CN115931092A - Belt scale peeling weight detection method based on fitting curve - Google Patents
Belt scale peeling weight detection method based on fitting curve Download PDFInfo
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Abstract
The invention discloses a belt scale peeling weight detection method based on a fitting curve, which has the main design concept that the sampling tare weight is divided by an average division principle, a plurality of groups of maximum values and minimum values in a division unit are fitted into a curve, a closed area between the fitting curves is compared with a set threshold value, whether peeling is accurate or not is judged by a comparison result, and the tare weight is functionally described in a multi-section fitting curve mode. The invention can effectively solve a plurality of defects existing in the prior peeling method, improve the weighing accuracy of a large-numerical-value accumulated weighing application scene as much as possible, and approximately express a plurality of points of all unit lengths in the total length of the belt scale in a scientific description mode, thereby solving the error generated when the single numerical value of the tare weight is obtained based on accumulation summation to describe the tare weight.
Description
Technical Field
The invention relates to the field of cigarette manufacturing, in particular to a belt scale peeling weight detection method based on a fitting curve.
Background
The method for removing the weight of the belt (called as peeling for short) by using a belt scale in the tobacco industry at present generally comprises a positive and negative integral method and a threshold value method. The two methods firstly measure the length of the whole circle of the conveyer belt, and carry out the total accumulation of the weight of the whole circle of the empty conveyer belt when no material exists, and calculate the average linear density value of the conveyer belt, which is used as the basis for calculating the tare weight when the weighing accumulated data is processed, and the difference value obtained by subtracting the tare weight average value from the gross weight is used as the net weight of the material when weighing.
In the positive and negative integration method, "empty scale runs out of characters" inevitably, or a phenomenon that an accumulated value is rather reduced over time may occur, and the user often cannot accept the measurement which is contrary to the conventional principle. Although the threshold value method has the advantage of avoiding the phenomenon of 'empty scale word running', the method inhibits the phenomenon of 'empty scale word running' by the preset weighing sensitive threshold value, the weighing sensitivity of the belt scale is reduced, and the phenomenon of 'material not word running' can occur. In addition, since the average linear density of the conveyor belt is used in the two peeling modes, the correct measurement of the length of the conveyor belt and the uneven dispersion of the linear density are very important for the accuracy of weighing and metering the belt stalks.
Generally, most industrial belt weighers are long in total length, and the conveyor belt has actual unevenness such as texture, thickness and seams, the linear density changes excessively, and the average value of multiple average measurements deviates from the actual theoretical optimal quality, so that the peeling method for describing the tare weight by a certain numerical value has various defects, such as reduction of weighing accuracy along with increase of the measured total weight, regular deviation of the tare weight value, irregular deviation of the tare weight value caused by unexpected factors, and the like.
Disclosure of Invention
In view of the above, the present invention aims to provide a belt scale peeling weight detecting method based on a fitted curve to solve the aforementioned technical problems.
The technical scheme adopted by the invention is as follows:
the invention provides a belt scale peeling weight detection method based on a fitting curve, which comprises the following steps:
controlling the conveyor belt to run at a constant speed at a preset speed, taking one round of running as a detection process, and recording a plurality of data points for peeling detection at preset data acquisition intervals in each detection process;
after the detection is finished, drawing coordinates by using all data points collected and stored in each detection process; the X axis corresponds to the value point position of each detection process of the data acquisition interval, and the Y axis corresponds to the numerical value of each detection record;
segmenting an X axis, wherein each segment comprises a plurality of value points;
solving the maximum value and the minimum value of the detection data recorded by each value point in the segment;
fitting the maximum value curve and the minimum value curve section by section, and solving the area value of an envelope region between the maximum value curve and the minimum value curve of each section;
comparing the area value corresponding to each section with a preset threshold value respectively;
when the comparison result shows that the area values of all the segments are smaller than the preset threshold value, the value points on the X axis are taken as a unit, and the average value of the data recorded by each value point after peeling is obtained;
and performing curve fitting on each average value in the section, and representing the fluctuation condition of the peeling weight value of the whole conveying belt by taking the section as a unit.
In at least one possible implementation manner, the detection method further includes: a first tare weight value of the whole conveying belt of the belt weigher for peeling is represented by a piecewise function, and a second tare weight value of a single position point of the belt weigher is obtained according to the first tare value described by the function by combining an integral area calculation mechanism.
