Method, system, equipment, medium and program product for confirming the working condition of slitting line system

Abstract

The present invention provides a method, system, device, medium and program product for confirming the working condition of a slitting line system, the method comprising: obtaining equipment data of the slitting line system within a target time range, the equipment data comprising: motor speed data, slitting line system switch quantity, slitting line feeding data and slitting line discharging data; based on the equipment data, determining multiple steel coil intervals within the target time range; performing work order interval identification based on the equipment data and the steel coil interval, determining multiple work order intervals for each of the steel coil intervals; performing working condition identification based on the equipment data and the work order interval, determining the working condition interval within each of the work order intervals. The present invention can more accurately confirm the operation and status of each stage, improve the recognition accuracy of the actual working condition of the slitting line, and improve the recognition accuracy of multiple working conditions in complex equipment steel coils and unclear work order divisions.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of transformer technology, and in particular to a method, system, device, medium and program product for confirming the working condition of a slitting line system. Background Art

[0002] The existing technology can only distinguish the on / off status and production shutdown status of the slitting line equipment through a single switch quantity change and a fixed threshold, and cannot subdivide other stages that are not controlled by the switch quantity; and the fixed threshold method will also make it difficult to distinguish whether the slitting line system is in the production operation state or the equipment debugging state, and the thresholds of different types of steel are difficult to determine; there is no accurate way to eliminate problems such as false switch touches and abnormal feeding, resulting in low accuracy in the recognition of the slitting line system status; further, there is no accurate start and end signal recognition method for the tool change time that accounts for a large proportion of the time in the production line. Now the factory's requirements for leanness and efficiency are gradually increasing, and the existing technology can no longer meet the accurate recognition of the actual working conditions of the slitting line. Summary of the invention

[0003] The embodiments of the present invention provide a method, system, device, medium and program product for confirming the working condition of a slitting line system, so as to solve the problem that the actual working condition of the slitting line cannot be accurately identified in the prior art.

[0004] In order to solve the above-mentioned technical problems, the present invention is achieved as follows:

[0005] In a first aspect, an embodiment of the present invention provides a method for confirming the operating condition of a slitting line system, comprising:

[0006] Acquire equipment data of the slitting line system within the target time range, the equipment data including: motor speed data, slitting line system switch quantity, slitting line feeding data and slitting line discharging data;

[0007] Based on the equipment data, determining a plurality of steel coil intervals within a target time range;

[0008] Perform work order interval identification based on the equipment data and the steel coil interval, and determine multiple work order intervals for each of the steel coil intervals;

[0009] The operating condition is identified based on the equipment data and the work order interval, and the operating condition interval within each work order interval is determined.

[0010] Optionally, the determining of the working condition interval within each work order interval further includes:

[0011] Determining a work order execution efficiency index for the work order interval based on the working condition interval within the work order interval, wherein the work order execution efficiency index includes at least one of the following: work order tool change time, work order start-up rate, and work order cutting speed;

[0012] Based on the work order execution efficiency index, the work order execution efficiency of the work order interval is determined.

[0013] Optionally, the determining of multiple steel coil intervals within the target time range includes:

[0014] Fitting an actual data curve according to the slitting line feeding data to obtain first main line data;

[0015] Based on the first main line data, calculating the lifting index of the slitting line feeding data, and determining the step characteristics of the slitting line feeding data;

[0016] Based on the slitting line feeding data, the slitting line system switching quantity and the step characteristics of the slitting line feeding data, the steel coil interval is divided through the steel coil recognition model to determine multiple steel coil intervals within the target time range.

[0017] Optionally, the determining of the multiple work order intervals of each of the steel coil intervals includes:

[0018] For each of the steel coil sections, an actual data curve is fitted according to the discharge data of the slitting line to obtain second main line data;

[0019] Based on the second main line data, calculating the rise and fall index of the slitting line discharge data, and determining the step characteristics of the slitting line discharge data;

[0020] Based on the discharging data of the slitting line, the switching quantity of the slitting line system and the step characteristics of the discharging data of the slitting line, the work order intervals are divided through the work order recognition model to determine multiple work order intervals for each of the steel coil intervals.

