소음진동분야에활용가능한딥러닝

Prof. Seungchul Lee

Industrial AI Lab.

강사소개

• 이승철교수 (포항공과대학교)

– 전임: 기계공학과

– 겸임: 산업경영공학과, 인공지능대학원

– 한국소음진동공학회 18대학술이사및평의원

– 한국설비진단자격인증원진동기술자격인증위원장

– KSPHM 창립멤버및교육이사

– KSME 편집이사, 인공지능머신연구회이사

• 관심분야: 산업인공지능, 소음진동, 자가진단

• http://iai.postech.ac.kr/

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생활속, 우리에게인공지능이란?

알파고 영상인식

자율주행자동차인공지능스피커

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변화는갑자기 (인공지능 ?)

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Systems

InformationKnowledge

Sensors

(Big) Data

First Principles

Statistics

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Systems

InformationKnowledge

Sensors

(Big) Data

First Principles

Statistics + Computer ScienceStatistics

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Systems

InformationKnowledge

Sensors

(Big) Data

First Principles

Artificial Intelligence (AI)

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Systems

InformationKnowledge

Sensors

(Big) Data

First Principles

Machine Learning and Deep Learning

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딥러닝, 소음진동분야에도유용한가?

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Data-driven Models: Deep Learning

• ANN: Universal function approximator– 물리법칙과아무런상관이없다

– 물리법칙을따르는시스템에서나온데이터를분석

• CNN: image pattern recognition– Best performance

• RNN: sequential data– Looks good, but difficult to train models

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Deep Learning

• Image of digit 0

• Image of digit 1

Image

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Machine Learning Deep Learning

Data

Features

Decision

Data

Decision

• Less depends on domain knowledge• AI-discovered features

Signal processing + Domain knowledge

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“ 딥러닝은기계학습보다는

Domain Knowledge의존도가 낮다. ”

Deep Learning

• Convolutional Neural Networks (CNN)

• Image pattern recognition problems

Image

0

1

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Deep Learning

• Convolutional Neural Networks (CNN)

• Image pattern recognition problems

Image

0

1

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Handwritten Digit Recognition

Ind

ust

rial

AI L

ab.

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Real-time Human Recognition

Industrial AI Lab.

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문제해결과정변화:데이터를잘준비하는것이더중요In

du

stri

al A

I Lab

.

Ind

ust

rial

AI L

ab.

“Change data. That’s it”

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Image Only? Sound Classification

Ind

ust

rial

AI L

ab.

Time Signal

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Image Only? Sound Classification

Ind

ust

rial

AI L

ab.

Time Signal

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진동신호를이미지로전처리하는방법들

• Spectrograms

Wavelet TransformSTFT

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2018년추계소음진동학술대회

Typical Data Types of Mechanical Systems

Vibration signal Temperature Sound signal

영상화 후 CNN 으로 분석

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에어콘조립검사: Sound Signal Classification

• Inspecting a rotating fan

• NG sound

• OK sound

In collaboration with Samsung Electronics 22

후두암진단

• Doctors can see the condition of the patients by their voice sounds

• Detecting pathological voice (dysphagia/aspiration, laryngeal cancer) by AI

– A model that tells which voice sounds have pathological symptoms

Normal Cancer

In collaboration with 부천성모병원 23

주목모델:인공지능이바라보는세상

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인공지능은어디를주목하고있는가?

• Ask AI what makes them different?

• Activation map (like a heat map)

원인영역시각화

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과연사람을바라보고있을까?

Industrial AI Lab.

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Cantilever

In collaboration with KIMM 27

Cantilever

Localizing the most vibrating regions without measuring vibration

공학과 인공지능이 만나는 순간

In collaboration with KIMM 28

Images for Vibration

Vibrating (1)Normal (0)

In collaboration with KIMM 29

시계열데이터

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인공지능

• Generally correct in ideal cases

• Difficult to reflect uncertainties in reality

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AI Core vs. AI + X

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(홍보) 인공지능온라인강좌

• 강의자료– 머신러닝

– 딥러닝

– 제어

– 신호처리

– http://iai.postech.ac.kr/index.php/machine-learning/

– http://iai.postech.ac.kr/index.php/tutorials/

• 동영상강의– YouTube

– iAI POSTECH 검색

– 구독

• 이번 tutorial 에서는자세한내용보다는큰그림위주로

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Tutorial 목차

1) 신호처리 (FFT & STFT)

2) 진동, 열, 음향신호분석을위한합성곱신경망 (CNN)

3) 설명가능한인공지능 (CAM)

4) 진동신호분석을위한순환신경망 (RNN)

5) 진동신호생성을위한적대적생성신경망 (GAN)

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