21results about How to "Reliable calculation" patented technology

The invention discloses a multifunctional test bed for a horizontal rolling linear guide rail pair. The multifunctional test bed comprises a lower bed body, an upper bed body, a test assembly, a loading assembly and a dragging assembly, the lower lathe bed is composed of a base, a main guide rail and leveling ground feet, the upper lathe bed is composed of a moving plate, an auxiliary guide rail and a test assembly mounting table, the loading assembly is composed of a gantry, a hydraulic cylinder and a force sensor, the test assembly is composed of a tested guide rail pair, an adapter plate, a measuring frame, various sensors and a loading block, and the dragging assembly is composed of a lead screw guide rail pair and a servo motor. Various tests of comprehensive performance measurement, reliability, fatigue life and static rigidity of the rolling guide rail pair can be carried out on one device, two guide rail pairs can be tested at the same time, the performance and efficiency of the guide rail pair test bed are improved, and meanwhile the horizontal type mode facilitates installation of the tested guide rail pair.

The invention relates to the technical field of wind power plant output calculation, in particular to a reduction-considered wind power plant output calculation method, a storage medium and electronic device.The reduction-considered wind power plant output calculation method comprises the steps that time sequence simulation data of a wind power plant and draught fans are obtained; obtaining a simulation result summary sheet and a power curve; determining reduction coefficients, wherein the reduction coefficients comprise a plant power reduction coefficient, an uncertainty reduction coefficient and a total reduction coefficient of the wind power plant; calculating the output added with the uncertainty reduction; adjusting power above a rated wind speed; calculating the total loss below the rated wind speed; and obtaining a wind power plant output time sequence after the reduction is considered. According to the technical scheme, the problem that in the prior art, the wind power plant output calculation error is large is effectively solved.

The invention is suitable for the technical field of measurement, and provides a flatness measurement method, device and equipment and a storage medium, and the method comprises the steps: scanning the surface of a to-be-measured target through line laser according to a preset scanning track, obtaining the scanning data of the to-be-measured target, and enabling the scanning data to comprise brightness data and point cloud data; determining point location information of the to-be-measured target according to the brightness data, wherein the point location information of the to-be-measured target is used for determining a target positioning area of the to-be-measured target; filtering the point cloud data to obtain target point cloud data; generating height data of the to-be-measured target according to the target positioning area and the target point cloud data; generating a fitting reference plane according to the height data; and calculating the flatness of the to-be-measured target according to the fitting reference plane. According to the scheme, high-precision and high-efficiency flatness measurement can be realized.

The invention relates to the technical field of traffic transportation engineering, in particular to a method and system for constructing a high-speed railway line risk map by considering transportation efficiency loss, which comprises the following steps: constructing a train operation risk event type judgment model, and classifying and identifying station and interval risk events; high-speed rail line transportation efficiency loss is quantified, a calculation model is constructed, risk event probability analysis is carried out based on risk event type judgment and efficiency loss quantification, and space-time grid potential risk influences are measured and calculated; and drawing a line transportation risk map according to the quantized value, and analyzing influence factors. According to the method, various station and interval risk events are effectively extracted and judged, various risk influences are scientifically quantified by innovatively providing the instantaneous transportation loss rate and the line transportation loss rate, accurate mastering of the risk map on the severity level and the influence range of the risk events is improved, and the risk assessment accuracy is improved. Compared with the existing research, the time-space change and distribution condition of the risk influence of each level can be more intuitively mastered.

The invention discloses a scraper conveyor coal flow and coal quantity detection method based on a composite intelligent camera, and relates to the technical field of coal mining, and the coal flow and coal quantity detection method comprises the steps of equipment installation and calibration, image acquisition and processing, coal flow feature extraction, coal quantity calculation and result output, result verification and algorithm optimization. The coal flow quantity monitoring system has the advantages that comprehensive, real-time and intelligent monitoring of the coal flow quantity of the scraper conveyor is realized by integrating the composite intelligent camera, the light supplementing lamp, the illumination intensity sensor and the coal quality detection means, the coal quality change can be found in time by detecting the coal quality every other week, the coal density is re-evaluated according to the change, and the coal flow quantity can be accurately detected. According to the comprehensive intelligent monitoring and coal quality adaptability optimization strategy, the coal quantity detection precision is improved, the adaptability and reliability of the system are enhanced, and more accurate data support is provided for coal mine production.

