A Dynamic Measurement Accuracy Estimation Method Based on Loss-of-Weight Screw Speed ​​Data

Abstract

This invention provides a dynamic metering accuracy estimation method based on loss-in-weight weighing (CIW) screw speed data. The method includes: extracting and segmenting the actual screw speed data; performing linear regression analysis on the segmented data; predicting the theoretical screw speed during the feeding stage based on the linear regression analysis results; and calculating the dynamic metering accuracy of the screw cycle. This invention's dynamic metering accuracy estimation method based on CIW screw speed data can solve the problem of low dynamic metering accuracy in existing CIWs, which affects the accuracy of batching.

Description

Technical Field

[0001] This invention relates to the field of loss-in-weight weighing technology, and more specifically, to a method for estimating dynamic measurement accuracy based on loss-in-weight weighing screw speed data. Background Technology

[0002] In industrial applications, to ensure product consistency, material proportions must strictly adhere to the formula, necessitating precise material measurement, as seen in lithium battery manufacturing. In continuous production equipment, the feeding system employs a loss-in-weight scale to continuously feed material at a set flow rate. Current technology operates in volumetric mode during the loss-in-weight scale replenishment and post-replenishment stabilization phases. This means the discharge screw operates at the speed prior to replenishment or the average speed over a previous period, recording only weight data without closed-loop feedback; the replenishment phase remains a measurement blind spot.

[0003] In the prior art known to the inventor, dynamic metering accuracy is calculated based on the weight loss during the non-replenishment stage, which cannot truly reflect the actual dynamic metering accuracy and greatly affects the accuracy of batching. Summary of the Invention

[0004] The main objective of this invention is to provide a dynamic metering accuracy estimation method based on the screw speed data of a loss-in-weight weigher, which can solve the problem of low dynamic metering accuracy of existing loss-in-weight weighers, affecting the accuracy of batching.

[0005] To achieve the above objectives, according to one aspect of the present invention, a dynamic measurement accuracy estimation method based on loss-in-weight weighing screw speed data is provided, comprising:

[0006] Extract and segment the actual screw speed data;

[0007] Linear regression analysis of screw speed data was performed based on segmented data;

[0008] The theoretical screw speed during the feeding stage is predicted based on the results of linear regression analysis.

[0009] Calculate the dynamic metering accuracy of the screw cycle.

[0010] Furthermore, the step of extracting and segmenting the screw speed data includes:

[0011] The trigger interval between two consecutive material replenishments is defined as one cycle;

[0012] The actual rotational speed data of the loss-of-weight scale screw collected in one cycle is divided into two data sequences, V1 and V2, which correspond to the volume mode segment and the closed-loop control segment, respectively.

[0013] The actual screw speed V2 in the closed-loop control section is divided into two data sequences V. 21 V 22 .

[0014] Furthermore, the actual screw speed V2 in the closed-loop control section is divided into two data sequences V. 21 V 22 The steps include:

[0015] Using the minimum value of the actual screw speed sequence V2 in the closed-loop control section as the dividing point J, the actual screw speed V2 in the closed-loop control section is divided into two data sequences V. 21 V 22 .

[0016] Furthermore, the step of performing linear regression analysis on the screw speed data based on the segmented data includes:

[0017] For data sequence V 22 Perform linear regression analysis to obtain the regression line of the closed-loop control segment;

[0018] The theoretical screw rotation speed between the time of material replenishment completion and the breakpoint J is estimated based on the regression line.

[0019] Furthermore, the step of predicting the theoretical screw speed during the feeding stage based on the linear regression analysis results includes:

[0020] Linear regression was performed based on the actual screw speed just before replenishment and the estimated actual screw speed at the time of replenishment completion to estimate the theoretical screw speed during the replenishment phase.

[0021] Furthermore, the step of performing linear regression based on the actual screw speed at the moment before replenishment and the estimated actual screw speed at the moment of replenishment completion includes:

[0022] The theoretical screw rotation speed line for the second half of the feeding process is determined based on the regression line between the feeding completion time and the boundary point J.

