CN104296847A - Granary, stored grain weight detection system and method and sensor arrangement method - Google Patents

Abstract

The invention relates to a granary, a stored grain weight detection system and method and a sensor arrangement method, and provides the granary stored grain weight detection method based on the arrangement of two loops of sensors arranged on the bottom. The core technology comprises arrangement of inner and outer two loops of bottom pressure sensors, grain pile weight detection model based on bottom pressure intensity and side pressure intensity mean value estimation, and system calibration and modeling method and the like. The method has the advantages of high detection precision, low requirement for the performance of sensors, high applicability, simple device, convenient use and maintenance, and facilitating to carry out remote online granary quantity detection and granary condition monitoring and the like, and the demand for carrying out remote online quantity detection of grains stored in commonly-used granaries can be met. Since the detection method can be suitable for quantity detection of stored grains in a plurality of granary structures, the method has huge application value, and provides a new technological means for guaranteeing nation grain quantity safety.

Description

A kind of silo, grain storage weight detection system, method and sensor arrangement method

Technical field

The present invention relates to a kind of pressure transducer method for arranging for granary storage weight detecting, grain storage gravimetric analysis sensing method, system, and the silo adopting this system.

Background technology

Grain security comprises Quantity Security and quality safety.It is the important leverage technology of national food Quantity Security that Grain Quantity online measuring technique and systematic study are applied, and the research and apply carrying out this respect, concerning national food security, has great importance, and will produce huge economic results in society.

Due to the critical role of grain in national security, require that grain piles quantity on-line checkingi accurately, fast and reliably.Simultaneously because Grain Quantity is huge, price is low, requires grain to pile quantity online detection instrument cost low, simple and convenient.Therefore the high precision detected and the low cost of detection system are that silo quantity on-line detecting system develops the key issue that must solve.

Patent " the grain reserve in grain depot quantity measuring method based on pressure transducer " (license number: ZL201010240167.7), the core technology of this patent of invention comprises and exports the computation model of the quantity of stored grains in granary of average and concrete system calibrating method based on silo bottom surface, side pressure sensor.

The sensor of the scheme demand of above-mentioned patent is a lot, and cost is higher.In order to solve this problem, and improving accuracy of detection, The present invention gives the another kind of grain storage weight detecting thinking estimated based on bottom surface and side pressure.

Summary of the invention

The object of this invention is to provide a kind of pressure transducer method for arranging for granary storage weight detecting, grain storage gravimetric analysis sensing method, system, and the silo adopting this system, need in order to solve existing detection the problem that sensor is many, cost is high.

For achieving the above object, the solution of the present invention comprises:

For the pressure transducer method for arranging of granary storage weight detecting, pressure transducer is at least divided into two groups, and one group is interior coil sensor, and another group is outer coil sensor; Outer coil sensor be close to flank wall interval arrange, interior coil sensor all apart from flank wall setpoint distance and interval layout.

Inner ring sensor distance flank wall distance is d, d=1-3 rice.

Interval between interior coil sensor is not less than 1m, even or uneven layout, and inner ring number of probes is 6 ~ 10; Interval between outer coil sensor is not less than 1m, even or uneven layout, and outer ring number of probes is 6 ~ 10.

Granary storage gravimetric analysis sensing method, step is as follows:

1) detect the measured value of institute's layout pressure transducer, obtain inner ring measurement value sensor average with outer ring measurement value sensor average

2) bring into

$\hat{W}=A_B(a_0+a_1{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right)+a_2{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)+a_3{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right){\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)+a_4{\stackrel{\‾}{Q}}_B{\left(s_{\mathrm{Inner}}\right)}^2{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right))---\left(14\right)$

Calculate grain storage weight, for grain storage weight is estimated; a ₀, a ₁, a ₂, a ₃and a ₄for calibration coefficient; Formula (14) is the grain storage weight detecting model based on bottom surface pressure and side pressure Estimation of Mean.

