Granary grain storage quantity detection method based on support vector regression

A technology of support vector regression and detection methods, applied in the field of sensor networks, can solve problems such as not fully considering the mutual transfer problem

Active Publication Date: 2015-02-04
HENAN UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

Since the model does not fully consider the mutual transfer between side pressure and bottom pressure, it is only applicable to large granaries

Method used

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  • Granary grain storage quantity detection method based on support vector regression
  • Granary grain storage quantity detection method based on support vector regression
  • Granary grain storage quantity detection method based on support vector regression

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Embodiment Construction

[0025] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0026] The grain quantity detection method of the present invention relates to a unique grain quantity detection model based on support vector regression, the theoretical premise obtained by the model, the corresponding granary sensor arrangement, model derivation, system calibration and modeling and some The data are described in detail below.

[0027] 1. Granary weight theoretical detection model

[0028] Commonly used granaries include bungalows, shallow round bins, and silos. After the grain enters the warehouse, the top of the grain pile is required to be flattened. The shapes are roughly cylinders of varying sizes. For a given granary and grain type, it is assumed that the pressure at point s in the bottom and side of the grain pile is Q B (s), Q F (s), the average pressure on the bottom and side of the grain pile is shown in formula (1) and formula...

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Abstract

The invention relates to a granary grain storage quantity detection method based on support vector regression. The method comprises the following steps: arranging two circles of pressure sensors on the bottom surface of a granary, detecting an output value of each sensor, and computing granary grain storage weight estimation (FOMRULA) according to a detection model (FOMRULA). Aiming at urgent need of the nation to national grain storage online quantity detection and specific requirement of the detection, the invention provides the granary grain storage quantity detection method based on the support vector regression according to the granary bottom surface pressure intensity distribution and pressure intensity measured value change characteristics; the provided method is high in detection precision, and suitable for the grain storage quantity detection in various granary structure types.

Description

technical field [0001] The invention relates to a method for detecting the quantity of stored grain, in particular to a method for detecting the quantity of stored grain based on support vector regression. It belongs to the technical field of sensor networks. Background technique [0002] Food security includes quantity security and quality security. The research and application of online grain quantity detection technology and system is an important guarantee technology for national grain quantity security. Carrying out research and application in this area is related to national food security, which is of great significance and will generate huge social and economic benefits. [0003] Due to the important position of grain in national security, the online detection of grain pile quantity is required to be accurate, fast and reliable. At the same time, due to the huge amount of grain and the low price, it is required that the online detection equipment for the amount of g...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00G01G17/00
Inventor 张德贤张苗张元司海芳杨铁军肖乐邓淼磊张庆辉王高平樊超李磊杨卫东傅洪亮王洪群王贵财许伟涛金广锋王珂刘灿堵世良
Owner HENAN UNIVERSITY OF TECHNOLOGY
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