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Anti-islanding image detection and optimization of distributed power supply using neural network architecture search

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DISCOVER COMPUTING 2024年第1期27卷 32页

作者： Xiong, Suqin Li, Yang Wang, Jun Zhang, Zhi Wang, Hao Lu, Lijun China Elect Power Res Inst Beijing 100192 Peoples R China Henan XJ Metering Co Ltd Xuchang 461000 Peoples R China State Grid Shan Dong Mkt Serv Ctr Metrol Ctr Jinan 250002 Peoples R China

Anti-islanding detection (AILD) for distributed power sources plays an important role on the stable operation of power grid systems and the safety of electrical systems. In order to improve the detection accuracy, we propose neural network architecture search (NAS) based approach for anti-islanding image detection and optimization of distributed power sources. It combines the fast region-based convolutional neural network (Faster-R-CNN) with the differentiable architecture search (Darts), utilizing electrical signal image data acquired from cameras or photovoltaic (PV) inverters, thereby enhancing the accuracy and efficiency of detection. We conduct a comparative analysis of two methods for obtaining distributed power supply (DPS) anti-islanding image data: camera-based acquisition and PV inverter-based acquisition. Our observation reveals that the image data acquired through cameras is more conducive for the learning process of DCNN. The proposed algorithm was compared with other convolutional neural network (CNN) models, validating its performance superiority. This provides a novel perspective and methodology for the advancement of AILD for distributed power sources, and enhances the security and stability of DPS.

关键词： Deep convolutional neural network Distributed power supply Anti-islanding detection Image detection detection optimization

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detection optimization for resonance region radar with dense multi-carrier waveform

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Journal of Southeast University(English Edition) 2015年第3期31卷 304-310页

作者：陈鹏吴乐南东南大学信息科学与工程学院南京210096

Unlike the existing resonance region radar systems （RRRS ） that transmit the orthogonal frequency division multiplexing （OFDM）multi-carrier waveform,the dense multi-carrier （DMC）radar waveform which has a narrower frequency interval than the traditional OFDM waveform is ***,in the same frequency bandwidth,the DMC waveform contains more sub-carriers and provides more frequency ***,to further improve detection performance,a novel optimal weight accumulation target detection （OWATD）method is proposed,where the echo electromagnetic waves at different frequencies are accumulated with the optimal weight ***,with the signal-to-noise ratio （SNR）of echo waveform approaching infinity,the asymptotic detection performance is analyzed, and the condition that the OWATD method with the DMC outperforms the matched filter with the OFDM is *** results show that the DMC outperforms the OFDM in the target detection performance,and the OWATD method can further improve the detection performance of the traditional methods with both the OFDM and DMC radar waveform.

关键词： constant false alarm rate （CFAR） dense multi-carrier waveform detection optimization resonance regionradar system

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optimization of a Fire detection System Based on Radial Sector Scanning Using a UV Sensor

IEEE SENSORS LETTERS

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IEEE SENSORS LETTERS 2023年第7期7卷

作者： Rachman, Fathur Zaini Hendrantoro, Gamantyo Wirawan, Wirawan Inst Teknol Sepuluh Nopember Dept Elect Engn Surabaya 60111 Indonesia State Polytech Balikpapan Dept Elect Engn Balikpapan 76126 Indonesia

The UV sensor is an ultraviolet on/off detector that has high sensitivity and a detection width of up to 180 degrees. Until recently, this sensor was used for flame detection and fire alarms in homes and industries. The sensor detects directly on the object and only gets information from the sensor angular width. This letter presents the fire detection system based on radial sector scanning to improve sensor detection optimization up to 360 degrees and represents the detection results using an embedded system. The result of the detection experiment is that the detection data changes by the sensor azimuth width and the device height. Improved detection optimization up to 53% of the detection system with experimental scenarios in the detection sector for the sensor azimuth width = 5.625 degrees.

关键词： Sensor systems devices and systems detection optimization embedded system radial sector scanning sensor azimuth width UV sensor

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Part-based tracking for object pose estimation

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JOURNAL OF REAL-TIME IMAGE PROCESSING 2023年第5期20卷 99页

作者： Ye, Shuang Ye, Jianhong Lei, Qing Huaqiao Univ Sch Comp Sci & Technol Xiamen Peoples R China Huaqiao Univ Xiamen Key Lab Comp Vis & Pattern Recognit Xiamen 361000 Peoples R China Huaqiao Univ Fujian Prov Univ Key Lab Comp Vis & Machine Learning Xiamen Peoples R China

