4results about How to "Accurate and reliable sampling" patented technology

The invention discloses a raw material sampling device for photoresist production, which relates to the field of photoresist production and comprises a bottom plate and a storage box fixedly mounted on one side of the top of the bottom plate. In the sampling process, a driving motor drives a first crank through a belt transmission piece to promote a first push rod to perform circular motion so as to drive a first driving block to slide, and the mechanism ensures the swing of a swing rod, so that the reverse acting force of a second driving block is triggered, and a second crank also moves along with the second driving block; the rotating rod transmits force to the sliding block to trigger swinging of the movable rod, the action directly controls movement of the second fixed rod and the sampling piece, it is ensured that the sampling pipe can accurately cut into the sample storage box, stable and consistent sampling is achieved, sampling is conducted under the same standard and condition each time, and therefore the consistency of the sampling amount is ensured, and the sampling efficiency is improved. In addition, due to the automatic sampling process in the closed environment, the external pollution risk is reduced to the maximum extent.

The present application relates to absorption spectroscopy technology, and specifically provides a multi-gas measurement method based on GFC wheel, comprising the following steps: A1. obtaining standard deviation R of reference signal in multiple detection periods rsd and standard deviation M of measurement signal rsd ; A2. obtaining offset parameter K=f(R rsd , M rsd , t) according to the standard deviations, t is the absolute value of the difference between the rotation period at the last calibration and the current rotation period; A3. comparing the offset parameter K with a set range; if the offset parameter K is normal, no adjustment is needed; if the offset parameter K is abnormal, corresponding adjustment measures are implemented according to the set range where the offset parameter K is located, and the adjustment measures comprise: obtaining complete reference signal and measurement signal, thereby obtaining Δt, and replacing. The present application has the advantages of accurate measurement and the like.

The application discloses an infrared small target detection method and system based on gradient information guided deformable convolution, and belongs to the technical field of computer vision and infrared image processing. The method comprises the following steps: extracting a feature map from an input infrared image; calculating the gradient change intensity and the gradient change direction of each spatial position in the feature map; generating a deformation coefficient based on the gradient change intensity and constructing a scaling matrix to anisotropically compress the sampling grid of a standard convolution kernel; constructing a rotation matrix based on the gradient change direction to rotate the compressed sampling grid to be aligned with the gradient change direction; performing bilinear interpolation sampling and convolution operation according to the transformed sampling offset to output a gradient-guided enhanced feature map; and inputting the enhanced feature map into a target detection network to obtain an infrared small target detection result. The application effectively improves the extraction capability of the edge features of the infrared weak small target by explicitly fusing the gradient information to guide the convolution sampling, significantly improves the detection precision and recall rate under the premise that the calculation overhead is basically unchanged, and can be widely applied to the fields of disaster search and rescue, fire warning, night monitoring and the like.

This application relates to a current detection circuit, a motor controller, and a vehicle, including a comparison circuit, an overcurrent monitoring circuit, and a processing unit. The input terminal of the comparison circuit is connected to the output terminal of a differential current sampling circuit. The first output terminal of the comparison circuit is connected to both the input terminal of the overcurrent monitoring circuit and the processing unit. The second output terminal of the comparison circuit is connected to the output terminal of the overcurrent monitoring circuit, and the output terminal of the overcurrent monitoring circuit is connected to the processing unit. The comparison circuit converts the differential signal output by the differential current sampling circuit into a first conversion signal and a second conversion signal. The overcurrent monitoring circuit converts the first conversion signal into a third conversion signal. When either the second or third conversion signal is an overcurrent level signal, and the signal amplitude determined based on the first conversion signal is less than a set threshold, the processing unit determines that the differential signal output by the differential current sampling circuit is zero, thus improving the reliability of current sampling.