Unlock instant, AI-driven research and patent intelligence for your innovation.
Timber density determination method based on iteration weight least square estimate method
What is Al technical title?
Al technical title is built by PatSnap Al team. It summarizes the technical point description of the patent document.
A least squares, iterative weighting technique, applied in the estimation field of wood density determination, can solve the problem of large batch wood error, and achieve the effect of accurate estimation
Active Publication Date: 2016-09-21
黄时浩
View PDF2 Cites 0 Cited by
Summary
Abstract
Description
Claims
Application Information
AI Technical Summary
This helps you quickly interpret patents by identifying the three key elements:
Problems solved by technology
Method used
Benefits of technology
Problems solved by technology
[0004] The present invention estimates the density measurement of batches of wood for the traditional regression analysis method and other methods, and there is a problem of large error
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more
Image
Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
Click on the blue label to locate the original text in one second.
Reading with bidirectional positioning of images and text.
Smart Image
Examples
Experimental program
Comparison scheme
Effect test
specific Embodiment approach 1
[0042] A wood density determination method based on iterative weighted least squares estimation method, comprising the following steps:
[0043] Step 1. Randomly select samples for a batch of wood, and calculate the density ρ of each sample i ;
[0044] Step 2. Expected average estimate of sample density:
[0045] Step 2.1, frequency statistics of sample density:
[0046] from ρ i The maximum value ρ was determined in max and the minimum value ρ min ;
[0047] Take a=[ρ min *10 l-1 -0.5] / 10 l-1 , b=[ρ max *10 l-1 +0.5] / 10 l-1 ; l is ρ i , ρ max or ρ min The effective number of digits after the decimal point, the [ ] operation means to take an integer;
[0048] Divide the interval [a,b] into m small intervals, and calculate the number of sample densities p falling into each small interval j , this p j is the frequency, the total number of samples
[0049] Step 2.2, expected average estimate:
[0050] The expected average estimate of the sample density can b...
specific Embodiment approach 2
[0080] The specific process of step 1 of this embodiment is as follows:
[0081] Randomly select samples from a batch of wood (need to be representative, the number of samples should account for more than a quarter of the total samples, and not less than 20), and measure according to "GB / T 1933-2009 Wood Density Determination Method" Get the volume v of each sample i , mass g i , i is the serial number of the sample, i=1,2...n;
[0082] Calculate the density of each sample by formula (1)
[0083] ρ i = g i v i - - - ( 1 ) .
[0084] Other steps and parameters are the same as those in Embodiment 1.
specific Embodiment approach 3
[0085] The method for determining m described in step 2.1 of the present embodiment is as follows:
[0086] From the empirical formula m≈[Δ·(n-1) 0.4 ] Determine the interval m to be divided; Δ takes a value of 1.80 to 1.90;
[0087] In the formula, the [·] operation means to take an integer.
[0088] Other steps and parameters are the same as in the second embodiment.
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More
PUM
Login to View More
Abstract
A timber density determination method based on an iteration weight least square estimate method relates to the timber density determination estimate method; the novel method solves the problems that a conventional regression analysis method has big errors in batch timber density determination; the method uses expected average estimation having unbiased estimate property under limited samples to serve as the initial mean value estimate value, uses the iteration weight least square method to carry out regression estimate fine tuning, and the product between a weight coefficient sampling density frequency and an error inverse distance can be randomly converged to a set threshold without having divergency phenomenon, thus relatively accurately estimating the total sample density. The timber density determination method based on the iteration weight least square estimate method is suitable for the batch timber density estimate field.
Description
technical field [0001] The present invention relates to an estimation method for wood density determination. Background technique [0002] In the process of actual mass timber application, it is necessary to estimate the weight of the load-bearing timber structure or the applied timber in advance, but it is impossible to weigh each timber during the application process. In the process of actual load-bearing timber structure massestimation, it is generally calculated based on the density and volume of the timber, but in the actual timber application process it is impossible to measure the density of all the objects in a batch of timber, generally a batch of timber density is estimated. [0003] The determination of wood density is generally carried out according to "GB / T 1933-2009 Wood Density Determination Method", but "GB / T1933-2009 Wood Density Determination Method" does not involve how to estimate the total sample density of a batch of wood from the sample density meth...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More
Application Information
Patent Timeline
Application Date:The date an application was filed.
Publication Date:The date a patent or application was officially published.
First Publication Date:The earliest publication date of a patent with the same application number.
Issue Date:Publication date of the patent grant document.
PCT Entry Date:The Entry date of PCT National Phase.
Estimated Expiry Date:The statutory expiry date of a patent right according to the Patent Law, and it is the longest term of protection that the patent right can achieve without the termination of the patent right due to other reasons(Term extension factor has been taken into account ).
Invalid Date:Actual expiry date is based on effective date or publication date of legal transaction data of invalid patent.