In at least one possible implementation manner, the detection method further includes: after the piecewise average is calculated to carry out fitting curve and a function expression of the piecewise fitting curve is obtained, a function graph of a first tare value is drawn through an equipment graphical interface, a numerical value of a second tare value of a single point is obtained from the graph and finally output and displayed in an image form,
in at least one possible implementation manner, the segmenting the X axis includes:
dividing the X axis according to a fixed length to enable each segment to comprise equal number of value points;
or, except the last segment, other segments contain equal number of value-taking sites, and the number of the value-taking sites in the last segment is less than that of the value-taking sites in other segments.
In at least one possible implementation manner, the curve fitting operation uses a polynomial model, and the order of the polynomial model is selected according to the number of value points of each segment.
In at least one possible implementation manner, the obtaining the maximum value and the minimum value of the detection data recorded by each value point in the segment includes:
with the segments as units, pre-constructing a two-dimensional array corresponding to each segment;
storing the detection data recorded on each value point in each segment into a corresponding two-dimensional array;
and calculating the maximum value and the minimum value corresponding to each value point by using the two-dimensional array.
In at least one possible implementation manner, the data acquisition interval is set according to a PLC scanning period and a data storage frequency.
In at least one possible implementation manner, the manner of judging the one-circle running of the conveyer belt comprises the following steps:
installing an induction marker at a preset position on a conveying belt of the belt scale, and arranging a detection device on a rack of the belt scale for detecting a pulse signal generated based on the induction marker;
and (4) representing that the conveying belt runs for one circle by two adjacent detected pulse signals.
The method mainly comprises the steps of segmenting the sampled tare weight by using an average segmentation principle, fitting a plurality of groups of maximum values and minimum values in a segmentation unit into curves, comparing closed areas among the fitted curves with a set threshold value, judging whether the peeling is accurate or not according to comparison results, and performing functional description on the tare weight in a multi-section fitted curve mode. The invention can effectively solve the problems of various defects in the existing peeling method, improve the weighing accuracy of a large-numerical-value accumulated weighing application scene as much as possible, and perform approximate expression on a plurality of points of all unit lengths in the total length of the belt scale in a scientific description mode, thereby solving the error generated when the single numerical value of the tare weight is obtained based on accumulation summation to describe the tare weight.
Compared with the prior art, the invention has the beneficial effects at least as a whole that:
(1) The method of evenly dividing into fixed sections reduces the hardware calculation amount of the whole fitting curve and improves the calculation speed on the premise of ensuring the tare weight accuracy.
(2) And comparing the area value of an envelope region between the maximum value curve and the minimum value curve with a set threshold value by a method for calculating the area based on an integral formula so as to judge the accuracy of the peeling process and the reliability of data.
(3) The belt scale state monitoring method has the advantages that the curve is fitted based on the segmented average number, the curve of the tare weight value is drawn according to the function expression of the segmented fitting curve, the influence of the position change of the whole conveying belt on the tare weight value can be visually seen through the image, and the process control level of the belt scale state monitoring is improved.
(4) The order of the fitting curve model selection polynomial is determined according to the value number N of the fixed window X, so that the calculation efficiency and the accuracy of the fitting curve are improved, and the accuracy of the whole method for measuring the tare weight is further improved.
(5) The method for calculating the area sum based on the piecewise function integration and then dividing the area sum by the abscissa to obtain the tare weight value mean value is remarkably higher than the traditional method for calculating the mean value after accumulation.
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To make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described with reference to the accompanying drawings, in which:
fig. 1 is a flowchart of a belt scale peeling weight detection method based on a fitted curve according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention and are not to be construed as limiting the present invention.
The invention provides an embodiment of a belt scale peeling weight detection method based on a fitted curve, which is specifically shown in fig. 1 and comprises the following steps:
s1, controlling a conveyor belt to run at a constant speed at a preset speed, taking one round of running as a detection process, and recording a plurality of data points (belt scale detection values) for peeling detection at preset data acquisition intervals in each detection process;
the data acquisition interval can be set according to the PLC scanning period and the data storage frequency and by combining the performance of external CPU hardware and other conditions.