In calibration process, record into grain weight and pressure sensor value, for each pressure transducer s _iset up the pressure shown in formula (15) and the relational model entering grain weight

Q _B(s _i)＝b ₀+b ₁W+b ₂W ² (15)

Wherein, b ₀, b ₁, b ₂for returning the coefficient obtained; Q _b(s _i) be pressure transducer s _ipressure estimated value; W is whole granary storage weight; Utilize formula (15), calculate each pressure transducer s _iestimated value when Different Weight value, obtain experimental data sample, each sample point is expressed as (W _i, Q _b(s _1i), Q _b(s _2i) ..., Q _b(s _mn)), wherein, m is sensor number, and n is sample number; According to these sample datas, utilize multiple regression procedure, set up the grain based on bottom surface pressure and side pressure Estimation of Mean shown in formula (14) and pile weight detecting model.

A kind of granary storage weight detection system, pressure transducer is at least divided into two groups of layouts, and one group is interior coil sensor, and another group is outer coil sensor; Outer coil sensor be close to flank wall interval arrange, interior coil sensor all apart from flank wall setpoint distance and interval layout.

A kind of silo, comprise silo weight detection system, pressure transducer is at least divided into two groups of layouts, and one group is interior coil sensor, and another group is outer coil sensor; Outer coil sensor be close to flank wall interval arrange, interior coil sensor all apart from flank wall setpoint distance and interval layout.

From the solution of the present invention, the present invention is a kind of brand-new thinking, have employed a kind of sensor arrangement method of uniqueness, and gives a kind of brand-new grain storage weight detecting model based on this.This arrangement greatly reduces the use of sensor, does not need a large amount of bottom sensor, also no longer needs, by highly installing a large amount of side sensor, to save the cost of detection system.

Accompanying drawing explanation

Fig. 1 horizontal warehouse base pressure sensor placement model;

Fig. 2 silo base pressure sensor placement model;

Fig. 3 timing signal horizontal warehouse base pressure sensor is arranged;

Fig. 4 timing signal silo base pressure sensor is arranged;

The implementation step of Fig. 5 weight detecting.

Embodiment

Below in conjunction with accompanying drawing, the present invention will be further described in detail.

Basic scheme of the present invention is: for the pressure transducer method for arranging of granary storage weight detecting, pressure transducer is at least divided into two groups, and one group is interior coil sensor, and another group is outer coil sensor; Outer coil sensor be close to flank wall interval arrange, interior coil sensor all apart from flank wall setpoint distance and interval layout.

Based on this sensor arrangement method, provide a kind of grain storage gravimetric analysis sensing method, detection method core is adopted weight detecting model

$\hat{W}=A_B(a_0+a_1{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right)+a_2{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)+a_3{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right){\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)+a_4{\stackrel{\‾}{Q}}_B{\left(s_{\mathrm{Inner}}\right)}^2{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right))---\left(14\right)$

Calculate grain storage weight, for grain storage weight is estimated; a ₀, a ₁, a ₂, a ₃and a ₄for calibration coefficient.

And then the present invention gives a kind of silo and weight detection system thereof, they adopt the sensor arrangement of above-mentioned basic scheme.

First ultimate principle of the present invention is introduced.

Normally used silo has the types such as horizontal warehouse, silo, silo, and after conveying grain into storehouse, grain heap top requires to shakeout, and grain pile in horizontal warehouse shape is the cube of different size haply, and silo, silo grain heap shape is the right cylinder of different size haply.Can be drawn by grain heap force analysis, silo grain heap weight and silo pressure distribute the relation had shown in following formula.

$W={\∫}_{S_B}^{Q_B}\left(s\right)\mathrm{ds}+{\∫}_{S_F}^{f_F}\left(s\right)Q_F\left(s\right)\mathrm{ds}$

Wherein, W is grain heap weight; S _b, S _fbe respectively grain heap bottom surface and side; Q _b(s), Q _fs () is respectively grain heap bottom surface S _bwith side S _fin pressure; f _fs () is grain heap side S _fwith the friction factor of grain.Formula (1) shows, for given silo, silo grain heap weight with and only with Q _b(s), Q _f(s) distribution and f _fs () is relevant.

