17results about How to "Reduce the error value" patented technology

The invention discloses a method for measuring a hydrochloric acid tank solution, a neutralizing tank solution and analyzing a standard titration solution by using an automatic potentiometric titrator. The method comprises the following steps: S1, preparing a sample solution; s2, calibrating a sample solution; s3, determining a standard titration solution; selecting a sample solution meeting the requirements, wherein the sample solution is a standard titration solution; s4, titration treatment of hydrochloric acid tank liquid or neutralization tank liquid; accurately dropwise adding a calibrated standard titration solution into the hydrochloric acid tank solution or the neutralization tank solution until a titration end point is reached; and S5, measuring the concentration of the hydrochloric acid tank solution or the neutralization tank solution. The titration result of the potentiometric titration mode is not greatly different from the result of the manual titration mode, the potentiometric titration repeatability is good, the potentiometric titration reminds that the end point is advanced by artificial misjudgment by using an electric signal, and meanwhile, the program assists the calculation operation, so that the operation is simpler.

The present disclosure provides a neural network-based weight quantization method, device and electronic equipment. The method comprises: obtaining calibration data corresponding to a calibration data set of the neural network; obtaining first quantized weights corresponding to a preset first truncation ratio of original weights of the neural network, determining a first quantization error of the first quantized weights relative to the original weights according to the calibration data; in the case where the first quantization error is determined to satisfy a preset convergence condition according to the calibration data, performing truncation processing and quantization processing on the original weights of the neural network according to the first truncation ratio to obtain network weights of the neural network. This method can automatically determine an adjusted first truncation ratio, so that the error value of the network weights of the neural network is smaller.

The present invention relates to a storage method for concentrated onion juice, comprising: placing the concentrated onion juice in a plurality of storage tanks, setting a detection cycle of the concentrated onion juice; detecting the internal temperature of the storage tank, drawing a temperature change curve, comparing the temperature value with a preset internal temperature, and adjusting the temperature expression parameter of the temperature change curve; calculating the integral value of the temperature change curve and the preset internal temperature within a unit detection time, and adjusting the detection cycle accordingly according to the integral value; detecting the light transmittance and soluble solid content of the concentrated onion juice, comparing them with standard values, making a grade judgment on the storage state of the concentrated onion juice, and adjusting the detection cycle accordingly; detecting the storage time of the concentrated onion juice, comparing it with the preset storage time, and calculating the adjusted detection cycle. The present invention makes the storage detection of onion juice more intelligent.

The invention provides a DeepFLPS genome selection system based on CNN and multi-scale feature extraction, and belongs to the field of genome selection. The inherent limitations of single feature extraction scale and insufficient sparse feature utilization of the current deep convolutional neural network structure are overcome; the system comprises a deep feature learning genome selection DeepFLPS model, the model comprises an input layer, a multi-scale feature extraction module of a binding site interaction rule, a full connection layer and an output layer, and the multi-scale feature extraction module of the binding site interaction rule adopts a parallel convolution channel structure with a plurality of sliding windows increasing progressively. A hierarchical association relationship in genotype data is captured through a progressive expansion convolution kernel, and a hierarchical double-activation function mechanism is set; the novel CNN architecture provided by the invention not only can adaptively capture the interaction effect of different SNPs interval lengths, but also can more effectively retain sparse feature information in genotype data.

The invention provides a soil heavy metal content detection device for environmental detection, and relates to the technical field of soil sample preparation and test.The soil heavy metal content detection device comprises a detection device body, the detection device body comprises a sample preparation table, a digestion tank, a crushing assembly and a stirring mechanism, the bottom of the sample preparation table is in threaded connection with a driving base, and a rotating disc is welded to the top of the driving base; a digestion groove is formed in the bottom of the rotary disc, the digestion groove is embedded into the surface of the rotary disc, a sampling assembly is inserted into one end of the inner side of the digestion groove, the sampling assembly and the digestion groove are of a separable structure, and a stirring mechanism is in threaded connection with the surface of the sample preparation table. The digestion efficiency is improved, meanwhile, the quantitative process can be rapidly completed, more digestion solution samples can be prepared at a time, the safety during bottom stirring is higher, the digestion solution samples are taken more uniformly every time, and the error value of multiple measurements is reduced.

The invention relates to a dynamic calculation method for yarn stock of a yarn edge bin based on spinning ERP (Enterprise Resource Planning). The method comprises the following steps: S1, dynamically calculating yarn consumption data; and S2, dynamically calculating the yarn stock of the yarn edge bin according to the yarn consumption data. According to the invention, the dynamic calculation of the yarn consumption data is realized, and the yarn stock of the yarn edge bin is further dynamically calculated according to the data. According to the method, the yarn consumption condition is dynamically tracked in real time, and accurate adjustment is performed according to the bill of material of the gray fabric, the production process parameters of the production machine and the error parameter proportion, so that the calculated consumption value of the yarn can be tightly attached to the actual consumption quantity, and the purpose of accurately mastering the yarn stock of the yarn edge bin in real time is achieved; the problem that yarn stock quantity management is difficult is effectively solved.

