Laser scanning-based online detection method for thickness deviation of thermal paper

Abstract

The application discloses a laser scanning-based thermal paper thickness deviation online detection method and relates to the technical field of thermal paper thickness deviation detection, and comprises the following steps: constructing a laser scanning scene; obtaining a real-time detection thickness of the thermal paper based on the laser scanning scene; obtaining a first thickness threshold value and a second thickness threshold value based on a first number of normal thickness thermal papers; obtaining an abnormal thickness point by taking the real-time detection thickness, the first thickness threshold value and the second thickness threshold value; constructing a real-time detection ratio based on the abnormal thickness; obtaining a detection ratio threshold value based on a second number of abnormal thermal papers with coating heads; and judging whether the thermal paper thickness unevenness is caused by the coating head based on the real-time detection ratio and the detection ratio threshold value. The application is used to solve the problem that the existing thermal paper thickness deviation detection technology cannot further judge whether the thickness deviation is caused by the abnormal coating head, thereby causing the waste of cost and subsequent debugging time.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of thermal paper thickness deviation detection, in particular to a thermal paper thickness deviation online detection method based on laser scanning. BACKGROUND

[0002] As a printing medium widely used in commercial, medical, logistics and other fields, the thickness uniformity of thermal paper is one of its key physical indicators, which directly affects the subsequent processing suitability, printing clarity and running reliability in high-speed printing equipment; excessive thickness deviation may cause paper jam, uneven printing density, and even affect the contact heat transfer performance of the thermal element, resulting in poor development; the thickness uniformity of thermal paper has a crucial influence on printing quality, storage time and performance; therefore, it is necessary to detect the thickness deviation of thermal paper.

[0003] If the thickness deviation of thermal paper is caused by the production equipment of thermal paper, it is easy to evolve into a large-scale quality accident and cost loss if it cannot be found in time; if the thickness deviation of thermal paper is caused by the production equipment of thermal paper, it can be found in time, and the stability of production and the consistency of products can be ensured by reminding engineers to intervene and adjust; the main production equipment parts that can easily cause thickness deviation of thermal paper are coating heads, and subtle abnormalities of coating heads can cause thickness deviation of thermal paper produced; however, the existing thickness deviation detection of thermal paper only judges whether the thickness deviation occurs, and cannot further analyze whether the thickness deviation is caused by the coating head, resulting in waste of cost and debugging time; that is, the existing thickness deviation detection technology of thermal paper cannot further determine whether the thickness deviation is caused by the abnormality of the coating head, resulting in waste of cost and subsequent debugging time. SUMMARY

[0004] The present application aims to solve at least one of the technical problems in the prior art, by constructing a laser scanning scene; obtaining the real-time detection thickness of the thermal paper based on the laser scanning scene; obtaining the first thickness threshold and the second thickness threshold based on the first number of normal thickness thermal papers; obtaining the abnormal thickness point based on the real-time detection thickness, the first thickness threshold and the second thickness threshold; constructing the real-time detection ratio based on the abnormal thickness; obtaining the detection ratio threshold based on the second number of thermal papers with abnormal coating heads; determining whether the thickness deviation of the thermal paper is caused by the abnormality of the coating head based on the real-time detection ratio and the detection ratio threshold; to solve the problem that the existing thickness deviation detection technology of thermal paper cannot further determine whether the thickness deviation is caused by the abnormality of the coating head, resulting in waste of cost and subsequent debugging time.

[0005] To achieve the above purpose, the present application provides a thermal paper thickness deviation online detection method based on laser scanning, which comprises the following steps:

[0006] constructing a laser scanning scene;

[0007] acquiring a real-time detection thickness of the thermal paper based on the laser scanning scene;

[0008] acquiring a first thickness threshold and a second thickness threshold based on a first number of thermal papers of normal thickness;

[0009] acquiring an abnormal thickness point based on the real-time detection thickness, the first thickness threshold, and the second thickness threshold;

[0010] constructing a real-time detection ratio based on the abnormal thickness;

[0011] acquiring a detection ratio threshold based on a second number of thermal papers of abnormal coating head;

[0012] judging whether the thermal paper thickness unevenness is caused by the coating head based on the real-time detection ratio and the detection ratio threshold.

[0013] Further, the constructing the laser scanning scene comprises the following sub-steps:

[0014] constructing a horizontal plane as a first plane; placing the thermal paper horizontally on the first plane; acquiring a plane parallel to the first plane at a first distance above the first plane, marked as a second plane; acquiring a plane parallel to the first plane at a first distance below the first plane, marked as a third plane;

[0015] installing a laser sensor on the second plane, marked as a first sensor;

[0016] installing a laser sensor on the third plane, marked as a second sensor.