Grain being piled bottom surface separate division is n _bindividual homalographic zonule, each region area is Δ A _b, each regional barycenter place pressure is Q _b(s _i), i=1 ..., n _b; Grain being piled side separate division is n _findividual homalographic zonule, each region area is Δ A _f, each regional barycenter place pressure is Q _f(s _j), j=1 ..., n _f, suppose that side average friction coefficient is f _f, then have

$\hat{W}=\mathrm{\Δ}{A}_B\underset{i=0}{\overset{n_B}{\mathrm{\Σ}}}{Q}_B\left(s_i\right)+\mathrm{\Δ}{A}_F{f}_F\underset{j=0}{\overset{n_F}{\mathrm{\Σ}}}{Q}_F\left(s_j\right)---\left(2\right)$

Wherein, for estimating based on the grain heap weight of grain heap bottom surface and side pressure.Obviously, as Δ A _b→ 0, Δ A _f→ 0, must have

Further arrangement formula (2) has

$\hat{W}=A_B({\stackrel{\‾}{Q}}_B\left(s\right)+\frac{C_B}{A_B}{\mathrm{Hf}}_F{\stackrel{\‾}{Q}}_F\left(s\right))---\left(3\right)$

Wherein, A _bfor grain heap base area, C _bfor bottom surface girth, H is grain bulk height, ${\stackrel{\‾}{Q}}_F\left(s\right)=\frac{1}{n_F}\underset{j=0}{\overset{n_F}{\mathrm{\Σ}}}{Q}_F\left(s_j\right).$ Order

$P_F\left(s\right)=H{f}_F{\stackrel{\‾}{Q}}_F\left(s\right)---\left(4\right)$

Wherein, P _fs () is side unit girth friction force, substitution formula (3) has

$\hat{W}=A_B({\stackrel{\‾}{Q}}_B\left(s\right)+\frac{C_B}{A_B}{P}_F\left(s\right))---\left(5\right)$

As can be seen from formula (3) and formula (5), for given silo and types of food, silo grain heap weight with and only with silo bottom surface pressure average side pressure average relevant with grain bulk height H.Meanwhile, side friction power effect not only with the side friction power P of unit perimeter _fs () is relevant, go back and C _b/ A _brelevant, for Minitype granary, the impact of side friction power will increase more obvious than large granary.

For given silo and grain storage weight W, definition

Q _BNF＝W/A _B (6)

For friction pressure in silo bottom surface equivalence zero.Obviously, friction pressure in silo bottom surface equivalence zero ^q _bNFfor silo bottom surface pressure when friction is zero in silo.By formula (1), when friction is tending towards 0 in silo grain heap, bottom surface each point pressure must be had $Q_B\left(s\right)\→Q_{\mathrm{BNF}},{\∫}_{S_F}^{f_F}\left(s\right)Q_F\left(s\right)\mathrm{ds}\→0,W\→Q_{\mathrm{BNF}}{A}_B.$

Comparison expression (5) and formula (6), order

${\hat{Q}}_{\mathrm{BNF}}={\stackrel{\‾}{Q}}_B\left(s\right)+\frac{C_B}{A_B}{P}_F\left(s\right)---\left(7\right)$

Obviously, for based on bottom surface pressure Q _b(s) and side unit girth friction force P _ffriction pressure Q in the silo bottom surface equivalence zero of (s) _bNFestimation, substitute into formula (3) then have

$\hat{W}=A_B{\hat{Q}}_{\mathrm{BNF}}---\left(8\right)$

In silo bottom surface equivalence zero shown in formula (7), friction pressure is estimated for the unbiased esti-mator of QBNF, work as n _b→ ∞, n _fduring → ∞, must have

Therefore, silo grain heap weight detecting can be converted into the estimation of friction bottom surface pressure in silo grain heap equivalence zero, estimates as long as obtain friction bottom surface pressure in grain heap equivalence zero with enough accuracy then can estimate granary storage capacity quantity survey by enough accuracy meanwhile, by formula (3), in grain heap equivalence zero, friction bottom surface pressure is estimated with silo bottom surface pressure average side pressure average grain bulk height H and side average friction coefficient are f _frelevant, need rationally to estimate these parameters.