[0021] Optionally, determining the working condition interval within each work order interval includes:

[0022] For each work order interval, an actual data curve is fitted according to the motor speed data and the switch quantity of the slitting line system to obtain the third main line data;

[0023] Based on the third main line data, determining the amplitude index of the motor speed data and the amplitude index of the switching quantity of the slitting line system;

[0024] Based on the third main line data, calculating the lifting index of the motor speed data and the lifting index of the switch quantity of the slitting line system, the step characteristics of the motor speed data and the step characteristics of the switch quantity of the slitting line system;

[0025] Based on the motor speed data, the slitting line system switch quantity, the amplitude index of the motor speed data, the amplitude index of the slitting line system switch quantity, the step characteristics of the motor speed data and the step characteristics of the slitting line system switch quantity, the working conditions within the work order are divided through the work order recognition model to determine the working condition interval within each work order interval.

[0026] Optionally, the step of acquiring the equipment data of the slitting line system within the target time range further includes:

[0027] The device data is preprocessed, wherein the preprocessing includes at least one of the following: timestamp alignment, outlier processing, and missing value filling.

[0028] In a second aspect, an embodiment of the present invention provides a system for confirming the working condition of a slitting line system, comprising:

[0029] An acquisition module is used to acquire equipment data of the slitting line system within a target time range, wherein the equipment data includes: motor speed data, slitting line system switch quantity, slitting line feeding data, and slitting line discharging data;

[0030] A steel coil module, for determining a plurality of steel coil intervals within a target time range based on the equipment data;

[0031] A work order module, used for identifying work order intervals based on the equipment data and the steel coil intervals, and determining a plurality of work order intervals for each of the steel coil intervals;

[0032] The working condition module is used to identify the working condition based on the equipment data and the work order interval, and determine the working condition interval within each work order interval.

[0033] In a third aspect, an embodiment of the present invention provides an electronic device, comprising: a processor, a memory, and a program stored in the memory and executable on the processor, wherein when the program is executed by the processor, the steps of the method for confirming the operating condition of the longitudinal shearing line system as described in the first aspect above are implemented.

[0034] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method for confirming the operating condition of the longitudinal shearing line system as described in the first aspect above are implemented.

[0035] In a fifth aspect, a computer program product is provided, comprising computer instructions, which, when executed by a processor, implement the steps of the method for confirming the operating condition of the longitudinal shearing line system as described in the first aspect above.

[0036] In the present invention, by acquiring the equipment data of the slitting line system within the target time range, the equipment data includes: motor speed data, slitting line system switch quantity, slitting line feeding data and slitting line discharging data; based on the equipment data, multiple steel coil intervals within the target time range are determined; work order intervals are identified based on the equipment data and the steel coil intervals, and multiple work order intervals of each steel coil interval are determined; working condition identification is performed based on the equipment data and the work order intervals, and the working condition intervals within each work order interval are determined. In the present invention, by refining layer by layer, the operation and status of each stage can be confirmed more accurately, the recognition accuracy of the actual working condition of the slitting line can be improved, and the recognition accuracy of various working conditions in the case of complex equipment steel coils and unclear work order divisions can be improved. The use of abundant equipment data to achieve accurate identification of the working conditions of the slitting line system provides a solid foundation for the subsequent calculation of the work order execution efficiency from multiple dimensions. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0038] Figure 1 It is a flow chart of a method for confirming the working condition of a slitting line system provided by an embodiment of the present invention;

[0039] Figure 2 is a flow chart of another method for confirming the working condition of a slitting line system provided by an embodiment of the present invention;

[0040] Figure 3 It is a specific flow chart of a method for confirming the working condition of a slitting line system provided by an embodiment of the present invention;

[0041] Figure 4 It is a structural schematic diagram of a slitting line system working condition confirmation system provided by an embodiment of the present invention;

[0042] Figure 5 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] Please refer to Figure 1 , Figure 2 and Figure 3 The embodiment of the present invention provides a method for confirming the working condition of a slitting line system, comprising:

