The optimal control problem of reservoir group flood control is a complex, nonlinear, high-dimensional, multi-peak extremum problem with many complex constraints and interdependent decision variables. The traditional ...
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The optimal control problem of reservoir group flood control is a complex, nonlinear, high-dimensional, multi-peak extremum problem with many complex constraints and interdependent decision variables. The traditional algorithm is slow and easily falls into the local optimum when solving the problem of the flood control optimization of reservoir groups. The intelligent algorithm has the characteristics of fast computing speed and strong searching ability, which can make up for the shortcomings of the traditional algorithm. In this study, the improved sparrow algorithm (issa) combining Cauchy mutation and reverse learning strategy is used to solve the flood control optimization problem of reservoir groups. This study takes Sanmenxia Reservoir and Xiaolangdi Reservoir on the mainstream of the Yellow River as the research object and Huayuankou as the downstream control point to establish a joint flood control optimization operation model of cascade reservoirs. The results of the improved sparrow algorithm (issa), particle swarm optimization (POS) and sparrow algorithm (SSA) are compared and analyzed. The results show that when the improved issa algorithm is used to solve the problem, the maximum flood peak flow of the garden entrance control point is 11,676.3 m(3), and the peak cutting rate is 48%. The optimization effect is obviously better than the other two algorithms. This study provides a new and effective way to solve the problem of flood control optimization of reservoir groups.
Electric gate valve (EGV) is an essential equipment within nuclear power plant (NPP). This paper presents an advanced fault diagnosis (FD) approach, leveraging Variational Modal Decomposition (VMD), Mutual Dimensionle...
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Electric gate valve (EGV) is an essential equipment within nuclear power plant (NPP). This paper presents an advanced fault diagnosis (FD) approach, leveraging Variational Modal Decomposition (VMD), Mutual Dimensionless Indicator (MDI) and the Random Forest (RF) optimized through Improved Sparrow Search algorithm (issa), aimed at improving the accuracy of fault diagnosis and optimizing the FD model during EGV failure events. To commence, we employ the VMD algorithm for modal decomposition of raw electric gate valve signals. This process yields several Intrinsic Mode Function (IMF) components with diverse frequencies, enabling the capture of the underlying dynamics of the signals and facilitating a more comprehensive analysis of the fault conditions. We subsequently apply the K -L divergence to identify key IMF components that closely resemble the original signals. These selected key IMF components serve as the foundation for extracting dimensional indicators (DI) and mutual dimensionless indicators (MDI) as signal features. Furthermore, the Improved Sparrow Search algorithm (issa) is enlisted to optimize the maximum feature count and the number of decision trees in the Random Forest (RF) algorithm. Ultimately, the optimized RF algorithm is deployed for fault diagnosis. Our paper offers a comparative analysis, pitting the VMD method against Empirical Mode Decomposition (EMD) and Local Mean Decomposition (LMD). Additionally, we compare our proposed fault diagnosis model with traditional RF algorithm and the SSA-RF algorithm. Through rigorous experimentation, our results achieved an average fault diagnosis accuracy of up to 96.375%.
Aiming at the problem that the capsule endoscopy robot cannot accurately obtain the position and orientation information of the capsule robot after it enters the human body, this paper investigates the optimization al...
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ISBN:
(纸本)9798350366907;9789887581581
Aiming at the problem that the capsule endoscopy robot cannot accurately obtain the position and orientation information of the capsule robot after it enters the human body, this paper investigates the optimization algorithm to solve the position and orientation information of the permanent magnet based on the magnetic dipole model. Improved on the basis of Sparrow Search algorithm (SSA), this paper proposes an Improved Sparrow Search algorithm (issa). And a set of permanent magnet positioning experimental device is built by using the Hall effect-based IST8310 three-axis magnetic sensor from iSentek, and the standard positioning experimental board is customized to verify the accuracy and stability of the issa algorithm through the permanent magnet positioning experiment. The experimental results show that compared with the SSA algorithm, the issa algorithm has a great improvement in the positioning and orientation accuracy as well as the convergence speed, and it is also superior to many other optimization algorithms. Using the issa algorithm for permanent magnet localization experiments, the positioning error can be stabilized at about 1mm and the orientation error at about 2 degrees within tens of milliseconds, which greatly improves the positioning and orientation accuracy as well as the positioning speed of the permanent magnet, and provides a reliable method for accurately obtaining the position and orientation information of the capsule robot.
