9results about How to "Calculation method is simple" patented technology

The present application provides a kind of formation threshold WOB and threshold torque determination method and device, belong to drilling engineering technical field, the method includes: obtaining different preset top drive speed under, in the preset WOB interval, the mechanical drilling speed, torque value and drill bit vibration parameters corresponding to different WOB value;For each preset top drive speed: based on the WOB value of the preset top drive speed and the mechanical drilling speed corresponding to the WOB value, determine the initial threshold WOB of the preset top drive speed from the WOB value;Based on the initial threshold WOB of the preset top drive speed, the torque value corresponding to the preset top drive speed is determined as the initial threshold torque of the preset top drive speed;Based on the drill bit vibration parameters corresponding to initial threshold WOB, initial threshold WOB and initial threshold torque are corrected, and formation threshold WOB and formation threshold torque are obtained.The present application has the advantages of simple calculation method, more accurate result, can effectively guide the selection of drill bit and screw rod, improve the mechanical drilling speed, and improve the rock breaking efficiency.

This invention discloses a method for calculating crack stress intensity factor based on a three-dimensional weighted function method, belonging to the field of reliability technology. Based on the Taylor series expansion method of complex functions, a complex variable finite element program is run to obtain the weighting function for a given crack geometry. Then, the stress intensity factor of the crack is obtained by integrating the stress on the crack surface with the weighting function. Specifically, a finite element model containing the crack is established and meshed; the nodes of the crack tip are perturbed on the imaginary axis; the imaginary part of the crack opening direction at the nodes on the crack surface is obtained by running the complex variable finite element program, thus obtaining the weighting function on the crack surface; the stress intensity factor at the nozzle corner is solved by integrating the weighting function and the stress on the crack surface. Compared to two-dimensional weighting functions, this method extends to three-dimensional elliptical cracks, broadening its application range; the method provides accurate calculation results for the stress intensity factor at the nozzle corner under complex loads, and is simple and effective to use.

The present application provides a kind of rock drillability grading method, comprising the following steps: step S1, carries out cutter penetration test, calculates rock drillability index;Step S2, establish the single factor calculation model of rock drillability index and each influencing factor of rock drillability;Step S3, the correlation analysis of each influencing factor of rock drillability is carried out two by two, and determines key influencing factor;Step S4, based on key influencing factor, establish the prediction model of rock drillability index;Step S5, establish the calculation model of rock drillability index and underground engineering rock mass quality index;Step S6, establish the rock drillability classification standard of Cretaceous and Jurassic strata.The method is based on the penetration load-penetration curve obtained from cutter penetration test, determines rock drillability index, provides evaluation index for rock drillability research, the evaluation index is clear in meaning, and the calculation method is simple, realizes the rock drillability of Cretaceous and Jurassic strata is predicted.

The application discloses a wind power bearing capacity analysis method and system based on anti-peaking characteristics, and the method comprises the following steps: performing cluster analysis on the normalized daily wind power output characteristic data set to obtain a clustering result; based on the clustering result, calculating a wind power clustering weighted anti-peaking coefficient and a wind power clustering typical characteristic anti-peaking coefficient; according to the information of the installed capacity of each type in the to-be-tested region, calculating the total amount of peak regulation supply in the to-be-tested region; taking the total amount of peak regulation supply greater than or equal to the total demand for peak regulation as a constraint, and based on the wind power clustering weighted anti-peaking coefficient and the wind power clustering typical characteristic anti-peaking coefficient, respectively calculating a wind power clustering weighted bearing capacity and a wind power clustering typical characteristic bearing capacity; and based on the wind power clustering weighted bearing capacity and the wind power clustering typical characteristic bearing capacity, obtaining the wind power bearing capacity interval of the to-be-tested region. The application can accurately solve the range interval of the wind power bearing capacity of the region on the basis of calculating the peak regulation supply capacity of each type of power supply in the region.

