On-Line Error Detection and Mitigation for Time-Series Data of Cyber-Physical Systems using Deep Learning Based Methods

Ding, Kai; Ding, Sheng; Morozov, Andrey; Fabarisov, Tagir; Janschek, Klaus

doi:10.1109/edcc.2019.00015

Cited by 14 publications

(3 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The LSTM network has become the deep learning model of choice for sequential and temporal data because of its ability to learn long-range patterns. Relying on the proposed LSTM network for anomaly detection in [8], and utilizing the grid voltage V g a,b,c (t), the inverter current I inv a,b,c (t) and the inverter input voltage V * inv a,b,c (t) as inputs, the LSTM network predicts next step of the inverter input voltage V * i nv a,b,c (t + 1). In fact, this part of the controller allows detecting the grid fault occurrence and makes it possible to prevent it before the inverter failure.…”

Section: A Fault Detectionmentioning

confidence: 99%

Integrated Fault Diagnosis and Control Design for DER Inverters using Machine Learning Methods

Fallah¹,

Ramezani²,

Mehrizi‐Sani³

2022

Preprint

View full text Add to dashboard Cite

This paper employs a supervised machine learning (ML) algorithm to propose an integrated fault detection and diagnosis (FDD) and fault-tolerant control (FTC) strategy to detect, diagnose, and classify the grid faults and correct the input voltage before affecting the grid-connected distributed energy resources (DER) inverters. This controller can mitigate the impact of grid faults on inverters by predicting and modifying the time series of their input voltage. Simulation results show the effectiveness of the proposed controller and evaluate its operating performance.

show abstract

Section: A Fault Detectionmentioning

confidence: 99%

Integrated Fault Diagnosis and Control Design for DER Inverters using Machine Learning Methods

Fallah¹,

Ramezani²,

Mehrizi‐Sani³

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Some useful features that cannot be detected by manual feature engineering can be detected by DL algorithms. Accordingly, many NTMA applications [111][112][113][114] implement by using DL algorithms.…”

Section: Figure 4 Relation Between Ai ML and Dlmentioning

confidence: 99%

Modern ağ trafiği analizi için derin paket incelemesi hakkında kapsamlı bir çalışma: sorunlar ve zorluklar

Çelebi

ÖZBİLEN

Yavanoğlu

2022

NÖHÜ Müh. Bilim. Derg.

View full text Add to dashboard Cite

Deep Packet Inspection (DPI) provides full visibility into network traffic by performing detailed analysis on both packet header and packet payload. Accordingly, DPI has critical importance as it can be used in applications i.e network security or government surveillance. In this paper, we provide an extensive survey on DPI. Different from the previous studies, we try to efficiently integrate DPI techniques into network analysis mechanisms by identifying performance-limiting parameters in the analysis of modern network traffic. Analysis of the network traffic model with complex behaviors is carried out with powerful hybrid systems by combining more than one technique. Therefore, DPI methods are studied together with other techniques used in the analysis of network traffic. Security applications of DPI on Internet of Things (IoT) and Software-Defined Networking (SDN) architectures are discussed and Intrusion Detection Systems (IDS) mechanisms, in which the DPI is applied as a component of the hybrid system, are examined. In addition, methods that perform inspection of encrypted network traffic are emphasized and these methods are evaluated from the point of security, performance and functionality. Future research issues are also discussed taking into account the implementation challenges for all DPI processes.

show abstract

“…This DEPM computes the probability that the output variable, data variable 4, is corrupted. Given that SEUs are stochastic in nature, this may occur at any time [22]. To achieve this goal, expressions can be evaluated by employing quantifiable Boolean formulae (QBF) evaluating satisfiability solvers [23,24].…”

mentioning

confidence: 99%

Integrating Commercial-Off-The-Shelf Components into Radiation-Hardened Drone Designs for Nuclear-Contaminated Search and Rescue Missions

Earthperson

Diaconeasa

2023

Drones

View full text Add to dashboard Cite

This paper conducts a focused probabilistic risk assessment (PRA) on the reliability of commercial off-the-shelf (COTS) drones deployed for surveillance in areas with diverse radiation levels following a nuclear accident. The study employs the event tree/fault tree digraph approach, integrated with the dual-graph error propagation method (DEPM), to model sequences that could lead to loss of mission (LOM) scenarios due to combined hardware–software failures in the drone’s navigation system. The impact of radiation is simulated by a comparison of the total ionizing dose (TID) with the acceptable limit for each component. Errors are then propagated within the electronic hardware and software blocks to determine the navigation system’s reliability in different radiation zones. If the system is deemed unreliable, a strategy is suggested to identify the minimum radiation-hardening requirement for its subcomponents by reverse-engineering from the desired mission success criteria. The findings of this study can aid in the integration of COTS components into radiation-hardened (RAD-HARD) designs, optimizing the balance between cost, performance, and reliability in drone systems for nuclear-contaminated search and rescue missions.

show abstract

On-Line Error Detection and Mitigation for Time-Series Data of Cyber-Physical Systems using Deep Learning Based Methods

Cited by 14 publications

References 21 publications

Integrated Fault Diagnosis and Control Design for DER Inverters using Machine Learning Methods

Integrated Fault Diagnosis and Control Design for DER Inverters using Machine Learning Methods

Modern ağ trafiği analizi için derin paket incelemesi hakkında kapsamlı bir çalışma: sorunlar ve zorluklar

Integrating Commercial-Off-The-Shelf Components into Radiation-Hardened Drone Designs for Nuclear-Contaminated Search and Rescue Missions

Contact Info

Product

Resources

About