Measurement device, measurement method, and measurement program

Abstract

To improve thickness or basis weight measurement accuracy.SOLUTION: A measurement device 10 provided herein is configured to collect from a detection device 20 a detection profile including multiple detection values related to thickness or basis weight of an electrode sheet S to be delivered, smooth the multiple detection values included in the detection profile in a CD direction perpendicular to an MD direction of the electrode sheet S using a smoothing filter, and output a first smoothed profile.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a measurement device, a measurement method, and a measurement program. [Background technology]

[0002] Battery electrode sheets (sometimes referred to as "electrode sheets") are made by thinly coating a mixture of active materials and other materials on metal foil and then drying it. In the manufacture of electrode sheets, positive and negative electrode slurries (liquid mixtures) are coated onto the surfaces of aluminum or copper foil. When measuring the coating weight of the slurry in the coating process, a detection device calculates the thickness and basis weight before and after coating, and the coating weight is calculated from the difference between these values. Since the thickness and basis weight calculated by the detection device contain noise due to sensor characteristics, etc., the data must be smoothed. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-048808 Summary of the Invention [Problem to be solved by the invention]

[0004] However, it is difficult to improve the accuracy of thickness or basis weight measurements. For example, with conventional data smoothing, values ​​that indicate data variability, such as standard deviation σ and range R (the difference between the maximum and minimum values), do not decrease until a sufficient amount of data has been accumulated.

[0005] The present invention has been made in view of the above, and aims to provide a measurement device, a measurement method, and a measurement program that can improve the accuracy of measuring thickness or basis weight. [Means for solving the problem]

[0006] A measuring device according to one embodiment of the present invention comprises a collection unit that collects from a detection device a detection profile including multiple detection values ​​relating to the thickness or basis weight of a sheet-like measurement object being sent out, and a first smoothing unit that uses a predetermined filter to smooth the multiple detection values ​​included in the detection profile in a width direction perpendicular to the sending direction of the measurement object, and outputs a first smoothed profile.

[0007] A measurement method according to one embodiment of the present invention involves a computer collecting, from a detection device, a detection profile including multiple detection values ​​relating to the thickness or basis weight of a sheet-like measurement object being fed, and using a predetermined filter, smoothing the multiple detection values ​​included in the detection profile in a width direction perpendicular to the feed direction of the measurement object, thereby outputting a first smoothed profile.

[0008] A measurement program according to one embodiment of the present invention causes a computer to execute a process of collecting, from a detection device, a detection profile including multiple detection values ​​relating to the thickness or basis weight of a sheet-like measurement object being sent out, smoothing the multiple detection values ​​included in the detection profile in a width direction perpendicular to the sending direction of the measurement object using a predetermined filter, and outputting a first smoothed profile. [Effects of the Invention]

[0009] According to the present invention, it is possible to improve the accuracy of measuring thickness or basis weight. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a diagram illustrating an example of the configuration and processing of a coating mass measurement system according to an embodiment; [Figure 2] FIG. 2 is a diagram showing a specific example of a detection device of the coating mass measurement system according to the embodiment. [Figure 3] FIG. 1 is a diagram showing a specific example of a coating line of a coating mass measurement system according to an embodiment. [Figure 4]10A and 10B are diagrams showing specific examples of detection results of a detection device of the coating mass measurement system according to the embodiment. [Figure 5] 5A and 5B are diagrams showing specific examples of detection positions of detection devices in the coating mass measurement system according to the embodiment. [Figure 6] FIG. 2 is a block diagram showing an example of the configuration of each device of the coating mass measurement system according to the embodiment. [Figure 7] FIG. 4 is a diagram illustrating an example of a detection result storage unit of the measurement device according to the embodiment. [Figure 8] 4 is a diagram illustrating an example of a first smoothing result storage unit of the measurement device according to the embodiment. FIG. [Figure 9] 10 is a diagram illustrating an example of a second smoothing result storage unit of the measurement device according to the embodiment. FIG. [Figure 10] 1A to 1C are diagrams illustrating a specific example 1 of each process of the coating mass measurement system according to the embodiment. [Figure 11] FIG. 10 is a diagram showing a specific example 2 of each process of the coating mass measurement system according to the embodiment. [Figure 12] FIG. 10 is a diagram showing a specific example 3 of each process of the coating mass measurement system according to the embodiment. [Figure 13] FIG. 10 is a diagram showing a specific example 4 of each process of the coating mass measurement system according to the embodiment. [Figure 14] FIG. 5 is a diagram showing a specific example 5 of each process of the coating mass measurement system according to the embodiment. [Figure 15] FIG. 6 is a diagram showing a specific example 6 of each process of the coating mass measurement system according to the embodiment. [Figure 16] FIG. 7 is a diagram showing a specific example 7 of each process of the coating mass measurement system according to the embodiment. [Figure 17] FIG. 8 is a diagram showing a specific example 8 of each process of the coating mass measurement system according to the embodiment. [Figure 18] FIG. 9 is a diagram showing a specific example 9 of each process of the coating mass measurement system according to the embodiment. [Figure 19] FIG. 10 is a diagram showing a specific example 10 of each process of the coating mass measurement system according to the embodiment. [Figure 20] 1 is a flowchart showing an example of the overall flow of a coating mass measurement system according to an embodiment. [Figure 21] 10 is a flowchart showing an example of the flow of a detection result management process of the coating mass measurement system according to the embodiment. [Figure 22] 10 is a flowchart showing an example of the flow of a first smoothing result management process of the coating mass measurement system according to the embodiment. [Figure 23] 10 is a flowchart showing an example of the flow of a second smoothing result management process of the coating mass measurement system according to the embodiment. [Figure 24] FIG. 2 is a diagram illustrating an example of a hardware configuration according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] A measurement device, a measurement method, and a measurement program according to an embodiment of the present invention will be described in detail below with reference to the drawings. Note that the present invention is not limited to the embodiment described below.

[0012] The following describes the configuration and processing of the coating weight measurement system 100 according to the embodiment, the configuration and processing of each device of the coating weight measurement system 100, the flow of each process of the coating weight measurement system 100, and the effects of the embodiment.

[0013] 1. Configuration and Processing of Coating Weight Measurement System 100 The configuration and processing of a coating weight measurement system 100 according to an embodiment will be described using Figures 1 to 5. Below, an example of the overall configuration of the coating weight measurement system 100, the basic principles of the coating weight measurement system 100, an example of processing by the coating weight measurement system 100, and the effects of the coating weight measurement system 100 will be described. Note that in the embodiment, a measuring device 10 that measures the thickness and basis weight of an electrode sheet S online will be described as an example, but the measurement target and field of use are not limited thereto.

[0014] (1-1. Example of the overall configuration of the coating weight measurement system 100) An example of the overall configuration of a coating weight measurement system 100 will now be described using FIG. 1. FIG. 1 is a diagram showing an example of the configuration and processing of the coating weight measurement system 100 according to an embodiment. The coating weight measurement system 100 includes a measuring device 10 and a detecting device 20. The measuring device 10 and the detecting device 20 are connected to each other via a predetermined communication network (not shown) so as to be able to communicate with each other via wired or wireless communication. The predetermined communication network can be various communication networks such as the Internet or a dedicated line. The coating weight measurement system 100 may also include a coating device CM (not shown), a drying device DM (not shown), and a sending device (not shown) such as a roller (described below). The measuring device 10, the coating device (not shown), the drying device (not shown), and the sending device (not shown) are connected to each other so as to be able to communicate with each other via analog signals, pulse signals, Ethernet (registered trademark), or the like.

[0015] (1-1-1. Measuring device 10) The measuring device 10 is a device used by an operator W who manages a coating line for the electrode sheet S, and is a device for measuring the coating weight of the electrode sheet S, which is the measurement target. For example, the measuring device 10 is installed in an operator's room or the like that manages the coating line for the electrode sheet S. The coating weight measurement system 100 shown in FIG. 1 may include multiple measuring devices 10. Furthermore, although the example in FIG. 1 shows a case where the measuring device 10 is realized by a desktop PC (Personal Computer), it may also be realized by a notebook PC, a smartphone, a server device, a cloud system, etc.

[0016] (1-1-2.Detection equipment 20) The detection devices 20 (20-1, 20-2, ...) are arranged along the feeding direction of the electrode sheet S and are devices that detect the thickness or basis weight of the electrode sheet S. For example, the detection devices 20 are devices managed by an operator W and installed at the site of the coating line for the electrode sheet S. In the example of FIG. 1, the detection devices 20-1, 20-2, ... are installed from the upstream side (the side closer to the feed start point) to the downstream side (the side farther from the feed start point) of the electrode sheet S. Note that the coating weight measurement system 100 shown in FIG. 1 includes at least two detection devices 20, but may also include one detection device 20, or may include three or more detection devices 20.

[0017] (1-2. Basic Principles of Coating Weight Measurement System 100) 2 to 5, the basic principles of coating weight measurement system 100 will be described. Below, specific examples of detector 20 in coating weight measurement system 100, a specific example of a coating line in coating weight measurement system 100, specific examples of detection results by detector 20 in coating weight measurement system 100, and specific examples of detection positions by detector 20 in coating weight measurement system 100 will be described.

[0018] (1-2-1. Specific examples of the detection device 20) Here, a specific example of the detector 20 of the coating weight measurement system 100 will be described with reference to Fig. 2. Fig. 2 is a diagram showing a specific example of the detector 20 of the coating weight measurement system 100 according to the embodiment. As shown in the example of Fig. 2, the detector 20 has a frame unit 21, a sensor unit 22, and a control unit 23.

[0019] (1-2-1-1. Frame part 21) Frame section 21 is a housing portion of detection device 20, and is disposed perpendicular to the feeding direction of electrode sheet S. Frame section 21 has sensor section 22 (sensor section upper section 22U, sensor section lower section 22D) installed therein.

[0020] (1-2-1-2. Sensor unit 22) The sensor unit 22 is composed of a light source that irradiates measurement light such as X-rays, β rays, or infrared rays, and a sensor head, and reciprocates to scan the emitted electrode sheet S. At this time, the sensor unit 22 moves back and forth within the frame unit 21 perpendicular to the direction of emission of the electrode sheet S, while detecting the transmission intensity of the measurement light irradiated from the light source through the electrode sheet S.

[0021] (1-2-1-3. Control unit 23) The control unit 23 is connected to the sensor unit 22 so as to be able to communicate with it via wire or wirelessly. The control unit 23 determines the thickness [mm] and basis weight [g / m 2] of the electrode sheet S from the transmission intensity of the electrode sheet S detected by the sensor unit 22. 2 The control unit 23 also transmits the transmission intensity of the electrode sheet S detected by the sensor unit 22 to the measurement device 10, and the measurement device 10 calculates the thickness [mm] and basis weight [g / m 2 ] may be calculated.

