10results about How to "Strong response" patented technology

The invention discloses a hydraulic system and equipment for testing a hydraulic valve, and belongs to the technical field of hydraulic systems. An oil inlet of the hydraulic pump is connected with the oil tank; the tested valve comprises a plurality of inlets and outlets; one oil way of an oil outlet of the hydraulic pump is connected with the pressure regulating oil way, and the other oil way is connected with an oil inlet of the cartridge check valve; the pressure adjusting oil way adjusts the oil outlet pressure of the hydraulic pump; one oil way inserted into the oil outlet of the one-way valve is connected with a control oil way; the control oil way is used for adjusting the on-off and pressure of control oil of the tested valve; the other oil way is connected with an oil inlet of a proportional speed regulating valve, an oil outlet of the proportional speed regulating valve is connected with an oil inlet of a plug-in mounting type direction valve group, an oil outlet of the plug-in mounting type direction valve group is connected with an inlet of a tested valve, and a control cavity of the plug-in mounting type direction valve group is connected with an electromagnetic directional valve; an outlet of the tested valve is connected with the hydraulic cylinder and the throttling oil way. The hydraulic valve testing device can be suitable for testing high-pressure environments of various types of hydraulic valves.

The invention provides a multi-modal semantic guided three-dimensional target positioning method, a medium and equipment. The method is realized based on a multi-modal semantic guided three-dimensional target positioning model, and comprises a multi-view semantic prior module, a text coding module, a double-branch point cloud coding and multi-source comparison supervision module, a sparse scene graph construction and graph relationship learning module and a positioning decoding module. The multi-view semantic prior module is used for segmenting the 3D scene point cloud into a 3D object point cloud, generating a multi-view 2D visual representation and encoding the semantics of the multi-view 2D visual representation; the double-branch point cloud coding and multi-source comparison supervision module is used for injecting semantic features into a 3D object point cloud to obtain 3D fusion features and realizing multi-source feature alignment through multi-source comparison supervision; the sparse scene graph construction and graph relation learning module is used for constructing a sparse scene graph and optimizing the sparse scene graph through a graph attention network; and the positioning decoding module is used for decoding and outputting a positioning result. The method can improve the target positioning capability of the model in a complex scene.

The invention provides a real-time safe distance monitoring method and system for field operation and a storage medium, and the method comprises the following steps: calculating the distance between a field operator and a potential dangerous object or region as a first distance based on a real-time image of the field operation, and executing the subsequent steps if the first distance is smaller than a first set value; otherwise, continuing to calculate the first distance in real time; based on the real-time three-dimensional position data of the field operation, calculating the distance between the field operation personnel and the potential dangerous object or area as a second distance; performing data fusion on the first distance and the second distance to obtain a third distance; if the third distance is smaller than the second set value, alarm operation is executed; otherwise, continuing to calculate the first distance in real time. According to the invention, the technical advantages and advancement of various intelligent detection methods are fully combined, and the safety distance of field operation is effectively monitored in real time.

The invention provides a power supply industry-oriented large language model corpus construction method. The method comprises the following steps of 1, deploying an RAG system in a working environment of a power supply industry; 2, performing knowledge retrieval by using the RAG system to obtain a question text and a plurality of answer texts, namely question and answer texts corresponding to the question text; 3, vectorizing the question text to obtain a question vector; step 4, all problem vectors are clustered, and each cluster is coded to obtain a cluster code; 5, encoding all question and answer texts according to clustering categories, and segmenting the question and answer texts into question fragments according to a time sequence; step 6, extracting the question of the corpus in the question segment, generating an answer, and calculating the confidence of the answer; and 7, cataloguing the question, the corresponding answer and the confidence into a corpus record, and storing all corpus records to obtain a large language model corpus for the power supply industry.

The invention provides an ammonia gas sensor, a preparation method thereof and an ammonia gas detection device. The ammonia gas sensor comprises a substrate, an interdigital electrode and a gas sensitive layer, the interdigital electrode is arranged on at least one side of the substrate, and the gas sensitive layer is arranged on the surface of one side, far away from the substrate, of the interdigital electrode; the gas sensitive layer is prepared from a polyaniline-bismuth oxychloride composite material. The polyaniline-bismuth oxychloride composite material is used as a gas sensitive layer material of the ammonia gas sensor, so that the prepared ammonia gas sensor has the characteristics of strong response, fast recovery, high sensitivity and the like. Specifically, the strong covalent bond and weak Van der Waals force of bismuth oxychloride can enhance the adsorption effect and retention time of bismuth oxychloride on ammonia molecules, polyaniline has specific adsorption on ammonia, and the cooperation of bismuth oxychloride and polyaniline can enhance the response of the sensor to ammonia.

