7results about How to "Eliminate calculation errors" patented technology

The application provides a three-axle tractor slip ratio error elimination method, device and electronic equipment, which comprises the following steps: determining the tractive force and slip ratio of different tractive force sample points of the three-axle tractor; dividing the different tractive force sample points of the three-axle tractor into multiple regions based on the tractive force of the different tractive force sample points of the three-axle tractor; determining the tractive force average value and slip ratio average value of the tractive force sample points in each region based on the tractive force and slip ratio of the different tractive force sample points of the three-axle tractor; fitting the tractive force average value and slip ratio average value based on the weighted least square method, determining the slip ratio error caused by the rolling radius of the three-axle tractor based on the fitting result, and correcting the rolling radius based on the slip ratio error to eliminate the slip ratio error. The application can eliminate the slip ratio calculation error of the three-axle tractor without increasing the hardware cost, and the calculated slip ratio is more accurate.

The invention relates to a data processing method of a power market technical support system. The method comprises the following steps: acquiring a pre-configured target power plant list; controlling the automatic processing unit to execute the following operations: accessing the power market technical support system, and completing identity verification login; in the logged-in system, navigating to a specified analysis page containing real-time electricity price data of a plurality of power plants; for each target power plant in the target power plant list, executing data acquisition operation: positioning from a specified analysis page and entering a detail page of the target power plant, and obtaining electricity price data of a current time period; after electricity price data collection of all target power plants is completed, a comprehensive electricity price value is obtained through calculation; and sending a notification message containing the comprehensive electricity price value and / or the current time to a specified communication terminal. According to the method, the bottlenecks of low efficiency, poor real-time performance and difficulty in guaranteeing accuracy in real-time electricity price data acquisition, calculation and synchronization links in the electricity market in a manual operation mode are overcome.

The embodiment of the application provides a real-time acquisition method and system of welding heat input, the method comprises the following steps: perceiving displacement movement of a welding torch or a welding wire through a diffuse reflection photoelectric switch array installed on the surface of a pipeline, and generating a corresponding pulse trigger signal; perceiving current data and voltage data of a welding circuit through a Hall sensor system, and generating a corresponding analog electric signal; synchronously acquiring the pulse trigger signal and the analog electric signal through a multi-channel data acquisition device, and converting the analog electric signal into a digital signal with a time stamp; calculating real-time welding speed data according to the time sequence of the pulse trigger signal and the preset spatial geometric relationship of a plurality of diffuse reflection photoelectric switches; performing multi-stage filtering processing on the current data and the voltage data; determining a unified time stamp, and performing time sequence matching on the filtered current data, the voltage data and the welding speed data based on the unified time stamp; and calculating a welding heat input value.

The application discloses an open pit slope groundwater seepage and stability coupling early warning method and system, belongs to the field of geotechnical engineering monitoring and geological disaster early warning, and the method comprises the following steps: acquiring real-time monitoring data set of the open pit slope; calculating the volume strain state of the slope rock mass unit based on the surface displacement vector data, and combining a rock mass damage evolution model to inversely calculate the permeability coefficient tensor of the slope rock mass at the current time, thereby generating a dynamic permeation parameter set; taking the rainfall data and the groundwater level data as boundary conditions, and inputting the dynamic permeation parameter set into a three-dimensional unsaturated seepage-stress coupling model for iterative calculation; and according to the pore water pressure field distribution data and the stress field distribution data, calculating the real-time stability coefficient of the slope by using a strength reduction method, generating a graded early warning signal and outputting the same. The application realizes two-way strong coupling of fluid and solid, and restores the real disaster-causing mechanism.

The application discloses a bearing fault classification method and related device. The method comprises the following steps: inputting a first vibration signal collected under a plurality of known fault types of a bearing into a preset dictionary learning algorithm model after processing, and constructing a sparse dictionary containing a plurality of fault type training samples; processing a second vibration signal collected for fault classification to obtain a test sample, performing sparse optimization solving on the test sample, and obtaining a first sparse coefficient; respectively reconstructing the first sparse coefficient and the training sample under a plurality of fault types, and obtaining a plurality of fault type corresponding reconstruction signals; comparing the test sample with the plurality of fault type corresponding reconstruction signals, and determining the fault type corresponding to the test sample according to the comparison result. The application can accurately and effectively realize bearing fault classification diagnosis.

The application relates to the technical field of river hydrological testing, in particular to a multi-channel river flow calculation method based on an acoustic time difference method, which comprises the following steps: calculating the average flow velocity of the near-river-bottom partial area according to the measured flow velocity of the near-river-bottom channel and a river bottom shape coefficient, multiplying the average flow velocity by the near-river-bottom partial area to obtain the near-river-bottom partial area flow; determining the average flow velocity of the inter-channel partial area according to the measured flow velocities of two adjacent channels, multiplying the average flow velocity by the inter-channel partial area determined according to the elevations of the two adjacent channels to obtain the inter-channel partial area flow; calculating the surface flow velocity according to a logarithmic flow velocity formula and the measured flow velocity of the near-surface channel, then calculating the average flow velocity of the near-surface partial area, multiplying the average flow velocity by the near-surface partial area to obtain the near-surface partial area flow; and adding the near-river-bottom partial area flow, the inter-channel partial area flow and the near-surface partial area flow to obtain the final river cross-section flow. The method effectively improves the accuracy of river flow calculation.

The present application relates to HVAC system intelligent control and fault diagnosis technical field, specifically to a kind of refrigeration system energy consumption optimization method based on machine learning;Contain ideal benchmark construction, virtual fault simulation, residual projection identification and closed-loop correction steps;System is through the collection real-time load and environmental data, based on inverse Carnot cycle constructs ideal state vector;Its core is to generate virtual fault state vector using Taylor series expansion, calculate the projection similarity of real-time characteristic residual and virtual characteristic residual, to accurately identify fault;When identifying specific fault, automatically adjust control parameters or alarm;The present application constructs thermodynamic ideal benchmark to replace traditional historical data modeling, effectively decouples environmental variables, avoids misjudging equipment aging as normal, ensures the purity and accuracy of benchmark.