Meanwhile, formula (3) embodies silo bottom surface pressure average with side pressure average relation, for given silo, types of food and grain storage weight W, no matter how to change, necessarily constant.Owing to entering the impact of the factors such as grain mode, side pressure average with bottom surface pressure average certain randomness will be had.When measurement is counted abundant, although constant, but with not necessarily constant.According to with this relation, for improving accuracy of detection, this patent proposes the silo gravimetric analysis sensing method based on bottom surface and side pressure Estimation of Mean.

The enforcement rule that sensor is arranged, and weight detecting model and system calibrating

For improving accuracy of detection, according to silo bottom surface pressure average with side pressure average relation, in conjunction with silo pressure characteristic distributions, this patent adopts silo bottom surface pressure average with side pressure average the strategy estimated respectively.

For normally used silo, base pressure sensor encloses by outer ring and inner ring two and arranges, horizontal warehouse sensor is arranged as shown in Figure 1, and as shown in Figure 2, circle is pressure transducer position to silo.Outer ring pressure transducer is close to flank wall and is arranged, practical application shows, it is preferred that number of probes can be taken as 6 ~ 10(), bottom surface, place, obvious outer ring pressure is also the pressure of side bottom, and therefore outer ring pressure transducer output valve average can be used for side pressure average estimation.Interior coil sensor all from flank wall distance be d, d between 1 ~ 3 meter, it is preferred that number of probes can be taken as 6 ~ 10().According to the principle conveniently entering grain, suitably select concrete sensing station, transducer spacing should be not less than 1m.For ensureing accuracy of detection, number of probes should according to the C of silo _b/ A _bwith enter grain height H and suitably change, C _b/ A _blarger with H, required number of probes is more.

Arrange for pressure transducer shown in Fig. 1, outer ring pressure transducer is close to flank wall and is arranged, because outer ring place bottom surface pressure is also the pressure of side bottom, according to side pressure characteristic distributions, obviously have

${\stackrel{\‾}{Q}}_F\left(s\right)\∝\frac{{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)}{2}---\left(9\right)$

Wherein, for outer ring measurement value sensor average.According to silo bottom surface pressure characteristic distributions, obviously have

$\begin{array}{c}{\stackrel{\‾}{Q}}_B\left(s\right)\∝{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right)---\left(10\right)\\ H\∝{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right)---\left(11\right)\end{array}$

Wherein, for inner ring measurement value sensor average.Get

$\hat{H}=h_0+h_1{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right)+h_2{\stackrel{\‾}{Q}}_B{\left(s_{\mathrm{Inner}}\right)}^2---\left(12\right)$

Formula (9), formula (10) and formula (11) are substituted into formula (3), can obtain after arrangement

${\hat{Q}}_{\mathrm{BNF}}=a_0+a_1{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right)+a_2{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)+a_3{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right){\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)+a_4{\stackrel{\‾}{Q}}_B{\left(s_{\mathrm{Inner}}\right)}^2{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)---\left(13\right)$

Wherein, a ₀, a ₁, a ₂, a ₃and a ₄for coefficient.Formula (13) is substituted into formula (8), has

$\hat{W}=A_B(a_0+a_1{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right)+a_2{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)+a_3{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right){\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)+a_4{\stackrel{\‾}{Q}}_B{\left(s_{\mathrm{Inner}}\right)}^2{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right))---\left(14\right)$

Formula (14) is the grain heap weight detecting model based on bottom surface pressure and side pressure Estimation of Mean.This detection model directly introduces the Estimation of Mean of bottom surface pressure and side pressure, effectively can reduce side pressure average with bottom surface pressure average randomness is on the impact of weight detecting.This model is applicable to CB/AB and enters the larger silo weight detecting of grain height H.