The present invention discloses a method and device for detecting fuel consumption anomaly based on a vehicle refueling bill, the method comprising: respectively acquiring a current refueling bill image and a historical refueling bill image, the current refueling bill image and the historical refueling bill image being bill images uploaded by the vehicle after completing fuel filling at a current time node and a previous time node; respectively determining the refueling amount value and the fuel consumption value of the vehicle based on the current refueling bill image and the historical refueling bill image; calculating the ratio of the refueling amount value and the fuel consumption value to obtain a fuel consumption ratio, and if the fuel consumption ratio is greater than a preset ratio, determining that the vehicle has fuel consumption anomaly. The present invention can use two refueling bill images to respectively determine the refueling amount value and the fuel consumption value of the vehicle after acquiring two adjacent refueling bill images, and determine whether the vehicle has fuel consumption anomaly based on the refueling amount value and the fuel consumption value, so as to reduce the calculated error value and improve the accuracy of fuel consumption anomaly detection.

The present invention belongs to the field of digital medical technology, and discloses a wound model construction method and system, flap planning, and visualization projection method. The wound model construction method includes: step one, obtaining a skin model by processing the original CTA image; step two, extracting the wound model according to the test wound on the skin model; step three, obtaining a second target plane according to the vertices in all vertex groups in the wound model, projecting the vertices into the second target plane to obtain projection points and dividing the projection point groups; selecting edge points from the projection points, calculating the flattening points of the edge points and dividing the flattening point groups, and obtaining a flattened wound model according to the projection point groups and the flattening point groups. The present invention reduces the difficulty of operation by selecting key points on the skin model to obtain the wound surface; processing the wound surface in groups to improve the operation speed; orthogonally projecting each group and calculating the difference between the group and the projection area to flatten the group in sequence, thereby reducing the error value of the wound surface after flattening.

This application proposes a stepper motor drive correction system and method, relating to the field of stepper motor drive technology. The system includes an H-bridge, a sensing circuit, a sampling circuit, a current-to-voltage conversion circuit, a sine wave generator, a proportional amplifier, a comparator circuit, and a calibration control circuit. The sensing circuit samples the current of the low-side switch transistor of the H-bridge, which is then converted into a sensing voltage by the current-to-voltage conversion circuit according to a first preset ratio. The sine wave generator produces an ideal sine waveform, which is scaled by the proportional amplifier according to a second preset ratio to form a reference voltage. The comparator circuit compares the sensing voltage with the reference voltage and outputs the comparison result. Based on the comparison result, the calibration control circuit calibrates the first and second preset ratios sequentially, gradually reducing the error between the two voltages. Through these multiple calibrations, the system error is reduced to below a preset threshold, significantly improving the driving accuracy and smoothness of the stepper motor in high-microstepping mode.

The utility model relates to the field of precast slabs, in particular to a concrete precast slab hardness detection device which comprises a bottom plate, supporting rods are symmetrically installed at one end of the outer wall of the top of the bottom plate, a top plate is installed on the outer walls of the top ends of the supporting rods, and a hydraulic push rod is installed in the center of the outer wall of one end of the top plate. A pressure block is installed on the outer wall of the bottom end of the hydraulic push rod, protection assemblies are arranged on the positions, located on the four sides of the hydraulic push rod, of the outer wall of the top of the bottom plate, and a storage assembly is arranged on the outer wall of one end of the bottom plate. The protection assembly comprises sliding grooves formed in the two ends of the top of the bottom plate and inserting grooves formed in the outer wall of the top of the bottom plate and located in the outer walls of the two ends of the top plate. The hydraulic push rod applies pressure to the precast slab through the pressure block, the pressure generated by the hydraulic push rod and the pressure value displayed by the pressure sensor are displayed on the control panel, the detected pressure is recorded in a dual mode, the error value is reduced, use is convenient, and interference is avoided.

A leaf photosynthetic rate prediction method based on an image relates to the technical field of plant photosynthesis evaluation. In order to solve the technical problems existing in the prior art, the existing photosynthetic rate measurement technology has the following problems: high cost and difficulty in large-scale application, and lack of effective analysis of the comprehensive characteristics of leaf images, resulting in low prediction accuracy. The technical solution provided by the present invention is: a leaf photosynthetic rate prediction model construction method based on an image, the method comprising: preprocessing the collected training image, including the step of dividing it into multiple intervals; counting the number of pixels in the partitions within a preset measurement area; obtaining the quantitative relationship between the number of pixels and the photosynthetic rate based on the least squares method; and constructing a photosynthetic rate prediction model based on the quantitative relationship. It can be applied to the work of analyzing the photosynthetic rate of leaves.

