이상 감지

딥러닝 신경망을 비롯한 AI 모델을 사용해 신호 이상 감지

희소화된 시간-주파수 특징을 추출하여 전자기 데이터, 음향 데이터 및 진동 데이터에서 이상을 감지합니다.

함수

모두 확장

deepSignalAnomalyDetectorCreate signal anomaly detector (R2023a 이후)
audioDatastoreDatastore for collection of audio files
arrayDatastoreDatastore for in-memory data
signalDatastoreDatastore for collection of signals
imageDatastore이미지 데이터의 데이터저장소
waveletScatteringWavelet time scattering
signalTimeFeatureExtractorStreamline signal time feature extraction (R2021a 이후)
signalFrequencyFeatureExtractorStreamline signal frequency feature extraction (R2021b 이후)
signalTimeFrequencyFeatureExtractorStreamline signal time-frequency feature extraction (R2024a 이후)
stftLayerShort-time Fourier transform layer (R2021b 이후)
istftLayerInverse short-time Fourier transform layer (R2024a 이후)
cwtLayerContinuous wavelet transform layer (R2022b 이후)
icwtLayerInverse continuous wavelet transform layer (R2024b 이후)
modwtLayerMaximal overlap discrete wavelet transform layer (R2022b 이후)

관련 정보

추천 예제

Anomaly Detection Using Convolutional Autoencoder with Wavelet Scattering Sequences

Anomaly Detection Using Convolutional Autoencoder with Wavelet Scattering Sequences

Detect anomalies in acoustic data using wavelet scattering and the deepSignalAnomalyDetector object.

Detect Anomalies in Signals Using deepSignalAnomalyDetector

Detect Anomalies in Signals Using deepSignalAnomalyDetector

Use autoencoders to detect abnormal points or segments in time-series data.

Detect Anomalies in Machinery Using LSTM Autoencoder

Detect Anomalies in Machinery Using LSTM Autoencoder

Use a long short-term memory autoencoder to detect anomalies in data from an industrial machine.

Crack Identification from Accelerometer Data

Crack Identification from Accelerometer Data

Use wavelet and deep learning techniques to detect and localize transverse pavement cracks.

(Deep Learning Toolbox)

Detect Anomalies Using Wavelet Scattering with Autoencoders

Detect Anomalies Using Wavelet Scattering with Autoencoders

Learn how to develop an alert system for predictive maintenance using wavelet scattering and deep learning.

(Deep Learning Toolbox)

Fault Detection Using Wavelet Scattering and Recurrent Deep Networks

Fault Detection Using Wavelet Scattering and Recurrent Deep Networks

Classify faults in acoustic recordings of air compressors using a wavelet scattering network paired with a recurrent neural network.

(Deep Learning Toolbox)