[0022] (1-2-2. Specific examples of coating lines) Here, a specific example of a coating line of the coating weight measurement system 100 will be described with reference to Fig. 3. Fig. 3 is a diagram showing a specific example of a coating line of the coating weight measurement system 100 according to the embodiment. As shown in the example of Fig. 3, the coating line of the coating weight measurement system 100 has detection devices 20 (20-1, 20-2, 20-3, 20-4, 20-5), coating devices CM (CM-1, CM-2), and drying devices DM (DM-1, DM-2).

[0023] In the example of FIG. 3, first, the electrode sheet S is fed at a constant speed by a feeding device (not shown) such as a roller. Second, the detector 20-1, "detector #1," detects the thickness and basis weight of the electrode sheet S before the first coating (see thin dashed line). Third, the coater CM-1, "coater #1," applies the first coating to the electrode sheet S (see light shading). Fourth, the detector 20-2, "detector #2," detects the thickness and basis weight of the electrode sheet S after the first coating and before drying (see thin solid line). Fifth, the dryer DM-1, "dryer #1," dries the electrode sheet S after the first coating. Sixth, the detector 20-3, "detector #3," detects the thickness and basis weight of the electrode sheet S after the first coating and drying and before the second coating (see thin dashed line). Seventh, "coating device #2", which is coating device CM-2, performs a second coating on the electrode sheet S (see dark shading). Eighth, "detecting device #4", which is detecting device 20-4, detects the thickness and basis weight of the electrode sheet S after the second coating and before drying (see thick solid line). Ninth, "dryer #2", which is drying device DM-2, dries the electrode sheet S after the second coating. Tenth, "detecting device #5", which is detecting device 20-5, detects the thickness and basis weight of the electrode sheet S after the second coating and after drying (see thick dashed line).

[0024] (1-2-3. Specific examples of detection results) Here, a specific example of the detection result of the detection device 20 of the coating mass measurement system 100 will be described with reference to Fig. 4. Fig. 4 is a diagram showing a specific example of the detection result of the detection device 20 of the coating mass measurement system 100 according to the embodiment.

[0025] As shown in the example of FIG. 4, the detection device 20 plots the weight per unit area of ​​the electrode sheet S [g / m 2 The output shows the detection results, with the horizontal axis indicating the basis weight, and the horizontal axis indicating the position where the basis weight was detected. In the example of Figure 4, the basis weight of the electrode sheet S is 162 to 172 g / m2 in the range of 580 to 780 mm in the width direction of the electrode sheet S. 2In this case, the detection device 20 may output the detection result in which the vertical axis indicates "thickness" which indicates the thickness [mm] of the electrode sheet S.

[0026] The detector 20 also obtains the detection results for each half reciprocation as a detection profile P0. Here, the detection profile P0 is made up of a pair of a detection position Y in the width direction of the electrode sheet S, which is the position of the sensor unit 22, and a detection value D0 of the thickness or basis weight of the electrode sheet S. For example, the detection profile P0 is made up of m detection positions Y1, Y2, Y3, . . . , Y m The set of detected values ​​D0(1), D0(2), D0(3), ···, D0(m) corresponding to the above is P0={(Y1,D0(1)),(Y2,D0(2)),(Y3,D0(3)),···,(Y m , D0(m))}.

[0027] (1-2-4. Specific examples of detection positions) Here, a specific example of the detection position of the detector 20 of the coating mass measurement system 100 will be described with reference to Fig. 5. Fig. 5 is a diagram showing a specific example of the detection position of the detector 20 of the coating mass measurement system 100 according to the embodiment.

[0028] As shown in the example of Figure 5(1), the sensor unit 22 of the detection device 20 moves back and forth across the frame unit 21 perpendicular to the sending direction of the electrode sheet S, acquiring the transmission intensity of the measurement light irradiated from the light source through the electrode sheet S (see thin dashed line). Here, the sending direction of the electrode sheet S, i.e., the flow direction of the electrode sheet S, is called the MD (Machine Direction). Furthermore, the direction perpendicular to the sending direction of the electrode sheet S, i.e., the width direction of the electrode sheet S, is called the CD (Cross Direction).

[0029] As shown in the example of FIG. 5(2), the control unit 23 of the detection device 20 determines the MD detection positions X1, X2, X3, . . . , X4, which are the detection positions X in the MD direction, based on the feeding speed of the electrode sheet S and the moving speed of the sensor unit 22. n-1 , X n, and the CD detection positions Y1, Y2, Y3, ... Y m-1 , Y m and store it together with the detected values ​​D0 of the thickness and basis weight of the electrode sheet S calculated from the transmission intensity of the electrode sheet S. In the example of FIG. 5(2), the MD detection position X and the CD detection position Y m-1 Only the MD detection position X corresponding to the

[0030] As described above, the detection device 20 acquires one detection profile P0 including detection values ​​D0 at m CD detection positions Y each time the sensor unit 22 makes a half reciprocation across the electrode sheet S. Furthermore, when the sensor unit 22 makes n and a half reciprocations across the electrode sheet S (n / 2 reciprocations), the detection device 20 acquires detection values ​​D0 at n MD detection positions X for each CD detection position Y.

[0031] (1-3. Processing example of coating weight measurement system 100) Referring again to Figure 1, an example of processing by the coating weight measurement system 100 will be described. Below, a sheet sending process, a detection profile acquisition process, a detection profile collection process, a CD smoothing process, and an MD smoothing process will be described. Note that the following processes (1) to (5) can also be executed in a different order. Also, some of the following processes (1) to (5) may be omitted.

[0032] (1-3-1. Sheet sending process) First, the worker W feeds the electrode sheet S, which is the object to be measured, at a constant speed (see FIG. 1(1)). For example, the worker W feeds the electrode sheet S at a constant speed by operating rollers on a coating line (not shown). Here, the object to be measured is not limited to metal foil such as the electrode sheet S, but may be a sheet-like object such as paper or plastic film.

[0033] (1-3-2. Detection profile acquisition process) Second, the detection device 20 acquires a detection profile P0 of the delivered electrode sheet S (see FIG. 1(2)). For example, the detection device 20 acquires n data groups P0(1), P0(2), P0(3), ..., P0(n), each including m detection values ​​D0, as the detection profile P0 outputted each time the sensor unit 22 of the detection device 20 makes a half-reciprocating motion.

[0034] (1-3-3. Discovery profile collection process) Third, the measurement device 10 collects a detection profile P0 from the detection device 20 (see FIG. 1(3)). For example, the measurement device 10 collects, from the detection device 20-1, a detection profile P0-1 acquired by the detection device 20-1. The measurement device 10 also collects, from the detection device 20-2, a detection profile P0-2 acquired by the detection device 20-2.

[0035] (1-3-4. CD smoothing processing) Fourth, the measurement device 10 smoothes the detection profile P0 in the CD direction (see FIG. 1(4)). For example, the measurement device 10 applies a smoothing filter that performs smoothing, smoothing the detection profiles P0(1), P0(2), P0(3), . . . , P0(n) for the same MD detection position X unit, i.e., for m detection values ​​D0 in the detection profile P0, and outputs P1(1), P1(2), P1(3), . . . , P1(n) as a CD-smoothed profile P1, each including m first smoothed detection values ​​D1.

[0036] At this time, the measuring device 10 can select a moving average filter, a median filter, a Gaussian filter, a moving average filter with a threshold, a median filter with a threshold, or a Gaussian filter with a threshold as the smoothing filter. The measuring device 10 also performs smoothing based on the calculation width, variance, threshold, etc. specified by the operator W. Here, in the CD smoothing process, the measuring device 10 performs smoothing using values ​​on both sides of the point of interest (point i) as the center.

[0037] (1-3-5. MD smoothing processing) Fifth, the measurement apparatus 10 smoothes the CD-smoothed profile P1 in the MD direction (see FIG. 1(4)). For example, the measurement apparatus 10 applies a smoothing filter to perform smoothing, smoothing the CD-smoothed profiles P1(1), P1(2), P1(3), . . . , P1(n) for the same CD detection position Y, i.e., for n first smoothed detection values ​​D1 between the CD-smoothed profiles P1, and outputs P2(1), P2(2), P2(3), . . . , P2(n) as MD-smoothed profiles P2, each including m second smoothed detection values ​​D2.

[0038] At this time, the measuring device 10 can select a smoothing filter from a moving average filter, a median filter, a Gaussian filter, a thresholded moving average filter, a thresholded median filter, or a thresholded Gaussian filter, just like in the CD smoothing process. Furthermore, the measuring device 10 performs smoothing based on the calculation width, variance, threshold, SMF (current value ratio), and the like, specified by the operator W. Here, in the MD smoothing process, the measuring device 10 always focuses on the most recent profile, so it performs smoothing using only past data. Furthermore, the measuring device 10 can apply exponential smoothing in addition to the above smoothing filters.

[0039] (1-3-6. Other) 1(1) to 1(5) have been described as an example of a process in which CD smoothing is performed first and then MD smoothing is performed as the smoothing process for the detection profile P0, but the order of smoothing is not particularly limited. For example, in the coating weight measurement system 100, the measurement device 10 can perform the smoothing processes in the order of MD smoothing and then CD smoothing. Furthermore, the measurement device 10 can perform either the CD smoothing process or the MD smoothing process.

[0040] 1(1) to 1(5) illustrate an example process in which one type of smoothing filter is selected as the smoothing filter and smoothing is performed. However, the number of applicable smoothing filters is not particularly limited. For example, in the coating weight measurement system 100, the measurement device 10 can apply a combination of two or more types of smoothing filters from six types of smoothing filters: a moving average filter, a median filter, a Gaussian filter, a thresholded moving average filter, a thresholded median filter, and a thresholded Gaussian filter. The measurement device 10 may apply the same smoothing filter or different smoothing filters in the CD smoothing process and the MD smoothing process. The measurement device 10 can also select a smoothing filter for each characteristic of the object to be measured (e.g., material, thickness) or the target standard deviation σ or range R. The measurement device 10 can also repeatedly apply the same smoothing filter.

[0041] (1-4. Effects of Coating Weight Measurement System 100) Below, an overview and problems of the coating weight measurement system 100P according to the reference technology will be described, and then the effects of the coating weight measurement system 100 will be described.

