CN113916125A - Vinasse volume measuring method based on depth imaging - Google Patents

Vinasse volume measuring method based on depth imaging Download PDF

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CN113916125A
CN113916125A CN202110891647.8A CN202110891647A CN113916125A CN 113916125 A CN113916125 A CN 113916125A CN 202110891647 A CN202110891647 A CN 202110891647A CN 113916125 A CN113916125 A CN 113916125A
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vinasse
container
point cloud
volume
depth
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CN113916125B (en
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李群庆
赵雨心
金元浩
刘淼
张宿义
熊燕飞
许德富
杨平
秦辉
涂飞勇
周军
蔡小波
黄孟阳
罗杰
李慧娟
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Tsinghua University
Luzhou Laojiao Co Ltd
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Luzhou Laojiao Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates

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  • Length Measuring Devices By Optical Means (AREA)
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Abstract

The invention provides a vinasse volume measuring method based on depth imaging, which comprises the following steps of: s1, providing a container with an inner bottom surface; s2, acquiring the topography of the inner bottom surface by using a depth camera to obtain a first data point cloud picture; s3, arranging a vinasse in the container, wherein the vinasse forms a vinasse pile; s4, acquiring the surface appearance of the vinasse by using the depth camera to obtain a second data point cloud picture; and S5, performing data processing according to the point cloud data in the first data point cloud picture and the second data point cloud picture, establishing a model, and calculating the volume of the vinasse. The vinasse volume measuring method based on depth imaging has the advantages of high precision, no contact, no influence of working environment and the like, and is suitable for being used in the vinasse transferring and mixing processes.