[0017] Further, the acquiring the real-time detection thickness of the thermal paper based on the laser scanning scene comprises the following sub-steps:

[0018] moving the first sensor on the second plane to acquire a vertical distance from the first sensor to the thermal paper, marked as a first sensor distance;

[0019] moving the second sensor on the third plane to acquire a vertical distance from the second sensor to the thermal paper, marked as a second sensor distance;

[0020] acquiring a detection thickness of the thermal paper at a position on the first plane as Hj=2×Dj1-C1-C2; wherein Hj is the detection thickness of the thermal paper at a position on the first plane, Dj1 is the first distance, C1 is the first sensor distance at the same position of the thermal paper on the first plane, and C2 is the second sensor distance at the same position of the thermal paper on the first plane.

[0021] Further, the obtaining the first thickness threshold and the second thickness threshold based on the first number of normal thicknesses of the thermal paper comprises the following sub-steps:

[0022] The first number of normal thicknesses of the thermal paper are obtained based on the laser scanning scene to obtain real-time detection thicknesses, which are marked as historical detection thicknesses;

[0023] The range of the historical detection thicknesses is obtained; and the range of the historical detection thicknesses is divided into a third number of equal interval intervals, which are marked as thickness division intervals;

[0024] The frequency of the historical detection thicknesses in each thickness division interval is obtained, which is marked as a thickness division frequency;

[0025] The thickness frequency threshold is calculated as A1 = b1 × (E1 ÷ F1); wherein A1 is the thickness frequency threshold, b1 is the thickness frequency ratio, E1 is the sum of all thickness division frequencies, and F1 is the third number;

[0026] The thickness division frequency less than the thickness frequency threshold is marked as a thickness abnormal frequency.

[0027] Further, the obtaining the first thickness threshold and the second thickness threshold based on the first number of normal thicknesses of the thermal paper comprises the following sub-steps:

[0028] The minimum value and the maximum value of each thickness division interval are obtained, which are marked as a first interval value and a second interval value, respectively;

[0029] The thickness division frequencies are sorted from left to right according to the corresponding first interval values from small to large;

[0030] If the leftmost thickness division frequency is a thickness abnormal frequency, the thickness abnormal frequency is deleted until the leftmost thickness division frequency is not a thickness abnormal frequency; then the first interval value corresponding to the leftmost thickness division frequency is obtained, which is marked as the first thickness threshold;

[0031] If the rightmost thickness division frequency is a thickness abnormal frequency, the thickness abnormal frequency is deleted until the rightmost thickness division frequency is not a thickness abnormal frequency; then the second interval value corresponding to the rightmost thickness division frequency is obtained, which is marked as the second thickness threshold.

[0032] Further, the obtaining the abnormal thickness point based on the real-time detection thickness, the first thickness threshold and the second thickness threshold comprises the following sub-steps:

[0033] If the real-time detection thickness is between the first thickness threshold and the second thickness threshold, it indicates that the thickness of the thermal paper is normal; if the real-time detection thickness is less than the first thickness threshold or greater than the second thickness threshold, the position point of the real-time detection thickness on the first plane is obtained, which is marked as the abnormal thickness point.

[0034] Further, the real-time detection ratio based on the abnormal thickness is constructed by the following sub-steps:

[0035] In the first plane, the angle between the moving direction of the thermal paper during production and the X-axis is 0, a plane rectangular coordinate system is established, which is marked as a two-dimensional analysis coordinate system; the abnormal thickness points are plotted in the two-dimensional analysis coordinate system;

[0036] The minimum and maximum values of the abscissa of all the abnormal thickness points are obtained, which are marked as a first abscissa range value and a second abscissa range value;

[0037] The minimum and maximum values of the ordinate of all the abnormal thickness points are obtained, which are marked as a first ordinate range value and a second ordinate range value;

[0038] The first abscissa range value and the first ordinate range value are taken as the abscissa and the ordinate of a first connecting coordinate point respectively; the second abscissa range value and the first ordinate range value are taken as the abscissa and the ordinate of a second connecting coordinate point respectively; the second abscissa range value and the second ordinate range value are taken as the abscissa and the ordinate of a third connecting coordinate point respectively; the first abscissa range value and the second ordinate range value are taken as the abscissa and the ordinate of a fourth connecting coordinate point respectively;

[0039] The first connecting coordinate point and the second connecting coordinate point are connected to obtain a first connecting line segment; the second connecting coordinate point and the third connecting coordinate point are connected to obtain a second connecting line segment; the third connecting coordinate point and the fourth connecting coordinate point are connected to obtain a third connecting line segment; the fourth connecting coordinate point and the first connecting coordinate point are connected to obtain a fourth connecting line segment;

[0040] The rectangle area formed by the first connecting line segment, the second connecting line segment, the third connecting line segment and the fourth connecting line segment is marked as a target rectangle;

[0041] The ratio of the length to the width of the target rectangle is obtained, which is marked as a real-time detection ratio.