[0023] Determine the time point at which the weight loss value reaches its maximum;

[0024] The time point at which the theoretical screw speed is minimum is determined based on the time point at which the weight loss value is maximum.

[0025] The theoretical screw speed corresponding to the time point when the theoretical screw speed is at its minimum is determined by the linear curve of the theoretical screw speed in the second half of the feeding process.

[0026] The linear curve of the actual screw speed in the first half of the feeding process is determined by the time point corresponding to the minimum theoretical screw speed at the moment before feeding and the actual screw speed.

[0027] Furthermore, the screw cycle dynamic metering accuracy e is calculated using the following formula:

[0028]

[0029] Where {V1,V 21} represents the data sequence V1, V 21 The set, For data sequences The set of , sum is the summation function, τ is the time between the start of feeding and the boundary point J, and T is the cycle time.

[0030] Furthermore, the dynamic measurement accuracy estimation method also includes:

[0031] Obtain dynamic measurement accuracy for multiple consecutive cycles;

[0032] The dynamic measurement accuracy of the screw speed data of the loss-in-weight weigher is calculated based on the dynamic measurement accuracy of multiple consecutive cycles.

[0033] Furthermore, the volumetric mode segment represents the constant speed stage of the actual screw rotation speed, while the closed-loop control segment represents the variable speed stage of the actual screw rotation speed.

[0034] Furthermore, the step of performing linear regression analysis on the screw speed data based on the segmented data also includes:

[0035] The stable time t1 of the actual screw speed in the uniform speed stage after the feeding is completed;

[0036] Obtain the replenishment time t2;

[0037] Obtain the ratio t1 / t2 of t1 and t2;

[0038] When t1 / t2≤1 / 4

[0039] The steps for performing linear regression analysis on screw speed data based on segmented data include:

[0040] For data sequence V 22 Perform linear regression analysis and estimate the actual screw speed at the breakpoint J based on the regression line;

[0041] The steps for predicting the theoretical screw speed during the feeding stage based on the results of linear regression analysis include:

[0042] The theoretical screw speed during the feeding phase is estimated by performing linear regression between the actual screw speed immediately before feeding and the actual screw speed at the breakpoint J.

[0043] The steps for calculating the dynamic metering accuracy of the screw cycle include:

[0044] The periodic dynamic measurement accuracy e is calculated using the following formula:

[0045]

[0046] Where {V1,V 21} represents sequences V1, V 21 The set of , sum is the summation function, τ is the time between the start of feeding and the boundary point J, and T is the cycle time.

[0047] The present invention provides a method for estimating dynamic metering accuracy based on screw speed data from a loss-in-weight weighing system. This method includes: extracting and segmenting the actual screw speed data; performing linear regression analysis on the segmented data; predicting the theoretical screw speed during the replenishment stage based on the linear regression analysis results; and calculating the dynamic metering accuracy of the screw cycle. This dynamic metering accuracy estimation method segments the actual screw speed data, then uses the determined segmented data to obtain the theoretical screw speed data. By performing linear regression on the obtained theoretical screw speed data, the theoretical screw speed during the replenishment stage is predicted. This allows the metering accuracy of the replenishment stage, which is a metering blind zone, to be represented by a linear function. Furthermore, the linear function obtained from the linear regression of the replenishment stage can be used to determine the dynamic metering accuracy of the replenishment stage, calculate the cycle dynamic metering accuracy, and achieve accurate estimation of dynamic metering accuracy in continuous production. This enables the dynamic accuracy measurement of the loss-in-weight weighing system to more accurately reflect the true accuracy, greatly improving the accuracy of batching. Attached Figure Description

[0048] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0049] Figure 1 A flowchart illustrating a dynamic measurement accuracy estimation method based on loss-of-weight scale screw speed data according to an embodiment of the present invention is shown.

