuracy for corrosion pattern classification
- Network bandwidth management for distributed architecture
Problem Direction 3 :
ImproveMeasurement spatial resolution
VSConstraintSystem complexity
Inspiration 1 : Cross-domain reference
Application Principle: #2 Taking out (Extraction)
Cross-domain Case Inspiration
This patent improves network performance by [extracting] and dynamically allocating virtualized resources only where needed, rather than deploying full capacity everywhere. This directly mirrors the current contradiction of improving measurement precision while preventing device complexity increase by selectively deploying high-resolution sensing.
Network virtualization apparatus and method with scheduling capabilities
Innovative Solution View detail
Selective high-resolution fiber deployment with corrosion-risk mapping for localized pitting detection
Deploy high-resolution fiber only in corrosion-prone zones identified by risk mapping
How to solve :
- Perform corrosion susceptibility mapping using electrochemical impedance spectroscopy (EIS) and metallurgical analysis to identify high-risk zones (welds, crevices, galvanic interfaces) covering 15–25% of total structure surface
- Install ultra-high-resolution fiber segments (1–3mm spatial resolution using OFDR interrogation at 10 µm gauge length) exclusively in mapped high-risk zones, while deploying standard 20–50mm resolution fiber in low-risk flat surfaces
- Implement dynamic zone reclassification protocol — quarterly EIS rescanning updates risk map, triggering high-resolution fiber redeployment to newly identified corrosion initiation sites within 48 hours, maintaining adaptive coverage without permanent system-wide density increase
Expected Effect : Hardware reduction 70–80%; 1–3mm resolution in critical zones; total optical channels reduced from 1000+ to 150–200
Risk Control :
- initial risk mapping accuracy <85%
- corrosion initiation in unmapped zones
- fiber redeployment response delay
Inspiration 2 : Technology in this field
Search: Multi-electrode array sensor, Scanning electrochemical microscopy, Chemical imaging sensor, Optical measurement system, Electrochemical noise detection
Existing SolutionView detail
Distributed Fiber-Optic Sensing with Spatially-Resolved Rayleigh Backscatter Interrogation for High-Resolution Corrosion Detection
Use distributed fiber-optic sensing based on high-resolution corrosion mapping without multiplying hardware channels
How to solve :
- Deploy optical frequency domain reflectometry (OFDR) or phase-sensitive OTDR (φ-OTDR) with continuous single-mode fiber along metal structure, achieving 1-3mm spatial sampling through Rayleigh backscatter analysis at measurement frequencies 10-50 kHz
- Apply strain-corrosion correlation algorithms processing localized strain anomalies (≥50 με) caused by pitting-induced thickness loss, using pre-calibrated lookup tables relating pit depth (0.1-2mm) to strain signatures
- Implement swept-wavelength laser interrogation (1520-1570nm, 0.16pm resolution) with single optical channel serving 10-40m fiber length, replacing 300-1000 discrete FBG sensors while maintaining sub-millimeter defect localization through coherent detection and digital signal processing with moving-average filtering (7-pixel window) to distinguish corrosion clusters from surface roughness noise
Expected Effect : 1-3mm spatial resolution; single-channel hardware for 10m+ sensing length; 50× reduction in optical components vs. FBG arrays
Risk Control :
- Fiber-metal interface bonding durability under corrosive exposure
- strain transfer accuracy from localized pitting to optical fiber core
- real-time processing of high-density backscatter data streams
Problem Direction 4 :
ImproveMeasurement spatial resolution
VSConstraintData processing burden
Inspiration 1 : Cross-domain reference
Application Principle: #5 Merging (Combining)
Cross-domain Case Inspiration
This patent improves resource utilization efficiency (analogous to measurement precision) by [combining/splitting] buffer data across multiple processing nodes while preventing communication delay deterioration (loss of time). It demonstrates how [merging] parallel processing paths with intelligent data distribution resolves the contradiction between handling granular data and maintaining speed, directly echoing the current need to process fine-resolution measurements without time penalty.
