5results about How to "High detection cost" patented technology

The present application relates to the technical field of steel strip defect detection, and particularly relates to a cold-rolled stainless steel strip surface defect detection device, which comprises a detection workbench, two groups of deviation prevention assemblies are slidably installed on the detection workbench; a width adjusting assembly is installed on one side of each group of the deviation prevention assemblies; a width adjusting driving assembly is installed on the detection workbench; a steel strip winding assembly is installed on the detection workbench; a steel strip clamping assembly is installed in the steel strip winding assembly; a clamping interval adjusting assembly is installed in the steel strip winding assembly; a clamping driving assembly is installed in the steel strip winding assembly; and a defect detector is fixedly installed in the middle of the detection workbench. The present application can detect the steel strip without completely disassembling the steel roll, thereby reducing the operation and maintenance costs of various devices and improving the detection work efficiency. In addition, the interval between the clamping plate and the deviation prevention wheel can be adjusted, and the present application can be applied to steel strips with various widths, thereby reducing the detection cost.

The present application belongs to the technical field of soil compaction degree prediction, and particularly relates to a soil compaction quality prediction method, medium and terminal based on image recognition, comprising the following steps: S10, collecting data of soil compaction degree and soil surface compaction pictures of sand under different conditions; S20, preprocessing the collected pictures, including picture normalization, grayscale and binarization processing, and constructing a data set; S30, constructing an improved CNN neural network model based on the preprocessed data set; S40, importing the data set into the improved CNN neural network model for pre-training to obtain a pre-training model; S50, importing the collected pictures into the pre-training model, and performing freezing and fine-tuning on the pre-training model to obtain a sand compaction quality prediction model; and S60, importing the preprocessed surface compaction pictures of the sand to be detected into the prediction model to output a compaction degree prediction value. The present application has simple process and convenient operation, the obtained prediction model has strong robustness and generalization ability, and the prediction efficiency and accuracy of sand compaction quality are high.

The invention discloses a hydrogen production circuit for a PEM electrolytic cell and an online impedance detection method of the hydrogen production circuit, and aims to overcome the defect that an existing electrolytic cell impedance detection method needs to be shut down. The circuit comprises a first power supply circuit as a current source and a second power supply circuit as a voltage source, the first power supply circuit is connected in series with a first end of a PEM load, and the second power supply circuit is connected in series with a second end of the PEM load. One of the first power supply circuit or the second power supply circuit is injected with excitation harmonic waves, voltage and current signal acquisition circuits are arranged at the two ends of the PEM load, and the excitation harmonic waves are generated through a control module. The aging state of the electrolytic cell can be detected online, so that performance reduction of the electrolytic cell can be found in time.

The application belongs to the technical field of water pump leakproofness detection, and particularly relates to a water pump leakproofness detection system and a detection method, which comprise a supporting mechanism, and the top of the supporting mechanism is respectively provided with a conveying mechanism, an intermittent mechanism, a clamping positioning mechanism, a sealing mechanism and a leakproofness detection mechanism, and the supporting mechanism realizes supporting operation of the conveying mechanism, the intermittent mechanism, the clamping positioning mechanism, the sealing mechanism and the leakproofness detection mechanism. The water pump leakproofness detection system and the detection method realize quick installation and fixing in water pump detection through the clamping positioning mechanism, are simple to operate, enhance the installation efficiency, reduce the operation difficulty of workers, realize quick sealing operation through the sealing mechanism, have strong sealing effect, can also realize sealing operation when the inner wall of the sealing end of the water pump is irregular, prevent air leakage from causing detection failure and affecting the qualified rate of products, thereby enhancing the detection efficiency, reducing the influence caused by the inflow of unqualified products into the market, and having high automation degree in the whole detection process.

The invention provides a track detection and maintenance method and device based on 3D vision, equipment and a medium, and the method comprises the steps that a data collection module obtains point cloud data of a ground track in real time, and inputs the point cloud data to a preprocessing module; the preprocessing module preprocesses the point cloud data to obtain track data, and inputs the track data to the feature extraction module; the feature extraction module extracts feature data of the track data and inputs the feature data to the damage detection module; the damage detection module analyzes the feature data to generate detection data and inputs the detection data to the decision output module; and the decision output module generates a maintenance decision and a visualization result according to the detection data and a preset processing rule. The invention provides a real-time online, high-precision and intelligent track detection and maintenance method, the detection efficiency, continuity, stability and precision during track damage detection are remarkably improved, the maintenance efficiency and maintenance intelligence are improved, and the maintenance cost is reduced.