[0050] Figure 2 This invention illustrates a dynamic metrological accuracy estimation method based on loss-in-weight weighing screw speed data according to an embodiment of the present invention, showing the relationship between screw speed data and loss-in-weight weighing weight over one cycle; and...

[0051] Figure 3 A graph showing the relationship between screw speed data and weight loss of a weighing scale in one cycle is illustrated in another embodiment of the present invention, which is a dynamic measurement accuracy estimation method based on screw speed data of a weighing scale. Detailed Implementation

[0052] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0053] See also Figures 1 to 3 As shown, this invention provides a dynamic measurement accuracy estimation method based on loss-in-weight weighing screw speed data, including:

[0054] Extract and segment the actual screw speed data;

[0055] Linear regression analysis of screw speed data was performed based on segmented data;

[0056] The theoretical screw speed during the feeding stage is predicted based on the results of linear regression analysis.

[0057] Calculate the dynamic metering accuracy of the screw cycle.

[0058] This dynamic metering accuracy estimation method segments the actual screw speed data, then uses the determined segmented data to obtain the theoretical screw speed data. By performing linear regression on the obtained theoretical screw speed data, the theoretical screw speed during the feeding stage is predicted. This allows the metering accuracy of the feeding stage, which is a metering blind zone, to be represented by a linear function. Furthermore, the dynamic metering accuracy of the feeding stage can be determined using the linear function obtained from the linear regression, and the periodic dynamic metering accuracy can be calculated. This enables accurate estimation of the dynamic metering accuracy in continuous production, allowing the dynamic accuracy measurement of the loss-in-weight scale to more accurately reflect the true accuracy and greatly improving the accuracy of batching.

[0059] In this embodiment, during the material proportioning process, the actual screw speed of a portion of the screws matches the theoretical screw speed. Therefore, a linear regression analysis method can be used to obtain a linear function of the theoretical screw speed of this portion based on the changes in the theoretical screw speed. After determining the linear function, the theoretical screw speed of the portion where the actual screw speed does not match the theoretical screw speed can be deduced using the straight line determined by the linear function. This method can provide a basis for dynamic accuracy measurement during the replenishment stage, thereby providing a basis for calculating the weight change accuracy of the loss-in-weight scale. The weight change of the loss-in-weight scale can be calculated based on the dynamic measurement accuracy of the screw speed data of the loss-in-weight scale, which in turn allows for adjustment of the material proportioning. This makes the material proportioning throughout the entire cycle controllable and more accurate, and can more effectively improve the accuracy and reliability of material proportioning.

[0060] In one embodiment, the step of extracting and segmenting the screw speed data includes:

[0061] The trigger interval between two consecutive material replenishments is defined as one cycle;

[0062] The actual rotational speed data of the loss-of-weight scale screw collected in one cycle is divided into two data sequences, V1 and V2, which correspond to the volume mode segment and the closed-loop control segment, respectively.

[0063] The actual screw speed V2 in the closed-loop control section is divided into two data sequences V. 21 V 22 .

[0064] In this embodiment, the trigger interval between two adjacent feedings is defined as a cycle. The working cycle of the loss-in-weight scale can be divided according to its working principle, so that the cycle division of the loss-in-weight scale matches its working principle. The cycle division is more reasonable, which can obtain more accurate and reliable data in subsequent dynamic measurement accuracy estimation, and can also effectively reduce the difficulty of dynamic measurement accuracy estimation.

[0065] In one embodiment, the volume mode segment is the constant speed stage of the actual screw rotation speed, and the closed-loop control segment is the variable speed stage of the actual screw rotation speed.