For the determination of one revolution of the conveyor belt, the following method can be referred to:
the method comprises the following steps that an induction marker is installed at a preset position on a conveying belt of the belt scale, and a detection device is arranged on a rack of the belt scale and used for detecting a pulse signal generated based on the induction marker;
after the belt weigher begins to peel, taking the pulse signal detected for the first time as a peeling detection starting point, and taking the pulse signal detected for the G +1 (G is a positive integer more than or equal to 1) th time as a peeling detection ending point;
and (4) representing that the conveyer belt runs for one circle by two adjacent pulse signals.
S2, after the detection is finished, drawing coordinates by using all data points collected and stored in each detection process; the X axis corresponds to the value point position of each detection process of the data acquisition interval, and the Y axis corresponds to the numerical value of each detection record;
in practical operation, it can be set that W pieces of tare weight data are recorded in each detection process (W pieces of data are recorded in a cycle representing the belt running), and as for the previous example, data collection and dotting are continuously performed in all the G detection processes from the 1 st detection of the induction marker to the G +1 st detection.
Because G rounds of detection processes need to be passed, G vertical coordinate points can be recorded at corresponding data acquisition positions on W X axes. I.e. until the end, X 1 The Y value of (A) is G (Y) 11 ，Y 12 ，Y 13 …Y 1G )，X 2 The Y value on the coordinate is G (Y) 21 ，Y 22 ，Y 23 …Y 2G )……X W There are G (Y) values of Y on the coordinate W1 ，Y W2 ，Y W3 …Y WG ) Wherein, the W value represents that W X values are totally obtained between every two detected induction markers, and X is 1 And X 2 (X W-1 And X W ) The difference between them is the preset data acquisition interval (which can also be understood as the data storage period): during the first round of detection (first cycle of belt operation), W data are collected, respectively X abscissa 1 Corresponds to Y 11 、X 2 Corresponds to Y 21 、X W Corresponds to Y W1 823060, in the detection process of the G-th wheel (G-th running circle of the belt), W data are collected, X is respectively 1 Corresponds to Y 1G 、X 2 Corresponds to Y 2G 、X W Corresponds to Y WG 。
S3, segmenting the X axis, wherein each segment comprises a plurality of value points;
based on different situations, the following segmentation implementation details are given here:
(1) if W is divided by M exactly, then take N = W/M, N ∈ N + The X axis is exactly divided into M segments, each segment having N X values.
(2) If W is divided by M and cannot be divided, then take N x (M-1) + R = W, which isWherein R is the remainder, R < N, N is the element of N + 、R∈N + And the representative X axis is divided into M sections, the X axis of the front M-1 section has N X values, and the X axis of the last section 1 has R X values because the X axis cannot be divided completely.
S4, solving the maximum value and the minimum value of the detection data recorded in each value point in the segment;
specifically, the following algorithm may be performed on all points on each X-axis by using hardware resources external to the PLC, and a maximum value Max (Y) at a jth X-axis point is finally obtained j ) And the minimum Min (Y) at the jth X-axis point j )。
Assuming that the segment X is the (F + 1) th segment (not the last 1 segment which cannot be divided in the above (2)), there are N X values in the segment, which are X respectively F*N+1 ，X F*N+2 ，X F*N+3 ...X F*N+N G Y-axis values corresponding to each X-axis value (X-axis value point location) are stored in the constructed two-dimensional array A [j][h] . The 1 st value of X F*N+1 The corresponding Y values are respectively Y (F*N+1)(1) ，Y (F*N+1)(2) ，Y (F*N+1)(3) …Y (F*N+1)(G) Respectively stored in two-dimensional arrays A [j][h] A of (A) [F*N+1][1] ，A [F*N+1][2] ，A [F*N+1][3] …A [F*N+1][G] (ii) a The 2 nd X value F*N+2 The corresponding Y values are respectively Y (F*N+2)(1) ，Y (F*N+2)(2) ，Y (F*N+2)(3) …Y (F*N+2)(G) Respectively stored in two-dimensional arrays A [j][h] A of (A) [F*N+2][1] ，A [F*N+2][2] ，A [F*N+2][3] …A [F*N+2][G] (ii) a The nth X value X F*N+N The corresponding Y values are respectively Y (F*N+N)(1) ，Y (F*N+N)(2) ，Y (F*N+N)(3) …Y (F*N+N)(G) Respectively stored in two-dimensional arrays A [j][h] A of (A) [F*N+N][1] ，A [F*N+N][2] ，A [F*N+N][3] …A [F*N+N][G] 。
