6results about How to "Quick and accurate judgment" patented technology

A battery assembly according to one embodiment can include: a plurality of battery cells each including an electrode assembly, an outer material internally accommodating the electrode assembly, and an electrode lead connected with the electrode assembly and protruding outside the outer material; a busbar electrically connected with each electrode lead of the plurality of battery cells; a through-hole formed through the busbar; a measurement portion measuring an electrical property of at least one battery cell of the plurality of battery cells; and an insulation measurement member one end of which is connected with the outer material of one battery cell of the plurality of battery cells and the other end of which is electrically connected with the measurement portion.

This invention discloses a method for rapidly detecting conventional and hybrid varieties of industrial chili peppers and its application, relating to the field of molecular breeding technology. The method includes: extracting DNA from fresh leaves of the industrial chili pepper to be tested and performing whole-genome resequencing at a sequencing depth of 8×–12×; aligning the sequencing data to the chili pepper reference genome (Capsicum chinense cv. 'PBC932') to screen for high-quality heterozygous SNP loci; using a 1 Mb sliding window to statistically analyze the distribution density of heterozygous SNPs across the entire genome; and determining the variety type based on density thresholds: an average density <300 SNPs / Mb indicates a conventional variety, and >2000 SNPs / Mb indicates a hybrid variety. This invention eliminates the need for phenotypic observation in subsequent generations, requiring only leaves from current-generation plants to rapidly and accurately distinguish conventional and hybrid varieties at the molecular level. It features a short detection cycle, objective and reliable results, and is not limited by the number of molecular markers, providing strong technical support for efficient identification and early screening of industrial chili pepper germplasm resources.

This invention proposes a high- and low-voltage line strong discharge monitoring system and method based on video image recognition, relating to the field of strong discharge monitoring. It includes a camera for acquiring video streams of high- and low-voltage lines and sending them to an image analyzer; the image analyzer extracts keyframe images from the video streams, extracts static and dynamic spark features based on the keyframe images, and inputs a feature vector composed of these features into an extreme learning machine for spark recognition, generating a discharge warning signal, which is then sent to a remote server; the remote server receives and displays the discharge warning signal. This invention improves the accuracy of video spark image recognition and can quickly and accurately determine the discharge location, ensuring the safe and stable operation of the power grid and reducing economic losses caused by transmission line discharge faults, thus having significant social and economic implications.

A multi-dimensional time series data dynamic evolution analysis method, device, medium and electronic equipment, the method comprises the steps of: obtaining and structuring pre-processing time series data; each of the time series data is quantified and attributed in multiple dimensions, and a three-dimensional data node containing spatial coordinates, initial weight and timestamp is constructed; based on the set of three-dimensional data nodes in a specific time window, a three-dimensional data density field is constructed which can represent the data hotspot distribution and intensity in the time window; in the three-dimensional data density field, the density peak area is identified as the core data cluster, and the cluster quality is calculated according to its density and coverage, and the association strength between different core data clusters is calculated; the sequence of the state snapshots of the continuous multiple time window data fields is serialized to form a dynamic evolution view which can show the birth and death of data hotspots, the fusion and splitting process of data clusters. The abstract multi-dimensional data is converted into intuitive three-dimensional density field.

The utility model belongs to the field of wheel hub detection, and particularly relates to a wheel hub end face flatness detection device, which comprises a workbench, the bottom of the workbench is fixedly connected with supporting legs, the upper surface of the workbench is fixedly connected with a bearing seat, the inner wall of the bearing seat is fixedly connected with a first bearing, and the inner wall of the first bearing is fixedly connected with a second bearing. The inner ring of the first bearing is fixedly connected with a first cylinder, the upper surface of the first cylinder is fixedly connected with a detection disc, and the upper surface of the detection disc is fixedly connected with a gasket. Through cooperation of a rectangular cylinder, a strip-shaped hole, a first sliding block, a first limiting ring, a first U-shaped plate, a second limiting ring, a second sliding block, a semicircular groove, a semicircular block, a mounting frame, an electronic dial indicator, a transverse plate, a rectangular hole and a feeler gauge, when the detection device detects the flatness of the end face of the hub, the flatness of the end face of the hub is detected by observing readings on the electronic dial indicator; therefore, the flatness of the end face of the hub can be quickly and accurately judged.

This application provides a method, apparatus, device, and medium for photovoltaic (PV) equipment fault detection, relating to the field of PV equipment maintenance. The method includes: acquiring the output voltage and current values ​​of the PV equipment under different temperatures and light intensities; determining a first training sample set; augmenting the training samples to obtain a second training sample set; training the second training sample set using a local Mahalanobis distance algorithm; determining the anchor point set and fault region boundary for detecting PV equipment faults; and finally, performing fault detection on the target PV equipment based on this set. This approach reduces the number of samples required for training, improving work efficiency. Furthermore, the augmented training samples cover various operating conditions and models of PV equipment, greatly enhancing the versatility of the fault detection method. Moreover, the local Mahalanobis distance algorithm can identify subtle deviations, resulting in higher sensitivity of the fault detection results, achieving accurate and efficient detection of PV equipment faults.