10results about How to "Data fluctuation is small" patented technology

The invention discloses a geological mineral exploration device and an exploration method, and particularly relates to the technical field of geological exploration. Mining area data are collected in a plurality of preset time periods, and data analysis is performed in each period, so that whether an early sign of insufficient data quality exists or not is judged; if a quality problem is found, feature analysis is further carried out, and the precision level and the coverage degree of the data are evaluated; dividing a data acquisition period into a high-quality period and a low-quality period according to an evaluation result; for a low-quality acquisition period, resampling or supplementary acquisition is executed, so that the data precision and coverage rate are improved, and the integrity and accuracy of exploration data are ensured; according to the method, through multi-level evaluation of the precision index and the coverage rate index, the quality problem in data collection can be identified in time, multiple times of correction processing are carried out, the precision and the coverage rate of the collected data are remarkably improved, and it is ensured that the collected data can accurately reflect the real geological condition of a mining area.

The present application relates to the field of optical detection technology, and more particularly to a multi-probe centering detection method, which drives a standard spherical lens to rotate, and synchronously completes optical data acquisition by means of multiple independent detection light paths; respectively fitting the data collected by each channel to obtain the corresponding spherical center rotation track of each channel; relying on the spherical center track, solving the spherical center difference of each channel relative to the rotation reference axis, and repeatedly performing the calibration process to obtain the measurement standard deviation of each channel; replacing the measured lens and repeating the detection process to obtain the spherical center track and the spherical center difference; combining the measurement standard deviation of each channel, the consistency error of the measured spherical center difference and the track circle fitting residual error to calculate the fusion weight of each light path channel; based on the obtained weight, using the weighted least squares method to fuse the effective spherical center difference data and output the comprehensive spherical center difference of the measured lens. The present application adopts a multi-light path synchronous detection and data weighted fusion scheme, effectively suppresses the random error and system error of a single channel, and improves the overall measurement accuracy of the lens spherical center deviation.

The invention discloses a test method for the pore size distribution of a hemodialysis hollow fiber membrane. The test method first uses an ultraviolet spectrophotometer to draw a "concentration-ultraviolet absorbance" linear regression fitting curve of polyethylene glycol (PEG) solutions with different concentrations and different molecular weights; PEG simulated solutions with different molecular weights are passed through a dialysis membrane to obtain a dialysis fluid, and the concentrations of the PEG simulated solutions with different molecular weights and the dialysis fluid are calculated using an optimal determination coefficient linear regression curve to further calculate the retention rate; Python is used to construct a relationship between the retention rate and the pore size, and finally the dialysis membrane pore size distribution is obtained in combination with Matlab fitting calculation. The invention can quickly measure the pore size distribution of the hemodialysis membrane, and its measurement data has high accuracy, a simple principle, and strong practicality.

This invention discloses a linearized thickness detection device and method for automotive sound-absorbing cotton, relating to the field of sound-absorbing cotton processing quality inspection technology. The invention includes a transmission component, a displacement guide, a lateral movement mechanism, a micro servo motor, a rotating probe, an auxiliary drive roller, and a driven roller. Through the coordinated movement of the lateral movement mechanism and the rotating probe, the auxiliary drive roller and the driven roller straighten the sound-absorbing cotton. The detection module continuously collects thickness data, which is processed by the PCB motherboard and transmitted to an external terminal. This invention achieves full-range lateral coverage detection of automotive sound-absorbing cotton, reducing missed detections, avoiding detection errors caused by wrinkles or excessive stretching of the sound-absorbing cotton, preventing interference from sound-absorbing cotton lint to the detection module, and improving detection accuracy and efficiency. It is suitable for thickness quality control in the production process of automotive sound-absorbing cotton.

The invention relates to the technical field of metal processing and manufacturing, and discloses a metal melt surface tension measuring and calculating method. According to the method, the length 2a, the height h and the bottom length 2l of the metal ball are calculated by recognizing the coordinates of the end points of the molten metal ball. Firstly, end point coordinates of a metal ball are obtained through an image recognition technology; then, relevant geometric parameters of the small balls are calculated; and then, calculating the surface tension of the metal melt according to a known physical model by utilizing the geometric parameters. Compared with a traditional surface tension measuring method, the method has the advantages that complex ellipse fitting is not needed, the contact angle does not need to be solved, and therefore the calculation process is simplified. In addition, the method provided by the invention has the advantages of higher identification precision, strong anti-interference capability and shorter calculation steps, and occupies less memory space after programming is realized. The method not only improves the measurement efficiency, but also reduces the requirement on hardware equipment.