[0042] Further, the detection ratio threshold value is obtained based on the second number of abnormal thermal papers of the coating heads, by the following sub-steps:

[0043] The real-time detection ratios of the second number of abnormal thermal papers of the coating heads are obtained, which are marked as historical detection ratios;

[0044] The range of the historical detection ratios is obtained; the range of the historical detection ratios is divided into a fourth number of equal interval intervals, which are marked as detection ratio division intervals;

[0045] The frequency of the historical detection ratios in each detection ratio division interval is obtained, which is marked as a detection ratio division frequency;

[0046] The detection ratio frequency threshold is calculated as: A2=b2*(E2 / F2), wherein A2 is the detection ratio frequency threshold, b2 is the detection ratio proportion, E2 is the sum of all detection ratio frequency, and F2 is the fourth quantity;

[0047] The detection ratio frequency less than the detection ratio frequency threshold is marked as a detection ratio abnormal frequency.

[0048] Further, the detection ratio threshold based on the second quantity of abnormal coating heads of the thermal paper further comprises the following sub-steps:

[0049] The minimum value and the maximum value of each detection ratio interval are obtained, and are marked as a third interval value and a fourth interval value, respectively.

[0050] The detection ratio frequency is sorted from left to right according to the corresponding third interval value from small to large;

[0051] If the leftmost detection ratio frequency is a detection ratio abnormal frequency, the detection ratio abnormal frequency is deleted until the leftmost detection ratio frequency is not a detection ratio abnormal frequency; then the third interval value corresponding to the leftmost detection ratio frequency is obtained and is marked as a detection ratio threshold.

[0052] Further, the determination of whether the thermal paper thickness unevenness is caused by the coating head based on the real-time detection ratio value and the detection ratio threshold comprises the following sub-steps:

[0053] It is determined whether the real-time detection ratio value is greater than or equal to the detection ratio threshold, and if so, the thermal paper thickness defect is identified as a defect caused by the abnormal coating head.

[0054] The present application has the following advantages: the present application constructs a laser scanning scene, obtains a real-time detection thickness of the thermal paper based on the laser scanning scene, obtains a first thickness threshold and a second thickness threshold based on a first quantity of thermal papers with normal thickness, obtains an abnormal thickness point based on the real-time detection thickness, the first thickness threshold and the second thickness threshold, constructs a real-time detection ratio value based on the abnormal thickness, obtains a detection ratio threshold based on a second quantity of abnormal thermal papers of the coating head, and determines whether the thermal paper thickness unevenness is caused by the coating head based on the real-time detection ratio value and the detection ratio threshold, which can further determine whether the thickness deviation is caused by the abnormal coating head, and reduces the cost and subsequent debugging time.

[0055] The present application constructs a real-time detection ratio value based on the abnormal thickness, which can construct the real-time detection ratio value based on the defect caused by the coating head, further determine whether the thickness deviation is caused by the abnormal coating head based on the real-time detection ratio value, and reduce the cost and subsequent debugging time. BRIEF DESCRIPTION OF DRAWINGS

[0056] Figure 1A flow chart of steps of the method of the present application;

[0057] Figure 2 A schematic diagram of the abnormal thickness point of the present application;

[0058] Figure 3 A drawing schematic diagram of the target rectangle of the present application;

[0059] Figure 4 A schematic diagram of the target rectangle of the present application; DETAILED DESCRIPTION

[0060] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0061] Embodiment 1, please refer to Figure 1 The present application provides a laser scanning-based thermal paper thickness deviation online detection method, which comprises the following steps:

[0062] Step S1, constructing a laser scanning scene; step S1 comprises the following sub-steps:

[0063] Step S101, constructing a horizontal plane as a first plane; placing the thermal paper horizontally at the first plane; acquiring a plane parallel to the first plane at a first distance above the first plane, and marking it as a second plane; acquiring a plane parallel to the first plane at a first distance below the first plane, and marking it as a third plane; the first distance is set to facilitate subsequent calculation of the detection thickness, so the first distance is set to a fixed value, for example, the first distance is 100000 μm; the unit is μm to facilitate the representation of the detection thickness;

[0064] Step S102, installing a laser sensor on the second plane, and marking it as a first sensor;

[0065] Step S103, installing a laser sensor on the third plane, and marking it as a second sensor; making the first sensor and the second sensor move at the first sensor and the second sensor, respectively, so that the distance from the first sensor and the second sensor to the first plane is fixed as the first distance.

