6results about How to "Valid calibration" patented technology

The application relates to an active band-pass filter Q value calibration circuit, which comprises an LDO circuit, a calibration signal filter circuit and a Q value calibration detection circuit; wherein the output ends V1 and V2 of the LDO circuit supply power to the calibration signal filter circuit, the output end VREF of the LDO circuit provides a reference voltage for the Q value calibration detection circuit, the output end signals VBP and VBN of the calibration signal filter circuit serve as inputs of the Q value calibration detection circuit, and the output signal VRZ of the Q value calibration detection circuit is outputted <n:0>The control signal is used as a calibration signal to filter circuit. The application can effectively tune the Q value of the filter and improve the consistency of the chip. Compared with the traditional active band-pass filter Q value calibration circuit, the application has the characteristics of small implementation difficulty and high integration.< / n:0>

The application discloses a kind of in-situ online self-calibration method and device of MEMS inclination sensor, its method includes when target MEMS inclination sensor is shipped and uses, respectively, to its self-detection port excitation voltage signal is applied and output signal is recorded;According to the excitation voltage signal and the output signal, the virtual scale factor and the virtual zero position when target MEMS inclination sensor is shipped and uses are calculated;According to the virtual scale factor and the virtual zero position, the scale factor drift and the zero drift when target MEMS inclination sensor uses are calculated;Actual output signal when target MEMS inclination sensor uses is acquired, and the scale factor drift and the zero drift are calculated according to the inclination angle;The application can effectively solve the drift error problem of MEMS inclination sensor in-situ online in use site at low cost, and avoids the calibration of sensor's return factory.

This application relates to the field of slope monitoring technology and discloses a calibration method and apparatus for highway slope monitoring signals based on deformation characteristics. The method includes: collecting raw monitoring data through a network of monitoring sensors installed on the surface of the highway slope; cleaning the raw monitoring data to remove outliers and noise interference, obtaining a standardized deformation data sequence; extracting deformation features based on the standardized deformation data sequence using a deformation trend recognition algorithm to generate a deformation feature set; converting the dimensions of multiple deformation features in the deformation feature set into calibration signal control dimensions; wherein the calibration signal control dimensions include control amplitude dimension, control frequency dimension, and control phase dimension, and each dimension of the deformation feature is converted into a corresponding calibration signal control dimension; generating a calibration monitoring signal based on the multiple dimensions of the calibration signal control dimensions and outputting it. This achieves effective calibration of slope deformation monitoring signals, providing reliable support for slope stability monitoring.

The application relates to the technical field of image processing, in particular to a clinical ultrasonic image auxiliary screening system based on deep learning. The system comprises an ultrasonic image preprocessing module, a lesion region segmentation module, an image lesion labeling module and a lesion auxiliary screening module, can acquire clinical ultrasonic images and carries out gray processing and neighborhood gray balance processing, so as to generate clinical ultrasonic balanced images; carries out pixel normalization and lesion region segmentation based on tissue boundary blur on the clinical ultrasonic balanced images, so as to generate clinical ultrasonic image lesion region blocks; carries out image lesion labeling through the clinical ultrasonic image lesion region blocks, so as to generate a clinical ultrasonic lesion labeling image set; constructs an image lesion auxiliary screening model and carries out lesion auxiliary screening, so as to output the lesion position, lesion type and lesion severity corresponding to the lesion existing on the clinical ultrasonic image. The application can realize accurate analysis of clinical ultrasonic images, so as to assist in efficiently completing lesion screening.

The utility model provides a sleeper static load testing machine convenient to calibrate, which comprises a movable sleeper trolley and a testing machine base, the upper end of the testing machine base is fixedly connected with testing machine stand columns, and the upper ends of the four testing machine stand columns are fixedly connected with a testing machine upper cross beam. The problems that the hydraulic jack is in an eccentric pressed state, the hydraulic jack and pressure sensors are damaged to a certain degree, each pressure sensor corresponds to one calibration coefficient, the two calibration coefficients and the calibration coefficient of resultant force are not the same, but the result is usually poor are solved, and the device is reasonable in structure, good in practicability and easy to popularize. On the premise of not influencing normal detection of the sleeper by the sleeper static load testing machine, not only can the pressure sensor in the middle be effectively calibrated, but also the resultant force of the pressure sensors on the two sides can be effectively calibrated, and the hydraulic jack can be prevented from being in an eccentric pressed state.

Embodiments of the invention disclose a chip calibration method and apparatus, an electronic device and a storage medium. The method comprises the steps of obtaining a target process corner category of a target event camera chip; acquiring target working temperature information of the target event camera chip; a calibration data set is obtained, a target calibration scheme of the target event camera chip is selected from the calibration data set based on the target process corner category and the target working temperature information, and the calibration data set covers a data mapping relation among the process corner category, the working temperature information and the calibration scheme; and calibrating the target event camera chip based on the target calibration scheme. Therefore, the target calibration scheme is determined according to the process corner category of the event camera chip and the working temperature information of the event camera chip, the target calibration scheme is called, and the event camera chip is quickly and effectively calibrated, so that the performance of each event camera chip with different process corners in different temperature scenes meets application requirements, and the user experience is improved.