The invention discloses an infectious disease trend prediction method based on hybrid decomposition and a Time2Vec-BiLSTM-SA model. The method comprises the following steps: directly constructing a first feature matrix according to a sample sliding window width by using daily newly-added definite case number data after smoothing processing; performing L types of decomposition on the smoothed daily newly-added definite diagnosis case number data by adopting a hybrid decomposition algorithm to obtain L types of decomposed daily newly-added definite diagnosis case number component data; constructing a second feature matrix for the L types of daily newly-added definite case number component data according to the width of a sample sliding window; constructing a multi-branch input network prediction model; and taking the first feature matrix and the L types of second feature matrixes as input of a multi-branch input network prediction model, and outputting a daily newly-added definite case number prediction value of single-step prediction by using the multi-branch input network prediction model. According to the method, the hybrid decomposition algorithm is ingeniously introduced, so that richer feature information is provided for the prediction model; the prediction model can greatly improve the precision and reliability of epidemic situation trend prediction.

A method for detecting the roundness of ion exchange resin infiltration grinding and a batch processing device. Under artificial conditions, the method allows osmotic pressure, water flow impact, friction and pressure to act on the ion exchange resin together to detect the particle integrity of the resin particles after being subjected to force, thereby reflecting the mechanical strength of the resin. The present invention also discloses an ion exchange resin infiltration grinding roundness detection and processing device, which is composed of a treatment agent storage module, a resin storage module, a dosing module, and a control module. The control module automatically adjusts the type of treatment agent, the dosage, the dosing sequence and other parameters according to the different types of resins. The present invention can meet the processing requirements of different types of ion exchange resin infiltration roundness tests, and realize the batch, automation and intelligence of ion exchange resin infiltration roundness processing, reduce the errors that may be caused by manual operation, improve the test efficiency of ion exchange resin infiltration roundness and reduce the labor intensity of testers.

The embodiment of the invention provides a training method and electronic equipment. The method is applied to the electronic equipment and comprises the steps that n original data samples and n original labels corresponding to the n original data samples are obtained, and n is an integer larger than or equal to 2; mixing the n original data samples to generate training sample data; generating a label set, wherein the label set comprises at least two original labels in the n original labels; taking the label set as a label corresponding to the training sample data; and training a classifier model by using the training sample data and the labels corresponding to the training sample data. According to the method provided by the embodiment of the invention, the training sample data is generated through data mixing, and the tag set is adopted as the tag corresponding to the training sample data, so that a classifier model with a better classification effect can be constructed under a severe noise background, and the recognition experience of a recognition model is promoted.

The utility model relates to the technical field of new energy automobile battery management systems, in particular to a new energy automobile BMS temperature monitoring parameter acquisition device. The system comprises a composite monitoring unit, a working condition identification unit and a filtering optimization unit. According to the utility model, the composite monitoring unit uses a surface contact type temperature sensor, an internal penetration type temperature sensor and a non-contact type temperature sensor to carry out multi-dimensional acquisition on battery temperature data, and the working condition identification unit uses a support vector machine to establish an optimal classification hyperplane to classify characteristic data of different working conditions. The current operation condition of the battery is judged, the size of a filtering window is dynamically adjusted according to the working condition, the filtering optimization unit carries out multi-stage amplification and filtering processing on collected temperature data through an amplification filtering circuit, the problem that a traditional single sensor cannot comprehensively reflect the thermal state of the battery is solved, and the integrity and accuracy of the temperature data are improved.

The present invention provides a photovoltaic cleaning robot and a driving method thereof, which relates to the technical field of photovoltaic cleaning robots, including: when the photovoltaic cleaning robot is driving on a photovoltaic panel, the positioning yaw angle in the camera coordinate system is obtained through the captured image and depth information of the depth camera; the positioning yaw angle is corrected based on the initial direction angle to obtain the heading yaw angle; the initial direction angle is the difference between the initial positioning yaw angle and the initial visual yaw angle of the photovoltaic cleaning robot; based on the heading yaw angle, the route offset distance is determined; at least based on the route offset distance, the robot is corrected to control the photovoltaic cleaning robot to travel along the straight texture of the photovoltaic panel. The present invention does not need to install any sensors, and can obtain relevant data for correction through a depth camera, and the hardware structure is simple; the data fluctuation of the positioning yaw angle in the camera coordinate system is small, and is not affected by external factors, so the robot can be better corrected to improve the cleaning effect of the photovoltaic panel.