Forensic Analysis of Fire in a Substation of a Commercial Center

Ala, Guido; Favuzza, Salvatore; Mitolo, Massimo; Musca, Rossano; Zizzo, Gaetano

doi:10.1109/tia.2020.2971675

Cited by 7 publications

(5 citation statements)

References 9 publications

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“…• The backbone of the algorithm refers to the idea of multi-scale feature perception in SSD [4], and builds a lightweight multi-scale convolutional network according to the task characteristics of target detection, so as to solve the problem of poor detection effect of the original SSD network on the small target.…”

Section: By Drawing On the Ideas Ofmentioning

confidence: 99%

“…Compared with the two-stage target detection framework, the single-stage detection framework has the advantages of simple structure and fast speed. Typical representatives are SSD [4] and Yolo [5] [6], they have achieved a balance between speed and accuracy. The latest single-stage detection framework Yolov5 achieves an accuracy comparable to the two-stage target detection framework.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A CNN-Based Single-Stage Occlusion Real-Time Target Detection Method

Liu,

Yang,

Liu

et al. 2024

JILSA

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Aiming at the problem of low accuracy of traditional target detection methods for target detection in endoscopes in substation environments, a CNN-based real-time detection method for masked targets is proposed. The method adopts the overall design of backbone network, detection network and algorithmic parameter optimisation method, completes the model training on the self-constructed occlusion target dataset, and adopts the multi-scale perception method for target detection. The HNM algorithm is used to screen positive and negative samples during the training process, and the NMS algorithm is used to post-process the prediction results during the detection process to improve the detection efficiency. After experimental validation, the obtained model has the multi-class average predicted value (mAP) of the dataset. It has general advantages over traditional target detection methods. The detection time of a single target on FDDB dataset is 39 ms, which can meet the need of real-time target detection. In addition, the project team has successfully deployed the method into substations and put it into use in many places in Beijing, which is important for achieving the anomaly of occlusion target detection.

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Section: By Drawing On the Ideas Ofmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A CNN-Based Single-Stage Occlusion Real-Time Target Detection Method

Liu,

Yang,

Liu

et al. 2024

JILSA

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show abstract

“…Delay in forensic inspections may make impossible to establish the root cause of accidents. Reference [12] describes the case of a fire in a shopping center, with a long delayed multi-party inspection. When the inspection was scheduled, the damaged equipment has been transported from the fire site to an outdoor storage area, without previous identification of parts or a documented chain of custody.…”

Section: The Importance Of Forensic Inspectionsmentioning

confidence: 99%

Safety Protocols for Forensic Inspections in the Time of COVID-19: An Approach to Protect Practitioners

Mitolo

Zizzo

Fox

et al. 2022

IEEE Ind. Appl. Mag.

Self Cite

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The global pandemic of COVID-19 has impacted the entire world in ways that were unimaginable months ago. It has changed how professionals work and interact with one another. To ensure the safety of experts and attorneys, also forensic inspection procedures must evolve, while still providing a reliable foundation for an expert testimony, relevant to the task at hand. Traditional field inspections require attendees to be physically present and generally in close proximity. Inspecting artifacts may also require that individual components be serially examined by multiple experts, which increases the risk of transmitting the disease. The authors propose a new approach to forensic inspections aimed at protecting consultants from the biological risk due to COVID-19. This approach takes into account the anticontagion safety protocols established in affected countries around the world.

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“…These factors will cause aging, oxidation and corrosion of various components in the substation. If they are not found and eliminated in time, the existing hidden dangers will develop into faults, thus posing a threat to the security and stability of the power system [3]. Therefore, in order to fundamentally ensure the safe and stable operation of the power grid and the safe supply of power, it is necessary to carry out regular and irregular inspection of each substation, timely find hidden dangers, prevent them before they happen, and reduce the failure rate of power equipment to the lowest.…”

Section: Introductionmentioning

confidence: 99%

An Early Warning Model for Intelligent Operation of Power Engineering based on Kalman Filter Algorithm

Shi¹,

Li²,

Sun³

et al. 2023

IJACSA

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The accurate early warning of intelligent operation of power engineering can find the abnormal operation of substation equipment in time and ensure the safe operation of substation equipment. Thus, an early warning model for intelligent operation of power engineering based on Kalman filter algorithm is constructed. In this model, the noise elimination method of substation equipment inspection image based on particle resampling filter algorithm is introduced. After removing the noise information of operation situation inspection image of substation equipment, the gradient direction histogram feature, lab color space feature and edge contour feature in the image are extracted by the multi-feature extraction method for intelligent operation of power engineering based on multi-feature fusion. These features are combined to form the feature description set of equipment operation situation. The feature description set is used as the identification attribute set of the anomaly identification and early warning model for intelligent operation of electric power engineering based on Kalman filter algorithm to complete the anomaly identification and early warning of equipment operation situation. The test shows that when the model is used to observe the temperature change trend of the top layer of the transformer, the temperature error is very small, and the early warning accuracy for the abnormal temperature of the top layer of the transformer is very high, so the abnormal operation of the substation equipment can be found in time.

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Forensic Analysis of Fire in a Substation of a Commercial Center

Cited by 7 publications

References 9 publications

A CNN-Based Single-Stage Occlusion Real-Time Target Detection Method

A CNN-Based Single-Stage Occlusion Real-Time Target Detection Method

Safety Protocols for Forensic Inspections in the Time of COVID-19: An Approach to Protect Practitioners

An Early Warning Model for Intelligent Operation of Power Engineering based on Kalman Filter Algorithm

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