[0066] Step S2, acquiring the real-time detection thickness of the thermal paper based on the laser scanning scene; step S2 comprises the following sub-steps:

[0067] Step S201, moving the first sensor on the second plane, obtaining the vertical distance from the first sensor to the thermal paper, marked as the first sensor distance;

[0068] Step S202, moving the second sensor on the third plane, obtaining the vertical distance from the second sensor to the thermal paper, marked as the second sensor distance;

[0069] Step S203, obtaining the detection thickness of the thermal paper at a position on the first plane: Hj=2×Dj1-C1-C2; wherein Hj is the detection thickness of the thermal paper at a position on the first plane, Dj1 is the first distance, C1 is the first sensor distance at the same position of the thermal paper on the first plane; C2 is the second sensor distance at the same position of the thermal paper on the first plane;

[0070] In practical application, it is necessary to pay attention to the detection of specific specifications of the thermal paper in sequence, for example, the first sensor distance of the thermal paper of 1m×1m at a position on the first plane is 99982μm; the second sensor distance of the thermal paper at the same position on the first plane is 99986μm; and the detection thickness of this position is calculated as: Hj=2×100000-99982-99986=32μm.

[0071] Step S3, obtaining the first thickness threshold and the second thickness threshold based on the first number of thermal papers of normal thickness; step S3 includes the following sub-steps:

[0072] Step S301, obtaining the real-time detection thickness of the first number of thermal papers of normal thickness based on the laser scanning scene, marked as the historical detection thickness; the obtaining process of the historical detection thickness is the same as the obtaining process of the real-time detection thickness, which will not be repeated here; in order to obtain the range of the historical detection thickness, the first number is set to be larger, so that the range of the historical detection thickness obtained is more accurate, for example, the first number is set to 1000; the specification of the thermal paper of normal thickness is 1m×1m thermal paper;

[0073] Step S302, obtaining the range of the historical detection thickness; dividing the range of the historical detection thickness into a third number of equal intervals, marked as the thickness division interval; the thickness division interval is to observe the distribution of the historical detection thickness, so the third number should not be too large or too small, for example, the third number is 12;

[0074] Step S303, obtaining the frequency of the historical detection thickness in each thickness division interval, marked as the thickness division frequency;

[0075] Step S304, the thickness frequency threshold is calculated as: A1 = b1 x (E1 ÷ F1); wherein A1 is the thickness frequency threshold, b1 is the thickness frequency ratio, E1 is the sum of all thickness division frequencies, and F1 is the third number; the thickness frequency threshold is used to obtain smaller thickness division frequencies, and therefore b1 is set to be smaller; for example, b1 is 0.1;

[0076] Step S305, the thickness division frequency smaller than the thickness frequency threshold is marked as the thickness abnormal frequency.

[0077] Step S306, the minimum value and the maximum value of each thickness division interval are obtained, and are marked as the first interval value and the second interval value, respectively;

[0078] Step S307, the thickness division frequencies are sorted from left to right according to the corresponding first interval values from small to large.

[0079] Step S308, if the leftmost thickness division frequency is the thickness abnormal frequency, the thickness abnormal frequency is deleted until the leftmost thickness division frequency is not the thickness abnormal frequency; then the first interval value corresponding to the leftmost thickness division frequency is obtained and is marked as the first thickness threshold.

[0080] Step S309, if the rightmost thickness division frequency is the thickness abnormal frequency, the thickness abnormal frequency is deleted until the rightmost thickness division frequency is not the thickness abnormal frequency; then the second interval value corresponding to the rightmost thickness division frequency is obtained and is marked as the second thickness threshold; the first thickness threshold and the second thickness threshold are used to exclude the historical detection thicknesses that are too small or too large and have small frequencies, so as to obtain a more accurate range of historical detection thicknesses.

[0081] In actual application, for example, the range of historical detection thicknesses is 68 μm to 92 μm; the range of historical detection thicknesses is divided into 12 thickness division intervals, which are 68 μm to 70 μm, 70 μm to 72 μm,..., 90 μm to 92 μm; the sum of all thickness division frequencies is 1000; the thickness frequency threshold is calculated as: A1 = 0.1 x (1000 ÷ 12) = 8.3; the calculation result is rounded to one decimal place; the thickness division frequency smaller than 8.3 is marked as the thickness abnormal frequency; the thickness division frequencies are sorted from left to right according to the corresponding first interval values from small to large as: 6, 23,..., 42, 8; the sorted thickness division frequencies after deletion are: 23,..., 42; the first interval value corresponding to the leftmost 23 is 70 μm, and therefore the first thickness threshold is 70 μm; the second interval value corresponding to the rightmost 42 is 90 μm, and therefore the second thickness threshold is 90 μm.