[0042] (1-4-1. Overview of Coating Weight Measurement System 100P) An overview of a coating weight measurement system 100P according to the reference technology will be described below. The coating weight measurement system 100P focuses only on the flow direction of the electrode sheet S, i.e., the MD direction, and applies a smoothing algorithm of either moving average or exponential smoothing using a past detection value D0 at the same CD detection position Y. In other words, the coating weight measurement system 100P performs only MD smoothing without performing CD smoothing. The moving average and exponential smoothing will be described below.

[0043] (1-4-1-1.moving average) The moving average is expressed by the following formula (1), and is a smoothing algorithm in which the current smoothed profile, which is the most recent smoothed data group, is the average value of multiple past detection profiles at the same detection position.

[0044]

number

[0045] In the above formula (1), "k" is the number of times averaging is specified, and "SPV n,i ” is the detected value D0 at point i of the nth smoothed profile, “MPV m,i ” indicates the detection value D0 at point i of the mth detection profile.

[0046] (1-4-1-2. Exponential smoothing method) The exponential smoothing method is expressed by the following formula (2), and is a smoothing algorithm in which the current smoothed profile, which is the most recent smoothed data group, is obtained by adding, at a fixed rate, the current detected profile, which is the most recent detected data group, and the previous smoothed profile, which is the data group smoothed the previous time at the same CD detection position Y.

[0047]

number

[0048] In the above formula (2), "SPV n,i ” is the detected value D0 at point i of the nth smoothed profile, “MPV n,i " indicates the detected value D0 at point i of the nth detection profile, and "SMF" indicates the smoothing factor value (proportion of the current detection profile value: 0 to 1).

[0049] (1-4-2. Problems with the Coating Weight Measurement System 100P) Problems with the coating weight measurement system 100P according to the reference technology will be described below. Problems 1 to 3 with the coating weight measurement system 100P will be described below.

[0050] (1-4-2-1.Problem 1) First, the coating weight measurement system 100P has the problem of large errors when there is little accumulated past data. Because the coating weight measurement system 100P only performs MD smoothing processing, the standard deviation σ and range R values ​​do not stabilize until 10 to 30 detection profiles P0 have been collected. As a result, with the coating weight measurement system 100P, products (e.g., sheets, paper) produced before the standard deviation σ and range R values ​​stabilize cannot be guaranteed in quality and must be discarded, resulting in raw material loss.

[0051] (1-4-2-2. Problem 2) Second, the coating weight measurement system 100P has the problem that it is difficult to change its hardware configuration. To accommodate various measurement targets, the coating weight measurement system 100P uses multiple types of radiation sources, such as beta rays, X-rays, and infrared rays. For example, in the case of beta rays, the coating weight measurement system 100P allows for the selection of various radiation sources depending on the basis weight, such as krypton-85 (85Kr: 15.54 GBq or 37 GBq), promethium-147 (147Pm: 12.95 GBq or 37 GBq), and strontium-90 (90Sr: 0.74 GBq or 3.7 GBq). Therefore, because the characteristics of the coating weight measurement system 100P vary depending on the radiation source used, the standard deviation σ and range R may not be reduced to the desired level unless the hardware configuration is changed. On the other hand, in the case of the Coating Weight Measurement System 100P, changing the hardware configuration would require significant development costs, so it is necessary to reduce the standard deviation σ and range R values ​​through software (program) innovation.

[0052] (1-4-2-3. Problem 3) Third, the coating weight measurement system 100P has the problem of difficulty in dealing with leakage radiation. In order to maintain low values ​​for the standard deviation σ and range R while reducing leakage radiation, it is difficult to do so with hardware-related measures alone; software-related measures must also be implemented.

[0053] (1-4-3. Overview of Coating Weight Measurement System 100) An overview of the coating weight measurement system 100 according to the embodiment will be described. The coating weight measurement system 100 executes the following processes. First, an operator W feeds the electrode sheet S, which is the object to be measured, at a constant speed. Second, a detection device 20 outputs a detection profile P0 of the fed electrode sheet S. Third, the measurement device 10 collects the detection profile P0 from the detection device 20. Fourth, the measurement device 10 smooths the detection profile P0 in the CD direction to output a CD-smoothed profile P1. Fifth, the measurement device 10 smooths the CD-smoothed profile P1 in the MD direction to output an MD-smoothed profile P2.

[0054] Furthermore, the measuring device 10 can select a moving average filter, a median filter, a Gaussian filter, a thresholded moving average filter, a thresholded median filter, or a thresholded Gaussian filter as the smoothing filter. Here, in the CD smoothing process, the measuring device 10 performs smoothing using values ​​on both sides of a point of interest (point i) as the center. In the MD smoothing process, the measuring device 10 performs smoothing using only past data, since the point of interest is always the most recent profile.

[0055] (1-4-4. Effects of Coating Weight Measurement System 100) The effects of the coating weight measurement system 100 according to the embodiment will be described below. Effects 1 to 3 of the coating weight measurement system 100 will be described below. As will be described below, the coating weight measurement system 100 can improve the measurement accuracy of thickness or basis weight.

[0056] (1-4-4-1. Effect 1) First, the coating weight measurement system 100 has the advantage of having small measurement errors even when there is little accumulated past data. In the coating weight measurement system 100, the MD smoothing process is performed after the CD smoothing process, so the standard deviation σ and range R values ​​are stable even at a stage where only a small number of detection profiles P0 have been collected compared to the coating weight measurement system 100P. Therefore, the coating weight measurement system 100 can reduce raw material loss due to the disposal of products produced before the standard deviation σ and range R values ​​have stabilized.

[0057] (1-4-4-2. Effect 2) Second, the coating weight measurement system 100 has the advantage of being able to accommodate a variety of measurement targets without changing the hardware configuration. The coating weight measurement system 100 allows a smoothing filter to be selected for each characteristic of the measurement target and the target standard deviation σ or range R, so the standard deviation σ or range R can be reduced simply by changing the software.

[0058] (1-4-4-3. Effect 3) Third, the coating weight measurement system 100 has the advantage of being able to handle leakage radiation. The coating weight measurement system 100 can select a smoothing filter for each characteristic of the object to be measured and the target standard deviation σ or range R, making it possible to implement software measures to keep the standard deviation σ and range R small while reducing leakage radiation.

[0059] 2. Configuration and Processing of Each Device of Coating Weight Measurement System 100 The configuration and processing of each device included in the coating weight measurement system 100 shown in Fig. 1 will be described using Fig. 6. Fig. 6 is a block diagram showing an example configuration of each device of the coating weight measurement system 100 according to an embodiment. Below, an example configuration of the entire coating weight measurement system 100 according to an embodiment, an example configuration and processing of the measuring device 10, and an example configuration and processing of the detection device 20 will be described.

[0060] (2-1. Example of the overall configuration of the coating weight measurement system 100) An example of the overall configuration of the coating weight measurement system 100 shown in Fig. 1 will be described using Fig. 6. As shown in Fig. 6, the coating weight measurement system 100 is made up of a measuring device 10 and a detecting device 20. The measuring device 10 and the detecting device 20 are communicably connected by a communication network N realized by the Internet, a dedicated line, or the like. The measuring device 10, a coating device CM (not shown), a drying device DM (not shown), and a sending device (not shown) are communicably connected by analog signals, pulse signals, Ethernet (registered trademark), or the like.

[0061] (2-2. Configuration Example and Processing Example of Measuring Device 10) An example of the configuration and processing of the measurement device 10 will be described with reference to Fig. 6. The measurement device 10 has an input unit 11, an output unit 12, a communication unit 13, a storage unit 14, and a control unit 15.

[0062] (2-2-1. Input section 11) The input unit 11 controls input of various information to the measurement device 10. For example, the input unit 11 is realized by a mouse, a keyboard, etc., and accepts input of various information to the measurement device 10.

[0063] (2-2-2. Output section 12) The output unit 12 controls the output of various information from the measurement device 10. For example, the output unit 12 is realized by a display or the like, and displays various information stored in the measurement device 10.

[0064] Furthermore, the output unit 12 displays various types of information output from the control unit 15. For example, the output unit 12 displays a first smoothing result output by a first smoothing unit 15b of the control unit 15, which will be described later. The output unit 12 also displays a second smoothing result output by a second smoothing unit 15c of the control unit 15, which will be described later.

[0065] (2-2-3. Communications Department 13) The communication unit 13 controls data communication with other devices. For example, the communication unit 13 performs data communication with each communication device via a router, etc. The communication unit 13 can also perform data communication with a terminal (not shown).

[0066] (2-2-4. Storage section 14) The storage unit 14 stores various pieces of information referenced by the control unit 15 when it operates, and various pieces of information acquired when the control unit 15 operates. The storage unit 14 includes a detection result storage unit 14a, a first smoothing result storage unit 14b, and a second smoothing result storage unit 14c. Here, the storage unit 14 may be realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. Note that, although the storage unit 14 is installed inside the measurement device 10 in the example of FIG. 6, it may be installed outside the measurement device 10, or multiple storage units may be installed.

[0067] (2-2-4-1. Detection result storage unit 14a) The detection result storage unit 14a stores the detection results. For example, the detection result storage unit 14a stores the detection results collected by the collection unit 15a of the control unit 15, which will be described later. Here, an example of data stored in the detection result storage unit 14a will be described with reference to FIG. 7. FIG. 7 is a diagram showing an example of the detection result storage unit 14a of the measurement device 10 according to the embodiment. In the example of FIG. 7, the detection result storage unit 14a has items such as "production line," "detection equipment," and "detection profile."

[0068] "Production line" indicates identification information for identifying the production process of the object to be measured, for example, the identification number or identification symbol of the coating line of the electrode sheet S. "Detection device" indicates identification information of the detection device 20 installed in the production process of the object to be measured, for example, the identification number or identification symbol of the detection device 20 installed in the coating line. "Detection profile" indicates the detection profile P0 collected by the collection unit 15a, and is, for example, a group of m sets of data consisting of the CD detection position Y in the width direction of the electrode sheet S and the detection values ​​D0 of the thickness and basis weight of the electrode sheet S.

[0069] That is, Figure 7 shows an example in which data such as "Detection Profile #1," "Detection Profile #2," "Detection Profile #3," ..., "Detection Profile #n-1," and "Detection Profile #n" are stored in the detection result memory unit 14a for the production line identified by "Coating Line #1" and the detection device 20-1 identified by "Detection Device #1."

