7results about How to "Reduce dependence on experience" patented technology

The invention belongs to the technical field of coal mine safety monitoring, and discloses a coal mine tunnel roof disaster real-time early warning system and method. Comprising the following steps: performing time sequence reasoning on monitoring data acquired in real time, respectively judging whether the key physical quantity of the roof triggers primary early warning or secondary early warning by acquiring an expected value prediction curve and an uncertainty boundary curve of the key physical quantity of the roof in a future time step, and acquiring corresponding early warning information when the early warning is triggered; constructing a dynamic causal graph, inputting the early warning information and the currently acquired key physical quantity into the dynamic causal graph for reasoning, calling candidate intervention measures based on the acquired current state node to perform anti-fact reasoning in the dynamic causal graph, and acquiring a risk evolution trajectory and a risk suppression efficiency index of the candidate intervention measures; and the risk suppression efficiency indexes are sorted and preferentially selected, and a causal decision early warning report containing the optimal intervention scheme is output, so that the scientificity and effectiveness of risk suppression are improved.

The present application belongs to the technical field of probe processing, and particularly relates to a novel welding method for a MEMS probe. The novel welding method for the MEMS probe constructs and initializes a digital twin model of core components of the MEMS probe welding, combines a real-time collected synchronous three-dimensional data set and a lightweight agent model, and accurately outputs thermal stress distribution data, so as to early understand the thermal stress change in the welding process, effectively control potential risks, and when the risk condition is determined, the potential root cause can be diagnosed in-depth and the final adjustment suggestion can be generated. The accurate dynamic regulation mechanism enables the welding process to be flexibly optimized according to the real-time working condition, ensures the stable and reliable welding quality, avoids the welding defects caused by the out-of-control thermal stress, greatly improves the yield of the MEMS probe welding, reduces the production cost, and improves the production efficiency.

The invention discloses a portable pipeline blockage point rapid positioning instrument and method based on pressure transient analysis, the positioning instrument comprises a positioning instrument host, a butt joint of a three-way structure, a high-speed electromagnetic valve and a high-frequency pressure sensor, the high-speed electromagnetic valve and the high-frequency pressure sensor are integrated in the butt joint; and signal and power supply connection with the host is realized through the quick connector. The positioning method comprises the following steps: connecting equipment and recovering a signal; the host controls the high-speed solenoid valve to instantly open and close to generate pressure pulse; the high-frequency pressure sensor collects incident and blocking point reflection pulse signals; the host preprocesses the data through wavelet transform, cross-correlation analysis and other algorithms and calculates a pulse time difference delta t; and calculating and displaying the distance of the blocking point according to a formula S = (wave velocity a * delta t) / 2, wherein the wave velocity can be calibrated through a self-adaptive algorithm. The positioning precision reaches the meter level, equipment is portable, operation is easy and convenient, point distribution and excavation in advance are not needed, the method is suitable for multi-material pipelines, and the detection cost and the technical threshold are reduced.

This invention relates to the field of metal cutting technology and discloses a steel coil slitting device integrating blade deep processing. The device includes a feeding machine tool with stabilizing side plates fixed at both ends. A drive assembly is mounted on the feeding machine tool, comprising two support frames fixed to the stabilizing side plates at both ends of the machine tool. A first drive mechanism and a second drive mechanism are mounted on the support frames. The first drive mechanism includes a rotating rod rotatably connected between the two support frames. By integrating blade maintenance functions onto the slitting machine tool and directly utilizing the cutting kinetic energy of the CNC blade rotation to drive the grinding and dust removal mechanisms, constant-pressure fine grinding and surface cleaning of the CNC blade sides can be simultaneously completed while the metal cutting and slitting operation continues. This achieves true online blade deep processing, avoiding the drawbacks of traditional methods that require stopping the machine to disassemble the blades, and greatly improving the overall operating efficiency and productivity of the equipment.

The invention relates to the field of image processing, and provides an image control point processing method and electronic equipment, and the method comprises the steps: obtaining at least one to-be-detected control point in a to-be-detected image, setting a plurality of epipolar lines corresponding to the to-be-detected control point according to the relative relation between a plurality of reference images and the to-be-detected image, the to-be-inspected control points are automatically inspected as the stable control points or the unstable control points by means of the multiple epipolar lines, manual intervention is not needed, experience dependence and subjective deviation of workers are remarkably reduced, and the efficiency, accuracy and reliability of processing the image control points can be considered easily.

This invention proposes a reconfigurable metasurface beamforming design method based on CGAN and Gumbel-Sinkhorn. This method constructs a conditional generative adversarial network (GAN) as the inverse design network. The generator takes the target beam pattern as a conditional input to generate the corresponding encoding matrix. The Gumbel-Sinkhorn operator is introduced to discretize this continuous matrix, transforming it into an approximately doubly random permutation matrix. The encoding is sorted and selected by multiplying this permutation matrix with a predefined structure vector (SV), outputting a discrete 0 / 1 metasurface encoding array. A noisy forward prediction network is trained to predict the beam pattern corresponding to a given encoding array. In the training of the inverse design network, the discretized encoding matrix output by the generator is input into the noisy-trained forward prediction network. The mean square error between the predicted beam pattern and the target beam pattern is calculated as the target loss term to optimize the network parameters and accurately learn the complex mapping relationship from the beam pattern to the encoding array.

The invention relates to an intelligent alignment compensation method for assembly of a liquid crystal panel and a backlight module, and aims to solve the problems of dynamic pose deviation and weight mismatch caused by material batch difference, nonlinear deformation and environmental factors in a high-precision fitting process. According to the core technology, an industrial camera array and a multi-source sensor are used for collecting multi-dimensional micro texture and environment data, a fingerprint spectrum of intrinsic deformation characteristics of a material is established in a fusion mode, spectrum matching and weight self-adaptive calibration are carried out in combination with real-time working conditions and visual feedback, and six-degree-of-freedom micro dynamic correction is achieved through FPGA acceleration driving control. According to the scheme, the sub-pixel-level precision in the attaching process of the liquid crystal panel and the backlight module is effectively improved, the nonlinear deformation trend of materials is restrained, the control instruction response speed is optimized, continuous and accurate calibration of self-adaptive compensation weights among batches is guaranteed, and the process consistency and the automation level are improved.