Description

Vinasse volume measuring method based on depth imaging
Technical Field
The invention relates to a vinasse volume measuring method.
Background
In the brewing process flow of the Luzhou-flavor liquor, after the fermentation process of the vinasse is finished, the vinasse subjected to the batching needs to be transferred to the vinasse subjected to the distillation process to be subjected to the retort loading process. In the process, a part of production workshops of the prior Luzhou Lao jiao adopt a full-automatic production line which rotates from a big hopper to a small hopper to carry out batching and retort loading processes. Wherein, in the existing process flow, the weight measurement is carried out on the vinasse and the ingredients in the small bucket to determine the overall level of the vinasse and the ingredients which are fed into the retort at each time. Due to the difference of the water content and the starch content of the vinasse caused by the fermentation condition of the vinasse, the vinasse with the same weight has different volumes, which further influences the process flow of the ingredients, thereby influencing the vinasse quality in the retort.
Disclosure of Invention
In view of the above, there is a need to provide a vinasse volume measurement method based on depth imaging, which has the advantages of high precision, no contact (no direct contact with vinasse), and no influence from the working environment.
A vinasse volume measurement method based on depth imaging comprises the following steps:
s1, providing a container with an inner bottom surface;
s2, acquiring the topography of the inner bottom surface by using a depth camera to obtain a first data point cloud picture;
s3, arranging a vinasse in the container, wherein the vinasse forms a vinasse pile;
s4, acquiring the surface appearance of the vinasse by using the depth camera to obtain a second data point cloud picture; and
and S5, performing data processing according to the point cloud data in the first data point cloud picture and the second data point cloud picture, establishing a model, and calculating the volume of the vinasse.
Compared with the prior art, the method for measuring the volume of the vinasse based on the depth imaging detects and collects the volumes of the vinasse and the ingredients in the processes of vinasse transfer and retort loading in real time by using the depth camera, and the volume is matched with the material weight data measured in real time to give the density data of the vinasse and the ingredients, so that the standardization degree of the vinasse and the retort loading ingredients is improved. The vinasse volume measuring method based on depth imaging has the advantages of high precision, no contact (no need of directly contacting vinasse), no influence of working environment and the like, and is suitable for being used in the vinasse transferring and mixing processes.
Drawings
FIG. 1 is a flow chart of a vinasse volume measurement method based on depth imaging provided by the invention.
Fig. 2 is a schematic structural diagram of the movable bucket and the weight collection device provided by the invention.
Fig. 3A to 3D are optical photographs of the cellar-out groove provided by the present invention at different angles.
Fig. 4A and 4B are an optical photograph of the front surface morphology of the cellar-out wine vessel and a corresponding second data point cloud chart, respectively.
Fig. 5A and 5B are another optical photograph of the cellar-out wine and a corresponding second data point cloud respectively.
Fig. 6A and 6B are another optical photograph of the cellar-out wine and a corresponding second data point cloud respectively.
Fig. 7A and 7B are point cloud calculation diagrams of the front surface morphology of the cellar-out grains provided by the invention.
Fig. 8 is a 3D view of mesh data of a depth camera provided by the present invention.
Fig. 9A and 9B are top view and height profile data, respectively, of a container filled with whole stillage according to the present invention.
Fig. 10A and 10B are a height profile of a slice sampled over time and an average height sampled over time, respectively, over 40 seconds as provided by the present invention.
Fig. 11A and 11B are the 5 independent full slice height profiles and the corresponding average heights with error bars, respectively.
Description of the main elements
Movable bucket 10
Weight acquisition device 20
The following detailed description will further illustrate the invention in conjunction with the above-described figures.
Detailed Description
The method for measuring the volume of vinasse based on depth imaging provided by the invention is further described in detail with reference to the accompanying drawings and specific embodiments.
Referring to fig. 1, the present invention provides a method for measuring volume of wine lees based on depth imaging, which comprises the following steps:
s1, providing a container with an inner bottom surface;
s2, acquiring the topography of the inner bottom surface by using a depth camera to obtain a first data point cloud picture;
s3, arranging a vinasse in the container;
s4, acquiring the surface appearance of the vinasse by using the depth camera to obtain a second data point cloud picture; and
and S5, performing data processing according to the point cloud data in the first data point cloud picture and the second data point cloud picture, establishing a model, and calculating the volume of the vinasse.
In step S1, the type and size of the container are not limited, for example, a tray used in a laboratory, a bucket used in a production line, and the like.
In step S3, in this embodiment, the lees are transferred by a moving bucket 10. As shown in fig. 2, in the present embodiment, the size of the upper opening of the moving bucket 10 is 2100 × 2100mm2(square mm) lower mouth size 1800 x 1600mm2And a height of 1100mm (millimeters). A weight collection device 20 is arranged below the movable hopper 10, and the collection frequency of the weight collection device 20 is 20 times/second. The movable hopper 10 is used for containing vinasse, and the weight acquisition device 20 is used for calculating the density of the vinasse by combining the volume measurement result. In the vinasse transferring process, vinasse transferred into the moving hopper 10 naturally forms a cone shape with a stack tip, and the requirement is to measure the volume change of the stack tip-shaped vinasse. The heap-shaped vinasse can also be called a vinasse heap.
In step S4, the depth camera is used to collect the surface topography of the distiller ' S grains to obtain a second data point cloud picture of the surface topography of the distiller ' S grains, so that data processing and calculation are performed subsequently to obtain volume data of the distiller ' S grains.
In the embodiment, the cellar-out grains are used as experimental samples for depth information acquisition, and the volume of the cellar-out grains is obtained by combining a corresponding data processing method and a volume calculation algorithm. The appearance of the cellar outlet is shown in figure 3. The volume of the cellar-out grains was found to be about 7750mL (milliliters) as measured with a graduated cylinder. And (3) acquiring the surface appearance of the cellar-out grains by using a depth camera, wherein fig. 4A and 4B are optical photos of the top view or the front surface appearance of the cellar-out grains and corresponding second data point cloud charts.
Therefore, a high-resolution topographic map of the surface of the vinasse pile can be obtained through data acquisition of the depth camera, in the implementation, the spatial resolution of the high-resolution topographic map is 640 × 480, a single pixel point is about 1.2 × 1.2mm2, and the minimum resolution of depth information can reach 0.1 mm. The depth camera is set to VGA resolution to ensure depth measurement accuracy and medium data storage. In this embodiment, the resolution of the depth camera is VGA (640 × 480). Table I shows the parameters of the depth camera in this embodiment.
TABLE I parameters of depth camera
Figure BDA0003196350600000041
And aiming at different angles of the vinasse pile, the depth camera can be utilized to carry out corresponding surface topography scanning. Fig. 5A and 5B are another optical photograph of the cellar for storing things and a corresponding second data point cloud, and fig. 6A and 6B are another optical photograph of the cellar for storing things and a corresponding second data point cloud.