[0070] (2-2-4-2. First smoothing result storage unit 14b) The first smoothing result storage unit 14b stores the first smoothing result. For example, the first smoothing result storage unit 14b stores the first smoothing result output by a first smoothing unit 15b of the control unit 15, which will be described later. Here, an example of data stored in the first smoothing result storage unit 14b will be described with reference to FIG. 8. FIG. 8 is a diagram showing an example of the first smoothing result storage unit 14b of the measurement device 10 according to the embodiment. In the example of FIG. 8, the first smoothing result storage unit 14b has items such as "production line," "detection equipment," and "first smoothing profile."

[0071] "Production line" indicates identification information for identifying the production process of the object to be measured, for example, the identification number or identification symbol of the coating line of the electrode sheet S. "Detection device" indicates identification information of the detection device 20 installed in the production process of the object to be measured, for example, the identification number or identification symbol of the detection device 20 installed in the coating line. "First smoothed profile" indicates the CD smoothed profile P1 output by the first smoothing unit 15b, and is, for example, an m-set data group consisting of the CD detection position Y in the width direction of the electrode sheet S and the first smoothed detection values ​​D1 of the thickness and basis weight of the electrode sheet S after the CD smoothing process has been performed.

[0072] That is, Figure 8 shows an example in which data such as "CD smoothing profile #1," "CD smoothing profile #2," "CD smoothing profile #3," ..., "CD smoothing profile #n-1," and "CD smoothing profile #n" are stored in the first smoothing result memory unit 14b for the production line identified by "coating line #1" and the detection device 20-1 identified by "detection device #1."

[0073] (2-2-4-3. Second smoothing result storage unit 14c) The second smoothing result storage unit 14c stores the second smoothing result. For example, the second smoothing result storage unit 14c stores the second smoothing result output by a second smoothing unit 15c of the control unit 15, which will be described later. Here, an example of data stored in the second smoothing result storage unit 14c will be described with reference to FIG. 9. FIG. 9 is a diagram showing an example of the second smoothing result storage unit 14c of the measurement device 10 according to the embodiment. In the example of FIG. 9, the second smoothing result storage unit 14c has items such as "production line," "detection equipment," and "second smoothing profile."

[0074] "Production line" indicates identification information for identifying the production process of the object to be measured, for example, the identification number or identification symbol of the coating line for the electrode sheet S. "Detection device" indicates identification information of the detection device 20 installed in the production process of the object to be measured, for example, the identification number or identification symbol of the detection device 20 installed in the coating line. "Second smoothed profile" indicates the MD smoothed profile P2 output by the second smoothing unit 15c, and is, for example, an m-set data group consisting of the CD detection position Y in the width direction of the electrode sheet S and the second smoothed detection values ​​D2 of the thickness and basis weight of the electrode sheet S after the CD smoothing process and the MD smoothing process are performed in order.

[0075] That is, Figure 9 shows an example in which data such as "MD smoothed profile #1," "MD smoothed profile #2," "MD smoothed profile #3," ..., "MD smoothed profile #n-1," and "MD smoothed profile #n" are stored in the second smoothing result memory unit 14c for the production line identified by "coating line #1" and the detection device 20-1 identified by "detection device #1."

[0076] (2-2-5. Control unit 15) The control unit 15 is responsible for overall control of the measurement device 10. The control unit 15 has a collection unit 15a, a first smoothing unit 15b, and a second smoothing unit 15c. Here, the control unit 15 can be realized by, for example, an electronic circuit such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit), or an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0077] (2-2-5-1. Collection unit 15a) The collection unit 15a collects various types of information via the communication network N. The collection unit 15a may store the collected various types of information in the storage unit 14. The detection profile collection control process will be described below.

[0078] (Discovery profile collection control process) The collecting unit 15a executes a detection profile collection control process. For example, the collecting unit 15a collects a detection profile P0 including a plurality of detection values ​​D0 relating to the thickness or basis weight of the sheet-like measurement object being sent from the detection device 20. At this time, the collecting unit 15a collects the basis weight [g / m 2] from the detection device 20. The collection unit 15a also collects from the detection device 20 a detection profile P0 including the thickness [mm] of the electrode sheet S to be sent out for each CD detection position. The collection unit 15a can also collect from the detection device 20 a detection profile P0 including the transmission intensity of measurement light such as beta rays, X-rays, and infrared rays for each CD detection position of the electrode sheet S to be sent out.

[0079] To explain a specific example of the detection profile collection control process, the collection unit 15a collects "Detection Profile #1," "Detection Profile #2," "Detection Profile #3," ..., "Detection Profile #n-1," and "Detection Profile #n" as detection profiles P0-1 acquired by the sensor unit 22-1 of "Detection Device #1," which is the detection device 20-1, and stores them in the detection result memory unit 14a.

[0080] (2-2-5-2. First smoothing section 15b) The first smoothing unit 15b outputs the first smoothing result. At this time, the first smoothing unit 15b outputs the first smoothing result to the second smoothing unit 15c. The first smoothing unit 15b may store the output first smoothing result in the storage unit 14. The first smoothing unit 15b may also display the output first smoothing result on the output unit 12. The first smoothing result management process will be described below.

[0081] (First smoothing result management process) The first smoothing unit 15b executes a first smoothing result management process. For example, the first smoothing unit 15b uses a smoothing filter to smooth the multiple detection values ​​D0 included in the detection profile P0 in the width direction (CD direction) perpendicular to the sending direction of the measurement object, and outputs a first smoothed profile P1. In this case, the smoothing filter is, for example, at least one of a moving average filter, a median filter, a Gaussian filter, a moving average filter with a threshold, a median filter with a threshold, and a Gaussian filter with a threshold. Details of the smoothing filter will be described later in "3. Specific Examples of Each Process of the Coating Weight Measurement System 100."

[0082] To explain a specific example of the first smoothing result management process, first, the first smoothing unit 15b refers to “detection profile #1,” “detection profile #2,” “detection profile #3,” . . ., “detection profile #n-1,” and “detection profile #n” as the detection profile P0-1 stored in the detection result storage unit 14a. Next, the first smoothing unit 15b selects a smoothing filter and smoothes the detection value D0-1 included in the detection profile P0-1 for each identical MD detection position X of each detection profile P0-1, i.e., smoothes it in the CD direction. Then, the first smoothing unit 15b outputs “CD smoothed profile #1,” “CD smoothed profile #2,” “CD smoothed profile #3,” . . ., “CD smoothed profile #n-1,” and “CD smoothed profile #n,” each including the first smoothed detection value D1-1 subjected to the first smoothing process, as the CD smoothed profile P1-1, and stores the CD smoothed profile P1-1 in the first smoothing result storage unit 14b.

[0083] (2-2-5-3.Second smoothing section 15c) The second smoothing unit 15c outputs the second smoothing result. The second smoothing unit 15c may store the outputted second smoothing result in the storage unit 14. The second smoothing unit 15c may also display the outputted second smoothing result on the output unit 12. The second smoothing result management process will be described below.

[0084] (Second smoothing result management process) The second smoothing unit 15c executes a first smoothing result management process. For example, the second smoothing unit 15c uses a smoothing filter to smooth a plurality of detection values ​​D1, which are included in the first smoothed profile P1 and have been smoothed in the width direction (CD direction) perpendicular to the sending direction of the measurement object, in the sending direction (MD direction) of the measurement object, and outputs a second smoothed profile P2. In this case, the smoothing filter is, for example, at least one of a moving average filter, a median filter, a Gaussian filter, a moving average filter with a threshold, a median filter with a threshold, and a Gaussian filter with a threshold. Furthermore, the second smoothing unit 15c can apply exponential smoothing in addition to applying the above smoothing filter. Details of the smoothing filter will be described later in "3. Specific Examples of Each Process of the Coating Weight Measurement System 100."

[0085] To explain a specific example of the second smoothing result management process, first, the second smoothing unit 15c refers to "CD smoothed profile #1," "CD smoothed profile #2," "CD smoothed profile #3," ..., "CD smoothed profile #n-1," and "CD smoothed profile #n" as the CD smoothed profile P1-1 stored in the first smoothing result storage unit 14b. Next, the second smoothing unit 15c selects a smoothing filter and smoothes the detection value D1-1 included in the CD smoothed profile P1-1 for each identical CD detection position Y of the CD smoothed profile P1-1, i.e., smooths in the MD direction. Then, the second smoothing unit 15c outputs, as the MD smoothed profile P2-1, "MD smoothed profile #1", "MD smoothed profile #2", "MD smoothed profile #3", ..., "MD smoothed profile #n-1", and "MD smoothed profile #n", each of which includes the second smoothed detection value D2-1 on which the second smoothing process has been performed, and stores them in the first smoothing result memory unit 14b.

[0086] (2-3. Configuration example and processing example of the detection device 20) Referring again to FIG. 6, a configuration example and a processing example of the detection device 20 will be described. The detection device 20 is installed on a coating line where a sheet-like object to be measured is coated. The detection device 20 calculates the thickness or basis weight of the sheet-like object to be measured at each detection position using the transmitted intensity detected by irradiating the sheet-like object to be measured with beta rays, X-rays, or infrared rays. For example, the detection device 20 is installed on a coating line where metal foil such as an electrode sheet S, paper, plastic film, or the like is coated as the sheet-like object to be measured. The detection device 20 also has a frame unit 21, a sensor unit 22, and a control unit 23.

[0087] (2-3-1. Frame part 21) The frame section 21 is a housing section made of metal, and the sensor section 22 (sensor section upper section 22U, sensor section lower section 22D) is installed therein.

[0088] (2-3-2. Sensor unit 22) The sensor unit 22 irradiates a sheet-like measurement object with measurement light such as β rays, X-rays, or infrared rays, and detects the transmission intensity of the measurement light. For example, the sensor unit 22 is realized by upper and lower sensor heads, a light source that generates X-rays or β rays, a light source that generates infrared rays, etc., and detects the transmission intensity of the measurement light irradiated onto the electrode sheet S.

[0089] (2-3-3. Control unit 23) The control unit 23 is connected to the sensor unit 22 so as to be able to communicate with it via wire or wirelessly. The control unit 23 also controls processes such as the reciprocating movement of the sensor unit 22 along the frame unit 21, the irradiation of the measurement light, and the detection of the transmission intensity of the measurement light. The control unit 23 also determines the thickness [mm] and basis weight [g / m2] of the electrode sheet S from the transmission intensity of the electrode sheet S detected by the sensor unit 22. 2 ] is calculated.

[0090] 3. Specific Examples of Each Process of Coating Weight Measurement System 100 10 to 19, specific examples of each process of the coating weight measurement system 100 according to the embodiment will be described. Below, an overview of the smoothing filter applied in the coating weight measurement system 100 will be described, followed by explanation of effects 1 to 3 of applying the smoothing filter.