The application relates to a terminal and a page generation method. The page generation method relates to the technical field of display devices. In the page generation method, when it is determined according to page information of a target page that a target content area in the target page contains a target function control, reference size information of a reference page is acquired; a reference direction of the target content area is selected from a width direction and a height direction according to a scrolling direction of the target content area; a scaling ratio of the target content area is determined according to actual pixel numbers of the target content area in the reference direction and reference pixel numbers of a reference content area in the reference direction in the reference size information; the reference size of the target function control in the reference content area in the reference size information is scaled according to the scaling ratio, so that the display size of the target function control in the target content area is obtained; and the target page is generated according to the page information and the display size of the target function control in the target content area, thereby improving the page display effect.

The present application relates to the field of laser measurement technology, and more particularly to a kind of steel rail piece geometric dimension intelligent measurement method based on laser scanning.The present application includes the following steps: measurement preparation and system calibration;Laser scanning data acquisition;Point cloud data preprocessing;Geometric dimension intelligent calculation, based on the profile feature extraction of rail head, rail waist and rail bottom of each section profile point cloud after standardization;Measurement result output and storage.The present application constructs global reference axis of steel rail, converts local coordinates of each section to global coordinate system and compensates scanner attitude deviation, establishes continuity constraint of adjacent section profile feature parameters according to steel rail model, obtains optimal profile feature parameters through global optimization, can stably extract profile features of rail head, rail waist and rail bottom under unified reference, reduces the influence of attitude deviation and point cloud noise, and realizes reliable calculation of geometric dimension of steel rail section, full-length straightness and twist degree form error.

The invention discloses a crossroad opposite coming vehicle orientation and trajectory determination method and related equipment. The method comprises the following steps: acquiring image information of an opposite vehicle; obtaining opposite vehicle corner point information based on the opposite vehicle image information; taking an intersection point closer to the vehicle as a reference point; acquiring reference point speed information and course angle information based on the reference point position information corresponding to the at least two signal periods; acquiring predicted position information and predicted course angle information of the vehicle according to the reference point speed information, the course angle information and the course angular speed information based on the basic motion model; performing one-step prediction by using a first Kalman filter according to the predicted position information and the predicted course angle information of the vehicle to obtain a state value at the next moment and a covariance thereof; based on the state value at the next moment, the covariance of the state value and the measurement data of the sensor, a second Kalman filter is used for correcting the predicted value, and the state estimation value and the covariance at the current moment are calculated; and determining an orientation and a trajectory based on the state estimation value and the covariance at the current moment.

The application discloses a kind of cable curvature risk assessment method, device, equipment and medium, belong to the risk assessment field of cable curvature.The method is: obtaining the visible image of the cable to be measured and extracting two-dimensional contour data;The cable to be measured is scanned non-contact, and three-dimensional point cloud data is obtained;Two-dimensional contour data is mapped to the three-dimensional coordinate system in which three-dimensional point cloud data is located, to obtain the three-dimensional point set after fusion, and least square method is used to fit spline curve;Finally, the risk assessment of the spline curve is carried out, and the risk assessment result of the cable to be measured is obtained.Therefore, by implementing the present application, the problem of low accuracy of cable curvature risk assessment in the prior art can be solved.

The utility model discloses a petrochemical engineering non-magnetic metal pipeline fluid flow direction detection device. The detection device comprises a non-magnetic metal pipeline; each pair of electrodes is mounted on the non-magnetic metal pipeline and is configured to detect an induced electromotive force induced by a fluid flowing through the non-magnetic metal pipeline, so that the detection device judges the flowing direction of the fluid in the non-magnetic metal pipeline based on the positive and negative of the induced electromotive force; and the magnetic field generating unit is configured to form a magnetic field perpendicular to the axis of the non-magnetic metal pipeline in the fluid.

The invention discloses a low-permeability reservoir carbon dioxide flooding numerical simulation method based on Maxwell-Stefan cross diffusion, and belongs to the technical field of reservoir numerical simulation and recovery efficiency improvement. Comprising the following steps: establishing a mass conservation equation of each component based on an oil reservoir thermodynamic field, a rock physical property field, an effective diffusion coefficient matrix and reaction kinetic parameters; a diffusion flux item is expressed by a generalized Fick law based on a Maxwell-Stefan theory so as to describe a multi-component cross diffusion effect; a reaction source convergence item is determined by a COand crude oil reversible miscible phase kinetic model so as to describe a miscible phase and split phase dynamic process; sequentially executing a diffusion transmission step and a chemical reaction step for solving by adopting an operator splitting method to obtain an updated concentration field, and synchronously updating the thermodynamic field, the rock physical property field, the reaction kinetic parameters and the effective diffusion coefficient matrix; repeatedly iterating until each field and parameter change meet a convergence condition, and completing simulation of each chemical component concentration field; according to the method, the physical simplification defect in low-permeability simulation is overcome, and high-precision prediction of the displacement process is achieved.