[0082] Step S4, acquiring an abnormal thickness point based on the real-time detected thickness, the first thickness threshold value and the second thickness threshold value; step S4 comprises the following sub-steps:

[0083] Step S401, if the real-time detected thickness is between the first thickness threshold value and the second thickness threshold value, it indicates that the thickness of the thermal paper is normal; if the real-time detected thickness is less than the first thickness threshold value or greater than the second thickness threshold value, a position point of the real-time detected thickness on the first plane is acquired and marked as an abnormal thickness point; the abnormal thickness point is a point where the thermal paper is too thick or too thin;

[0084] In practical application, if the real-time detected thickness is between 70 μm and 90 μm, it indicates that the thickness of the thermal paper is normal; if the real-time detected thickness is less than 70 μm or greater than 90 μm, a position point of the real-time detected thickness on the first plane is acquired and marked as an abnormal thickness point; for example, if the real-time detected thickness is 32 μm, the real-time detected thickness is less than 70 μm, and the position point of the real-time detected thickness of 32 μm on the first plane is marked as an abnormal thickness point.

[0085] Step S5, constructing a real-time detected ratio based on the abnormal thickness; step S5 comprises the following sub-steps:

[0086] Step S501, on the first plane, establishing a plane rectangular coordinate system with the angle between the moving direction of the thermal paper during production and the X axis being 0, and marking it as a two-dimensional analysis coordinate system; drawing the abnormal thickness points in the two-dimensional analysis coordinate system; the moving direction of the thermal paper during production is the direction in which the coating head passes first, i.e. the moving direction of the thermal paper is the direction in which the coating head passes first; in order to facilitate subsequent acquisition of a more representative real-time detected ratio;

[0087] In practical application, please refer to FIG. 2, which shows the drawn abnormal thickness points. Figure 2

[0088] Step S502, acquiring the minimum value and the maximum value of the abscissa of all the abnormal thickness points, and marking them as a first abscissa range value and a second abscissa range value;

[0089] Step S503, acquiring the minimum value and the maximum value of the ordinate of all the abnormal thickness points, and marking them as a first ordinate range value and a second ordinate range value;

[0090] Step S504, taking the first abscissa range value and the first ordinate range value as the abscissa and the ordinate of a first connecting coordinate point respectively; taking the second abscissa range value and the first ordinate range value as the abscissa and the ordinate of a second connecting coordinate point respectively; taking the second abscissa range value and the second ordinate range value as the abscissa and the ordinate of a third connecting coordinate point respectively; and taking the first abscissa range value and the second ordinate range value as the abscissa and the ordinate of a fourth connecting coordinate point respectively;

[0091] ​Step S505, connecting the first connection coordinate point and the second connection coordinate point to obtain a first connection line segment; connecting the second connection coordinate point and the third connection coordinate point to obtain a second connection line segment; connecting the third connection coordinate point and the fourth connection coordinate point to obtain a third connection line segment; and connecting the fourth connection coordinate point and the first connection coordinate point to obtain a fourth connection line segment;

[0092] Step S506, the rectangular region formed by the first connection line segment, the second connection line segment, the third connection line segment and the fourth connection line segment is marked as a target rectangle; and a rectangular range region of the target rectangle as an abnormal thickness point is obtained;

[0093] Step S507, a ratio of the length and the width of the target rectangle is obtained and marked as a real-time detection ratio; because the placement direction of the thermal paper is limited, if the coating head has a problem, the thickness of the produced thermal paper at a specific position will be abnormal; even if the target rectangle is long, that is, the real-time detection ratio is large; if not, the defect position is randomly distributed, so that the real-time detection ratio is small, and most of the real-time detection ratios are close to 1; therefore, whether the coating head has an abnormality can be determined by the real-time detection ratio;

[0094] In practical applications, please refer to Figure 3 and Figure 4 , the target rectangle is drawn; the real-time detection ratio is obtained as 15.26; and the obtained real-time detection ratio is kept to two decimal places.

[0095] Step S6, a detection ratio threshold value is obtained based on the second number of thermal papers with abnormal coating heads; step S6 includes the following sub-steps:

[0096] Step S601, real-time detection ratios of the second number of thermal papers with abnormal coating heads are obtained and marked as historical detection ratios; the second number is set to be large in order to obtain the distribution range of the historical detection ratios, so that the more accurate the distribution range of the obtained historical detection ratios is, for example, the second number is 1000;

[0097] Step S602, a range of the historical detection ratios is obtained; the range of the historical detection ratios is divided into a fourth number of equal intervals, which are marked as detection ratio division intervals; the fourth number is set not to be too large or too small in order to observe the distribution of the historical detection ratios, for example, the fourth number is 21;

[0098] Step S603, a frequency of the historical detection ratios in each detection ratio division interval is obtained and marked as a detection ratio division frequency;

[0099] Step S604, the detection ratio frequency threshold is calculated as: A2=b2×(E2÷F2); wherein A2 is the detection ratio frequency threshold, b2 is the detection ratio frequency ratio, E2 is the sum of all detection ratio division frequencies, and F2 is the fourth quantity; the detection ratio frequency threshold is used to distinguish the detection ratio division frequencies, so b2 is set to be small; for example, b2 is 0.1;

[0100] Step S605, the detection ratio division frequencies less than the detection ratio frequency threshold are marked as detection ratio abnormal frequencies.