The invention discloses a terrain live-action modeling system and method based on multi-source surveying and mapping data fusion, and relates to the field of three-dimensional modeling, and a terrain live-action model is generated by adopting multi-source surveying and mapping data of three dimensions of selected control points, image data shot in the air and image data shot on the ground; after the model is generated, the length and height of an object in the model and the coordinate positions of a plurality of points are compared with corresponding data in an actual environment, and according to a comparison result, the coordinates of a control point and shooting parameters when image data shot in the air and image data shot on the ground are collected are adjusted. By arranging a certain number of control points and measuring geodetic coordinates of the control points, ground measurement results and aerial photograph measurement data are fused in subsequent post-processing of aerial photograph, so that the geographic precision of terrain live-action modeling is improved.

This utility model relates to the field of separation membranes, and particularly to a sample testing device for separation membrane research and development. It includes a testing chamber with an insertion interface at the center of its top outer wall. A fixing structure is installed at the insertion interface, and partition plates are installed on the inner wall of the testing chamber at both ends of the fixing structure. The fixing structure includes a fixing frame, a placement groove on one side of the outer wall of the fixing frame, a pressing frame slidably connected in the placement groove, fastening grooves equidistantly located on one side of the outer wall of the fixing frame, and fastening protrusions equidistantly welded to the outer wall of the pressing frame at the fastening grooves. In this utility model, the detection gas enters the testing chamber under negative pressure. After passing through the separation membrane, the detection gas enters the other end of the testing chamber. An air quality sensor detects the air quality inside both ends of the testing chamber, facilitating detection, enabling quantitative detection, improving detection accuracy, and reducing error values.

The present invention discloses a mesh oblique pulling process, comprising the following steps: using a pair of manipulators to respectively clamp a pair of opposite sides of a rectangular steel mesh; then moving the pair of manipulators away from each other until the steel mesh is stretched and tightened; then rotating the pair of manipulators synchronously to stretch the mesh of the steel mesh from a square to a rhombus, and making the angle of a pair of acute angles in the rhombus mesh reach a predetermined angle range. The present invention uses a pair of manipulators to stretch the steel mesh, and can stretch the mesh of the steel mesh from a square to a rhombus. The present invention uses manipulators to replace manpower, which can produce more efficiently and stabilize the quality of the stretched mesh. The present invention can more accurately control the stretching angle, reduce labor costs, and ensure that the quality of the mesh is above a certain level, so that the subsequent process can reduce the error value. The present invention uses a manipulator to stretch the mesh, which minimizes human factors, can increase production capacity and improve production rate.

The invention relates to an infrared width sensor device and a detection method, and relates to the technical field of infrared detection, the infrared width sensor device comprises an infrared emission module, an infrared receiving module, a switch switching module, a signal amplification module, a control module, a power supply module and an analog output module, and the output end of the power supply module is connected with the power supply input end of the control module; the input end of the analog output module is connected with the analog output end of the control module; the infrared transmitting module comprises a plurality of infrared transmitting units which are arranged in sequence, the infrared receiving module comprises a plurality of infrared receiving units which are arranged in sequence, and the plurality of infrared receiving units and the plurality of infrared transmitting units are in one-to-one correspondence to form correlation; and the signal amplification module comprises a plurality of signal amplification units which are arranged in sequence. The method has the effect of improving the coiled material deviation rectifying reliability and the machining efficiency.

The present application provides a parameter optimization device and a parameter optimization method, which relates to the technical field of parameter optimization, including: a laser emission component, a triangular prism, an image acquisition component and a controller; the triangular prism is provided with a rectangular base; a plurality of triangular prisms are arranged side by side and adjacently on the rectangular base; scale lines are provided on both sides of the upper surface of the rectangular base parallel to the prisms of the triangular prisms; the laser emission component is used to emit laser to the triangular prism; the image acquisition component is used to acquire images of the triangular prism after emitting laser to the triangular prism; the controller is used to analyze the acquired image to obtain the coordinates of the intersection of the top edge of any two adjacent triangular prisms and the laser; based on the obtained coordinates of the intersection, a parameter optimization function is constructed; based on the parameter optimization function, the configured parameters to be optimized are optimized to obtain the optimized parameters. The present application optimizes the parameters of the laser measuring instrument to improve the accuracy of the calibration and measurement of the laser measuring instrument.

This invention provides a test fixture for a final-drive planetary reducer, aiming to solve the technical problem of large deviations in test data during traditional test fixture testing. The test fixture includes a base, a support component, a connecting assembly, a drive shaft, a motor, and a positioning block. The base is used to mount the support component, and the connecting assembly is housed inside the support component. Both the drive shaft and the motor are connected to the connecting assembly, achieving power connection through the connecting assembly. The positioning block is located at the end of the drive shaft to restrict the runout of the drive shaft end. By installing the positioning block at the end of the drive shaft and ensuring that the positioning block contacts the inner wall of the final-drive planetary reducer under test, this test fixture limits the runout of the drive shaft end during testing, thereby reducing the test error value.