This invention relates to the field of engineering data processing, and more particularly to an intelligent data acquisition and processing method and system for dredging engineering projects in tunnel drainage systems. The method includes the following steps: receiving processing tasks based on a cloud-based dredging management platform; setting acquisition constraints based on the processing tasks to obtain an acquisition constraint set; driving a pipeline detection robot to perform operational detection based on the acquisition constraint set, outputting a first dataset; adaptively optimizing the first dataset to output a second dataset; performing index-based analysis on the second dataset to output multi-dimensional analysis indicators; and planning the dredging operation path based on the multi-dimensional analysis indicators, synchronously uploading the data to the cloud-based dredging management platform to complete the data acquisition and analysis operation. This invention optimizes dredging operation planning, improves dredging efficiency, and enhances the accurate structural analysis of the drainage system in the early stages through precise data acquisition and processing.

The invention relates to the technical field of semiconductor integrated circuit package testing, and discloses a method for calculating lead frame stepping parameters, which comprises the following steps of: 1, inputting parameters; 2, calculating the number of stepping columns of each unit; 3, calculating lndex and the total length of each unit; 4, the number of Index numbers / the number of stepping times is calculated; step 5, calculating a light index center (Right index center); step 6, calculating a Left index center (Left index center); step 7, calculating the Y (Front Center offset), and calculating the Y (Front Center offset); step 8, calculating # imgabs0 #; and step 9, outputting: # imgabs 1 #. According to the method, the calculation deviation caused by human factors is avoided through automatic calculation, so that the calculation of the stepping parameters is more reliable, the universality and flexibility of the method are improved, an existing manual calculation method is improved into the mode that the needed stepping parameters are obtained through automatic calculation by inputting part of parameters of the lead frame, and the calculation efficiency is improved. And the operation is simple.

The present invention discloses hydrogen resource optimization, devices and equipment for storage devices and hydrogen systems, wherein the method comprises the steps of: logically dividing the hydrogen system and establishing corresponding unit models; establishing a material mathematical model and an energy mathematical model; judging whether the feed stream of the hydrogen recovery unit can be used as the feed of the hydrogen using unit to determine whether the feed stream is used as the hydrogen supply stream or the hydrogen recovery stream; simulating and solving the material mathematical model and the energy mathematical model to obtain the simulation operation results as the system initial value of the hydrogen system; obtaining the hydrogen consumption measurement results corresponding to the hydrogen using unit according to the preset hydrogen consumption prediction model; and determining the values ​​of each optimization variable according to the hydrogen consumption measurement results with the minimum energy consumption of the hydrogen system as the goal. The present invention first improves the accuracy of the hydrogen consumption result value, and then establishes the objective function and mathematical model from the perspective of minimizing the energy consumption of the hydrogen system to achieve the parallel optimization of the hydrogen consumption and energy consumption of the hydrogen system.

The invention relates to an optical mark positioning device for PC component mold visual inspection and a detection method. The method comprises the following detection steps: step 1, a preparation stage: selecting a base matched with the height of a to-be-detected mold, assembling the optical mark positioning device, and loading component quality inspection data by a machine vision system background; secondly, a mold and a mark are placed, specifically, an operator places the PC component mold on a mold table, and then an optical mark positioning device is adsorbed to the mold table according to a preset rule; step 3, triggering detection: triggering a machine vision system; step 4, image acquisition and processing: shooting by a camera, and identifying an optical mark and identification information thereof in an image by software; the machine vision system calculates the actual position and posture of the mold according to the marked position, the actual position and posture are compared with standard data, and whether the mold is qualified or not is judged; and step 6, result feedback and mark removal: the HMI displays the result, and the magnetically attracted mark positioning device is taken down from the mold table for storage after the detection is completed.

Embodiments of the present application provide a neural network compression method and device, electronic equipment and storage medium, and belong to the technical field of artificial intelligence. The method comprises: performing quantization processing on a target neural network to obtain a plurality of first compressed neural networks; training the plurality of first compressed neural networks to obtain a candidate network sequence; performing iterative compression processing on the candidate network sequence until an iteration end condition is met; and selecting at least one optimized compressed neural network from the candidate network sequence as a target compressed neural network. The embodiments of the present application can obtain a required neural network compression model, which is beneficial to improving the compression accuracy of the neural network.