[0091] (3-1. Overview of smoothing filters) An overview of the smoothing filters applied in the coating weight measurement system 100 will be given below. Below, a moving average filter, a median filter, a Gaussian filter, a moving average filter with a threshold, a median filter with a threshold, and a Gaussian filter with a threshold will be described.

[0092] (3-1-1. Moving average filter) The moving average filter is a smoothing algorithm that performs smoothing processing by calculating the average value of the detection values ​​D0 included in the past k detection profiles P0 within a specified calculation width.

[0093] (3-1-2. Median filter) The median filter is a smoothing algorithm that performs smoothing by outputting the median value of the detection values ​​D0 contained in the detection profile P0 within a specified calculation range. The median filter suppresses deterioration of the shape of the detection profile P0 due to the smoothing process, making it possible to clarify the shape of edge portions.

[0094] (3-1-3. Gaussian filter) The Gaussian filter is a smoothing algorithm that performs smoothing processing on the detection values ​​D0 included in the detection profile P0 using a kernel based on a Gaussian distribution function within a specified calculation range and variance. The Gaussian filter suppresses deterioration of the shape of the detection profile P0 due to the smoothing processing, making it possible to clarify the shape of edge portions.

[0095] (3-1-4. Moving average filter with threshold) A thresholded moving average filter is a moving average filter with a set threshold. Compared to a moving average filter, a thresholded moving average filter can retain the shape of sudden fluctuations that are not noise (for example, those that occur when there is dirt on the electrode sheet S). Also, if the threshold is set very high, the thresholded moving average filter will produce the same results as a moving average filter. Also, if the threshold is set to 0, the thresholded moving average filter will return the input value as is.

[0096] (3-1-5. Median filter with threshold) A thresholded median filter is a median filter with a set threshold. Compared to a median filter, a thresholded median filter can retain the shape of sudden changes that are not noise. Also, if the threshold is set very high, the thresholded median filter will produce the same results as a median filter. Also, if the threshold is set to 0, the thresholded median filter will return the input value as is.

[0097] (3-1-6. Gaussian filter with threshold) A thresholded Gaussian filter is a Gaussian filter with a set threshold. Compared to a Gaussian filter, a thresholded Gaussian filter can retain the shape of sudden changes that are not noise. Also, if the threshold is set very high, the Gaussian filter will produce the same results as a Gaussian filter. Also, if the threshold is set to 0, the Gaussian filter will return the input value as is.

[0098] (3-2. Effect of applying a smoothing filter 1) 10 and 11, a first effect of applying a smoothing filter to the coating mass measurement system 100 will be described. Below, as the first effect of applying a smoothing filter, an overview of the detection profile P0 will be described, and then the result of applying the smoothing filter to the detection profile P0 will be described.

[0099] (3-2-1. Overview of Detection Profile P0) An overview of the detection profile P0 will be described with reference to Fig. 10. Fig. 10 is a diagram showing a specific example 1 of each process of the coating mass measurement system 100 according to the embodiment. As shown in the example of Fig. 10, the detection profile P0 is used to calculate the weight per unit area [g / m 2 10, the detection profile P0 is data including a "basis weight" indicating the position where the basis weight was detected, and a "detection position" indicating the position where the basis weight was detected. In the example of FIG. ... 2 10 is the data of the detection profile P0 corresponding to the uppermost step of the electrode sheet S, which has a step, that is, the area with the greatest thickness and basis weight, and has 210 data points.

[0100] (3-2-2. Results of applying a smoothing filter to detection profile P0) The results of applying a smoothing filter to detection profile P0 will be described using Fig. 11. Fig. 11 is a diagram showing a specific example 2 of each process of coating mass measurement system 100 according to an embodiment. Below, the results of applying a thresholded Gaussian filter, a thresholded moving average filter, and a thresholded median filter to the data of the "ridge line portion" in Fig. 10 above will be described.

[0101] (3-2-2-1. Without smoothing filter) "None (detection profile)" in Fig. 11 shows the standard deviation σ and range R values ​​when no smoothing filter is applied to the "ridge line portion" data in Fig. 10. As shown in "None (detection profile)" in Fig. 11, the standard deviation σ is "0.65" and the range R is "3.00".

[0102] (3-2-2-2. Gaussian filter with threshold) The "Gaussian filter with threshold" in Figure 11 shows the standard deviation σ and range R values ​​when a Gaussian filter with threshold is applied to both the CD smoothing process and the MD smoothing process for the "ridge line portion" data in Figure 10 above. As shown in the "Gaussian filter with threshold" in Figure 11, when the calculation width is "15", the variance is "1.0", and the threshold is "1.0", the standard deviation σ is "0.59" and the range R is "2.65". Similarly, when the calculation width is "15", the variance is "2.0", and the threshold is "2.0", the standard deviation σ is "0.55" and the range R is "2.38".

[0103] As a result of applying the thresholded Gaussian filter as described above, the standard deviation σ and the range R become smaller than those of the unsmoothed detection profile P0.

[0104] (3-2-2-3. Moving average filter with threshold) The "Thresholded Moving Average Filter" in Figure 11 shows the standard deviation σ and range R values ​​when a thresholded moving average filter is applied to both the CD smoothing process and the MD smoothing process on the "ridge line portion" data in Figure 10 above. As shown in the "Thresholded Moving Average Filter" in Figure 11, when the calculation width is "15" and the threshold is "1.0", the standard deviation σ is "0.49" and the range R is "2.04". Similarly, when the calculation width is "15" and the threshold is "2.0", the standard deviation σ is "0.41" and the range R is "1.56".

[0105] As a result of applying the thresholded moving average filter as described above, the standard deviation σ and the range R become smaller than those of the unsmoothed detection profile P0.

[0106] (3-2-2-4. Median filter with threshold) The "Median Filter with Threshold" in Figure 11 shows the standard deviation σ and range R values ​​when a median filter with threshold is applied to both the CD smoothing process and the MD smoothing process for the "ridge line portion" data in Figure 10 above. As shown in the "Median Filter with Threshold" in Figure 11, when the calculation width is "15" and the threshold is "1.0", the standard deviation σ is "0.51" and the range R is "2.10". Similarly, when the calculation width is "15" and the threshold is "2.0", the standard deviation σ is "0.45" and the range R is "1.60".

[0107] As a result of applying the thresholded median filter as described above, the standard deviation σ and the range R become smaller than those of the unsmoothed detection profile P0.

[0108] (3-3. Effect of applying smoothing filter 2) 12 to 15, a second effect of applying the smoothing filter to the coating mass measurement system 100 will be described. Below, as the second effect of applying the smoothing filter, the results of applying the smoothing filter (standard deviation σ of the air layer, range R of the air layer, standard deviation σ of the ridgeline portion, range R of the ridgeline portion) when only CD smoothing processing is performed on the detected profile P0 will be described. Note that in the results of applying the smoothing filter below, the number of data points per profile is 2400, and the number of profiles is 77.

[0109] (3-3-1. Standard deviation of air layer σ) The standard deviation σ of the air layer will be described as a result of applying a smoothing filter to the detection profile P0 only in the CD smoothing process, with reference to Fig. 12. Fig. 12 is a diagram showing a specific example 3 of each process of the coating mass measurement system 100 according to the embodiment.

[0110] The vertical axis of FIG. 12 indicates the standard deviation σ of the detection value D0 or the first smoothed detection value D1 in the air layer where the electrode sheet S is not present. The horizontal axis of FIG. 12 indicates the number of profiles, i.e., the time series. FIG. 12(1) shows the time series change in the standard deviation σ of the detection value D0 included in the detection profile P0. FIG. 12(2) shows the time series change in the standard deviation σ of the first smoothed detection value D1 included in the CD smoothed profile P1 when only the CD smoothing process is performed.

[0111] As shown in FIG. 12(1), the standard deviation σ of the detection values ​​D0 included in the detection profile P0 varies within the range of 0.39 to 0.48, and does not decrease even when the number of profiles increases.

[0112] As shown in FIG. 12(2), the standard deviation σ of the first smoothed detection value D1 included in the CD smoothed profile P1 varies within the range of 0.15 to 0.21, and does not decrease even when the number of profiles increases.

[0113] When only CD smoothing processing is performed on the detection profile P0 as described above, the standard deviation σ in the air layer does not decrease as past data accumulates, but the value becomes smaller compared to the unsmoothed detection profile P0.

[0114] Note that the example in Figure 12 is the result of applying a thresholded moving average filter (calculation width 31, threshold 4.0), but even if other smoothing filters such as a thresholded median filter or a thresholded Gaussian filter are applied, the numerical values ​​will similarly be smaller than those of the unsmoothed detection profile P0.

[0115] (3-3-2. Air Layer Range R) The range R of the air layer will be described as a result of applying a smoothing filter to the detection profile P0 only in the CD smoothing process, with reference to Fig. 13. Fig. 13 is a diagram showing a fourth specific example of each process of the coating mass measurement system 100 according to the embodiment.

[0116] The vertical axis of FIG. 13 indicates the range R of the detection value D0 or the first smoothed detection value D1 in the air layer where the electrode sheet S is not present. The horizontal axis of FIG. 13 indicates the number of profiles, i.e., the time series. FIG. 13(1) shows the time series change in the range R of the detection value D0 included in the detection profile P0. FIG. 13(2) shows the time series change in the range R of the first smoothed detection value D1 included in the CD smoothed profile P1 when only the CD smoothing process is performed.

[0117] As shown in FIG. 13(1), the range R of the detection value D0 included in the detection profile P0 fluctuates within the range of 2.4 to 3.8, and does not decrease even if the number of profiles increases.

[0118] As shown in FIG. 13(2), the range R of the first smoothed detection value D1 included in the CD smoothed profile P1 fluctuates within a range of 0.7 to 1.3, and does not decrease even when the number of profiles increases.

[0119] When only CD smoothing processing is performed on the detection profile P0 as described above, the range R in the air layer does not decrease with the accumulation of past data, but the numerical value becomes smaller compared to the unsmoothed detection profile P0.

[0120] Note that the example in Figure 13 is the result of applying a thresholded moving average filter (calculation width 31, threshold 4.0), but even if other smoothing filters such as a thresholded median filter or a thresholded Gaussian filter are applied, the numerical values ​​will similarly be smaller than those of the unsmoothed detection profile P0.

[0121] (3-3-3. Standard deviation σ of the ridge line) The standard deviation σ of the ridge line portion will be described as a result of applying a smoothing filter to the detection profile P0 only in the CD smoothing process, with reference to Fig. 14. Fig. 14 is a diagram showing a specific example 5 of each process of the coating mass measurement system 100 according to the embodiment.