[0066] During the operation of the loss-in-weight weigher, the screw has a uniform speed working stage and a variable speed working stage. The uniform speed working stage includes a stage where feeding and replenishment coexist and a stage where feeding is performed alone. The variable speed working stage is a stage where feeding is performed alone. The volume mode segment and the closed-loop control segment are divided by using the uniform speed and variable speed stages of the screw's actual rotational speed. The linear function of the screw's theoretical rotational speed in the closed-loop control segment can be determined based on the changes in the screw's actual rotational speed in the closed-loop control segment. This linear function can be used to deduce the linear function of the feeding stage where feeding is performed alone during the uniform speed working stage. Furthermore, the theoretical rotational speed of the screw during the feeding stage where feeding and replenishment coexist during the uniform speed working stage can be calculated using the linear function of the feeding stage where feeding is performed alone during the uniform speed working stage and the actual rotational speed of the screw just before feeding.

[0067] In one embodiment, the actual screw rotation speed V2 of the closed-loop control section is divided into two data sequences V. 21 V 22 The steps include:

[0068] Using the minimum value of the actual screw speed sequence V2 in the closed-loop control section as the dividing point J, the actual screw speed V2 in the closed-loop control section is divided into two data sequences V. 21 V 22 .

[0069] In one embodiment, the step of performing linear regression analysis on screw speed data based on segmented data includes:

[0070] For data sequence V 22 Perform linear regression analysis to obtain the regression line of the closed-loop control segment;

[0071] The theoretical screw rotation speed between the time of material replenishment completion and the breakpoint J is estimated based on the regression line.

[0072] In this embodiment, since the minimum value of the actual screw speed sequence V2 in the closed-loop control section is the starting point when the actual screw speed and the theoretical screw speed are in the same range, the actual screw speed V2 in the closed-loop control section can be divided into two data sequences V2 based on this starting point. 21 V 22 After dividing the data into two segments, since the minimum value can be determined, and the actual screw speed just before feeding can also be determined, it is equivalent to determining V. 22 Given the values ​​at both endpoints, the data sequence V can be calculated in this case. 22 A linear function, due to the data sequence V 21 Linear functions and data sequences V 22 The linear functions are the same, and the data sequence V 21 The line segment is located in data sequence V 22 The extension end of the line segment, and the two relative to the boundary point J, therefore, in calculating the data sequence V 22 After obtaining the linear function, the linear regression method can be used to inversely deduce the data sequence V. 21 Based on the regression line, the screw speed data of the loss-in-weight weighing system in the volumetric mode segment can be further estimated to determine the linear function of the screw speed in the volumetric mode segment.

[0073] In one embodiment, the step of predicting the theoretical screw speed during the feeding stage based on the results of linear regression analysis includes:

[0074] Linear regression was performed based on the actual screw speed just before replenishment and the estimated actual screw speed at the time of replenishment completion to estimate the theoretical screw speed during the replenishment phase.

[0075] In one embodiment, the step of performing linear regression based on the actual screw speed at the moment before replenishment and the estimated actual screw speed at the moment of replenishment completion includes:

[0076] The theoretical screw rotation speed line for the second half of the feeding process is determined based on the regression line between the feeding completion time and the boundary point J.

[0077] Determine the time point at which the weight loss value reaches its maximum;

[0078] The time point at which the theoretical screw speed is minimum is determined based on the time point at which the weight loss value is maximum.

[0079] The theoretical screw speed corresponding to the time point when the theoretical screw speed is at its minimum is determined by the linear curve of the theoretical screw speed in the second half of the feeding process.

[0080] The linear curve of the actual screw speed in the first half of the feeding process is determined by the time point corresponding to the minimum theoretical screw speed at the moment before feeding and the actual screw speed.

[0081] In this embodiment, the maximum value of the loss-in-weight weighing is essentially relative to the minimum value of the theoretical screw speed. Therefore, by determining the moment when the loss-in-weight weighing reaches its maximum value, the moment when the minimum value of the theoretical screw speed is located can be determined. Since the minimum value of the theoretical screw speed is also located on the linear regression line of the theoretical screw speed obtained in the aforementioned manner, determining the theoretical screw speed at that moment on the linear regression line also determines the minimum value of the theoretical screw speed. At the same time, since the actual screw speed is determined just before feeding, the values ​​of the starting and ending points of the theoretical screw speed during the feeding stage are also determined. Based on the values ​​of the starting and ending points of the theoretical screw speed during the feeding stage, the linear function of the theoretical screw speed during the feeding stage can be determined. Furthermore, the weight accuracy of the loss-in-weight weighing can be calculated based on this linear function and the determined theoretical screw speed.