Assuming that the segment X split axis is the last segment 1 under the non-integer division condition (the last segment 1 which cannot be integer divided in (2) above), there are R X values in the segment, which are X respectively (M-1)*N+1 ，X (M-1)*N+2 ，X ( M -1)*N+3 ...X W G Y-axis values corresponding to each x value are stored in the constructed two-dimensional array A [j][h] . Value of 1X (M- 1 )*N+1 The corresponding Y values are respectively Y ((M-1)*N+1)(1) ，Y ((M-1)*N+1)(2) ，Y ((M-1)*N+1)(3) …Y ((M-1)*N+1)(G) Respectively stored in two-dimensional arrays A [j][h] A of (A) [(M-1)*N+1][1] ，A [(M-1)*N+1][2] ，A [(M-1)*N+1][3] …A [M+1][G] (ii) a The 2 nd X value (M-1)*N+2 The corresponding Y values are respectively Y ((M-1)*N+2)(1) ，Y ((M-1)*N+2)(2) ，Y ((M-1)*N+2)(3) …Y ((M-1)*N+2)(G) Respectively stored in two-dimensional arrays A [j][h] A of (A) [(M-1)*N+2][1] ，A [(M-1)*N+2][2] ，A [(M-1)*N+2][3] …A [(M-1)*N+2][G] (ii) a The value of the R X W The Y values corresponding to the last point of the X-axis coordinate are Y (W)(1) ，Y (W)(2) ，Y (W)(3) …Y (W)(G) Respectively stored in two-dimensional arrays A [j][h] A of (A) [W][1] ，A rW][2] ，A [W][3] …A [W][G] 。
In either case, the two-dimensional array A constructed as described above [j][h] Calculating the maximum value and the minimum value of the Y value corresponding to each x value, and defining as:
maximum value Max (Y) at jth X-axis point j )＝max(A [j][1] ，A [j][2] ，A [j][3] …A [j][G] )，j∈(1，W).
Minimum Min (Y) at jth X-axis point j )＝min(A [j][1] ，A [j][2] ，A [j][3] …A [j][G] )，j∈(1，W).
S5, fitting the maximum value curve and the minimum value curve section by section, and solving the area value of an envelope area between the maximum value curve and the minimum value curve of each section;
the method of operation can be referred to as follows: the curve _ fit () function of a Python programming tool can be selected for single curve fitting, a polynomial model can be selected for the fitting curve model, and the order is selected according to the size of the point number N.If N is more than 2 and less than 5, selecting 3 polynomial model order; if N is more than 6 and less than 8, selecting 4 polynomial model orders; if N is more than 9 and less than 15, selecting 5 polynomial model orders; if N is more than 16 and less than 20, selecting 6 polynomial model orders; if N is more than 20, in order to save hardware computing resources and improve the operation speed, the polynomial model order is selected to be 7. Carrying out single curve fitting on the segments from the 1 st segment to the M th segment which are divided by the X axis, and fitting the maximum values of N (or R) Y-axis values of each segment into a maximum value curve f max (x) Fitting the minimum value of N (or R) Y-axis values of each segment into a minimum value curve f min (x)。
Then, the area value of the envelope region between the maximum value curve and the minimum value curve of each segment is calculated by using an integral formula, and the formula is defined as follows:
if the segment has N X-axis points, the area value S of the envelope region between the maximum value curve and the minimum value curve c The formula is as follows:
if the segment has R X-axis points, the area value S of the envelope region between the maximum value curve and the minimum value curve R The formula is as follows:
s6, comparing the area value corresponding to each section with a preset threshold value respectively;
calculating the S of each segment c Value and set envelope area threshold S F Comparing, if there is some area value S of envelope region between maximum value curve and minimum value curve calculated c ＞S F And then, the value of the weight fluctuates between G times of peeling, and the peeling needs to be carried out again in the first step. If S of all segments c ＜S F Then the following steps are continued.
Corresponding to the non-integer special case, if there is the last oneIf there are R X-axis values, the calculated area value S of the envelope region between the maximum value curve and the minimum value curve of the last segment is used R And S F Comparing with/NxR, if S R ＞S F and/NR indicates how much the tare value of the last section fluctuates between G times of peeling, and the peeling needs to be carried out again in the first step. If S R ＜S F and/N R, then continuing to perform the following steps.