[0122] The vertical axis of FIG. 14 represents the standard deviation σ of the detection value D0 or the first smoothed detection value D1 at the ridge line portion corresponding to the area where the thickness or basis weight of the electrode sheet S is maximum. The horizontal axis of FIG. 14 represents the number of profiles, i.e., the time series. FIG. 14(1) shows the time series change in the standard deviation σ of the detection value D0 included in the detection profile P0. FIG. 14(2) shows the time series change in the standard deviation σ of the first smoothed detection value D1 included in the CD smoothed profile P1 when only the CD smoothing process is performed.

[0123] As shown in FIG. 14(1), the standard deviation σ of the detection values ​​D0 included in the detection profile P0 varies within the range of 0.58 to 0.80, and does not decrease even when the number of profiles increases.

[0124] As shown in FIG. 14(2), the standard deviation σ of the first smoothed detection value D1 included in the CD smoothed profile P1 varies within the range of 0.15 to 0.48, and does not decrease even when the number of profiles increases.

[0125] When only CD smoothing processing is performed on the detection profile P0 as described above, the standard deviation σ at the ridge line portion does not decrease as past data accumulates, but the numerical value becomes smaller compared to the unsmoothed detection profile P0.

[0126] Note that the example in Figure 14 is the result of applying a thresholded moving average filter (calculation width 31, threshold 4.0), but even if other smoothing filters such as a thresholded median filter or a thresholded Gaussian filter are applied, the numerical values ​​will similarly be smaller than those of the unsmoothed detection profile P0.

[0127] (3-3-4. Range R of the ridgeline) The range R of the ridge line portion will be described as a result of applying a smoothing filter to the detection profile P0 only in the CD smoothing process, with reference to Fig. 15. Fig. 15 is a diagram showing a specific example 6 of each process of the coating mass measurement system 100 according to the embodiment.

[0128] The vertical axis in FIG. 15 represents the range R of the detection value D0 or the first smoothed detection value D1 at the ridge line portion corresponding to the area where the thickness or basis weight of the electrode sheet S is maximum. The horizontal axis in FIG. 15 represents the number of profiles, i.e., the time series. FIG. 15(1) shows the time series change in the range R of the detection value D0 included in the detection profile P0. FIG. 15(2) shows the time series change in the range R of the first smoothed detection value D1 included in the CD smoothed profile P1 when only the CD smoothing process is performed.

[0129] As shown in FIG. 15(1), the range R of the detection value D0 included in the detection profile P0 fluctuates within the range of 2.9 to 4.3, and does not decrease even if the number of profiles increases.

[0130] As shown in FIG. 15(2), the range R of the first smoothed detection value D1 included in the CD smoothed profile P1 fluctuates within a range of 0.6 to 2.0, and does not decrease even when the number of profiles increases.

[0131] When only CD smoothing processing is performed on the detection profile P0 as described above, the range R at the ridge line portion does not decrease as past data accumulates, but the numerical value becomes smaller compared to the unsmoothed detection profile P0.

[0132] Note that the example in Figure 15 is the result of applying a thresholded moving average filter (calculation width 31, threshold 4.0), but even if other smoothing filters such as a thresholded median filter or a thresholded Gaussian filter are applied, the numerical values ​​will similarly be smaller than those of the unsmoothed detection profile P0.

[0133] (3-3-5. Summary of application effect 2) As described above, when only CD smoothing processing is performed on detection profile P0, the air layer standard deviation σ, air layer range R, ridgeline portion standard deviation σ, and ridgeline portion range R do not decrease with the accumulation of past data, but the values ​​become smaller compared to the unsmoothed detection profile P0. Therefore, in coating mass measurement system 100, by performing only CD smoothing processing on detection profile P0, the standard deviation σ and range R can be reduced, thereby improving the measurement accuracy of thickness or basis weight.

[0134] (3-4. Effect of applying smoothing filter 3) 16 to 19, the third effect of applying the smoothing filter to the coating mass measurement system 100 will be described. Below, as the third effect of applying the smoothing filter, the results of applying the smoothing filter (standard deviation σ of the air layer, range R of the air layer, standard deviation σ of the ridgeline portion, range R of the ridgeline portion) when CD smoothing processing and MD smoothing processing are performed on the detected profile P0 will be described. Note that in the results of applying the smoothing filter below, the number of data points per profile is 2400, and the number of profiles is 77.

[0135] (3-4-1. Standard deviation of air layer σ) The standard deviation σ of the air layer will be described as a result of applying the smoothing filters in the CD smoothing process and the MD smoothing process to the detection profile P0, using Fig. 16. Fig. 16 is a diagram showing a seventh specific example of each process of the coating mass measurement system 100 according to the embodiment.

[0136] The vertical axis of Figure 16 represents the standard deviation σ of the detection value D0, the exponentially smoothed detection value D1', or the second smoothed detection value D2 in the air layer where the electrode sheet S is not present. The horizontal axis of Figure 16 represents the number of profiles, i.e., the time series. Figure 16(1) shows the time series change in the standard deviation σ of the detection value D0 included in the detection profile P0. Figure 16(2) shows the time series change in the standard deviation σ of the exponentially smoothed detection value D1' included in the exponentially smoothed profile P1' when only MD smoothing processing (SMF0.1) using the exponential smoothing method is performed. Figure 16(3) shows the time series change in the standard deviation σ of the second smoothed detection value D2 included in the MD smoothed profile P2 when both CD smoothing processing and MD smoothing processing are performed.

[0137] As shown in FIG. 16(1), the standard deviation σ of the detection values ​​D0 included in the detection profile P0 varies within the range of 0.39 to 0.48, and does not decrease even when the number of profiles increases.

[0138] As shown in Figure 16(2), the standard deviation σ of the exponentially smoothed detection value D1' contained in the exponentially smoothed profile P1' is 0.43 when the number of profiles is 1, decreases as the number of profiles increases, becomes 0.09 when the number of profiles is about 30, and then becomes constant.

[0139] As shown in Figure 16(3), the standard deviation σ of the second smoothed detection value D2 contained in the MD smoothed profile P2 is 0.17 when the number of profiles is 1, decreases as the number of profiles increases, becomes 0.04 when the number of profiles is about 20, and then becomes constant.

[0140] When CD smoothing and MD smoothing are performed on the detection profile P0 as described above, the standard deviation σ in the air layer becomes smaller in value compared to the unsmoothed detection profile P0, decreases as past data accumulates, and becomes stable due to the accumulation of less past data compared to the exponentially smoothed profile P1' when only MD smoothing is performed.

[0141] Note that the example in Figure 16 is the result of applying a thresholded moving average filter (calculation width 31, threshold 4.0) and exponential smoothing (SMF 0.1), but even if other smoothing filters such as a thresholded median filter or a thresholded Gaussian filter are applied, the numerical values ​​will similarly be smaller compared to the unsmoothed detection profile P0, and will be stable due to the accumulation of less past data compared to the exponentially smoothed profile P1' when only MD smoothing processing is performed.

[0142] (3-4-2. Air Layer Range R) The range R of the air layer will be described as a result of applying the smoothing filters in the CD smoothing process and the MD smoothing process to the detection profile P0, with reference to Fig. 17. Fig. 17 is a diagram showing a specific example 8 of each process of the coating mass measurement system 100 according to the embodiment.

[0143] The vertical axis of FIG. 17 represents the range R of the detection value D0, the exponentially smoothed detection value D1', or the second smoothed detection value D2 in the air layer where the electrode sheet S is not present. The horizontal axis of FIG. 17 represents the number of profiles, i.e., the time series. FIG. 17(1) shows the time series change in the range R of the detection value D0 included in the detection profile P0. FIG. 17(2) shows the time series change in the range R of the exponentially smoothed detection value D1' included in the exponentially smoothed profile P1' when only MD smoothing processing (SMF0.1) using the exponential smoothing method is performed. FIG. 17(3) shows the time series change in the range R of the second smoothed detection value D2 included in the MD smoothed profile P2 when both CD smoothing processing and MD smoothing processing are performed.

[0144] As shown in FIG. 17(1), the range R of the detection value D0 included in the detection profile P0 fluctuates within the range of 2.4 to 3.8, and does not decrease even if the number of profiles increases.

[0145] As shown in Figure 17(2), the range R of the exponentially smoothed detection value D1' included in the exponentially smoothed profile P1' is 2.6 when the number of profiles is 1, decreases as the number of profiles increases, becomes 0.6 when the number of profiles is about 30, and then becomes constant.

[0146] As shown in Figure 17(3), the range R of the second smoothed detection value D2 included in the MD smoothed profile P2 is 0.9 when the number of profiles is 1, decreases as the number of profiles increases, becomes 0.2 when the number of profiles is around 20, and then becomes constant.

[0147] When CD smoothing and MD smoothing are performed on the detection profile P0 as described above, the range R in the air layer becomes smaller in value compared to the unsmoothed detection profile P0, decreases as past data accumulates, and becomes stable due to the accumulation of less past data compared to the exponentially smoothed profile P1' when only MD smoothing is performed.

[0148] Note that the example in Figure 17 is the result of applying a thresholded moving average filter (calculation width 31, threshold 4.0) and exponential smoothing (SMF 0.1), but even if other smoothing filters such as a thresholded median filter or a thresholded Gaussian filter are applied, the numerical values ​​will similarly be smaller compared to the unsmoothed detection profile P0, and will be stable due to the accumulation of less past data compared to the exponentially smoothed profile P1' when only MD smoothing processing is performed.

[0149] (3-4-3. Standard deviation σ of the ridge line) The standard deviation σ of the ridgeline portion will be described as a result of applying the smoothing filters in the CD smoothing process and the MD smoothing process to the detection profile P0, with reference to Fig. 18. Fig. 18 is a diagram showing a specific example 9 of each process of the coating mass measurement system 100 according to the embodiment.

[0150] The vertical axis of Figure 18 shows the standard deviation σ of the detected value D0, the exponentially smoothed detected value D1', or the second smoothed detected value D2 at the ridge line portion corresponding to the area where the thickness or basis weight of the electrode sheet S is maximum. The horizontal axis of Figure 18 shows the number of profiles, i.e., the time series. Figure 18(1) shows the time series change in the standard deviation σ of the detected value D0 included in the detected profile P0. Figure 18(2) shows the time series change in the standard deviation σ of the exponentially smoothed detected value D1' included in the exponentially smoothed profile P1' when only MD smoothing processing (SMF0.1) using exponential smoothing is performed. Figure 18(3) shows the time series change in the standard deviation σ of the second smoothed detected value D2 included in the MD smoothed profile P2 when both CD smoothing processing and MD smoothing processing are performed.

