Design of fault monitoring framework for multi-energy systems using Signed Directed Graph

Smaili, Rahma; Harabi, Rafika El; Abdelkrim, Mohamed Naceur

doi:10.1016/j.ifacol.2017.08.2304

Cited by 14 publications

(7 citation statements)

References 7 publications

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“…Using the ISDG model, complex logic can be displayed, multiple faults can be diagnosed, and the optimal sequence can be determined. Smaili et al (2017) proposed a new SDG-based framework for fault detection and isolation for the purpose of fault detection and isolation. The general model can systematically derive qualitative fault feature matrices from qualitative redundancy relations.…”

Section: Related Workmentioning

confidence: 99%

Research on the uncertainty problem of SDG fault diagnosis based on information flow

Huang

Liu²,

Yang³

et al. 2023

Front. Energy Res.

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Accurate and complete diagnosis of nuclear accidents is the primary link to nuclear emergencies. The signed directed graph (SDG), as a common method of fault diagnosis, has good completeness. However, if there are feedforward and negative feedback control loops, compensation response and reverse response will be generated in the process of fault occurrence and propagation, which makes the state of the compensation variable and reverse variable uncertain, thus destroying the compatibility of the fault propagation path, leading to incomplete SDG reverse reasoning. In order to solve this problem, this paper proposes a SDG fault diagnosis method based on information flow. This method first finds out all the directed edges with the compensation variable or inverse variable node as the endpoint. By comparing the goodness of fit between the information flow on these directed edges and their total information flow curves, the path that contained the directed edge represented by sub-information flow with the highest R2 is obtained, and it is used as the fault propagation path with the maximum probability to determine the state of the compensation variable or inverse variable and fault location. At the same time, this paper extends the SDG model from the structure to build an FR-SDG model that can intuitively describe the node steady-state information under the final response and the fault propagation path with the maximum probability, which improves the diagnosis resolution. Finally, this paper carried out the relevant experiments in the subsystem of the nuclear reactor primary loop by using the simulation system PCTran AP1000, which verified the feasibility of this method.

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Section: Related Workmentioning

confidence: 99%

Research on the uncertainty problem of SDG fault diagnosis based on information flow

Huang

Liu²,

Yang³

et al. 2023

Front. Energy Res.

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“…Thirdly, the positive solution r + and the negative solution r − can be determined based on the normalized decision matrix R, see Equations (20) and (21), where J and J are the sets of benefit criteria (the higher the criterion, the more important the node is) and cost criteria (the higher the criterion, the less important the node is), respectively. The four criteria are all benefit criteria.…”

Section: Selection Of Key Nodes In Sdg Modelmentioning

confidence: 99%

“…By integrating multilevel flow modeling (MFM) and SDG, a functional modeling method of fault diagnosis systems was designed to address the difficulties regarding the interpretation of results and consistent graph generation [20]. A graphic construction methodology that builds the SDG directly from a bond graph was proposed to reduce modeling complexity [21]. A new method was presented to improve the resolution of fault identification, which integrates the completeness feature of SDG with the good diagnostic resolution feature of qualitative trend analysis (QTA) [22].…”

Section: Introductionmentioning

confidence: 99%

A Fault Identification Method in Distillation Process Based on Dynamic Mechanism Analysis and Signed Directed Graph

et al. 2021

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Due to the complexity of materials and energy cycles, the distillation system has numerous working conditions difficult to troubleshoot in time. To address the problem, a novel DMA-SDG fault identification method that combines dynamic mechanism analysis based on process simulation and signed directed graph is proposed for the distillation process. Firstly, dynamic simulation is employed to build a mechanism model to provide the potential relationships between variables. Secondly, sensitivity analysis and dynamic mechanism analysis in process simulation are introduced to the SDG model to improve the completeness of this model based on expert knowledge. Finally, a quantitative analysis based on complex network theory is used to select the most important nodes in SDG model for identifying the severe malfunctions. The application of DMA-SDG method in a benzene-toluene-xylene (BTX) hydrogenation prefractionation system shows sound fault identification performance.

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“…It also tracks the root causes of faults based on abnormal system conditions. At present, symbolic diagrams [2][3][4], fault trees [5], Petri nets [6,7], and topology models are commonly used to describe the fault propagation process [8][9][10] and rule inference based on experts and prior information [11,12] or on data-driven methods to calculate and discriminate causality according to the process of variables to realize fault root cause identification and location [13][14][15]. Signal-based fault diagnosis methods use measured signals to extract features and make diagnosis decisions based on symptom analysis and prior knowledge [16].…”

Section: Introductionmentioning

confidence: 99%

Fault Root Cause Tracking of the Mechanical Components of CNC Lathes Based on Information Transmission

Zhang

Guo

Liu

2023

Sensors

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This study proposes a new method for the immediate fault warning and fault root tracing of CNC lathes. Here, the information acquisition scheme was formulated based on the analysis of the coupling relationship between the mechanical parts of CNC lathes. Once the collected status signals were de-noised and coarse-grained, transfer entropy theory was introduced to calculate the net entropy of information transfer between the mechanical parts, after which the information transfer model was constructed. The sliding window method was used to determine the probability threshold interval of the net information transfer entropy between the lathe mechanical parts under different processing modes. Therefore, the transition critical point was determined according to the information entropy, and the fault development process was clarified. By analyzing the information transfer changes between the parts, fault early warning and fault root tracking on the CNC lathe were realized. The proposed method realizes the digitalization and intelligentization of fault diagnosis and has the advantages of timely and efficient diagnosis. Finally, the effectiveness of the proposed method is verified by a numerical control lathe tool processing experiment.

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Design of fault monitoring framework for multi-energy systems using Signed Directed Graph

Cited by 14 publications

References 7 publications

Research on the uncertainty problem of SDG fault diagnosis based on information flow

Research on the uncertainty problem of SDG fault diagnosis based on information flow

A Fault Identification Method in Distillation Process Based on Dynamic Mechanism Analysis and Signed Directed Graph

Fault Root Cause Tracking of the Mechanical Components of CNC Lathes Based on Information Transmission

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