Thermographic analysis of power oil transformer surface hot spot areas combined with analysis of acoustic signals recorded on line

2019 ◽  
Author(s):  
Agnieszka Lisowska Lis ◽  
Franciszek Witos ◽  
Grzegorz Szerszen
Keyword(s):  
Hot Spot ◽  
Acoustic Signals ◽  
On Line ◽  
Thermographic Analysis

Smartphone-based Handwritten Signature Verification using Acoustic Signals

2021 ◽  
Vol 5 (ISS) ◽  
pp. 1-26
Author(s):  
Run Zhao ◽  
Professor Dong Wang ◽  
Qian Zhang ◽  
Xueyi Jin ◽  
Ke Liu
Keyword(s):  
Information Exchange ◽  
Characteristic Curve ◽  
Acoustic Signals ◽  
Signature Verification ◽  
Special Device ◽  
Dominant Hand ◽  
Siamese Network ◽  
On Line ◽  
Handwritten Signature ◽  
Verification Techniques

Handwritten signature verification techniques, which can facilitate user authentication and enable secure information exchange, are still important in property safety. However, on-line automatic handwritten signature verification usually requires dynamic handwritten patterns captured by a special device, such as a sensor-instrumented pen, a tablet or a smartwatch on the dominant hand. This paper presents SonarSign, an on-line handwritten signature verification system based on inaudible acoustic signals. The key insight is to use acoustic signals to capture the dynamic handwritten signature patterns for verification. Particularly, SonarSign exploits the built-in speakers and microphones of smartphones to transmit a specially designed training sequence and record the corresponding echo for channel impulse response (CIR) estimation, respectively. Based on the sensitivity of CIR to the tiny surrounding environment changes including handwritten signature actions, SonarSign designs an attentional multi-modal Siamese network for end-to-end signatures verification. First, multi-modal CIR streams are fused to extract representative signature pattern features from spatio-temporal dimensions. Then an attentional Siamese network is elaborated to verify whether the given two signatures are from the same signatory. Extensive experiments in real-world scenarios show that SonarSign can achieve accurate and robust signatures verification with an AUC (Area Under ROC (Receiver Operating Characteristic) Curve) of 98.02% and an EER (Equal Error Rate) of 5.79% for unseen users.

Real-Time Temperature On-Line Monitoring and Analysis System for Transformers

2014 ◽  
Vol 521 ◽  
pp. 409-413 ◽  
Author(s):  
Ya Bo Chen ◽  
Yue Sun ◽  
Xu Ri Sun ◽  
Ge Hao Sheng ◽  
Xiu Chen Jiang
Keyword(s):  
Real Time ◽  
Hot Spot ◽  
Load Ratio ◽  
Distribution Transformers ◽  
Insulation Aging ◽  
On Line ◽  
Analysis System ◽  
Operation Status ◽  
Process Fault Diagnosis ◽  
Spot Temperature

The safe operation of power transformers mainly depends on proper functioning of insulation, whose status is revealed by temperatures. Applying ZigBee wireless network, a real-time temperature on-line monitoring and analysis system is developed to view the operation status of underground distribution transformers and process fault diagnosis. Furthermore, using the top-oil and hot-spot temperature calculation method in IEEE Std C57.91-1995, the system can compute a prediction of those temperatures with current load ratio and ambient temperature. System will display early warnings if temperatures are much higher than expected ones, in which way insulation aging can be handled in advance. Insulation fault and big disasters will be prevented.

Risk Based Inspection (RBI) Technology in the Application of Syngas-Purification Units

2012 ◽  
Author(s):  
Zhifeng Li ◽  
Zhengxiang Wang ◽  
Junke Miao ◽  
Hui Wang
Keyword(s):  
Failure Mechanism ◽  
Chemical Industry ◽  
Hot Spot ◽  
Clean Energy ◽  
Risk Level ◽  
Corrosion Failure ◽  
On Line ◽  
Purification Unit ◽  
Gasification Reaction ◽  
Purification Equipment

In recent years, the coal chemical industry project which can replace the petrochemical products is an investment hot spot. The Syngas-purification Unit is a main part of the coal chemical industry. Its role is: purify the syngas obtained from the gasification reaction (absorb the hydrogen sulfide and carbon dioxide). Yet, there is no research and the summary about the corrosion, failure mechanism and risk level of this unit. In this paper, the syngas-purification equipment of Sinopec Qilu Corporation were quantified by RBI analysis, and investigated the corrosion of the syngas-purification equipment, and discussed the device typical failure mechanism, and proposed the recommendations of the corrosion and on-line monitoring, etc. In last few years, the production of clean energy and alternative oil chemical products from the new coal chemical projects become of great interest[1]. Because the purification of the syngas is necessary, the syngas-purification unit is one of the main equipment of coal chemical industry. In the country, there is no systematic study or summary about the corrosion, failure mechanism and risk level of the device. The RBI analysis of the Syngas-purification unit is necessary, and has some guiding significance for the routine maintenance and periodic inspection of the device. This paper introduces the corrosion and the typical failure mechanism of Syngas-purification unit followed by the risk assessment results. Then the paper puts forward the suggestion on line monitoring.

An Adaptive Smart Sensor Network for Overhead Lines Thermal Rating Prediction

2008 ◽  
Vol 9 (4) ◽  
Author(s):  
Alfredo Vaccaro ◽  
Domenico Villacci
Keyword(s):  
Sensor Network ◽  
Thermal State ◽  
Hot Spot ◽  
Experimental Studies ◽  
Load Level ◽  
Assessment Tools ◽  
Smart Sensor ◽  
Overhead Lines ◽  
Reliable Assessment ◽  
On Line

The need for dynamic loading of overhead lines requires reliable assessment tools that should be able to predict both the evolution of the hot-spot temperature and the associated maximum allowed duration, at any load level and on the basis of the actual conductor thermal state and environmental conditions. In order to address this problem, the paper proposes the employment of a smart sensor network distributed along the line route. Each network's node, starting from on-line measurements, assesses, by an indirect method of parameter identification, the value of the main variables which regulate the heat exchange between the conductor and its surrounding. Then, starting from these data, each node calculates the load capability curve by solving iteratively a built in dynamic thermal model and transmits the results to a central server by a cooperative based communication paradigm. To assess the performances of the proposed solution, experimental studies obtained on a laboratory overhead line are presented and discussed.

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