8results about How to "Verify robustness" patented technology

This invention discloses an adaptive proximity valve block assembly and its control method based on hydraulic potential energy recovery. The valve block assembly is fixedly connected to a hydraulic cylinder. The valve block internally includes a balance and stabilization passage, a pre-charge buffer passage, a flow-limiting access passage, a main recovery passage, and a buffer chamber. The pre-charge buffer passage has a one-way throttling element and connects to the buffer chamber. The flow-limiting access passage has a fixed throttling orifice connecting the buffer chamber and an energy storage unit. The main recovery passage has a hydraulically controlled directional valve driven by the pressure difference between the buffer chamber and the energy storage unit. After recovery is enabled, the high-pressure return oil preferentially enters the buffer chamber to absorb the first wave of pressure redistribution due to the fast-forward characteristic of the one-way throttling element. Then, it slowly releases the second wave of impact by charging the energy storage unit at a low flow rate through the fixed throttling orifice. After the pressure difference shrinks to a threshold, the hydraulically controlled directional valve automatically opens the main recovery passage. This invention reconstructs the recovery entry from a one-step opening to a hydraulically automatic graded access sequence, significantly suppressing entry pulsation, avoiding main control misjudgment, and improving execution stability.

This invention discloses a method for registering industrial printed images based on a lightweight network. The method includes: S1 Image acquisition and dataset construction, which uses a CCD industrial camera to acquire images of the front and back of printed materials and constructs a training dataset by combining multispectral images; S2 Constructing a DHSiam network, which includes two parallel feature extraction networks; S3 Proposing an attention heterogeneous mechanism, which includes a position regression unit and a lightweight unit to enhance data representation and reduce model parameters; S4 Constructing a cross-entropy loss function with additional margin to enhance network performance metrics. This invention builds a hardware platform with 8 parallel GPUs, uses only AMC-Loss to distinguish image similarity, utilizes the attention heterogeneous mechanism to extract important information from feature maps at different scales, and adjusts model parameters to enhance the algorithm's performance on mobile devices, thereby comprehensively improving the model's ability to register printed images with different perspectives and deformations.

The application discloses a kind of multi-agent preset time formation control methods based on backstepping method under distance rigidity matrix, comprising: 1) based on the double integrator dynamics model of multi-agent system is established based on rigidity graph theory, define the minimum and infinitesimal rigidity frame corresponding to the expected formation;2) introduce backstepping design framework, define virtual speed error variable;3) introduce time-varying scaling function to construct time scale transformation;4) design distributed preset time controller;5) through numerical simulation and physical platform are verified, verify the effectiveness of distance error in user preset time under different initial conditions converges to the vicinity of zero.The application is fused by backstepping and preset time scaling function, for the first time in only local relative measurement distance rigidity formation Convergence time user self-defined preset is realized, and convergence time upper bound is independent of initial condition and controller parameter, provides reliable, engineering implementation solution for time-critical multi-agent cooperative task.

The invention aims to provide a phase unwrapping method based on extended Kalman filtering. The method comprises the following steps: A, constructing a two-dimensional phase unwrapping program MCC-EKFPU; and B, performing phase unwrapping processing on the interferogram by using a two-dimensional phase unwrapping program MCC-EKFPU to obtain an unwrapped phase of the interferogram. According to the method, the maximum correlation entropy criterion extended Kalman filtering theory is introduced into interferogram wrapping phase unwrapping, and an interferogram phase gradient estimation technology and a robust path tracking strategy are combined, so that the method has higher phase unwrapping precision and better robustness; the method has good application potential in interferogram phase unwrapping application with high accuracy requirements.

This invention discloses a method and system for collaborative scheduling of multiple types of V2G resources in the electricity-carbon certificate coupled market, belonging to the field of resource collaborative scheduling technology. The method includes: designing a two-way conversion mechanism between carbon quotas and green certificates in an established first model, introducing a carbon emission factor; constructing a master-slave game and Wasserstein split-bar optimization model based on the first model with the two-way conversion mechanism; establishing objective functions for a DSO multi-market joint clearing model and an EVA split-bar Mean-CVaR bidding decision model respectively; solving each objective function based on the constraints corresponding to each model, and performing collaborative scheduling of resources based on the solution results; balancing the economy and robustness of the scheduling strategy, achieving collaborative response of multiple types of V2G resources in the electricity-carbon-certificate multi-market, effectively improving the system's operational economy, power supply reliability, and decarbonization level.

The application discloses a kind of lithium ion battery distributed thermal process sensor fault estimation method, comprising: using two-dimensional partial differential equation to describe rectangular lithium ion battery distributed thermodynamic equation;Distributed thermal model of large size lithium ion battery is constructed;Using Chebyshev-Galerkin method, distributed thermodynamic equation and distributed thermal model are decomposed into reduced order model described by standard state space equation in time domain;State variable in reduced order model is constructed using sensor measurement output and a Hurwitz matrix, and enhanced reduced order model is constructed;Enhanced adaptive observer and error state space equation are constructed using enhanced reduced order model;Based on error state space equation, the fault strength of temperature sensor that fails is estimated using fast adaptive algorithm.The application can effectively estimate sensor fault, including time-invariant and time-varying fault, and single sensor and multiple sensor fault.

The invention belongs to the field of automatic control technology and multi-agent system cooperative control, and particularly relates to a multi-agent system fault-tolerant inclusion control method and system based on a neural network, and the control method comprises the following steps: S1, constructing a second-order multi-agent system; s2, constructing a full connection-fuzzy neural network; performing high-precision online fitting and approximation on non-ideal factors in the second-order multi-agent system to generate corresponding compensation items; s3, constructing a fixed time state observer, and estimating unknown position states and speed states of all the following intelligent agents within a preset time upper limit irrelevant to the initial state of the system; s4, constructing a fixed time sliding mode control law based on the estimation state and the compensation item; and S5, applying a fixed time sliding mode control law to the following agents, so that all the following agents converge and are stabilized in a dynamic convex hull formed by a plurality of leader states within a fixed time, and realizing inclusion control. According to the invention, the risk in practical application can be effectively reduced.

This invention belongs to the field of knee joint MRI segmentation technology, specifically relating to an efficient knee joint 3D MRI segmentation method and system based on iterative pseudo-label refinement. The method includes: constructing a training set based on knee joint 3D MRI volume data; training an initial segmentation model using a pseudo-label self-refinement strategy based on the training set to obtain a refined iterative segmentation model; and implementing knee joint 3D MRI segmentation based on the refined iterative segmentation model. This invention first analyzes the relationship between different annotation ratios and segmentation performance, and based on this, proposes an iterative pseudo-label refinement strategy. By progressively optimizing the quality of pseudo-labels to reduce reliance on manually labeled data, a more efficient knee joint MRI segmentation method is explored.