[0045] Step 11: Acquire the equipment data of the slitting line system within the target time range, wherein the equipment data includes: motor speed data, slitting line system switch quantity, slitting line feeding data and slitting line discharging data;

[0046] Step 12: determining a plurality of steel coil intervals within a target time range based on the equipment data;

[0047] Step 13: performing work order interval identification based on the equipment data and the steel coil interval, and determining a plurality of work order intervals for each of the steel coil intervals;

[0048] Step 14: Perform operating condition identification based on the equipment data and the work order interval, and determine the operating condition interval within each work order interval.

[0049] In the present invention, by acquiring the equipment data of the slitting line system within the target time range, the equipment data includes: motor speed data, slitting line system switch quantity, slitting line feeding data and slitting line discharging data; based on the equipment data, multiple steel coil intervals within the target time range are determined; work order intervals are identified based on the equipment data and the steel coil intervals, and multiple work order intervals of each steel coil interval are determined; working condition identification is performed based on the equipment data and the work order intervals, and the working condition intervals within each work order interval are determined. In the present invention, by refining layer by layer, the operation and status of each stage can be confirmed more accurately, the recognition accuracy of the actual working condition of the slitting line can be improved, and the recognition accuracy of various working conditions in the case of complex equipment steel coils and unclear work order divisions can be improved. The use of abundant equipment data to achieve accurate identification of the working conditions of the slitting line system provides a solid foundation for the subsequent calculation of the work order execution efficiency from multiple dimensions.

[0050] Optionally, in an embodiment of the present invention, the equipment data includes: motor speed data, slitting line system switch quantity, slitting line feeding data and slitting line discharging data;

[0051] Among them, the motor speed data includes: "unwinder motor speed" x_kj , “Slitting machine motor speed” x_zj , "Pinch roller motor speed" x_jg and "Winder motor speed" x_sj .

[0052] The switch quantity of the slitting line system includes "slitting line system automatic" x_zd , "End processing of slitting line system" x_db .

[0053] The feeding data of the slitting line includes: "Silicon steel coil winding length" x_jlcd , and "Feeding Silicon Steel Coil Diameter" x_jlzj .

[0054] The discharge data of the slitting line includes: "length of the feeding silicon steel coil" x_sjcd and "Silicon steel coil winding diameter" x_sjj .

[0055] Also includes, timestamp x_t , the time range of the data ( t 0 ，t 1 ).

[0056] Optionally, the step of acquiring equipment data of the slitting line system further includes:

[0057] The device data is preprocessed, wherein the preprocessing includes at least one of the following: timestamp alignment, outlier processing, and missing value filling.

[0058] Timestamp alignment ensures that records from different data sources remain consistent in the time dimension, making subsequent analysis comparable. By identifying and processing outliers, the analysis results are avoided from being affected. Data sets that may have missing values ​​are filled to ensure completeness and consistency. In the embodiment of the present invention, through the three main preprocessing steps of timestamp alignment, outlier processing and missing value filling, the quality and consistency of device data can be significantly improved, providing a solid foundation for subsequent data analysis and work order management.

[0059] Please refer to Figure 2 and Figure 3 Optionally, the multiple steel coil intervals within the target time range are determined to include:

[0060] Fitting an actual data curve according to the slitting line feeding data to obtain first main line data;

[0061] Based on the first main line data, calculating the lifting index of the slitting line feeding data, and determining the step characteristics of the slitting line feeding data;

[0062] Based on the slitting line feeding data, the slitting line system switching quantity and the step characteristics of the slitting line feeding data, the steel coil interval is divided through the steel coil recognition model to determine multiple steel coil intervals within the target time range.

[0063] Optionally, since the collected data of the slitting line feeding data may contain noise, the slitting line feeding data is fitted, and the main line curve M is obtained by fitting the actual data curve (slitting line feeding data) with one-dimensional convolution, that is, the "silicon steel coil winding length" x_jlcd , and "Feeding Silicon Steel Coil Diameter" x_jlzj Fitting into the main line, smoothing and removing noise, and obtaining the main line M_jlcd , M_jlz .