Object pose estimation is crucial in human-computer interaction systems. The traditional point-based detection approaches rely on the robustness of feature points, the tracking methods utilize the similarity between frames to improve the speed, while the recent studies based on neural networks concentrate on solving specific invariance problems. Different from these methods, PTPE (Part-based Tracking for Pose Estimation) proposed in this paper focuses on how to balance the speed and accuracy under different conditions. In this method, the point matching is transformed into the part matching inside an object to enhance the reliability of the features. Additionally, a fast interframe tracking method is combined with learning models and structural information to enhance robustness. During tracking, multiple strategies are adopted for the different parts according to the matching effects evaluated by the learning models, so as to develop the locality and avoid the time consumption caused by undifferentiated full frame detection or learning. In addition, the constraints between parts are applied for parts detection optimization. Experiments show that PTPE is efficient both in accuracy and speed, especially in complex environments, when compared with classical algorithms that focus only on detection, interframe tracking, self-supervised models, and graph matching.

关键词： Object pose estimation Part-based tracking Local features matching detection optimization Object tracking Frame-by-frame tracking

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A new framework for analysing automated acoustic species detection data: Occupancy estimation and optimization of recordings post-processing

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METHODS IN ECOLOGY AND EVOLUTION 2018年第3期9卷 560-570页

作者： Chambert, Thierry Waddle, J. Hardin Miller, David A. W. Walls, Susan C. Nichols, James D. Penn State Univ Dept Ecosyst Sci & Management University Pk PA 16802 USA US Geol Survey Patuxent Wildlife Res Ctr Laurel MD 20192 USA US Geol Survey Wetland & Aquat Res Lafayette LA USA US Geol Survey Wetland & Aquat Res Gainesville FL USA

The development and use of automated species detection technologies, such as acoustic recorders, for monitoring wildlife are rapidly expanding. Automated classification algorithms provide cost- and time-effective means to process information-rich data, but often at the cost of additional detection errors. Appropriate methods are necessary to analyse such data while dealing with the different types of detection errors. We developed a hierarchical modelling framework for estimating species occupancy from automated species detection data. We explore design and optimization of data post-processing procedures to account for detection errors and generate accurate estimates. Our proposed method accounts for both imperfect detection and false-positive errors and utilizes information about both occurrence and abundance of detections to improve estimation. Using simulations, we show that our method provides much more accurate estimates than models ignoring the abundance of detections. The same findings are reached when we apply the methods to two real datasets on North American frogs surveyed with acoustic recorders. When false positives occur, estimator accuracy can be improved when a subset of detections produced by the classification algorithm is post-validated by a human observer. We use simulations to investigate the relationship between accuracy and effort spent on post-validation, and found that very accurate occupancy estimates can be obtained with as little as 1% of data being validated. Automated monitoring of wildlife provides opportunity and challenges. Our methods for analysing automated species detection data help to meet key challenges unique to these data and will prove useful for many wildlife monitoring programmes.

关键词： acoustic recorder units detection optimization false positives Hyla cinerea information-rich data Lithobates grylio sensitivity signal processing specificity

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A lightweight and optimized deep learning model for detecting banana bunches and stalks in autonomous harvesting vehicles

Smart Agricultural Technology

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Smart Agricultural Technology 2025年 11卷

作者： Duc Tai Nguyen Phuoc Bao Long Do Doan Dang Khoa Nguyen Wei-Chih Lin Department of Mechanical and Electro-Mechanical Engineering National Sun Yat-sen University Kaohsiung City Taiwan

Developing algorithms to identify fruit cutting locations is important for the functionality of harvesting robots. However, existing studies often rely on multi-stage detection processes. This complicates system design and hinders real-time performance. To address these challenges, this study proposes a novel detection model for banana-harvesting robots. The model simultaneously detects banana bunches and stalks in orchard environments. It is built upon the YOLOv8n (You Only Look Once version 8 nano) baseline and includes enhancements to improve accuracy while preserving a lightweight architecture. Specifically, the standard convolution layers are upgraded with a lightweight group-shuffle convolution module, reducing complexity while preserving efficiency. Additionally, a novel C2f-fast efficient channel attention module is proposed in the backbone, significantly enhancing the model's feature extraction capabilities. Furthermore, the bidirectional feature pyramid network is introduced in the original neck network, improving feature aggregation and adaptability to varying environmental conditions. Experimental results demonstrate that the proposed model achieves performance, with precision, recall, and mAP50 metrics of 96.3 %, 90 %, and 94.5 %, respectively, exceeding the baseline model by 0.5 %, 2.6 %, and 1 %. Moreover, the parameters and size of the proposed model are optimized to 1.7 M and 3.7 MB, reflecting reductions of 43.3 % and 40.3 %, respectively, in comparison to the baseline. Notably, the proposed model outperforms the previous detection models, offering high accuracy while optimizing computational efficiency. These advancements make the proposed model highly suitable for deployment on embedded systems in agricultural robots.

