Multi-Vehicle Tracking Using an Environment Interaction Potential Force Model

Tian, Zhen; Li, Yinguo; Cen, Ming; Zhu, Hao

doi:10.1109/jsen.2020.2999095

Cited by 16 publications

(4 citation statements)

References 32 publications

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“…In the model switching stage, the main goal in correcting the model probability was to ensure it transformed quickly when the system mode changed [ 46 ]. The likelihood function of the model can also mirror the matching degree between the model and system.…”

Section: Methodsmentioning

confidence: 99%

Interactive multi-model fault diagnosis method of switched reluctance motor based on low delay anti-interference

Zhou

Wang

et al. 2023

PLoS ONE

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Given fault false alarm and fault control failure caused by the decrease of fault identification accuracy and fault delay of Switched Reluctance Motor (SRM) power converter in complex working conditions, a method based on the Interactive Multi-Model (IMM) algorithm was proposed in this paper. Besides, the corresponding equivalent circuit models were established according to the different working states of the SRM power converter. The Kalman filter was employed to estimate the state of the model, and the fault detection and location were realized depending on the residual signal. Additionally, a transition probability correction function of the IMM was constructed using the difference of the n-th order to suppress the influence of external disturbance on the fault diagnosis accuracy. Concurrently, a model jump threshold was introduced to reduce delay when the matched model was switched, so as to realize the rapid separation of faults and effective fault control. The simulation and experiment results demonstrate that the IMM algorithm based on low delay anti-interference can effectively reduce the influence of complex working conditions, improve the anti-interference ability of SRM power converter fault diagnosis, and identify fault information accurately and quickly.

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Section: Methodsmentioning

confidence: 99%

Interactive multi-model fault diagnosis method of switched reluctance motor based on low delay anti-interference

Zhou

Wang

et al. 2023

PLoS ONE

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“…A comprehensive presentation of various defect characteristics during wire rope defect detection cannot be achieved by using only detection under natural light conditions. Considering the interaction between surface defect features and the lighting environment [32], and to ensure the preservation of defect feature integrity in our established dataset, we collected three types of defect feature information under different light and shadow conditions: natural light, strong light, and strip light. To facilitate dataset construction and defect detection, we developed a dedicated experimental platform for studying light and shadow environments as depicted in figure 9.…”

Section: The Build Environment For the Datasetmentioning

confidence: 99%

A more efficient method for wire rope surface defect detection based on fusing cross-stage features and lightweight convolution modules

Jin,

Duan,

et al. 2024

Meas. Sci. Technol.

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Detecting surface defects in industrial production presents challenges, including deploying lightweight algorithms on edge devices and balance between detection speed and accuracy. This paper introduces a novel lightweight method for real-time detection of wire rope defects in industrial environments. Utilizing the YOLOv7tiny framework, we developed a lightweight cross-stage feature fusion module (CSPP) to enhance processing feature information. This mitigates the impact of redundant information from traditional convolution, reducing network size and improving detection speed. Additionally, the YOLO-FP network integrates lightweight convolution modules and an attention mechanism. Trained and tested on data from Changan, Great Wall, and Guangzhou Automobile models, our method achieved a 96.06% mean average precision (mAP), surpassing the original YOLOv7tiny model. Furthermore, it reduces the model size by 41.09% and enhances detection speed by 18.53%, making it promising for real-time edge device applications in wire rope production.

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“…In the model switching stage, the main goal in correcting the model probability was to ensure it transformed quickly when the system mode changed [50]. The IMM algorithm was a soft switching mechanism, and when the matched model was switched, a large inertia would be generated.…”

Section: Inertia Reduction Algorithm In the Model Transformation Stagementioning

confidence: 99%

Multi-Fault Diagnosis of Interacting Multiple Model Batteries Based on Low Inertia Noise Reduction

Wang

Meng

et al. 2021

IEEE Access

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In view of the problems of declined estimation and diagnostic accuracy, as well as diagnosis delay caused by the fixed model transformation probability of the interacting multiple model (IMM) fault diagnosis algorithm, an IMM algorithm based on low inertia noise reduction (LN-IMM) was presented in this paper. The proposed algorithm realized the multi-fault diagnosis of lithium-ion batteries in combination with strong tracking Kalman filter (STKF). In the non-model transformation stage, a transition probability correction function was constructed using the difference of the n-th order based on model probability to suppress the effect of noise on the estimation accuracy of the algorithm. In the model transformation stage, a model jump threshold was introduced in order to reduce inertia when the matched model was switched and realized quick model transformation. Accordingly, the final experiment proved that the LN-IMM-STKF algorithm efficiently completed the state estimation of lithium-ion batteries and improved the diagnostic accuracy of faults while reducing diagnosis delay and attaining accurate detection as well as rapid separation of battery fault information.INDEX TERMS Interactive multiple model, low inertia, noise reduction, strong tracking Kalman filter, lithium-ion battery.

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Multi-Vehicle Tracking Using an Environment Interaction Potential Force Model

Cited by 16 publications

References 32 publications

Interactive multi-model fault diagnosis method of switched reluctance motor based on low delay anti-interference

Interactive multi-model fault diagnosis method of switched reluctance motor based on low delay anti-interference

A more efficient method for wire rope surface defect detection based on fusing cross-stage features and lightweight convolution modules

Multi-Fault Diagnosis of Interacting Multiple Model Batteries Based on Low Inertia Noise Reduction

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