[0151] As shown in FIG. 18(1), the standard deviation σ of the detection values ​​D0 included in the detection profile P0 varies within the range of 0.58 to 0.80, and does not decrease even when the number of profiles increases.

[0152] As shown in Figure 18(2), the standard deviation σ of the exponentially smoothed detection value D1' contained in the exponentially smoothed profile P1' is 0.65 when the number of profiles is 1, decreases as the number of profiles increases, becomes 0.24 when the number of profiles is about 30, and then becomes constant.

[0153] As shown in Figure 18(3), the standard deviation σ of the second smoothed detection value D2 contained in the MD smoothed profile P2 is 0.31 when the number of profiles is 1, decreases as the number of profiles increases, becomes 0.15 when the number of profiles is about 20, and then becomes constant.

[0154] When CD smoothing and MD smoothing are performed on the detection profile P0 as described above, the standard deviation σ at the ridge line portion becomes smaller in value compared to the unsmoothed detection profile P0, decreases as past data accumulates, and becomes stable due to the accumulation of less past data compared to the exponentially smoothed profile P1' when only MD smoothing is performed.

[0155] Note that the example in Figure 18 is the result of applying a thresholded moving average filter (calculation width 31, threshold 4.0) and exponential smoothing (SMF 0.1), but even if other smoothing filters such as a thresholded median filter or a thresholded Gaussian filter are applied, the numerical values ​​will similarly be smaller compared to the unsmoothed detection profile P0, and will be stable due to the accumulation of less past data compared to the exponentially smoothed profile P1' when only MD smoothing processing is performed.

[0156] (3-4-4. Range R of the ridgeline) The range R of the ridge line portion will be described as a result of applying the smoothing filters in the CD smoothing process and the MD smoothing process to the detection profile P0, using Fig. 19. Fig. 19 is a diagram showing a specific example 10 of each process of the coating mass measurement system 100 according to the embodiment.

[0157] The vertical axis in Figure 19 represents the range R of the detected value D0, the exponentially smoothed detected value D1', or the second smoothed detected value D2 at the ridgeline portion corresponding to the area where the thickness or basis weight of the electrode sheet S is maximum. The horizontal axis in Figure 19 represents the number of profiles, i.e., the time series. Figure 19(1) shows the time series change in the range R of the detected value D0 included in the detected profile P0. Figure 19(2) shows the time series change in the range R of the exponentially smoothed detected value D1' included in the exponentially smoothed profile P1' when only MD smoothing processing (SMF0.1) using exponential smoothing is performed. Figure 19(3) shows the time series change in the range R of the second smoothed detected value D2 included in the MD smoothed profile P2 when both CD smoothing processing and MD smoothing processing are performed.

[0158] As shown in FIG. 19(1), the range R of the detection value D0 included in the detection profile P0 varies within the range of 2.9 to 4.3, and does not decrease even if the number of profiles increases.

[0159] As shown in Figure 19(2), the range R of the exponentially smoothed detection value D1' included in the exponentially smoothed profile P1' is 3.0 when the number of profiles is 1, decreases as the number of profiles increases, becomes 1.1 when the number of profiles is about 30, and then remains constant.

[0160] As shown in Figure 19(3), the range R of the second smoothed detection value D2 included in the MD smoothed profile P2 is 1.1 when the number of profiles is 1, decreases as the number of profiles increases, becomes 0.6 when the number of profiles is around 20, and then becomes constant.

[0161] When CD smoothing and MD smoothing are performed on the detection profile P0 as described above, the range R at the ridge line portion becomes smaller in value compared to the unsmoothed detection profile P0, decreases as past data accumulates, and becomes stable due to the accumulation of less past data compared to the exponentially smoothed profile P1' when only MD smoothing is performed.

[0162] Note that the example in Figure 19 is the result of applying a thresholded moving average filter (calculation width 31, threshold 4.0) and exponential smoothing (SMF 0.1), but even if other smoothing filters such as a thresholded median filter or a thresholded Gaussian filter are applied, the numerical values ​​will similarly be smaller compared to the unsmoothed detection profile P0, and will be stable due to the accumulation of less past data compared to the exponentially smoothed profile P1' when only MD smoothing processing is performed.

[0163] (3-4-5. Summary of application effect 3) As described above, when CD smoothing and MD smoothing are performed on detection profile P0, the air layer standard deviation σ, air layer range R, ridgeline portion standard deviation σ, and ridgeline portion range R become smaller in numerical value compared to the unsmoothed detection profile P0, and are stabilized due to the accumulation of less past data compared to the exponentially smoothed profile P1' obtained when only MD smoothing is performed. Therefore, in coating mass measurement system 100, by performing CD smoothing and MD smoothing on detection profile P0, the standard deviation σ and range R can be reduced in numerical value and stabilized quickly, thereby improving the measurement accuracy of thickness or basis weight.

[0164] 4. Flow of each process in the coating weight measurement system 100 20 to 23, the process flow of the coating weight measurement system 100 according to the embodiment will be described. Below, the overall process flow of the coating weight measurement system 100 will be described, and then each process, that is, the detection result management process, the first smoothing result management process, and the second smoothing result management process, will be described.

[0165] (4-1. Overall processing of the coating weight measurement system 100) The overall processing flow of the coating weight measurement system 100 according to the embodiment will be described using Figure 20. Figure 20 is a flowchart showing an example of the overall processing flow of the coating weight measurement system 100 according to the embodiment. Note that the processing of steps S101 to S103 below can also be performed in a different order. Furthermore, some of the processing of steps S101 to S103 below may be omitted.

[0166] (4-1-1. Detection result management process) First, the coating weight measurement system 100 executes a detection result management process (step S101). For example, the coating weight measurement system 100 executes the processes of steps S201 to S204 described below to manage n detection profiles P0 for the sent electrode sheet S as detection results.

[0167] (4-1-2. First smoothing result management process) Second, the coating mass measurement system 100 executes a first smoothing result management process (step S102). For example, the coating mass measurement system 100 executes the processes of steps S301 to S303 described below to manage a CD-smoothed profile P1 obtained by smoothing the detected profile P0 in the CD direction as the first smoothing result.

[0168] (4-1-3. Second smoothing result management process) Third, the coating mass measurement system 100 executes a second smoothing result management process (step S103). For example, the coating mass measurement system 100 executes the processes of steps S401 to S403 described below to manage an MD-smoothed profile P2 obtained by smoothing the CD-smoothed profile P1 in the MD direction as the second smoothing result.

[0169] (4-2. Detection result management process) The flow of the detection result management process of the coating mass measurement system 100 according to the embodiment will be described with reference to Fig. 21. Fig. 21 is a flowchart showing an example of the flow of the detection result management process of the coating mass measurement system 100 according to the embodiment. Note that the processes of steps S201 to S204 below can also be executed in a different order. Furthermore, some of the processes of steps S201 to S204 below may be omitted.

[0170] (4-2-1. Sheet sending process) First, the worker W executes a sheet feeding process (step S201). For example, the worker W operates a roller, which is a feeding device of the coating line, to feed the electrode sheet S at a constant speed.

[0171] (4-2-2. Detection profile acquisition process) Second, the detection device 20 executes a profile detection process (step S202). For example, the detection device 20 detects a detection value D0, which is the thickness or basis weight of the delivered electrode sheet S, and obtains a detection profile P0 including m detection values ​​D0 in the CD direction.

[0172] (4-2-3. Discovery profile collection process) Third, the measurement device 10 executes a detection profile collection process (step S203). For example, the measurement device 10 collects n detection profiles P0(1), P0(2), P0(3), . . . , P0(n) in the MD direction from the detection device 20, which are acquired by the detection device 20 for each half round trip.

[0173] (4-2-4.Detection profile storage process) Fourth, the measurement device 10 executes a detection profile storage process (step S204). For example, the measurement device 10 stores the collected detection profile P0 in the detection result storage unit 14a.

[0174] (4-3. First smoothing result management process) The flow of the first smoothing result management process of the coating mass measurement system 100 according to the embodiment will be described using Figure 22. Figure 22 is a flowchart showing an example of the flow of the first smoothing result management process of the coating mass measurement system 100 according to the embodiment. Note that the processes of steps S301 to S303 below can also be executed in a different order. Furthermore, some of the processes of steps S301 to S303 below may be omitted.

[0175] (4-3-1. Detection profile reference process) First, the measurement device 10 executes a detection profile reference process (step S301). For example, the measurement device 10 refers to n detection profiles P0(1), P0(2), P0(3), . . . , P0(n) stored in the detection result storage unit 14a.

[0176] (4-3-2. CD smoothing processing) Second, the measurement device 10 executes CD smoothing processing (step S302). For example, the measurement device 10 applies a moving average filter, a median filter, a Gaussian filter, a thresholded moving average filter, a thresholded median filter, or a thresholded Gaussian filter as a smoothing filter to smooth the detection profiles P0(1), P0(2), P0(3), . . . , P0(n) for the detection value D0 at the same MD detection position X, and outputs P1(1), P1(2), P1(3), . . . , P1(n) as CD smoothed profiles P1 each including m first smoothed detection values ​​D1.

[0177] (4-3-3. CD smoothing profile storage process) Third, the measurement apparatus 10 executes a CD smoothed profile storage process (step S303). For example, the measurement apparatus 10 stores the CD smoothed profile P1 smoothed in the CD direction in the first smoothing result storage unit 14b.

[0178] (4-4. Second smoothing result management process) The flow of the second smoothing result management process of the coating mass measurement system 100 according to the embodiment will be described using Figure 23. Figure 23 is a flowchart showing an example of the flow of the second smoothing result management process of the coating mass measurement system 100 according to the embodiment. Note that the processes of steps S401 to S403 below can also be executed in a different order. Furthermore, some of the processes of steps S401 to S403 below may be omitted.

[0179] (4-4-1. CD smoothing profile reference processing) First, the measurement apparatus 10 executes a CD smoothed profile reference process (step S401). For example, the measurement apparatus 10 refers to n CD smoothed profiles P1(1), P1(2), P1(3), . . . , P1(n) stored in the first smoothing result storage unit 14b.

[0180] (4-4-2. MD smoothing processing) Second, the measurement apparatus 10 executes MD smoothing processing (step S402). For example, the measurement apparatus 10 applies a moving average filter, a median filter, a Gaussian filter, a thresholded moving average filter, a thresholded median filter, or a thresholded Gaussian filter as a smoothing filter to smooth the CD smoothed profiles P1(1), P1(2), P1(3), . . . , P1(n) for the first smoothed detection value D1 at the same CD detection position Y, and outputs P2(1), P2(2), P2(3), . . . , P2(n) as MD smoothed profiles P2 each including m second smoothed detection values ​​D2.