System calibrating and detection model modeling are carried out according to the following steps:

(1) demarcation Jin Liang district is set up.In one end of silo according to aforementioned pressure sensor model placement sensor, and utilize sandbag to set up demarcation Jin Liang district, as shown in Figure 3 and Figure 4, wherein spacing d and the flank wall of actual measurement silo sensor are apart from equal, d is between 2 ~ 3 meters, and space D is about 3 ~ 4 meters is appropriate, to reduce the instability of wall of sandbags to the impact of demarcating Jin Liang district pressure distribution, wall of sandbags height 1.5 ~ 2 meters, pressure transducer is evenly arranged.

(2) nominal data obtains.For demarcation Jin Liang district, progressively enter grain, often criticize and shakeout after 0.5 meter, grain, record into grain weight and pressure sensor value, and according to demarcating the ratio of Jin Liang district area and the silo total area, the whole silo calculating corresponding height enters grain weight.3 ~ 4 groups of experimental datas can be obtained like this.Then by normal mode loading, after to be done, record into grain general assembly (TW) and silo base pressure sensor values, obtainable like this 4 ~ 5 groups of data.

(3) detection model modeling.

Due to the grain heap weight detecting model more complicated shown in formula (14), need more data during modeling, therefore, according to the experimental data that step 2 obtains, utilize homing method, for each pressure transducer s _iset up the pressure shown in formula (15) and the relational model entering grain weight

Q _B(s _i)＝b ₀+b ₁W+b ₂W ² (15)

Wherein, b ₀, b ₁, b ₂for returning the coefficient obtained; Q _b(s _i) be pressure transducer s _ipressure estimated value; W is that whole silo enters grain weight.

Entering grain weight range according to silo, entering uniform design 20 ~ 30 grain gravimetric values in grain weight range, being expressed as { W ₁, W ₂..., W _n, n is sample number, wherein n=20 ~ 30, utilizes formula (15), calculates each pressure transducer s _iestimated value when Different Weight value, can obtain 20 ~ 30 experimental data samples like this, each sample point is expressed as (W _i, Q _b(s _1i), Q _b(s _2i) ..., Q _b(s _mn)), wherein, m is sensor number.According to these sample datas, utilize multiple regression procedure, the grain based on bottom surface pressure and side pressure Estimation of Mean shown in formula (14) can be set up and pile weight detecting model.

Complete implementation step, as shown in Figure 5, comprising:

(1) system configuration

Selected concrete pressure transducer, and configure the system such as corresponding data acquisition, data transmission.

(2) base pressure sensor is installed

Horizontal warehouse sensor is arranged as shown in Figure 1, silo as shown in Figure 2, base pressure sensor encloses by outer ring and inner ring two and arranges, outer ring pressure transducer is close to flank wall and is arranged, number of probes can be taken as 6 ~ 10, interior coil sensor all with flank wall distance be d, d between 2 ~ 3 meters, number of probes can be taken as 6 ~ 10.According to the principle conveniently entering grain, suitably select concrete sensing station, transducer spacing should be not less than 1m.For ensureing accuracy of detection, number of probes should according to the C of silo _b/ A _bwith enter grain height H and suitably change, C _b/ A _blarger with H, required number of probes is more.

(3) system calibrating and modeling

For given sensor, types of food and storehouse type, if system not yet has demarcation, then select several silos as demarcation silo.Specific requirement is as follows:

1. set up and demarcate Jin Liang district.For each demarcation silo, set up according to Fig. 3 ~ Fig. 4 and demarcate Jin Liang district, and utilize sandbag to set up demarcation Jin Liang district, wherein spacing d and the flank wall of actual measurement silo sensor are apart from equal, space D is about 3 ~ 4 meters is appropriate, and wall of sandbags height 1.5 ~ 2 meters, pressure transducer is evenly arranged.

