7results about How to "Avoid human interference" patented technology

The invention discloses a novel automatic oil cylinder assembling device which comprises a base, a cylinder barrel clamping mechanism, a centering device, a piston rod position adjusting mechanism and a piston rod press-fitting mechanism. A high-precision guide rail is laid on the base, and all the mechanisms are installed on the guide rail through sliding blocks and can be movably locked. The centering device measures the positions of the inner wall of a cylinder barrel and the outer wall of a piston rod in a non-contact mode through two sets of high-precision laser sensors, a control system drives a servo electric cylinder to adjust the pose of the piston rod according to measured data, and full-automatic high-precision centering of the axes of the cylinder barrel and the piston rod is achieved. The piston rod press-fitting mechanism adopts an electric cylinder with a force measuring sensor, and real-time monitoring of press-fitting thrust is achieved. The problems that traditional assembly depends on manual work, the centering precision is low, and the quality consistency is poor are solved, and high precision, high efficiency and high reliability of oil cylinder assembly are achieved.

The embodiment of the application discloses an ecological health assessment and repair decision method and system based on multi-modal data, and the method comprises the following steps: acquiring ecological time series data, spatial distribution image data and gene sequence data of an ecological system by using a multi-modal data perception layer; analyzing, identifying and extracting the three types of data respectively by using a time series ecological evolution analysis network, a spatial salinization distribution identification network and a gene sequence feature extraction network of an intelligent analysis layer to obtain time series ecological evolution features, spatial salinization distribution features and gene ecological adaptability features; performing feature fusion based on the time series ecological evolution features, the spatial salinization distribution features and the gene ecological adaptability features by using a multi-modal fusion network of the intelligent analysis layer to obtain fusion features; and determining a groundwater layer recharge adjustment scheme, an ecological restoration strategy and an ecological health state assessment result based on the fusion features by using a multi-task decision output layer.

This invention belongs to the field of high-speed data testing technology and discloses a method and system for testing high-speed signal eye diagrams based on automated testing equipment. The method includes: dividing the high-speed signal configuration vector into a configuration segment and an action segment. The configuration segment is used for quickly configuring the test environment, and the action segment is used for controlling test actions. In the action segment, a virtual clock is constructed as a reference trigger signal, and the virtual clock is synchronized with the high-speed signal under test to the same sequence group. The synchronized high-speed signal under test is waveform captured to generate a two-dimensional array composed of sampling time and level value. The two-dimensional array is processed using a differential peak-valley segmentation method, and eye height, rise / fall time, and jitter are measured based on the processing results. Automated testing equipment enables automated control, measurement, and output of test data, facilitating data analysis and processing, improving testing efficiency, and avoiding human interference.

The embodiment of the invention discloses an ecological health assessment and restoration decision-making method and system based on multi-modal data. The method comprises the following steps: acquiring ecological time sequence data, spatial distribution image data and gene sequence data of an ecological system by utilizing a multi-modal data sensing layer; respectively analyzing, identifying and extracting the three types of data through a time sequence ecological evolution analysis network, a spatial salinization distribution identification network and a gene sequence feature extraction network of the intelligent analysis layer to obtain time sequence ecological evolution features, spatial salinization distribution features and gene ecological adaptability features; performing feature fusion based on the time sequence ecological evolution features, the spatial salinization distribution features and the gene ecological adaptability features by using a multi-modal fusion network of the intelligent analysis layer to obtain fusion features; and a multi-task decision output layer is utilized to determine an underground water layer supplement amount adjustment scheme, an ecological restoration strategy and an ecological health state evaluation result based on the fusion features.

This invention discloses a method for calculating the carbon emission intensity and carbon emission amount of a pure condensing coal-fired power generation unit. It establishes a mathematical model to obtain a formula for calculating carbon emission intensity, calculates the as-received nitrogen and hydrogen content of coal using industrial analysis and calorific value data of coal from power plants, calculates the as-received carbon content of coal using empirical formulas, and calculates the standard coal carbon dioxide emission coefficient by combining data on the combustible content in ash. It obtains a relationship between the unit's power generation coal consumption and load rate by fitting coal consumption data under typical operating conditions. It calculates the power generation coal consumption for each statistical period based on the load rate, and combines this with the carbon dioxide emission coefficient to obtain the carbon emission intensity and carbon emission amount for each statistical period, thereby obtaining the cumulative carbon emission amount E. This invention does not require elemental analysis of the coal, uses readily available basic power plant monitoring data, is highly practical, and can promptly obtain carbon emission intensity and carbon emission amount for each statistical period. The data is accurate and timely, greatly facilitating carbon reduction management.

The present disclosure relates to a dynamic evaluation method and device for the peak regulation and frequency modulation response capability of a battery swap station based on two-dimensional analysis. The method comprises: constructing a multi-working condition evaluation index system for the peak regulation and frequency modulation response capability of the battery swap station, setting evaluation grades and score thresholds according to the grid operation working condition; using a subjective and objective fusion weight distribution method to calculate the comprehensive weights of static dimension indexes and dynamic dimension indexes respectively, and fusing by the product normalization method; calculating the closeness score of the static dimension of the battery swap station; constructing a dynamic response capability evaluation model based on the grey correlation degree method to calculate the grey correlation degree score of the dynamic dimension of the battery swap station; weighting and fusing the static score and the dynamic score to obtain the comprehensive score of the peak regulation and frequency modulation response capability of the battery swap station, and judging whether it meets the standard and participates in the priority according to the preset threshold. The present disclosure constructs a benchmark sequence consistent with the grid dispatching rules for different evaluation working conditions of the dynamic dimension, and improves the accuracy of the grey correlation degree method in the dynamic dimension evaluation.

The invention belongs to the technical field of greenhouse crop water and fertilizer management and green efficient sustainable production, and particularly relates to a greenhouse tomato yield and quality grading evaluation water and fertilizer management method, which is characterized by sequentially comprising the steps of data collection, weight determination, sorting, grading and optimal mode determination, weight determination adopts an integrated entropy weight method, sorting adopts a TOPSIS model, and the optimal mode determination adopts a TOPSIS model. And an AISM model is adopted in a grading manner, and finally an EWM-TOPSIS-AISM comprehensive evaluation model is constructed. The method has the advantages that an EWM-TOPSIS-AISM comprehensive evaluation model is constructed on the basis of field experiments, water and nitrogen management of greenhouse drip irrigation tomatoes in the northeast region is optimized on the basis of multiple targets, an optimal water and nitrogen supply mode is established, and a theoretical basis and technical support are provided for formulating a precise drip irrigation and fertilization strategy for greenhouse tomatoes in the northeast region; (2) the EWM-TOPSIS-AISM comprehensive evaluation model has the advantage that the problems of subjectivity and inconsistent results of a single model are effectively solved through a combined evaluation method, and (3) the evaluation result is stable and reliable through bidirectional verification of UP type and DOWN type topological hierarchy directed graphs.