Efficient uplink scheduling mechanisms for dual connectivity
Innovative Solution View detail
Parallel multi-channel fiber interrogation with distributed processing architecture for real-time corrosion monitoring
Parallel processing via multi-channel architecture
How to solve :
- Divide continuous distributed fiber-optic sensor (DFOS) into 8-16 independent interrogation channels, each covering 5-10m structure length with 1mm spatial resolution
- deploy dedicated FPGA-based edge processors (≥200 GFLOPS) at each channel to perform parallel wavelet decomposition and corrosion feature extraction simultaneously, reducing total scan time from sequential hours to parallel 3-8 minutes
- Implement two-tier data filtering: Tier-1 applies fast Fourier transform at 10kHz sampling to extract corrosion-indicative frequency bands (2-15 Hz strain oscillations), transmitting only 8-12% flagged segments
- Tier-2 central processor performs detailed convolutional neural network analysis on flagged zones using pre-trained corrosion progression models (trained on 10,000+ pitting samples), achieving 2-3mm pitting detection within 5-minute total cycle
- Use wavelength-division multiplexing (WDM) with 16-channel optical demultiplexer to interrogate all fiber segments simultaneously at distinct wavelengths (1525-1565nm, 2.5nm spacing), eliminating sequential scanning delays and enabling true parallel acquisition with <0.5s per channel
Expected Effect : Processing time reduced from 120-180min to 5-8min; 1.5mm pitting detection capability; 85-92% data volume reduction via edge filtering
Risk Control :
- FPGA processing latency variation under thermal drift
- optical channel crosstalk in WDM system
- CNN model accuracy degradation for novel corrosion morphologies
Inspiration 2 : Technology in this field
Search: Scanning Electrochemical Microscopy, High Resolution Surface Mapping, Real-time Corrosion Monitoring, Computational Image Analysis, Area vs Point Measurement
Existing SolutionView detail
Hierarchical Spatial Sampling with Adaptive Zone Refinement for Real-Time Localized Corrosion Detection
Implement a two-tier fiber-optic sensing architecture combining macro measurement at standard 10-50mm intervals with micro measurement zones at 1-3mm resolution in high-risk areas
How to solve :
- Deploy macro-resolution fiber Bragg grating (FBG) sensors at 10-50mm spacing across entire structure for baseline monitoring, with distributed Rayleigh scattering sensors at 1-3mm resolution in pre-identified corrosion-prone zones (welds, crevices, stress concentrations)
- Apply real-time linear regression analysis on macro data to detect anomalous strain/temperature patterns indicating corrosion initiation, triggering automatic activation of adjacent micro-resolution zones
- Use parallel processing architecture with dedicated processors for each micro-zone (similar to reference [10]'s macro/micro calculation sections), performing digital subtraction of baseline vs. current measurements to quantify metal loss within 2-5 minutes per scan cycle
Expected Effect : Processing time <5 min for 100+ measurement points; detection sensitivity 0.1mm pit depth; 85% reduction in continuous high-resolution data volume
Risk Control :
- Accurate pre-identification of high-risk zones requiring micro-resolution coverage
- calibration stability between macro and micro sensor systems
- computational load balancing across parallel processors
Problem Direction 5 :
ImproveSpatial sampling density
VSConstraintMust not deteriorate
Inspiration 1 : Cross-domain reference
Application Principle: #1 Segmentation
Cross-domain Case Inspiration
This patent applies [Segmentation] to improve quantity of substance (sensor density) while preventing deterioration of system complexity through simplified 1T pixel structure and cascoded readout circuits, directly paralleling the current contradiction of achieving dense detection coverage without overwhelming data processing capacity.
CCD-based multi-transistor active pixel sensor array
Innovative Solution View detail
Risk-stratified hierarchical fiber-optic sensing network with zone-adaptive spatial resolution
Divide structure into risk zones with adaptive sampling density
How to solve :
- Perform corrosion susceptibility mapping using electrochemical impedance spectroscopy (EIS) and historical failure data to classify structure into three zones: Zone-A (welds, crevices, galvanic interfaces—15-25% area) requiring 1-3mm fiber spacing, Zone-B (moderate-risk flat surfaces—30-40% area) with 10mm spacing, Zone-C (low-risk areas—40-50% area) with 50mm spacing
- Deploy segmented fiber-optic arrays with zone-specific interrogators: Zone-A uses high-NA (numerical aperture ≥0.22) multicore fiber with OFDR (optical frequency domain reflectometry) achieving 1mm resolution, Zone-B uses standard single-mode fiber with FBG arrays at 10mm intervals, Zone-C uses low-cost plastic optical fiber at 50mm spacing
- Implement column-level data aggregation where each zone's interrogator performs local signal processing—Zone-A outputs only corrosion probability indices (binary flags), Zone-B transmits averaged strain values per 50mm segment, Zone-C reports threshold-exceeded alerts only, reducing total data throughput by 85-92% compared to uniform 1-3mm coverage
Expected Effect : Total sensor count reduced 60-75%; data volume reduced 85-92%; 1-3mm pitting detection in critical zones maintained; scan cycle <8 minutes
Risk Control :
- Zone boundary misclassification causing coverage gaps
- fiber routing complexity at zone interfaces
- interrogator synchronization drift between zones
Inspiration 2 : Technology in this field
Search: Image-based pit detection and sizing, 3D surface mapping and reconstruction, Electrochemical sensing methods, Multi-point ultrasonic inspection, Statistical pit analysis algorithms
Existing SolutionView detail
Spatially-Adaptive Fiber-Optic Array with Signature-Based Pit Detection
Deploy fiber-optic sensor array with spatially-adaptive sampling density using signature library correlation method
How to solve :
- Implement segmented field fiber-optic sensor array with variable drive-sense gaps (0.5-3mm spacing in critical zones, 10-20mm in low-risk areas) using multiplexed sensing channels
- establish pit signature library containing response patterns for pits of 0.25-3mm diameter and 0.5-5mm depth through calibration samples with drilled flat-bottom holes, correlating transimpedance measurements at multiple frequencies (2.56-40.96 kHz) with pit geometry
- apply shape filtering algorithm using moving average window (7-element) and pattern recognition to distinguish genuine corrosion pits from surface roughness noise, calculating correlation coefficients between measured responses and library signatures to identify pits when correlation exceeds 0.5 threshold, enabling depth estimation through filtered response amplitude mapping
Expected Effect : Detect 1mm diameter pits at 95% reliability; reduce data volume by 60% through adaptive sampling
Risk Control :
- Signature library completeness for varied pit morphologies
- optical fiber durability under thermal cycling
- correlation threshold calibration for different alloy compositions