2. nominal data obtains.For demarcation Jin Liang district, progressively enter grain, often criticize and shakeout after 0.5 meter, grain, record into grain weight and pressure sensor value, and according to demarcating the ratio of Jin Liang district area and the silo total area, the whole silo calculating corresponding height enters grain weight.3 ~ 4 groups of experimental datas can be obtained like this.Then by normal mode loading, after to be done, record into grain general assembly (TW) and silo base pressure sensor values, obtainable like this 4 ~ 5 groups of data.

3. detection model modeling.According to the experimental data that step 2 obtains, utilize homing method, for each pressure transducer s _iset up the pressure shown in formula (15) and the relational model entering grain weight.Entering grain weight range according to silo, entering uniform design 20 ~ 30 grain gravimetric values in grain weight range, utilizing the model shown in formula (15) to calculate each pressure transducer s _iin the estimated value of Different Weight value, 20 ~ 30 experimental data samples can be obtained like this.According to these sample datas, utilize multiple regression procedure to set up the grain based on bottom surface pressure and side pressure Estimation of Mean shown in formula (14) and pile weight detecting model.

Floorage and lateral area ratio are piled for the different sensors of different manufacturers, different types of food, different storehouse types and the grain according to silo, scope of application classification is carried out to system and demarcates, and set up system parameter table, so that the reusing of calibrating parameters.

(4) real storehouse weight detecting.If system is demarcated, detect base pressure sensor and export and utilize formula (14) institute representation model to carry out quantity of stored grains in granary detection.

Specific experiment example

Test the long 9m of horizontal warehouse adopted, wide 4.2m, area is 37.8m ², C _b/ A _b≈ 0.698.Silo diameter is 6m, and area is 28.26m ², C _b/ A _b≈ 0.67.Two kinds of silos all belong to Minitype granary, C _b/ A _brelatively large.Experiment types of food is wheat, and horizontal warehouse carries out 4 experiments altogether.Divide in each experiment and enter grain 6 times, enter about 1 meter, grain at every turn and shakeout.Silo carries out 3 experiments altogether, and experiment condition and horizontal warehouse first three situation is identical, divides and enters grain 8 times, enter about 1 meter, grain at every turn and shakeout in each experiment.

Pressure transducer placement model according to Fig. 1 and Fig. 2, for horizontal warehouse, arranges 2 row pressure force snesor along its length, from wall distance d=2 rice, often arranges 15, totally 30.Silo pressure transducer divides 2 circles to arrange, often encloses 20, from wall distance d=1 rice, and totally 40.

According to horizontal warehouse 4 experimental datas, utilize 3 experiments (experiment 2,3 and 4) data, as the formula (16), the granary storage Weight computation result of each experiment is as shown in table 1 to table 4 for the forecast model set up by formula (14).

$\begin{array}{c}\hat{W}=A_B(0.1171+0.04882{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right)+0.02308{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)+0.00181{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right){\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)\\ -1.62504E-5{\stackrel{\‾}{Q}}_B{\left(s_{\mathrm{Inner}}\right)}^2{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right))\end{array}---\left(16\right)$

According to silo 3 experimental datas, utilize 2 experiments (experiment 1 and 2) data, as the formula (17), the granary storage Weight computation result of each experiment is as shown in table 5 to table 7 for the forecast model set up by formula (14).

$\begin{array}{c}\hat{W}=A_B(0.13017+0.06921{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right)+0.00554{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)+0.00146{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right){\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)\\ -4.7592E-5{\stackrel{\‾}{Q}}_B{\left(s_{\mathrm{Inner}}\right)}^2{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right))\end{array}---\left(17\right)$

As can be seen from the granary storage Weight computation result estimated with upper bottom surface pressure and side pressure, except the little situation of grain storage weight, the testing result of other check point is more satisfactory.Therefore, this granary storage monitoring weight method measuring accuracy is high, also relatively low to the performance requirement of sensor, is applicable to the detection of various structures type granary storage capacity weight.

