Dynamic Noise Reduction with Deep Residual Shrinkage Networks for Online Fault Classification

Fault signals in high-voltage (HV) power plant assets are captured using the electromagnetic interference (EMI) technique. The extracted EMI signals are taken under different conditions, introducing varying noise levels to the signals. The aim of this work is to address the varying noise levels found in captured EMI fault signals, using a deep-residual-shrinkage-network (DRSN) that implements shrinkage methods with learned thresholds to carry out de-noising for classification, along with a time-frequency signal decomposition method for feature engineering of raw time-series signals. The approach will be to train and validate several alternative DRSN architectures with previously expertly labeled EMI fault signals, with architectures then being tested on previously unseen data, the signals used will firstly be de-noised and a controlled amount of noise will be added to the signals at various levels. DRSN architectures are assessed based on their testing accuracy in the varying controlled noise levels. Results show DRSN architectures using the newly proposed residual-shrinkage-building-unit-2 (RSBU-2) to outperform the residual-shrinkage-building-unit-1 (RSBU-1) architectures in low signal-to-noise ratios. The findings show that implementing thresholding methods in noise environments provides attractive results and their methods prove to work well with real-world EMI fault signals, proving them to be sufficient for real-world EMI fault classification and condition monitoring.

Entanglement of Square Nets in Covalent Organic Frameworks

Two entangled 2D square COFs have been synthesized from 4,4',4'',4'''-(9,9'-spirobi[fluorene]-2,2',7,7'-tetrayl)-tetrabenzaldehhyde (SFTB) and p-phenylenediamine (PPA) and benzidine (BZD) to form COF-38, [(SFTB)(PPA)2]imine and its isoreticular form COF-39, [(SFTB)(BZD)2]imine. We also report the single crystal electron diffraction structure of COF-39 and find that it is composed of mutually entangled 2D square nets (sql). These COFs represent the first examples of entangled 2D COF structures, which as we illustrate were made possible by our strategy of using the distorted tetrahedral SFTB building unit. SFTB overcomes the propencity of 2D COFs to stack through π-π stacking and allows for entanglements to form. This work adds significantly to the design principles of COFs.