[0064] Optionally, the main line fitting formula is:

[0065] (1);

[0066] Among them, X is the original sequence, k is the set fitting k value, and k=4 is set here.

[0067] Optionally, based on the first main line data, the slitting line feeding data ("silicon steel coil winding length" x_ jlcd , and "Feeding Silicon Steel Coil Diameter" x_jlzj ) to obtain the step characteristics of the slitting line feeding and discharging data, and the obtained lifting index is recorded For L_jlcd, L_jlzj .

[0068] Optionally, the lift index refers to the difference within a section of the main line, recorded as Lift; the lift index calculation formula is:

[0069] (2);

[0070] Where M is the main line fitted by formula (1), lift_itv For the set lifting range, it can be set to 4. is the lifting index data length, and the difference of the main line in this interval is recorded as the lifting index of point i Lift[i] .

[0071] Optional, based on slitting line feed data ("Silicon steel coil winding length" x_jlcd , and "Feeding Silicon Steel Coil Diameter" x_ Jlj ), slitting line system switch quantity x_zd And its step characteristics, the steel coil interval is divided:

[0072] Optionally, the coil identification model is used to divide the coil into sections including:

[0073] Determine the rising step signal of the slitting line feed data;

[0074] Based on the rising step signal of the slitting line feed data, an initial steel coil interval is obtained;

[0075] Determine the descending step signal of the slitting line feed data;

[0076] Based on the descending step signal of the slitting line feeding data, the normal shearing interval and the abnormal shearing interval are obtained;

[0077] Based on the initial coil interval, normal shear interval and abnormal shear interval, the coil interval is determined. Specifically:

[0078] First, according to the step characteristics, find the slitting line feeding data x_jlcd、x_jlzj The rising step signal , recorded as the signal of the steel coil feeding to the slitting line system, the interval between every two steel coil feeding signals is an initial steel coil interval, recorded as ,in .

[0079] Secondly, according to the step characteristics, find the slitting line feeding data x_jlcd、x_jlzj The falling step signal This is the signal that the remaining material of the steel coil is unloaded from the slitting line system. The period between a pair of loading and unloading signals is recorded as the steel coil shearing interval, recorded as ,in .

[0080] In some cases, the system may classify some abnormal signals as shearing intervals, such as abnormal signals caused by false switch contact and abnormal feeding. Therefore, the embodiment of the present invention also eliminates abnormal signals through the following formula. Under normal circumstances, within a steel coil shearing interval, as the system automatically cuts (there is a switch of the slitting line system x_zd=1 ), the length and diameter of the silicon steel coil gradually decrease. No system automatic shearing (slitting line system switch quantity x_zd=0 ) is an abnormal shearing range, so please refer to formula (3):

[0081] (3);

[0082] Finally, the steel coil interval can be obtained by formula (4). The steel coil division interval is obtained by removing the abnormal shear interval from the initial steel coil interval: :

[0083] (4);

[0084] The above formula (4) means that for each obtained steel coil interval, if the initial steel coil interval is It is neither in the normal shearing range nor in the abnormal shearing range, so the initial steel coil range is taken. ; If the normal shearing range belongs to the initial coil range , then the normal shear interval is taken; if the abnormal shear interval belongs to the initial steel coil interval , then abandon the steel coil interval.

[0085] In the above embodiment, by fitting the actual data curve, calculating the lifting index, identifying the step characteristics, and applying the steel coil recognition model to divide the steel coil interval, multiple steel coil intervals within the target time range can be determined, which not only improves the accuracy and automation of the division process, but also significantly improves the ability to understand complex production processes. This method eliminates the impact of data noise, reduces the need for human intervention, and provides an important basis for production optimization, resource allocation and decision support, and overall improves production efficiency and system stability.