Be presented above a kind of concrete embodiment, but the present invention is not limited to described embodiment.Basic ideas of the present invention are above-mentioned basic scheme, and for those of ordinary skill in the art, according to instruction of the present invention, designing the model of various distortion, formula, parameter does not need to spend creative work.The change carried out embodiment without departing from the principles and spirit of the present invention, amendment, replacement and modification still fall within the scope of protection of the present invention.

Claims (7)

1. for the pressure transducer method for arranging of granary storage weight detecting, it is characterized in that, pressure transducer is at least divided into two groups, and one group is interior coil sensor, and another group is outer coil sensor; Outer coil sensor be close to flank wall interval arrange, interior coil sensor all apart from flank wall setpoint distance and interval layout.

2. the pressure transducer method for arranging for granary storage weight detecting according to claim 1, is characterized in that, inner ring sensor distance flank wall distance is d, d=1-3 rice.

3. the pressure transducer method for arranging for granary storage weight detecting according to claim 1, it is characterized in that, the interval between interior coil sensor is not less than 1m, even or uneven layout, and inner ring number of probes is 6 ~ 10; Interval between outer coil sensor is not less than 1m, even or uneven layout, and outer ring number of probes is 6 ~ 10.

4. application rights requires the granary storage gravimetric analysis sensing method of method for arranging described in 1, and it is characterized in that, step is as follows:

1) detect the measured value of institute's layout pressure transducer, obtain inner ring measurement value sensor average with outer ring measurement value sensor average

2) bring into

$\hat{W}=A_B(a_0+a_1{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right)+a_2{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)+a_3{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Inner}}\right){\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right)+a_4{\stackrel{\‾}{Q}}_B{\left(s_{\mathrm{Inner}}\right)}^2{\stackrel{\‾}{Q}}_B\left(s_{\mathrm{Outer}}\right))---\left(14\right)$ Calculate grain storage weight, for grain storage weight is estimated; a ₀, a ₁, a ₂, a ₃and a ₄for calibration coefficient; Formula (14) is the grain storage weight detecting model based on bottom surface pressure and side pressure Estimation of Mean.

5. detection method according to claim 4, is characterized in that, in calibration process, records into grain weight and pressure sensor value, for each pressure transducer s _iset up the pressure shown in formula (15) and the relational model entering grain weight

Q _B(s _i)＝b ₀+b ₁W+b ₂W ² (15)

Wherein, b ₀, b ₁, b ₂for returning the coefficient obtained; Q _b(s _i) be pressure transducer s _ipressure estimated value; W is whole granary storage weight; Utilize formula (15), calculate each pressure transducer s _iestimated value when Different Weight value, obtain experimental data sample, each sample point is expressed as (W _i, Q _b(s _1i), Q _b(s _2i) ..., Q _b(s _mn)), wherein, m is sensor number, and n is sample number; According to these sample datas, utilize multiple regression procedure, set up the grain based on bottom surface pressure and side pressure Estimation of Mean shown in formula (14) and pile weight detecting model.

6. a granary storage weight detection system, is characterized in that, pressure transducer is at least divided into two groups of layouts, and one group is interior coil sensor, and another group is outer coil sensor; Outer coil sensor be close to flank wall interval arrange, interior coil sensor all apart from flank wall setpoint distance and interval layout.

7. a silo, comprises silo weight detection system, it is characterized in that, pressure transducer is at least divided into two groups of layouts, and one group is interior coil sensor, and another group is outer coil sensor; Outer coil sensor be close to flank wall interval arrange, interior coil sensor all apart from flank wall setpoint distance and interval layout.