[0082] In one embodiment, the screw cycle dynamic metering accuracy e is calculated using the following formula:

[0083]

[0084] Where {V1,V 21} represents the data sequence V1, V 21 The set, For data sequences The set of , sum is the summation function, τ is the time between the start of feeding and the boundary point J, and T is the cycle time.

[0085] In this embodiment, {V1,V 21} represents the data sequence V1, V 21 The set consists of V1 and V1 within the same period range. 21 The set formed by the combination of numerical values, For data sequences The set consists of elements within the same periodic range. The set of numerical combinations can be used to calculate the dynamic metering accuracy e of the screw cycle through the above method.

[0086] In one embodiment, the dynamic measurement accuracy estimation method further includes:

[0087] Obtain dynamic measurement accuracy for multiple consecutive cycles;

[0088] The dynamic measurement accuracy of the screw speed data of the loss-in-weight weigher is calculated based on the dynamic measurement accuracy of multiple consecutive cycles.

[0089] When calculating the dynamic measurement accuracy of the screw speed data of a loss-in-weight weigher, it can be calculated by averaging the dynamic measurement accuracy of multiple consecutive periods, or by using the variance method.

[0090] In one embodiment, the method further includes the following step before performing linear regression analysis of screw speed data based on segmented data:

[0091] The stable time t1 of the actual screw speed in the uniform speed stage after the feeding is completed;

[0092] Obtain the replenishment time t2;

[0093] Obtain the ratio t1 / t2 of t1 and t2;

[0094] When t1 / t2≤1 / 4

[0095] The steps for performing linear regression analysis on screw speed data based on segmented data include:

[0096] For data sequence V 22 Perform linear regression analysis and estimate the actual screw speed at the breakpoint J based on the regression line;

[0097] The steps for predicting the theoretical screw speed during the feeding stage based on the results of linear regression analysis include:

[0098] The theoretical screw speed during the feeding phase is estimated by performing linear regression between the actual screw speed immediately before feeding and the actual screw speed at the breakpoint J.

[0099] The steps for calculating the dynamic metering accuracy of the screw cycle include:

[0100] The periodic dynamic measurement accuracy e is calculated using the following formula:

[0101]

[0102] Where {V1,V 21} represents sequences V1, V 21 The set of , sum is the summation function, τ is the time between the start of feeding and the boundary point J, and T is the cycle time.

[0103] In this embodiment, when the ratio between the stabilization time t1 and the feeding time t2 of the screw's actual rotational speed after feeding is less than or equal to 1 / 4, it is considered that the stabilization time after feeding is much shorter than the feeding time. In this case, the stabilization time after feeding can be ignored, and the dividing point J is directly used as the end point of the theoretical screw rotational speed in the feeding stage. The actual screw rotational speed just before feeding is used as the starting point of the theoretical screw rotational speed in the feeding stage. The screw rotational speed in the feeding stage is estimated using linear regression. It can significantly reduce the workload of calculations, simplify the dynamic measurement accuracy estimation method based on loss-in-weight scale screw speed data, make the overall calculation process easier to implement, and improve calculation efficiency.

[0104] Through the above embodiments, the present invention proposes a dynamic metering accuracy estimation method based on loss-in-weight weighing screw speed data. The start time of two adjacent feeding cycles is defined as a cycle, and each cycle is divided into a volume mode stage and a closed-loop control stage. Linear regression analysis is performed on the loss-in-weight weighing screw speed data in the closed-loop control stage to estimate the theoretical screw speed in the volume mode stage, thereby calculating the cycle metering accuracy and subsequently estimating the dynamic metering accuracy for continuous production.

[0105] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0106] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in sequences other than those illustrated or described herein.