S7, when the area values of all the segments are smaller than the preset threshold value according to the comparison result, taking the value points on the X axis as a unit, and calculating the average value of the data recorded by each value point after peeling;
the calculation method and formula are referred to as follows:
1 st X-axis value point X 1 The average value of the ordinate of (a) is calculated by the formula:
value X of the 2 nd X axis 2 The formula for calculating the average value of the ordinate is:
……
the W-th (last X value) X-axis value X W The formula for calculating the average value of the ordinate is:
and S8, performing curve fitting on each average value in the section, and representing the fluctuation condition of the peeling weight value of the whole conveying belt by taking the section as a unit.
In actual operation, a current _ fit () function of a Python programming tool can also be selected for single curve fitting, a polynomial model is selected for the fitting curve model, and the order is selected according to the number of points N. If N is more than 2 and less than 5, selecting 3 polynomial model order; if N is more than 6 and less than 8, selecting 4 polynomial model orders; if N is more than 9 and less than 15, selecting 5 polynomial model orders; if N is more than 16 and less than 20, selecting 6 polynomial model orders; if N is more than 20, in order to save hardware computing resources and improve the computing speed, the order of the polynomial model is selected 7.
The specific fitting method is referred to as follows:
1 st point of the 1 st segment is denoted as d 1 (x 1 ，AVG(x 1 ) Is namely
The 2 nd point of the 1 st segment is denoted as d 2 (x 2 ，AVG(x 2 ) Is namely
……
The Nth point of the 1 st segment is denoted as d N (x N ，AVG(x N ) Is obtained as
Fitting the N mean values of the 1 st segment to a curve f 1 (x) Curve f 1 (x) The fluctuation of the peeling value of the physically corresponding 1 st segment conveyor is represented in the form of a function.
……
And (3) fitting a curve of N points of the 2 nd section by the method for fitting the 1 st section into the curve, wherein the curve is denoted as f2 (x), and the curve f2 (x) represents the fluctuation condition of the peeling value of the 2 nd section conveying belt which corresponds to the physical form in a functional form.
And fitting all curves of the M sections by using the same method, wherein the curves comprise curve functions:
the complex rules corresponding to the physics are described in the form of M-section function, namely the rules that the peeling weight value changes with the change of the position of the belt in a sectional form and a formula of the whole conveying belt of the belt scale.
On the basis of the above embodiment, the method further includes: a first tare value (tare value G (x)) of the whole conveying belt of the belt scale for peeling is represented by a piecewise function, and a second tare value (tare value V (x)) of a single position of the belt scale is obtained according to the first tare value described by the function by combining a mechanism of integrating and solving the area.
Wherein the expression formula of the first tare value (tare value G (x)) is:
furthermore, by applying the principle of integrating and solving the area, a second tare value V (x) of a single value of the belt scale in the traditional sense can be calculated, and the expression formula is as follows:
finally, it can be supplemented that, after a fitting curve is carried out based on the prior sectional averaging, and a function expression of the sectional fitting curve is obtained, a graph of the peeling weight value function can be drawn in an equipment graphical interface, and a numerical value of the tare value V (x) of a single site is obtained from the graph and is output and displayed in an image form, so that the influence of the position change of the whole conveying belt of the belt scale on the tare value can be conveniently and visually seen, and the process control level of the belt scale state monitoring can be improved.
In summary, the main design concept of the present invention is to divide the sampled tare weight by the average division principle, fit multiple groups of maximum and minimum values in the division unit into curves, compare the closed region between the fitted curves with the set threshold, determine whether the peeling is accurate according to the comparison result, and functionally describe the tare weight by the way of multiple sections of fitted curves. The invention can effectively solve a plurality of defects existing in the prior peeling method, improve the weighing accuracy of a large-numerical-value accumulated weighing application scene as much as possible, and approximately express a plurality of points of all unit lengths in the total length of the belt scale in a scientific description mode, thereby solving the error generated when the single numerical value of the tare weight is obtained based on accumulation summation to describe the tare weight.
In the embodiments of the present invention, "at least one" means one or more, "a plurality" means two or more. "and/or" describes the association relationship of the associated objects, and means that there may be three relationships, for example, a and/or B, and may mean that a exists alone, a and B exist simultaneously, and B exists alone. Wherein A and B can be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c may represent: a, b, c, a and b, a and c, b and c or a and b and c, wherein a, b and c can be single or multiple.