[0101] Step S606, the minimum value and the maximum value of each detection ratio division interval are obtained, and are marked as the third interval value and the fourth interval value respectively;

[0102] Step S607, the detection ratio division frequencies are sorted from left to right according to the corresponding third interval value from small to large;

[0103] Step S608, if the leftmost detection ratio division frequency is a detection ratio abnormal frequency, the detection ratio abnormal frequency is deleted until the leftmost detection ratio division frequency is not a detection ratio abnormal frequency; then the third interval value corresponding to the leftmost detection ratio division frequency is obtained and is marked as the detection ratio threshold; the historical detection ratio values that are too small and have small frequencies are excluded through the detection ratio threshold, and the range of more accurate historical detection ratio values is obtained;

[0104] In actual application, for example, the range of historical detection ratio values is 8 to 50; 8 to 50 is divided into the 21 equal interval detection ratio division intervals, which are 8 to 10, 10 to 12,..., 48 to 50 respectively; the sum of all detection ratio division frequencies is 1000; the detection ratio frequency threshold is calculated as: A2=0.1×(1000÷21)=4.8, and the calculation result is rounded to one decimal place; the detection ratio division frequencies less than 4.8 are marked as detection ratio abnormal frequencies; the detection ratio division frequencies are sorted from left to right according to the corresponding third interval value from small to large as: 3, 8,..., 12, 4; the sorted detection ratio division frequencies after deletion are: 8,..., 12; the third interval value corresponding to the leftmost 23 is 10, so the first thickness threshold is 10.

[0105] Step S7, whether the thermal paper thickness unevenness caused by the coating head is judged based on the real-time detection ratio value and the detection ratio threshold; step S7 includes the following sub-steps:

[0106] Step S701, whether the real-time detection ratio value is greater than or equal to the detection ratio threshold is judged; if yes, the thermal paper thickness defect is identified as a defect caused by the coating head abnormality; because the defect caused by the coating head is a long strip, the greater the real-time detection ratio value is, the detection ratio threshold is the minimum value of the real-time detection ratio value of the defect caused by the coating head abnormality;

[0107] In practical application, the real-time detection ratio 15.26 is greater than the detection ratio threshold 10, and thus the thermal paper thickness defect is identified as a defect caused by the coating head abnormality.

[0108] In an embodiment, the electronic device can include a processor, a communication interface, a memory, and a communication bus. The processor, the communication interface, and the memory can communicate with each other through the communication bus. The memory can store computer readable instructions. The processor can call the instructions in the memory. When the computer readable instructions are executed by the processor, the steps in the method for online detection of thermal paper thickness deviation based on laser scanning can be executed to achieve the following functions: constructing a laser scanning scene; obtaining a real-time detection thickness of the thermal paper based on the laser scanning scene; obtaining a first thickness threshold and a second thickness threshold based on a first number of thermal papers with normal thickness; obtaining an abnormal thickness point based on the real-time detection thickness, the first thickness threshold, and the second thickness threshold; constructing a real-time detection ratio based on the abnormal thickness; obtaining a detection ratio threshold based on a second number of thermal papers with coating head abnormality; and determining whether the thermal paper thickness deviation is caused by the coating head based on the real-time detection ratio and the detection ratio threshold.

[0109] In addition, the logic instructions in the memory described above can be implemented in the form of a software function unit and sold or used as an independent product, and can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various program code storage media.

[0110] In embodiment 3, the application further provides a computer program product, which comprises a computer program stored on a computer readable storage medium, and the computer program comprises program instructions, when the program instructions are executed by a computer, the computer can execute the laser scanning based thermal paper thickness deviation online detection method provided by each method, and the method comprises: constructing a laser scanning scene; obtaining a real-time detection thickness of the thermal paper based on the laser scanning scene; obtaining a first thickness threshold and a second thickness threshold based on a first number of thermal papers with normal thickness; obtaining an abnormal thickness point based on the real-time detection thickness, the first thickness threshold and the second thickness threshold; constructing a real-time detection ratio based on the abnormal thickness; obtaining a detection ratio threshold based on a second number of thermal papers with abnormal coating heads; and determining whether the thermal paper thickness deviation is caused by the coating head based on the real-time detection ratio and the detection ratio threshold.