This invention relates to the field of automotive control methods, specifically to a method for estimating the driving range of a pure electric vehicle. The method comprises the following steps: S1, obtaining the real-time power consumption and remaining battery power of the vehicle's auxiliary components; S2, dividing the vehicle's historical mileage into short and long mileage segments according to a set distance, and calculating the average motor power consumption for the short and long mileage segments respectively; S3, calculating the current average motor power consumption based on the average motor power consumption for the short and long mileage segments and their respective weighting coefficients; S4, calculating the remaining driving range of the electric vehicle based on the current average motor power consumption, remaining battery power, and real-time power consumption of the auxiliary components. The method for estimating the driving range of a pure electric vehicle in this application is simple. By distinguishing between short and long mileage segments and calculating the average motor power consumption for each segment, the final driving range is calculated. This method considers the power consumption characteristics of the motor under different mileage segments, resulting in a more accurate calculation.

This application relates to the field of autonomous driving technology, and particularly to a method, apparatus, vehicle, and storage medium for generating laser point clouds. The method includes the following steps: acquiring the horizontal position information, longitudinal position information, size information, and heading angle information of each detected target within the detection area of ​​a lidar; calculating the two-dimensional point cloud coordinates of each corner point of the detected target based on the horizontal position information, size information, and heading angle information, and calculating the angle between the lidar and the upper and lower edges of the detected target based on the longitudinal position information and size information; calculating the actual height of each corner point based on the angle, and generating the laser point cloud coordinates of the detected target based on the two-dimensional point cloud coordinates of each corner point and the actual height. This solves the problems of high complexity, high resource consumption, and difficulty in applying to implementation testing and large-scale scenario testing in current point cloud generation methods.

An early fault diagnosis method for cross-stage multi-condition based on permutation spectrum difference measurement, including: collecting vibration signals of mechanical equipment under different states in the manufacturing test stage and the actual use stage, dividing the vibration signals into multiple subsequences through a combination of characteristic parameters, and reconstructing the subsequences into the original phase space; obtaining all possible permutation patterns according to the embedding dimension of the vibration signals, and converting the original phase space into a symbolic phase space; counting the number of occurrences of various permutation patterns in the symbolic phase space to obtain permutation spectrum characteristics; obtaining the difference degree between the vibration signals collected under different states; establishing a parameter selection model to select the best parameter combination; calculating the permutation spectrum characteristics of each time series using the best parameter combination, inputting the permutation spectrum characteristics of the data in the manufacturing test stage into a multi-class SVM classifier to obtain a training model, and inputting the permutation spectrum of the data in the actual use stage into the training model to identify the fault type and operating condition corresponding to the time series.

This invention proposes a three-phase parameter detection circuit and method for power systems with a power frequency transformer connected, relating to the field of three-phase parameter detection in power electronics. With a power frequency transformer connected at the input, this solution, through a first and second power system three-phase parameter detection circuit, can detect phase loss in the S-phase, R-phase, and T-phase, and also performs phase sequence detection. Compared to traditional circuits, this solution has advantages such as low interference from external components, low cost, and wide application range. It can accurately determine the input phase loss of each phase and achieve phase sequence detection.

A method and apparatus for detecting the working parameters of a forklift includes: 1) obtaining a top-view image of the current forklift; 2) calculating the current pixel distance A1 of a first set of labels and comparing it with the initial pixel distance A0 to determine whether a change has occurred; if so, calculating the distance H1 between the current image acquisition module and the forks according to a first proportional relationship, and proceeding to step 3); if not, calculating the final height H of the current forks as H = H0; 3) determining whether a second set of labels appears in the top-view image; if so, calculating the current pixel distance B1 of the second set of labels in the top-view image and calculating the current height change value H2 of the inner mast according to a second proportional relationship, and proceeding to step 4); if not, calculating the final height H of the current forks as H = X - H1; 4) calculating the final height H of the current forks as H = (X - H1) + H2. This invention only requires the acquired image to calculate the working parameters of the forklift, eliminating the need for sensors and reducing costs.