The articulated arm coordinate measuring machine (AACMM), widely utilized in the field of industrial measurement, is assessed based on key performance indicators such as measurement accuracy, measurement space, and fl...
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The articulated arm coordinate measuring machine (AACMM), widely utilized in the field of industrial measurement, is assessed based on key performance indicators such as measurement accuracy, measurement space, and flexibility. To enhance these aspects of the AACMM, this paper introduces a novel type of AACMM. The new model is based on a 3-RPS (revolute joint R, prismatic joint P, spherical joint S) parallel mechanism (3-RPSPM). The working principle of the 3-RPSPM is detailed, and a corresponding computational model is established. An algorithm is proposed based on this mathematical model to determine the theoretical achievable accuracy of the 3-RPSPM. Additionally, a spatial error analysis of the 3-RPSPM is conducted to verify its compliance with AACMM accuracy requirements and to demonstrate a certain level of accuracy improvement. Through simulation analysis, the differences in measurement accuracy, measurement space, and flexibility between the new type of AACMM based on the 3-RPS parallel mechanism (3-RPSAACMM) and traditional AACMMs are compared. The results indicate that the 3-RPSAACMM, with its novel parallel structure free from series accumulation errors, not only maintains measurement flexibility but also achieves improvements in measurement accuracy and space. The hybrid structure adopted by the new 3-RPSAACMM offers a new direction for the future development of AACMMs, presenting significant research value and application prospects.
In this paper, the innovative research of the autonomous control system of the once-through steam generator (OTSG) is carried out, which is mainly aimed at the normal operating condition, especially the fault conditio...
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In this paper, the innovative research of the autonomous control system of the once-through steam generator (OTSG) is carried out, which is mainly aimed at the normal operating condition, especially the fault condition when the operating characteristics of the system change dramatically. The autonomous control system includes fault diagnosis, autonomous decision-making, hybrid control modules. The issa algorithm is applied in the research of autonomous decision-making modules because of its strong ability of optimization and fast convergence. This paper improves the SSA algorithm from two aspects: population initialization and finder position update and the optimization ability. The simulation results show that the autonomous control system proposed in this paper can make a decision in the shortest possible time, and provide an effective automatic control method to make the OTSG quickly and smoothly reach the safe state.
Aiming at the problem that the capsule endoscopy robot cannot accurately obtain the position and orientation information of the capsule robot after it enters the human body,this paper investigates the optimization alg...
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ISBN:
(数字)9789887581581
ISBN:
(纸本)9798350366907
Aiming at the problem that the capsule endoscopy robot cannot accurately obtain the position and orientation information of the capsule robot after it enters the human body,this paper investigates the optimization algorithm to solve the position and orientation information of the permanent magnet based on the magnetic dipole *** on the basis of Sparrow Search algorithm(SSA),this paper proposes an Improved Sparrow Search algorithm(issa).And a set of permanent magnet positioning experimental device is built by using the Hall effect-based IST8310 three-axis magnetic sensor from iSentek,and the standard positioning experimental board is customized to verify the accuracy and stability of the issa algorithm through the permanent magnet positioning *** experimental results show that compared with the SSA algorithm,the issa algorithm has a great improvement in the positioning and orientation accuracy as well as the convergence speed,and it is also superior to many other optimization *** the issa algorithm for permanent magnet localization experiments,the positioning error can be stabilized at about 1mm and the orientation error at about 2° within tens of milliseconds,which greatly improves the positioning and orientation accuracy as well as the positioning speed of the permanent magnet,and provides a reliable method for accurately obtaining the position and orientation information of the capsule robot.
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