[0111] In embodiment 4, the application further provides a computer readable storage medium, and the application provides a storage medium, which stores a computer program, and when the computer program is executed by a processor, the steps in the laser scanning based thermal paper thickness deviation online detection method are run to realize the following functions: constructing a laser scanning scene; obtaining a real-time detection thickness of the thermal paper based on the laser scanning scene; obtaining a first thickness threshold and a second thickness threshold based on a first number of thermal papers with normal thickness; obtaining an abnormal thickness point based on the real-time detection thickness, the first thickness threshold and the second thickness threshold; constructing a real-time detection ratio based on the abnormal thickness; obtaining a detection ratio threshold based on a second number of thermal papers with abnormal coating heads; and determining whether the thermal paper thickness deviation is caused by the coating head based on the real-time detection ratio and the detection ratio threshold.

[0112] Through the description of the above embodiments, the embodiments of the application can be provided as a method, a system or a computer program product. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the method described in each embodiment or some parts of the embodiment.

[0113] In the embodiments of the present application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are only illustrative, for example, the division of modules or units is only a logical function division, and other division manners can be used in actual implementation, for example, a plurality of modules or units can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be through some communication interface, the indirect coupling or communication connection between the system, the module and the unit can be electrical, mechanical or other forms.

[0114] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for on-line detection of thermal paper thickness deviation based on laser scanning, characterized in that, The method comprises the following steps: Constructing a laser scanning scene; Obtaining a real-time detection thickness of the thermal paper based on the laser scanning scene; Obtaining a first thickness threshold and a second thickness threshold based on a first number of thermal papers with normal thickness; Obtaining an abnormal thickness point based on the real-time detection thickness, the first thickness threshold and the second thickness threshold; Constructing a real-time detection ratio based on the abnormal thickness; Obtaining a detection ratio threshold based on a second number of thermal papers with abnormal coating heads; Judging whether the thermal paper thickness unevenness is caused by the coating head based on the real-time detection ratio and the detection ratio threshold; The step of constructing a real-time detection ratio based on the abnormal thickness comprises the following sub-steps: On the first plane, the moving direction of the thermal paper during production is 0 with the X-axis, a plane rectangular coordinate system is established, and is marked as a two-dimensional analysis coordinate system; the abnormal thickness point is plotted in the two-dimensional analysis coordinate system; Obtaining the minimum and maximum values of the horizontal coordinates of all abnormal thickness points, and marking them as a first horizontal range value and a second horizontal range value; Obtaining the minimum and maximum values of the vertical coordinates of all abnormal thickness points, and marking them as a first vertical range value and a second vertical range value; Taking the first horizontal range value and the first vertical range value as the horizontal coordinate and the vertical coordinate of the first connection coordinate point respectively; Taking the second horizontal range value and the first vertical range value as the horizontal coordinate and the vertical coordinate of the second connection coordinate point respectively; taking the second horizontal range value and the second vertical range value as the horizontal coordinate and the vertical coordinate of the third connection coordinate point respectively; and taking the first horizontal range value and the second vertical range value as the horizontal coordinate and the vertical coordinate of the fourth connection coordinate point respectively; Connecting the first connection coordinate point and the second connection coordinate point to obtain a first connection line segment; Connecting the second connection coordinate point and the third connection coordinate point to obtain a second connection line segment; Connecting the third connection coordinate point and the fourth connection coordinate point to obtain a third connection line segment; and connecting the fourth connection coordinate point and the first connection coordinate point to obtain a fourth connection line segment; The rectangle region formed by the first connection line segment, the second connection line segment, the third connection line segment and the fourth connection line segment is marked as a target rectangle; Obtaining the ratio of the length and the width of the target rectangle, and marking it as a real-time detection ratio.

2. The online detection method of thickness deviation of thermal paper based on laser scanning according to claim 1, characterized in that, The step of constructing a laser scanning scene comprises the following sub-steps: Constructing a horizontal plane, which is marked as a first plane; placing the thermal paper horizontally on the first plane; obtaining a plane parallel to the first plane at a first distance above the first plane, which is marked as a second plane; and obtaining a plane parallel to the first plane at a first distance below the first plane, which is marked as a third plane; Installing a laser sensor on the second plane, which is marked as a first sensor; Installing a laser sensor on the third plane, which is marked as a second sensor.

3. The method for online detection of thermal paper thickness deviation based on laser scanning according to claim 2, characterized in that, The step of obtaining a real-time detection thickness of the thermal paper based on the laser scanning scene comprises the following sub-steps: Making the first sensor move on the second plane to obtain a vertical distance from the first sensor to the thermal paper, which is marked as a first sensor distance; Making the second sensor move on the third plane to obtain a vertical distance from the second sensor to the thermal paper, which is marked as a second sensor distance; The detection thickness of the thermal paper at a position in the first plane is Hj=2×Dj1-C1-C2; wherein Hj is the detection thickness of the thermal paper at a position in the first plane, Dj1 is the first distance, C1 is the first sensor distance at the same position of the thermal paper in the first plane, and C2 is the second sensor distance at the same position of the thermal paper in the first plane.

