A parameter-adaptive VMD method based on grasshopper optimization algorithm to analyze vibration signals from rotating machinery

Zhang, Xin; Miao, Qiang; Zhang, Heng; Wang, Lei

doi:10.1016/j.ymssp.2017.11.029

Cited by 413 publications

(233 citation statements)

References 39 publications

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“…The Kurtosis Index (KI) and the correlation coefficient (CC) both are very powerful parameters in the field of disturbance diagnosis . KI is a powerful parameter to distinguish the faulted signal and the CC shows the correlation between two signals.…”

Section: Adaptive Cross Variational Mode Decomposition Based Reduced mentioning

confidence: 99%

Islanding and power quality disturbance monitoring in microgrid using adaptive cross variational mode decomposition and reduced kernel ridge regression

Dash

Satapathy

Nayak

2020

Int Trans Electr Energ Syst

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Summary This article presents the detection and classification of islanding and power quality (PQ) disturbances for a multiple distributed generation based using an adaptive cross variational mode decomposition (XVMD) with reduced kernel ridge regression (RKRR). This article considers photovoltaic as the primary DG and studied the effect of the solar irradiation variation. Further the considered microgrid is subjected to different operating conditions pertaining to both islanding and non‐islanding disturbances. The proposed XVMD is an extension of VMD and with RKRR, it is a new contribution to the earlier studies to deal dynamic detection threshold requirement. The XVMD based RKRR needs simple features to classify the disturbances in less time as compared to the VMD based methods. The features to classify the events are calculated from the optimal mode selected by the hybrid firefly algorithm. For the performance analysis, voltage signals across the PV based DGs are obtained by initiating various power qualities and islanding disturbances. A validation case study through TMS 320C6713 Starter Kit (DSK) is presented for capacitor switching. The robustness of the proposed XVMD‐RKRR is observed from a large number of numerical experimentation by comparing it with other well‐known approaches.

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Section: Adaptive Cross Variational Mode Decomposition Based Reduced mentioning

confidence: 99%

Islanding and power quality disturbance monitoring in microgrid using adaptive cross variational mode decomposition and reduced kernel ridge regression

Dash

Satapathy

Nayak

2020

Int Trans Electr Energ Syst

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“…GOA has simple algorithm without gradient mechanism, which can effectively avoid falling into local optimum, and has very few parameters to adjust, which minimizes the adjustment of empirical parameters. ese characteristics make GOA get some good applications; paper [42] presents a parameter adaptive VMD method based on GOA to analyze vibration signals of rotating machinery and proves that this method is effective for fault diagnosis of mechanical vibration signals. In [43], a hybrid method based on GOA is proposed to optimize the parameters of support vector machine (SVM) model and find the best feature subset, which is verified that this method is superior to other methods in classification accuracy, while minimizing the number of selected features.…”

Section: Introductionmentioning

confidence: 99%

Optimal Pattern Synthesis of Linear Array and Broadband Design of Whip Antenna Using Grasshopper Optimization Algorithm

Wang

Liu

et al. 2020

International Journal of Antennas and Propagation

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Antenna arrays with high directivity, low side-lobe level, and null control in desired direction and whip antenna with wider bandwidth both need to be optimized to meet different needs of communication systems. A new natural heuristic algorithm simulating social behavior of grasshoppers, grasshopper optimization algorithm (GOA), is applied to electromagnetic field as a new effective technology to solve the antenna optimization problem for the first time. Its algorithm is simple and has no gradient mechanism, can effectively avoid falling into local optimum, and is suitable for single-objective and multiobjective optimization problems. GOA is used to optimize the side lobe suppression, null depth, and notch control of arbitrary linear array and then used to optimize the loading and matching network of 10-meter HF broadband whip antenna compared with other algorithms. The results show that GOA has more advantages in side-lobe suppression, null depth, and notch control of linear array than other algorithms and has better broadband optimization performance for HF whip antenna. The pattern synthesis and antenna broadband optimization based on GOA provide a new and effective method for antenna performance optimization.

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“…There are many applications in which GOA has been used. Among such applications the most recent and relevant are [14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Grasshopper Optimization Algorithm Applied to the Open Vehicle Routing Problem

et al. 2020

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This paper presents a hybrid grasshopper optimization algorithm using a novel decoder and local search to solve instances of the open vehicle routing problem with capacity and distance constraints. The algorithm's decoder first defines the number of vehicles to be used and then it partitions the clients, assigning them to the available routes. The algorithm performs a local search in three neighborhoods after decoding. When a new best solution is found, every route is locally optimized by solving a traveling salesman problem, considering the depot and clients in the route. Three sets containing a total of 30 benchmark problems from the literature were used to test the algorithm. The experiments considered two cases of the problem. In the first, the primary objective is to minimize the total number of vehicles and then the total distance to be traveled. In the second case, the total distance traveled by the vehicles is minimized. The obtained results showed the algorithm's proficient performance. For the first case, the algorithm was able to improve or match the best-known solutions for 21 of the 30 benchmark problems. For the second case, the best-known solutions for 18 of the 30 benchmark problems were found or improved by the algorithm. Finally, a case study from a real-life problem is included.

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A parameter-adaptive VMD method based on grasshopper optimization algorithm to analyze vibration signals from rotating machinery

Cited by 413 publications

References 39 publications

Islanding and power quality disturbance monitoring in microgrid using adaptive cross variational mode decomposition and reduced kernel ridge regression

Islanding and power quality disturbance monitoring in microgrid using adaptive cross variational mode decomposition and reduced kernel ridge regression

Optimal Pattern Synthesis of Linear Array and Broadband Design of Whip Antenna Using Grasshopper Optimization Algorithm

A Hybrid Grasshopper Optimization Algorithm Applied to the Open Vehicle Routing Problem

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