The structure, features and effects of the present invention have been described in detail with reference to the embodiments shown in the drawings, but the above embodiments are merely preferred embodiments of the present invention, and it should be understood that technical features related to the above embodiments and preferred modes thereof can be reasonably combined and configured into various equivalent schemes by those skilled in the art without departing from and changing the design idea and technical effects of the present invention; therefore, the invention is not limited to the embodiments shown in the drawings, and all the modifications and equivalent embodiments that can be made according to the idea of the invention are within the scope of the invention as long as they are not beyond the spirit of the description and the drawings.
Claims (8)
1. A belt scale peeling weight detection method based on a fitting curve is characterized by comprising the following steps:
controlling the conveyer belt to run at a constant speed at a preset speed, taking one round of running as a detection process, and recording a plurality of data points for peeling detection at preset data acquisition intervals in each detection process;
after the detection is finished, drawing coordinates by using all data points collected and stored in each detection process; the X axis corresponds to the value point position of each detection process of the data acquisition interval, and the Y axis corresponds to the numerical value of each detection record;
segmenting an X axis, wherein each segment comprises a plurality of value points;
solving the maximum value and the minimum value of the detection data recorded by each value point in the segment;
fitting the maximum value curve and the minimum value curve section by section, and solving the area value of an envelope region between the maximum value curve and the minimum value curve of each section;
comparing the area value corresponding to each section with a preset threshold value respectively;
when the comparison result shows that the area values of all the segments are smaller than the preset threshold value, the value points on the X axis are taken as a unit, and the average value of the data recorded by each value point after peeling is obtained;
and performing curve fitting on each average value in the section, and representing the fluctuation condition of the peeling weight value of the whole conveying belt by taking the section as a unit.
2. The method of claim 1, further comprising: a first tare weight value of the whole conveying belt of the belt weigher for peeling is represented by a piecewise function, and a second tare weight value of a single position point of the belt weigher is obtained according to the first tare value described by the function by combining an integral area calculation mechanism.
3. The belt scale peeling weight detection method based on the fitted curve as claimed in claim 2, wherein the detection method further comprises: and after the average is calculated in a segmentation mode to carry out a fitting curve and a function expression of the segmentation fitting curve is obtained, a function graph of a first tare weight value is drawn through an equipment graphical interface, a numerical value of a second tare weight value of a single point is obtained from the graph, and the numerical value is finally output and displayed in an image form.
4. The method of claim 1, wherein the segmenting the X-axis comprises:
dividing the X axis according to a fixed length to enable each segment to comprise equal number of value points;
or, except the last segment, other segments contain equal number of value-taking sites, and the number of the value-taking sites in the last segment is less than that of the value-taking sites in other segments.
5. The belt scale coat weight detection method of claim 1 wherein the curve fitting operation uses a polynomial model with an order selected according to the number of point locations of each segment.
6. The belt scale coat weight detection method based on the fitted curve of claim 1, wherein the step of obtaining the maximum value and the minimum value of the detection data recorded at each point in the segment comprises:
pre-constructing a two-dimensional array corresponding to each segment by taking the segment as a unit;
storing the detection data recorded on each value point in each segment into a corresponding two-dimensional array;
and calculating the maximum value and the minimum value corresponding to each value point by using the two-dimensional array.
7. The belt weigher peeled weight detection method based on the fitted curve according to any one of claims 1 to 6, wherein the data acquisition interval is set according to a PLC scanning period and data storage frequency.
8. The belt scale peeled weight detecting method based on the fitted curve according to any one of claims 1 to 6, wherein the manner of judging one-week running of the conveyer belt comprises:
the method comprises the following steps that an induction marker is installed at a preset position on a conveying belt of the belt scale, and a detection device is arranged on a rack of the belt scale and used for detecting a pulse signal generated based on the induction marker;
and (4) representing that the conveying belt runs for one circle by two adjacent detected pulse signals.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116612123A (en) * | 2023-07-21 | 2023-08-18 | 山东金胜粮油食品有限公司 | Visual detection method for peanut oil processing quality |
| CN116612123B (en) * | 2023-07-21 | 2023-10-13 | 山东金胜粮油食品有限公司 | Visual detection method for peanut oil processing quality |
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