[0181] (4-4-3. MD smoothed profile storage process) Third, the measurement device 10 executes an MD smoothed profile storage process (step S403). For example, the measurement device 10 stores the MD smoothed profile P2 smoothed in the MD direction in the second smoothing result storage unit 14c.

[0182] 5. Effects of the embodiment Finally, the effects of the embodiment will be described below: Effects 1 to 9 corresponding to the processing according to the embodiment will be described below.

[0183] (5-1. Effect 1) First, in the process according to the embodiment described above, the measuring device 10 collects from the detecting device 20 a detection profile P0 including multiple detection values ​​D0 related to the thickness or basis weight of the sheet-like measurement object being sent, and then uses a smoothing filter to smooth the multiple detection values ​​D0 included in the detection profile P0 in the CD direction perpendicular to the MD direction of the measurement object, thereby outputting a first smoothed profile P1. Therefore, this process can improve the measurement accuracy of the thickness or basis weight.

[0184] (5-2. Effect 2) Second, in the process according to the embodiment described above, the measuring device 10 uses a smoothing filter to smooth, in the MD direction, the plurality of first smoothed detection values ​​D1 that are smoothed in the CD direction and are included in the first smoothed profile P1, and outputs a second smoothed profile P2. Therefore, in this process, the measurement accuracy of the thickness or basis weight can be further improved.

[0185] (5-3. Effect 3) Third, in the process according to the above embodiment, the smoothing filter is a moving average filter. Therefore, in this process, the smoothing using the moving average filter can improve the measurement accuracy of the thickness or basis weight.

[0186] (5-4. Effect 4) Fourth, in the process according to the above embodiment, the smoothing filter is a median filter. Therefore, in this process, the smoothing using the median filter can improve the measurement accuracy of the thickness or basis weight.

[0187] (5-5. Effect 5) Fifth, in the process according to the above embodiment, the smoothing filter is a Gaussian filter. Therefore, in this process, the smoothing using the Gaussian filter can improve the measurement accuracy of the thickness or basis weight.

[0188] (5-6. Effect 6) Sixth, in the process according to the above embodiment, the smoothing filter is a thresholded moving average filter. Therefore, in this process, the smoothing using the thresholded moving average filter can improve the measurement accuracy of thickness or basis weight.

[0189] (5-7. Effect 7) Seventh, in the process according to the above embodiment, the smoothing filter is a thresholded median filter. Therefore, in this process, the smoothing using the thresholded median filter can improve the accuracy of measuring thickness or basis weight.

[0190] (5-8. Effect 8) Eighth, in the process according to the above embodiment, the smoothing filter is a thresholded Gaussian filter. Therefore, in this process, the smoothing using the thresholded Gaussian filter can improve the measurement accuracy of thickness or basis weight.

[0191] (5-9. Effect 9) Ninth, in the process according to the above-described embodiment, the detector 20 is installed on a coating line where the object to be measured is coated, and detects the thickness or basis weight of the object at each detection position using the transmission intensity obtained by irradiating the object with β rays, X-rays, or infrared rays. Therefore, this process can improve the accuracy of measuring the thickness or basis weight on the coating line.

[0192] [6. System] The information including the processing procedures, control procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified.

[0193] Furthermore, the components of each device shown in the figure are conceptual functional components and do not necessarily have to be physically configured as shown. In other words, the specific form of distribution or integration of each device is not limited to that shown. In other words, all or part of the devices can be functionally or physically distributed or integrated in any unit depending on various loads, usage conditions, etc.

[0194] Furthermore, all or any part of the processing functions performed by each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware using wired logic.

[0195] [7. Hardware] Next, an example of the hardware configuration of the measurement device 10 will be described. Note that other devices may also have a similar hardware configuration. FIG. 24 is a diagram showing an example of the hardware configuration according to an embodiment. As shown in FIG. 24, the measurement device 10 has a communication device 10a, an HDD (Hard Disk Drive) 10b, a memory 10c, and a processor 10d. Furthermore, the components shown in FIG. 24 are connected to each other via a bus or the like.

[0196] The communication device 10a is a network interface card or the like, and communicates with other servers. The HDD 10b stores programs and databases that operate the functions shown in FIG.

[0197] The processor 10d reads out from the HDD 10b or the like a program that executes the same processes as the respective processing units shown in FIG. 6 and loads it into the memory 10c, thereby operating a process that executes each function described in FIG. 6 or the like. For example, this process executes the same functions as the respective processing units of the measurement device 10. Specifically, the processor 10d reads out from the HDD 10b or the like a program that has the same functions as the collection unit 15a, the first smoothing unit 15b, the second smoothing unit 15c, and the like. Then, the processor 10d executes a process that executes the same processes as the collection unit 15a, the first smoothing unit 15b, the second smoothing unit 15c, and the like.

[0198] In this way, the measuring device 10 operates as a device that executes various processing methods by reading and executing a program. The measuring device 10 can also realize the same functions as the embodiments by reading the program from a recording medium using a media reader and executing the read program. Note that the program is not limited to being executed by the measuring device 10. For example, the present invention can also be applied in a similar manner to cases where another computer or server executes the program, or where these execute the program in cooperation with each other.

[0199] This program can be distributed via a network such as the Internet. In addition, this program can be recorded on a computer-readable recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, a magneto-optical disk (MO), or a digital versatile disk (DVD), and can be executed by being read from the recording medium by a computer.

[0200] [8. Other] Some examples of combinations of the disclosed technical features are set out below.

[0201] (1) A measuring device comprising: a collection unit that collects, from a detection device, a detection profile including multiple detection values ​​related to the thickness or basis weight of a sheet-like measurement object being sent out; and a first smoothing unit that uses a predetermined filter to smooth the multiple detection values ​​included in the detection profile in a width direction perpendicular to the sending direction of the measurement object, and outputs a first smoothed profile.

[0202] (2) The measuring device described in (1) further includes a second smoothing unit that uses the predetermined filter to smooth the plurality of detection values ​​smoothed in the width direction included in the first smoothed profile in the transmission direction, and outputs a second smoothed profile.

[0203] (3) The measurement device according to (1) or (2), wherein the predetermined filter is a moving average filter.

[0204] (4) The measurement device according to any one of (1) to (3), wherein the predetermined filter is a median filter.

[0205] (5) The measurement device according to any one of (1) to (4), wherein the predetermined filter is a Gaussian filter.

[0206] (6) The measurement device according to any one of (1) to (5), wherein the predetermined filter is a thresholded moving average filter.

[0207] (7) The measurement device according to any one of (1) to (6), wherein the predetermined filter is a median filter with a threshold.

[0208] (8) The measurement device according to any one of (1) to (7), wherein the predetermined filter is a Gaussian filter with a threshold.

[0209] (9) The measuring device according to any one of (1) to (8), wherein the detection device is installed in a coating line where the object to be measured is coated, and detects the thickness or basis weight of each detection position of the object to be measured using transmission intensity obtained by irradiating the object to be measured with beta rays, X-rays, or infrared rays.

[0210] (10) A measurement method in which a computer collects from a detection device a detection profile including multiple detection values ​​related to the thickness or basis weight of a sheet-like measurement object being sent out, uses a predetermined filter to smooth the multiple detection values ​​included in the detection profile in a width direction perpendicular to the sending direction of the measurement object, and outputs a first smoothed profile.

[0211] (11) A measurement program that causes a computer to execute a process of collecting, from a detection device, a detection profile including multiple detection values ​​related to the thickness or basis weight of a sheet-like measurement object being sent out, smoothing the multiple detection values ​​included in the detection profile in a width direction perpendicular to the sending direction of the measurement object using a predetermined filter, and outputting a first smoothed profile. [Explanation of symbols]

[0212] 10. Measuring equipment 10a Communication equipment 10b HDD 10c memory 10d processor 11 Input section 12 Output section 13 Communications Department 14 Storage section 14a Detection result storage unit 14b First smoothing result storage section 14c Second smoothing result storage section 15 Control Unit 15a Collection Section 15b 1st smoothing section 15c 2nd smoothing section 20 Detection equipment 21 Frame section 22 Sensor section 23 Control Unit 100 Coating Weight Measurement System

Claims

1. a collection unit that collects a detection profile including a plurality of detection values ​​relating to the thickness or basis weight of the sheet-like measurement object being delivered from the detection device; a first smoothing unit that smooths the plurality of detection values ​​included in the detection profile in a width direction perpendicular to the sending direction of the measurement object using a predetermined filter, and outputs a first smoothed profile; A measuring device comprising:

2. a second smoothing unit that smooths, in the transmission direction, the plurality of detection values ​​that have been smoothed in the width direction and are included in the first smoothed profile using the predetermined filter, and outputs a second smoothed profile; The measurement device of claim 1 further comprising:

3. The predetermined filter is a moving average filter.

3. The measuring device according to claim 1 or 2.

4. The predetermined filter is a median filter.

3. The measuring device according to claim 1 or 2.

5. The predetermined filter is a Gaussian filter.

3. The measuring device according to claim 1 or 2.

6. The predetermined filter is a thresholded moving average filter.

3. The measuring device according to claim 1 or 2.

7. The predetermined filter is a thresholded median filter.

3. The measuring device according to claim 1 or 2.

8. The predetermined filter is a thresholded Gaussian filter.

3. The measuring device according to claim 1 or 2.

9. The detection device is installed in a coating line in which the object to be measured is coated, and calculates the thickness or basis weight at each detection position of the object to be measured using a transmission intensity detected by irradiating the object to be measured with β rays, X-rays, or infrared rays.

3. The measuring device according to claim 1 or 2.

10. The computer collecting a detection profile from the detection device, the detection profile including a plurality of detection values ​​relating to the thickness or basis weight of the sheet-like measurement object being delivered; smoothing the plurality of detection values ​​included in the detection profile in a width direction perpendicular to the sending direction of the measurement object using a predetermined filter, and outputting a first smoothed profile; The measurement method by which the process is performed.

11. On the computer, collecting a detection profile from the detection device, the detection profile including a plurality of detection values ​​relating to the thickness or basis weight of the sheet-like measurement object being delivered; smoothing the plurality of detection values ​​included in the detection profile in a width direction perpendicular to the sending direction of the measurement object using a predetermined filter, and outputting a first smoothed profile; A measurement program that executes the process.

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