[0107] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A dynamic metrology accuracy estimation method based on loss-in-weight scale screw speed data, characterized by, The method comprises the following steps: extracting and segmenting the screw actual speed data; performing linear regression analysis on the segmented data; predicting the screw theoretical speed during the feeding stage according to the linear regression analysis result; calculating the screw periodic dynamic metering accuracy; the step of extracting and segmenting the screw speed data comprises: setting the interval between two adjacent feedings as a period; dividing the weight loss scale screw actual speed data collected in one period into two data sequences V1 and V2, which correspond to the volume mode segment and the closed-loop control segment, respectively; The closed-loop control section screw actual speed V2 is divided into two data sequences V 21 , V 22 ; The step of dividing the actual speed V2 of the closed-loop control section screw into two data sequences V 21 , V 22 includes: With the minimum value of the actual speed sequence V2 of the closed-loop control section screw as the demarcation point J, the actual speed V2 of the closed-loop control section screw is divided into two data sequences V 21 , 22 ; the step of performing linear regression analysis on the segmented data comprises: A linear regression analysis is performed on the data sequence V 22 to obtain a regression straight line of the closed-loop control section. According to the regression straight line, the theoretical rotation speed of the screw between the moment when the feeding is completed and the moment J of the demarcation point is estimated ; the step of predicting the screw theoretical speed during the feeding stage according to the linear regression analysis result comprises: According to the actual screw speed at the moment before feeding and the estimated actual screw speed at the moment when the feeding is completed, linear regression is performed to estimate the theoretical screw speed during the feeding stage ; the step of performing linear regression analysis on the segmented data comprises: determining the screw theoretical speed linear line in the second half of the feeding according to the regression straight line between the feeding completion time point and the demarcation point J; determining the time point of the maximum weight loss scale weight value; determining the time point of the minimum screw theoretical speed according to the time point of the maximum weight loss scale weight value; determining the screw theoretical speed corresponding to the time point of the minimum screw theoretical speed according to the screw theoretical speed linear line in the second half of the feeding; determining the screw actual speed linear line in the first half of the feeding according to the screw actual speed at the moment before feeding and the screw theoretical speed corresponding to the time point of the minimum screw theoretical speed.

2. The dynamic metrology accuracy estimation method of claim 1, wherein, The screw periodic dynamic metering accuracy e is calculated by the following formula: ， wherein is a set of data sequences V1, V 21 , is a set of data sequences , , is the time from the start of the feed to the point J, T is the cycle time.

3. The method of claim 1, wherein, The dynamic metering accuracy estimation method further comprises: obtaining a plurality of continuous periodic dynamic metering accuracies; calculating the dynamic metering accuracy of the weight loss scale screw speed data according to the plurality of continuous periodic dynamic metering accuracies.

4. The method of claim 1, wherein, The volume mode segment is the uniform speed stage of the screw actual speed, and the closed-loop control segment is the variable speed stage of the screw actual speed.

5. The method of claim 1, wherein, Before the step of performing linear regression analysis on the segmented data, the method further comprises the following steps: obtaining the stable time t1 of the screw actual speed in the uniform speed stage after the feeding is completed; obtaining the feeding time t2; obtaining the ratio t1 / t2 of t1 and t2; when t1 / t2≤1 / 4, the step of performing linear regression analysis on the segmented data comprises: A linear regression analysis is performed on the data sequence V 22 The actual screw speed at the demarcation point J is estimated according to the regression line. the step of predicting the screw theoretical speed during the feeding stage according to the linear regression analysis result comprises: According to linear regression of the actual screw speed at the moment before feeding and the actual screw speed at the moment of the demarcation point J, the theoretical screw speed during the feeding stage is estimated ; the step of calculating the screw periodic dynamic metering accuracy comprises: the periodic dynamic metering accuracy e is calculated by the following formula: ， wherein is the set of sequences V1, V 21 is the sum function, is the time from the beginning of the feed to the point J, T is the cycle time.

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