关键词： Deep learning detection optimization Banana detection Lightweight architecture Banana harvesting vehicles

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optimization of amphetamines multivariate detection by GC-FTIR spectra preprocessing

Optimization of amphetamines multivariate detection by GC-FT...

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17th International Conference System Theory, Control and Computing (ICSTCC)

作者： Ciochina, Stefanut Praisler, Mirela Dunarea de Jos Univ Galati Galati Romania

ISBN: (纸本)9781479922284;9781479922277

A chemometric method developed for the automatic detection of illicit amphetamines, which represent the most popular drugs in Europe, is presented. The detection system is based on Principal Component Analysis. The training database includes the GC-FTIR spectra of the main amphetamines, their precursors and derivatives. Although the system does not include any information on the biological activity of modeled compounds, the amphetamine analogues form two distinct clusters, according to their biological activity and toxic side effects (stimulants or hallucinogens). The clustering was optimized by preprocessing the spectra with a selective amplifier. This procedure increases significantly the efficiency of the detection system. The system correctly assigns the class identity of an unknown compound, even if its spectrum is not present in the database.

关键词： amphetamine principal component analysis detection optimization

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Signal selective amplification: a solution for an improved detection of amphetamines with QCL equipped portable GC-IRAS spectrometers 18

Signal selective amplification: a solution for an improved d...

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18th International Conference on System Theory, Control and Computing (ICSTCC)

作者： Praisler, Mirela Ciochina, Stefanut Stoica, Atanasia Dumitriu, Luminita Dunarea de Jos Univ Galati Dept Chem Phys & Environm Galati Romania Dunarea de Jos Univ Galati Dept Comp & Informat Technol Galati Romania

ISBN: (纸本)9781479946013

In this article we are presenting a signal selective amplification method that was used for improving the automatic detection of amphetamines based on their infrared absorptions recorded in the narrow spectral window in which the QCL source of a new portable GC-IRAS spectrometer is emitting (1550 - 1330 cm(-1)). The expert system developed for class identity assignment is based on Principal Component Analysis (PCA) and distinguishes the amphetamines according to their toxic effect (stimulant and hallucinogenic amphetamines). The detection efficiency and accuracy was evaluated by using Cluster Analysis (CA).

关键词： amphetamines Principal Component Analysis detection optimization

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optimization of electrode alignment for electrochemical detection in capillary electrophoresis using a scanning electrochemical microscope

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ELECTROANALYSIS 2005年第24期17卷 2254-2259页

作者： Roach, DM Hooper, SE Anderson, MR Virginia Polytech Inst & State Univ Dept Chem Blacksburg VA 24061 USA

Electrochemical detection in capillary electrophoresis requires decoupling the voltage applied to the working electrode from the separation voltage applied across the capillary. End-capillary electrochemical detection achieves this by placing the electrode just outside the ground end of the separation capillary. Obtaining adequate signal-to-noise in this arrangement requires using small inner diameter capillaries. Decreasing the inner diameter of the separation capillary, however, increases the difficulty of aligning the microelectrode with the open end of the capillary. Using scanning electrochemical microscopy (SECM), the position of the capillary opening is determined while electroactive material is continuously emerging from the end of the capillary. The SECM instrument is then used to place the electrode at the position of maximum current for subsequent separations. Subsequent measurements found that the best signal-to-noise is obtained when the detection electrode is placed directly opposite the capillary opening and just outside of the capillary opening. When the electrode is further above the opening (but still opposite the capillary opening), the signal-to-noise does not dramatically decrease until the electrode is more than 30 mu m above the 10 mu m inner-diameter capillary.

关键词： electrophoresis scanning electrochemical microscopy electrochemical detection electrode alignment detection optimization

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Observations on the use of electrochemical detection for the high-performance liquid chromatographic determination of catechol and indole derivatives

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ANALYTICAL LETTERS 2003年第5期36卷 1001-1016页

作者： Pappa-Louisi, A Aristotle Univ Thessaloniki Dept Chem Phys Chem Lab Thessaloniki 54124 Greece

This work presents the dependence of the electrochemical (EC) detection of catechol and indole-related compounds on the pH and organic solvent composition of the mobile phase as well as on the column temperature, including a performance comparison with the UV detection. Particular attention has been paid to the effect of the above chromatographic conditions on the peak shape and peak area recorded by two detection modes. It was found that EC detector gave significantly worse peak shape than UV detector for some derivatives in certain eluents. Furthermore, chromatographic parameters and especially mobile phase pH influenced oxidation of these compounds much more than their UV absorbance. As a result, it was proved that the selectivity and flexibility of the EC detector can be varied not only by variation of electrochemical conditions but also by variation of the mobile phase pH taking into account the excess peak tailing obtained for some basic solutes at near neutral pH.

关键词： catecholamines catechol and indole-related compounds detection optimization

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