The invention discloses a preparation method and application of a sulfur passivation-resistant coupled energy-saving hydrogen production difunctional electrocatalyst, and relates to the technical field of preparation of energy-saving hydrogen production electrocatalysts, and the preparation method comprises the following steps: pretreatment of foamed nickel, hydrothermal reduction preparation of a MoSe2 / NiSex / NF catalyst, and coupled application of SOR and HER. According to the preparation method, a porous network and a multi-dimensional electron transfer path which are mutually connected in foamed nickel are utilized, and a high-temperature and high-pressure hydrothermal reduction method is adopted to anchor and grow a mixed phase component on a conductive substrate foamed nickel framework, so that effective compounding of multi-phase components is realized, and mass transfer and charge transfer are enhanced; the conductivity and the electrocatalytic activity are further improved; the prepared MoSe2 / NiSex / NF not only has the sulfur phobic characteristic, but also has selectivity on S < 2-> conversion, so that a polysulfide product instead of elemental sulfur is generated in the electrooxidation process, and the electrocatalytic activity of the MoSe2 / NiSex / NF in the long-term SOR process is maintained, thereby preparing the difunctional electrocatalyst with good conductivity, high catalytic activity and sulfur passivation resistance.

This invention discloses a training-free neurorehabilitation system combining peripheral visual stimulation and motor imagery, and its usage method. The system includes: a stimulation module, an SSVEP data acquisition module, an SSVEP classification and recognition module, a motor imagery data acquisition module, a motor imagery decoding model training module, a comparison module, and a motor imagery recognition accuracy statistics module. The system uses peripheral visual stimulation as the SSVEP signal induction paradigm. After each visual stimulus, SSVEP signal classification and recognition are performed, and the classification results are converted into control commands for rehabilitation equipment to drive limb training. Within 5 seconds thereafter, an active motor imagery task is performed, while motor imagery data is collected. The SSVEP signal classification results are used as training sample labels. Once the motor imagery data meets the training sample size, the motor imagery decoding model is trained, and the model's performance in recognizing motor intentions is evaluated, gradually reducing its dependence on peripheral visual stimulation.

The present invention provides a detection device for leakage of electric high-voltage equipment and its application. The detection device includes: a sampling unit, a carrier gas unit, a GC column and a detection unit. The sampling unit includes a first sampling pipeline, a quantitative loop, a control valve, a second sampling pipeline and a vacuum pump which are sequentially connected. The carrier gas unit includes a carrier gas pipeline, a pressure storage tank and a booster pump. The input end of the GC column is connected to the quantitative loop through a control valve. The detection unit includes an IMS detection system and an MS detection system, which are respectively connected to the output end of the GC column through a first injection pipeline and a second injection pipeline, and an injection solenoid valve is arranged on the second injection pipeline. The detection device in the present invention conveniently and quickly realizes single-mode and dual-mode switching of GC-IMS and MS through the interface of the sampling solenoid valve, thereby enhancing the environmental detection adaptability of the detection device and being able to realize SF detection of leakage of high-voltage equipment. 6 and SF 6 Decomposition products are tested in one stop.

The utility model relates to the technical field of smoke sensor, specifically relates to a power battery smoke sensor, and technical scheme main points include casing, circuit mainboard and top cap, set up the mounting surface on the casing, set up the side window on the opposite side of mounting surface, set up the emission seat, receiving seat, maze structure and bottom window on the casing, the emission seat is used for infrared emission pipe joint, receiving seat is used for infrared receiving pipe joint, based on emission and receiving route, the included angle of emission seat and receiving seat is greater than 90 degrees, the area between emission seat and receiving seat sets up maze structure, bottom window is close to maze structure, and the main circuit board covers the top of maze structure and is set up with the through -hole of position directly opposite bottom window in the middle, the top cap is buckled on the casing and covers circuit mainboard, and the top window of position directly opposite through -hole is set up on the top cap. The utility model discloses through adopt greater than 90 degrees infrared emission receiving route, adopt maze structure, improve the inductive accuracy.