presented by, gokul narayanan, p.e – asec, inc. locke

SEPTEMBER 4 - 6, 2019

ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING FOR INSPECTION OF TRANSMISSION LINES

Presented by,Gokul Narayanan, P.E – ASEC, Inc.Locke Brillhart – Kleinfelder, Inc.


ProjectOverview

Data Collection

ArtificialIntelligence Benefits


Determining conductor issues and severity of damage for a 51-mile transmission line by ground inspection

Time & Money QualitySafety


As an alternative to a ground inspection of all 51-miles of transmission line Kleinfelder utilized UAS/Drones to inspect all conductors

Completed in 1/3 of the estimated time

Saved over $50,000 in overall budget

Gathered 4 times as many photos than ground

inspection w/bird’s eye view

Deployed only 2 technicians and no

bucket trucks


CODE FIELDOBSERVATIONS

STRUCTURE NUMBERS COMMENTS

BIR 4 155,189,259,331 Bird flying/perchedBDC 5 109,110,301,302,306 Broken/Damaged

conductorBSW 1 Between 324 & 325 Shield strands frayedDIS 29 10,14,23,33,42, 53,83,87,112,114,120,121,130,136,137,141,

142,144,146,147,151,160,193,196,208,303,324,329,350Discoloration around

damper clamp

MIS 4 126,129,135,306 Missing dampersDIM 2 140,143 Damper distance not

typicalDDE 5 1,11,15,24,284 Discolored at Deadend SC 5 169,249,250,251,307 Soiled (by birds)

SPA 1 90 Spalling concreteTotal 56


Good Suspect Unknown


Machine Learning algorithms use computational

methods to “learn” information directly from data without

relying on a predetermined equation as a

model.


1000’s of Images

Improveswith more

Data

HomogeneousSmall Corpus

ROITraining

VSManual

Tenets of AIFairnessAccountabilityTransparencyEthics

AccuracyHumanVSMachine


Filters & Reductions

Math Transforms

Good 0.9Damaged 0.1

Deep Neural Net

Labeled Image

Convolution


Good

• 91 Good• 2 Suspect

• 24 Suspect• 6 Good

Suspect

• 4 Unknown• 51 Good• 22 Suspect

Unknown

200Test

Photos


SuspectGood

Unknown


Efficiency

Quali

ty

Traditional Approach

UAS/Human Review

Artificial Intelligence

Efficiency


QUESTIONS?

presented by, gokul narayanan, p.e – asec, inc. locke

Documents