The invention discloses a three-dimensional target detection system based on two-dimensional perception. The three-dimensional target detection system comprises a two-dimensional perception module, a three-dimensional coordinate acquisition module and a post-processing module, the two-dimensional sensing module is used for performing feature extraction and region detection on an input image based on a deep learning target detection and key point detection algorithm, and outputting a bounding box of a to-be-detected target and two-dimensional coordinates of a plurality of key points; the three-dimensional coordinate acquisition module is used for performing spatial mapping on the two-dimensional coordinates of the plurality of key points and depth data acquired by the depth sensor, and calculating the three-dimensional coordinates of the key points; and the post-processing module is used for performing space consistency optimization on the three-dimensional coordinates of the key points in combination with the structure prior of the to-be-detected target, and calculating the pose of the to-be-detected target. According to the method, the high-precision three-dimensional pose of the to-be-measured target can be directly calculated from the two-dimensional visual information and the depth data without depending on complex three-dimensional modeling, the calculation precision is improved while the calculation amount is greatly reduced, and the calculation process is more stable and reliable.

The present invention discloses a cooking control method, device and medium for an oven, which specifically includes obtaining a preset recipe for oven cooking and specific heat data of corresponding food; obtaining the initial state of food in the oven cavity; determining the target temperature and the first temperature based on the preset recipe; obtaining the real-time temperature of the oven cavity; recording the working time of the oven heating tube during the time period when the real-time temperature of the oven cavity rises from the first temperature to the target temperature; determining the weight of the food in the oven cavity based on the preset recipe, the specific heat data of the food, the initial state of the food and the working time of each heating tube of the oven; and determining the cooking time of the oven based on the weight of the food. The oven cooking control method, device and medium provided by the present invention can enable the oven to automatically measure the weight of the food in the oven cavity, adaptively adjust the cooking time of the food, ensure the cooking effect, and do not need to add additional hardware.

This application provides a monocular vision distance estimation method, system, and product for aerial targets. The method is applied to a monocular camera and includes: acquiring a monocular image containing an aerial target, prior geometric parameters of the aerial target, and camera intrinsic parameters; performing target detection on the monocular image to obtain a two-dimensional bounding box of the aerial target in the monocular image; calculating a first candidate depth and a second candidate depth based on the prior geometric parameters and the camera intrinsic parameters, according to the width and height of the two-dimensional bounding box; selecting the smaller value between the first candidate depth and the second candidate depth as the estimated target depth; and determining the distance of the aerial target relative to the camera based on the estimated target depth and the center point of the two-dimensional bounding box. This invention, by employing a bounding box model combined with a minimum value selection strategy, can perform stable and reliable distance measurement of aerial targets based solely on monocular vision. Furthermore, this method is computationally efficient and easily integrated and deployed.

The present application provides a method for calculating the equalization time of a battery cell and a method for controlling the equalization of a battery. The method for calculating the equalization time of a battery cell includes: obtaining the current data and voltage data of the battery cell in the process of charging and discharging in real time; calculating the first amount of electricity required to be equalized of the battery cell at the end of this charging according to the current data and voltage data; obtaining the current equalization current of the battery cell; calculating the first equalization time of the battery cell according to the first amount of electricity required to be equalized and the current equalization current; obtaining the previous equalization time of the battery cell during the last charging and discharging process; calculating the credibility of the battery cell according to the previous equalization time; calculating the equalization time of charging the battery cell according to the first equalization time and credibility, so that the equalization time of charging a single battery cell can be accurately calculated, and the accuracy of balancing the entire battery can be improved by balancing each battery cell in the battery separately.

The invention discloses a reliable insurance releasing control method based on a CPLD (Complex Programmable Logic Device), which comprises the following steps: after the CPLD is powered on and reset, defining a multi-bit shift register and assigning an initial value; in the overload identification time window, carrying out sliding window value taking on the overload signal in the overload identification time window by using a shift register; before the shift register is completely replaced, the overload duration is calculated through a sampling value; after the shifting register is completely replaced, the overload duration is calculated through the shifting register; and the overload duration is judged, the overload is considered to be effective after the judgment condition is met, and at the moment, if the first-stage insurance release feedback input port is in an insurance release state, a second-stage insurance release signal is output. The method has the advantages of high recognition speed and high reliability, can be popularized and applied to various scenes in which the CPLD reliably recognizes external signals, and improves the anti-interference capability of products.