9results about How to "Accurate judgment basis" patented technology

The invention discloses a mudstone intelligent identification method for seismic indication crossing fracturing, and belongs to the technical field of unconventional oil and gas fracturing development. The intelligent mudstone identification method comprises the steps of making a horizontal well actual drilling track 2D lithologic label, solving a depth domain inversion body, constructing a lithologic sample earthquake 4D intelligent discrimination label, calculating a lithologic comprehensive evaluation body S5, intelligently indicating cross-layer fracturing transformation and the like. By using three-dimensional seismic data to carry out technical means such as accurate identification of a spatial mudstone section, accurate identification of effective reservoirs around the mudstone section and comprehensive evaluation of a reservoir structure and a combination relation of the reservoir structure, intelligent prompting of a strata-penetrable fracturing section in space is realized, and an accurate judgment basis can be provided for accurate strata-penetrable fracturing transformation of an unconventional oil and gas horizontal well; and the purpose of fully utilizing underground geological reserves is achieved. The intelligent identification method provided by the invention can be applied to fracturing development of unconventional oil and gas.

The invention provides a device for testing an intelligent switch, and the device comprises a workbench and a switch body, a main body seat is installed on the workbench, the main body seat is provided with a main body plate, the main body plate is provided with a sliding rail, and the sliding rail is provided with an electric sliding block; a fixing assembly is arranged between the two sets of electric sliding blocks, and the switch body is clamped in the fixing assembly through a connecting box. Transmission plates are arranged at the two ends of the connecting box, the workbench and the main body cover are connected to form a main body cavity, two communicating assemblies are arranged in the main body cavity, and the transmission plates are clamped in the communicating assemblies; a test module is installed on the workbench, and the test module is electrically connected with the switch body through two groups of switching-on assemblies. According to the testing device, the switch body is fixed in the fixing assembly through the connecting box, the transmission plate arranged on the connecting box is clamped in the switching-on assembly, and the switch body is electrically connected with the testing module through the transmission plate and the switching-on assembly, so that the problems of connection errors, poor contact and the like caused by human factors are reduced, and the testing accuracy and reliability are improved.

This invention discloses a method, device, equipment, and medium for monitoring high physiological stress based on rPPG. First, a video sequence containing the user's face is acquired, and the region of interest (ROI) sequence is extracted and input into a deep learning network model. A spatiotemporal encoder extracts preliminary spatiotemporal physiological feature sequences from these sequences. Then, relying on an adaptive frequency-aware decoder, multi-scale parallel processing and dynamic feature fusion are performed on these preliminary spatiotemporal physiological feature sequences to output feature representations of abnormal high-frequency rhythmic events. Finally, a state determiner, combined with the abnormal high-frequency rhythmic event identification results, directly outputs a binary classification result indicating whether the user is in a state of high physiological stress. This invention effectively solves the problem of abnormal high-frequency rhythmic signal loss caused by existing fixed filters, achieving high-precision identification of abnormal high-frequency rhythmic events and accurately determining the user's state of high physiological stress.

The invention discloses a stator winding end portion corona discharge detection method based on multi-signal joint monitoring, and relates to the technical field of large generator stator winding end portion corona discharge detection, and the method comprises the steps: S1, collecting corona discharge signals; s2, processing a corona discharge signal; s3, judging the state of corona discharge; and S4, the detection result is stored and conveyed, and corona discharge signal collection comprises three parts of high-frequency signal monitoring, ultraviolet monitoring and characteristic product monitoring. According to the method, three different corona discharge signals of high-frequency signals, ultraviolet rays and characteristic products are integrated, and the corona discharge of the end part of the stator winding is comprehensively judged, so that the problems of limitation, easiness in interference and the like existing in a traditional single-factor detection method are solved; and an accurate judgment basis is provided for corona discharge detection of the end part of the stator winding. A high-frequency sensor of an improved composite antenna is selected to monitor high-frequency signals, and the width of a monitoring frequency band is expanded.

The present invention relates to a method and device for predicting the output ramp rate of a photovoltaic power station during a solar eclipse, comprising: obtaining a total radiation attenuation rate prediction sequence of a photovoltaic power station during a future solar eclipse period; assuming the future solar eclipse period to be a clear sky period, and obtaining a clear sky total radiation prediction sequence of the photovoltaic power station during the clear sky period; determining a total radiation prediction sequence of the photovoltaic power station during a future solar eclipse period based on the total radiation attenuation rate prediction sequence of the photovoltaic power station during the future solar eclipse period and the clear sky total radiation prediction sequence of the photovoltaic power station during the clear sky period; determining an output ramp rate prediction sequence of the photovoltaic power station during a future solar eclipse period based on the total radiation prediction sequence of the photovoltaic power station during the future solar eclipse period; the output ramp rate of the photovoltaic power station during a solar eclipse predicted by the present invention can provide an accurate judgment basis for reflecting the impact of the solar eclipse on the output of the photovoltaic power station.

The invention provides an interlocking control method, device and equipment for oil depot unloading equipment and a medium, and the method comprises the steps: receiving a state change signal sent by a position detection switch of the unloading equipment, judging the operation state of the unloading equipment according to preset interlocking logic based on the received signal, and outputting the operation state of the unloading equipment. When the operation state of the unloading equipment meets the interlocking control condition, an interlocking action signal is sent to execution equipment, and a signal fed back by the execution equipment after the execution equipment executes an interlocking action according to the interlocking action signal is received, the technical problems that in the transfer oil depot loading and unloading process, equipment is not effectively reset, so that loading and unloading equipment is damaged, personnel are injured, and oil leaks are solved.

This invention provides a method and system for taking over autonomous driving in vehicles. The method includes the following steps: identifying the driver's fatigue level based on real-time acquired facial images; outputting corresponding reminders based on the driver's fatigue level, and selecting between maintaining vehicle operation through autonomous driving or controlling the vehicle to pull over through autonomous driving. This invention can provide safety reminders while automatically activating different levels of autonomous driving functions, effectively reducing vehicle safety accidents caused by sudden health issues of the driver.

The present application relates to the technical field of liquid pressure measurement, in particular to accuracy optimization design in the process of liquid pressure measurement. The purpose of the present application is to provide a pressure self-drainage type pressure measuring tube nozzle device and a monitoring method thereof. A physically isolated liquid phase pressure transmission path and a self-drainage exhaust path are constructed inside the nozzle piece, and the gathering and conditional discharge of gas are automatically completed. It is ensured that the signals obtained by the pressure acquisition module purely reflect the liquid phase pressure. The authenticity and reliability of the pressure data are improved, and the present application is suitable for long-term, continuous and automatic engineering monitoring scenes.

This invention provides a scheduling method and related equipment based on large model output length prediction. The method includes: acquiring a large model input request set, wherein the large model input request set includes multiple large model input requests within a time period; determining the corresponding predicted output length based on each input request; determining the scheduling priority of each input request based on each predicted output length; and controlling the output order of each input request in the large model input request set based on the scheduling priority. The method in this application solves the problem of head-of-line blocking that often occurs in current Model-as-a-Service platforms, improving the utilization rate of platform computing resources and the overall efficiency of request processing.