In step S5, data processing is performed according to the point cloud data in the first data point cloud picture and the second data point cloud picture, a model is built, and the volume of the distiller' S grains is calculated. The specific process is as follows: the surface model of the vinasse pile is defined as zl(x, y) wherein zlX and y in (x, y) are respectively the abscissa and the ordinate of the point data in the second data point cloud. The surface model of the inner bottom surface of the container is defined as zc(x, y) wherein zcX and y in (x, y) are respectively the abscissa and the ordinate of the point data in the first data point cloud.
Volume V of the pile of vinasse when the image plane of the depth camera is parallel to the inner bottom surface of the containerlIs zlAnd zcThe integral in between. That is, the volume V of the heap of vinasse when the image plane of the depth camera is parallel to the inner bottom surface of the containerlCan be obtained by the formula (1).
Vl＝∫∫szl(xy)-zc(x,y)dxdy. (1)
However, in actual production, the image plane of the depth camera is notParallel to the inner bottom surface of the container, the image plane of the depth camera forms an angle with the inner bottom surface of the container, which angle is defined as the dislocation angle θ. At this time, the volume V of the heap of leeslShould be corrected by cos θ. Thus, when the image plane of the depth camera has an offset angle θ with the inner bottom surface of the container, the volume V of the heap of vinasselThis can be obtained by the formula (2).
Vl＝cosθ∫∫szl(x,y)-zc(x，y)dxdy. (2)
In this embodiment, the point cloud calculation map of the front surface topography of the cellar output wine is shown in fig. 7A and 7B, where fig. 7B is a data schematic diagram in which a container frame is cut off. And performing meshing processing by using the point cloud data obtained by the depth camera to obtain surface grid data of the cellar, as shown in fig. 8. In this embodiment, the volume of the cellar-out grains is 7625mL through data processing and integral operation and calculation according to point cloud data measured by a depth camera, and the volume of the cellar-out grains is 7750mL through measurement by a measuring cylinder. Therefore, the relative error between the vinasse volume measuring method based on depth imaging and the measuring cylinder measuring data is 1.6%. In addition, the present invention calculated 5 sets of simulated volume data and compared them to the actual volume measured by the graduated cylinder, with the results shown in table II. Therefore, the relative errors of the vinasse volume measuring method based on the depth imaging and the measuring cylinder measuring data are less than 2%. Namely, the relative error between the depth imaging-based vinasse volume measurement method and the actual accurate value is less than 2%.
TABLE II volumetric measurement data
Calculating volume (m ^3) 0.770 0.752 0.788 0.740 0.813
Actual volume (m ^3) 0.782 0.765 0.722 0.732 0.935
Relative error (%) 1.6 1.7 2 1.1 1.2
Further, the method for measuring volume of vinasse based on depth imaging further comprises a step S6 'of calculating the average height of the bottom of the container, thereby calculating the average height standard'. Specifically, the surface of the heap is cut into a slice at l (x, y) ═ 0, and a stable statistical threshold is generated to determine whether the container is full, which is defined as follows:
Figure BDA0003196350600000051
where l is the length of the slice. This criterion based on empirical mean height should be stable for determining the condition of the container, since the stack profile is substantially stable when the container is full. The depth camera provides real-time point cloud data of the surface of the vinasse pile, and modifies a formula (3) to obtain a formula (4):
Figure BDA0003196350600000061
wherein, TcThreshold value for determining whether the container is filled with wine lees, zc＝(1/N)，l(x,y)＝0，zc(x, y) is the average height of the bottom of the container, and N is the total number of points for which the second data point cloud satisfies l (x, y) 0. Therefore, adding step S6 "calculating the average height of the bottom surface of the container and thus the average height level", it is possible to apply a practical and stable level to determine whether the container is full of vinasse without completely measuring and calculating the volume of the vinasse pile.
The accessibility and stability of the method are verified by bringing the method to the actual liquor production line. Five batches of data of the same production line on the same day are collected. Each batch of data contains a measurement of the surface of the heap of stillage from an empty container to a full container, i.e. a container filled with stillage. The vinasse bulk density is consistent on the day, and the misalignment angle of the depth camera can be ignored. From these data, a height profile is selected and an average height criterion is calculated. Fig. 9A and 9B show a top view and height profile of a full container. The selected contour is parallel to the boundary of the container, avoiding the influence of the container boundary on the depth camera view. Fig. 9A is a top view of full container surface data, with the dotted lines showing the height profile used to calculate the average height criteria. Fig. 10 shows how the height profile varies over time. The calculated average height of the height profile of the 5 batches of data when the container is full is shown in fig. 11A and 11B. The data in fig. 11A and 11B show that the average height of the slices of the selected profile is highly stable throughout the day with a maximum fluctuation in average height of less than 3%. To determine a practical average height criterion for determining whether a container is full, the threshold value Tc may be set to 0.95m (meters) and the next sequence in the wine making process may be triggered.
Therefore, the point cloud data obtained by the depth camera is used for gridding processing to obtain the surface grid data of the cellar. The pit volume can be calculated based on the grid data, the slicing data of the pit slot is obtained, and the pit volume criterion is obtained by calculating the average value of the slicing height.
Therefore, the volume of the vinasse can be accurately determined according to the measuring method of the depth camera and the corresponding data processing and modeling calculation process. That is, the depth imaging-based stillage volume measuring method can accurately determine the volume of the stillage. And can also judge whether the container is full of vinasse.
In addition, the vinasse volume measurement method based on depth imaging can also carry out dynamic measurement on the stacking process of the vinasse stacking tips. In this example, the dynamic measurement of the pit tip was measured at 30 times/second.
Further, the depth imaging-based vinasse volume measurement method is also applicable to the volume of ingredients used in brewing white spirit.
The vinasse volume measurement method based on depth imaging has the following advantages: firstly, the vinasse volume measuring method based on depth imaging has the advantages of high precision, no contact, no influence of working environment and the like, and is suitable for being used in the vinasse transferring and mixing process; secondly, the volume of the vinasse and the ingredients in the vinasse transfer and retort loading processes is detected and collected in real time by using a depth camera, and the volume is matched with the material weight data measured in real time to give the density data of the vinasse and the ingredients, so that the standardization degree of the vinasse and the retort loading ingredients is improved; thirdly, a standard based on average height is provided for quickly and accurately judging whether the container is full of vinasse, and the method is suitable for complex factory scenes due to simple measurement and installation, such as application to a white spirit production line.
In addition, other modifications within the spirit of the invention will occur to those skilled in the art, and it is understood that such modifications are included within the scope of the invention as claimed.