4. The online laser scanning based thermal paper thickness deviation detection method according to claim 3, wherein, The first thickness threshold and the second thickness threshold based on the first number of thermal papers with normal thicknesses include the following sub-steps: The real-time detection thickness of the first number of thermal papers with normal thicknesses is obtained based on laser scanning of a scene, and is marked as a historical detection thickness; The range of the historical detection thickness is obtained; the range of the historical detection thickness is divided into a third number of equal intervals, and is marked as a thickness division interval; The frequency of the historical detection thickness in each thickness division interval is obtained, and is marked as a thickness division frequency; The thickness frequency threshold is calculated as A1=b1×(E1÷F1); wherein A1 is the thickness frequency threshold, b1 is a thickness frequency ratio, E1 is the sum of all thickness division frequencies, and F1 is the third number; The thickness division frequency less than the thickness frequency threshold is marked as an abnormal thickness frequency.

5. The method for online detection of thermal paper thickness deviation based on laser scanning according to claim 4, characterized in that, The first thickness threshold and the second thickness threshold based on the first number of thermal papers with normal thicknesses also include the following sub-steps: The minimum value and the maximum value of each thickness division interval are obtained, and are marked as a first interval value and a second interval value, respectively; The thickness division frequencies are sorted from left to right in ascending order according to the corresponding first interval values; If the leftmost thickness division frequency is an abnormal thickness frequency, the abnormal thickness frequency is deleted until the leftmost thickness division frequency is not an abnormal thickness frequency; then the first interval value corresponding to the leftmost thickness division frequency is obtained, and is marked as the first thickness threshold; If the rightmost thickness division frequency is an abnormal thickness frequency, the abnormal thickness frequency is deleted until the rightmost thickness division frequency is not an abnormal thickness frequency; then the second interval value corresponding to the rightmost thickness division frequency is obtained, and is marked as the second thickness threshold.

6. The method for online detection of thermal paper thickness deviation based on laser scanning according to claim 5, characterized in that, The abnormal thickness point based on the real-time detection thickness, the first thickness threshold, and the second thickness threshold includes the following sub-steps: If the real-time detection thickness is between the first thickness threshold and the second thickness threshold, it indicates that the thickness of the thermal paper is normal; if the real-time detection thickness is less than the first thickness threshold or greater than the second thickness threshold, the position point of the real-time detection thickness on the first plane is obtained, and is marked as an abnormal thickness point.

7. The laser scanning based online detection method of thermal paper thickness deviation according to claim 6, characterized in that, The detection ratio threshold based on the second number of thermal papers with abnormal coating heads includes the following sub-steps: The real-time detection ratio of the second number of thermal papers with abnormal coating heads is obtained, and is marked as a historical detection ratio; The range of the historical detection ratio is obtained; the range of the historical detection ratio is divided into a fourth number of equal intervals, and is marked as a detection ratio division interval; The frequency of the historical detection ratio in each detection ratio division interval is obtained, and is marked as a detection ratio division frequency; The detection ratio frequency threshold is calculated as A2=b2×(E2÷F2); wherein A2 is the detection ratio frequency threshold, b2 is a detection ratio frequency ratio, E2 is the sum of all detection ratio division frequencies, and F2 is the fourth number; The detection ratio division frequency less than the detection ratio frequency threshold is marked as an abnormal detection ratio frequency. The detection ratio abnormal frequency is marked as a detection ratio threshold value if the detection ratio is less than the detection ratio frequency threshold value. 8.The laser scanning based online detection method of thermal paper thickness deviation according to claim 7, wherein, The detection ratio threshold value is obtained based on the second number of abnormal coating heads of the thermal paper, and the method comprises the following steps: Obtaining the minimum value and the maximum value of each detection ratio interval, and marking them as a third interval value and a fourth interval value respectively. The detection ratio frequency is sorted from left to right according to the corresponding third interval value from small to large. If the leftmost detection ratio frequency is a detection ratio abnormal frequency, the detection ratio abnormal frequency is deleted until the leftmost detection ratio frequency is not a detection ratio abnormal frequency. Then, the third interval value corresponding to the leftmost detection ratio frequency is obtained and marked as a detection ratio threshold value. 9.The laser scanning based online detection method of thermal paper thickness deviation according to claim 8, wherein, Based on the real-time detection ratio value and the detection ratio threshold value, it is determined whether the thermal paper thickness unevenness is caused by the coating head, and the method comprises the following steps: If the real-time detection ratio value is greater than or equal to the detection ratio threshold value, the thermal paper thickness defect is determined to be caused by the abnormal coating head.

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