The implementation of A3S information fusion algorithm for interpreting Dissolved Gas Analysis (DGA) based on Doernenburg Ratio

Bachri, Karel Octavianus; Sumari, Arwin Datumaya Wahyudi; Soedjarno, Bambang Anggoro; Ahmad, Adang Suwandi

doi:10.1109/isesd.2017.8253360

Cited by 6 publications

(5 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the DTM and DPM versions proposed in the previous section, DGA samples extracted from [5,6,13,14,[22][23][24][25][26][27][28][29][30][31] were used to validate the proposed modifications in the methods, as shown in Tables A1-A3. The DGA samples used were identified in their references as D1 or D2 faults or oil contamination from OLTC gases.…”

Section: Results-application Of Proposed Dtm and Dpm To Dga Data Extr...mentioning

confidence: 99%

See 1 more Smart Citation

Distinction between Arcing Faults and Oil Contamination from OLTC Gases

Bustamante,

Martinez Lastra,

Manana

et al. 2024

Electronics

View full text Add to dashboard Cite

Power transformers are the most important and expensive assets in high-voltage power systems. To ensure an adequate level of reliability throughout the transformer’s lifetime, its maintenance strategy must be well defined. When an incipient fault occurs in the transformer insulation, a gas concentration pattern, representative of the type of fault, is generated. Fault-identification methods use gas concentrations and their ratios to identify the type of fault. None of the traditional or new fault-identification methods attempt to detect transformer oil contamination from on-load tap changer (OLTC) gases. In this study, from dissolved gas analysis (DGA) samples of transformers identified as contaminated in a previous study, fault-identification methods based on graphical representations were used to observe the patterns of results. From such patterns, Duval’s triangle and pentagon methods were modified to include a new zone indicating oil contamination (OC) from OLTC gases. Finally, the proposed modifications were validated using 75 DGA samples extracted from previous studies that were identified as D1 or D2 faults or contaminated from OLTC. This validation showed that only 14.7% and 13.3% of the DGA samples fell within the new OC zone of the proposed triangle and pentagon, respectively.

show abstract

Section: Results-application Of Proposed Dtm and Dpm To Dga Data Extr...mentioning

confidence: 99%

“…These methods were intended to improve the accuracy of traditional fault-identification methods. In [5][6][7], some of the traditional fault interpretation methods were improved or modified. An extended version of DTM to detect simple and multiple faults was developed in [7].…”

Section: Introductionmentioning

confidence: 99%

Distinction between Arcing Faults and Oil Contamination from OLTC Gases

Bustamante,

Martinez Lastra,

Manana

et al. 2024

Electronics

View full text Add to dashboard Cite

show abstract

“…As Figure 8 shows, we could obtain the intermediate value modelled as haming weight (8 bit) for every message. In future research, we will try to randomize the intermediate value by using information fusion [23][24][25][26][27][28][29][30][31] and constant weight encoding [27], [32] approach. Those approaches could deceive attackers in recovering AES encryption device's secret key.…”

Section: Discussionmentioning

confidence: 99%

Revealing AES Encryption Device Key on 328P Microcontrollers with Differential Power Analysis

Putra¹,

Ahmad

Sutikno

et al. 2018

IJECE

Self Cite

View full text Add to dashboard Cite

This research demonstrates the revealing of an advanced encryption standard (AES) encryption device key. The encryption device is applied to an ATMEGA328P microcontroller. The said microcontroller is a device commonly used in internet of things (IoT). We measured power consumption when the encryption process is taking place. The message sent to the encryption device is randomly generated, but the key used has a fixed value. The novelty of this research is the creation of a systematic and optimal circuit in carrying the differential power analysis or difference of means (DPA/DoM) technique, so the technique can be applied in key revealing on a microcontroller device by using 500 traces in 120 seconds.

show abstract

“…This Robot uses the KGS algorithm to determine the direction of movement, based on the input of the attached sensors. In the field of instrumentation, KGS is being developed to assist the decision-making process for monitoring the condition of the transformer [3]. In the field of hardware security KGS has also been developed as a system for side channel attack countermeasure [4] and to detect an intrusion in network environment [5].…”

Section: Related Workmentioning

confidence: 99%

Architecture design for a multi-sensor information fusion processor

et al. 2019

Self Cite

View full text Add to dashboard Cite

This paper discusses the design of the architecture of an information fusion processor. This processor emulates the way of human thinking, namely by drawing conclusions from the obtained collection of information. Architecture design for this processor is based on Knowledge Growing System (KGS) algorithm. KGS is a novelty in Artificial Intelligence field. Compared to other AI methods, KGS focuses on the observation of the process of the knowledge growth within human brain based on information received from the surrounding environment. By using KGS algorithm, this processor works by receiving inputs from a set of sensors and possible hypotheses obtained after the processing of the information. The processor generates a value which is called as Degree of Certainty (DoC), which show the most possible hypothesis among all alternative ones. The Processor Elements which are used to perform KGS algorithm is designed based on systolic array architecture. The design of this processor is realized with VHSIC Hardware Design Language (VHDL) and synthesized by using FPGA Quartus II.13.1. The results show that the data path which has been design is able to perform the mechanism of KGS computation

show abstract

The implementation of A3S information fusion algorithm for interpreting Dissolved Gas Analysis (DGA) based on Doernenburg Ratio

Cited by 6 publications

References 17 publications

Distinction between Arcing Faults and Oil Contamination from OLTC Gases

Distinction between Arcing Faults and Oil Contamination from OLTC Gases

Revealing AES Encryption Device Key on 328P Microcontrollers with Differential Power Analysis

Architecture design for a multi-sensor information fusion processor

Contact Info

Product

Resources

About