Claims (10)

1. A vinasse volume measurement method based on depth imaging comprises the following steps:
s1, providing a container with an inner bottom surface;
s2, acquiring the topography of the inner bottom surface by using a depth camera to obtain a first data point cloud picture;
s3, arranging a vinasse in the container, wherein the vinasse forms a vinasse pile;
s4, acquiring the surface appearance of the vinasse by using the depth camera to obtain a second data point cloud picture; and
and S5, performing data processing according to the point cloud data in the first data point cloud picture and the second data point cloud picture, establishing a model, and calculating the volume of the vinasse.
2. The depth imaging-based vinasse volume measurement method of claim 1, wherein in step S5, the surface model of the vinasse stack is defined as zl(x, y), the surface model of the inner bottom surface of the container being defined as zc(x, y), the image plane of the depth camera being parallel to the inner bottom surface of the container, the volume V of the heap of vinasselComprises the following steps:
Vl＝∫∫szl(x，y)-zc(x，y)dxdy. (1)。
3. the depth imaging-based vinasse volume measurement method of claim 1, wherein in step S5, the surface model of the vinasse stack is defined as zl(x, y), the surface model of the inner bottom surface of the container being defined as zc(x, y), the image plane of the depth camera forming an offset angle θ with the inner bottom surface of the container, the volume V of the heap of vinasselComprises the following steps:
Vl＝cosθ∫∫szl(x，y)-zc(x，y)dxdy. (2)。
4. the depth imaging-based vinasse volume measurement method of claim 1, wherein the container is a tray or a bucket.
5. The method of measuring volume of vinasse based on depth imaging of claim 1, wherein the container is a moving bucket, and a weight collection device is arranged below the moving bucket.
6. The depth imaging-based vinasse volume measurement method of claim 1, wherein the resolution of the depth camera is VGA (640 x 480).
7. The depth imaging-based vinasse volume measurement method of claim 1, wherein the relative error of the depth imaging-based vinasse volume measurement method from an actual accurate value is less than 2%.
8. The depth imaging-based vinasse volume measurement method of claim 1, further comprising a step S6: calculating the average height of the bottom of the container, thereby calculating an average height criterion.
9. The depth imaging-based vinasse volume measurement method of claim 8, wherein a threshold T for determining whether the container is full of vinasse is determinedcComprises the following steps:
Figure FDA0003196350590000021
wherein the surface model of the vinasse pile is defined as zl(x, y) the image plane of the depth camera forms an offset angle θ, z with the inner bottom surface of the containercN is the total number of points for which the second data point cloud satisfies l (x, y) is 0.
10. The depth imaging-based vinasse volume measurement method of claim 9, wherein the Tc is 0.95 m.
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