[0086] Then, divide each obtained steel coil into intervals Within, corresponding to the time range , based on the slitting line discharge data ("feed silicon steel coil length" x_sjcd and "Silicon steel coil winding diameter" x_sjj . ), slitting line system switch quantity (slitting line system automatic x_zd , "End processing of slitting line system" x_db . ) and "unwinder motor speed" x_kj Work orders are divided through work order identification model.

[0087] Please refer to Figure 2 and Figure 3 Optionally, the determining of the multiple work order intervals of each of the steel coil intervals includes:

[0088] For each of the steel coil sections, an actual data curve is fitted according to the discharge data of the slitting line to obtain second main line data;

[0089] Based on the second main line data, calculating the rise and fall index of the slitting line discharge data, and determining the step characteristics of the slitting line discharge data;

[0090] Based on the discharging data of the slitting line, the switching quantity of the slitting line system and the step characteristics of the discharging data of the slitting line, the work order intervals are divided through the work order recognition model to determine multiple work order intervals for each of the steel coil intervals.

[0091] Optionally, first set the discharge data "feed silicon steel coil length" x_sjcd and "Silicon steel coil winding diameter" x_sjj Fit the main line, smooth and remove noise, and record the second main line For M_sjcd, M_sjzj ; Among them, the second main line is similar to the same formula (1), which will not be repeated in the embodiments of the present invention.

[0092] Optionally, calculate the "feed silicon steel coil length" x_sjcd and "Silicon steel coil winding diameter" x_sjjThe lifting index is used to obtain the step characteristics of the slitting line feeding and discharging data. The obtained lifting index is recorded as L_sjcd and L_sjzj. The calculation of the lifting index is the same as formula (2) and will not be repeated in the embodiments of the present invention.

[0093] Optionally, based on the slitting line discharge data ("feed silicon steel coil length" x_sjcd and "Silicon steel coil winding diameter" x_sjj ), slitting line system switch quantity x_db and the step characteristics of the slitting line discharge data, the work order intervals are divided through the work order recognition model, and multiple work order intervals for each of the steel coil intervals are determined.

[0094] Optionally, the work order interval division by the work order identification model includes:

[0095] Determine the descending step signal of the slitting line discharge data;

[0096] Based on the descending step signal of the slitting line discharge data, an initial work order interval is obtained;

[0097] Determine a descending step signal of the switch quantity data of the slitting line system;

[0098] Based on the descending step signal of the switch quantity data of the slitting line system, the work order start time is corrected;

[0099] The work order interval is divided based on the initial work order interval and the revised work order start time.

[0100] Specifically:

[0101] First, based on the step characteristics of the slitting line discharge data, find the slitting line discharge data x_sjcd , x_sjj The falling step signal This is the signal that the finished silicon steel coil is unloaded from the slitting line system after shearing. The interval between every two finished steel coil unloading signals is an initial work order interval, recorded as , where a single interval is expressed as follows:

[0102] (5);

[0103] Secondly, find the initial work order interval for target analysis , start and end time , the previous initial work order interval is , time range , find the system switch quantity x_db Falling step signal , this is the initial work order The signal for the end processing of the finished steel coil means The shearing is finished and the end processing is in progress;

[0104] Furthermore, the initial work order interval can also be analyzed for the target , time range , modify the work order start time as follows:

[0105] (6);

[0106] Finally, the work order intervals are divided based on the initial work order interval and the corrected work order start time, and multiple work order intervals for each of the steel coil intervals are determined.

[0107] In the above embodiment, after the coil interval is determined, the present invention further divides the work order interval in a refined manner. This embodiment based on the fitting curve, the lifting index and the step characteristics and the work order recognition model not only greatly improves the accuracy and automation of data processing, but also makes the time management and execution of work order tasks more efficient.

[0108] Please refer to Figure 2 and Figure 3 Optionally, determining the working condition interval within each work order interval includes:

[0109] For each work order interval, an actual data curve is fitted according to the motor speed data and the switch quantity of the slitting line system to obtain the third main line data;

[0110] Based on the third main line data, determining the amplitude index of the motor speed data and the amplitude index of the switching quantity of the slitting line system;

[0111] Based on the third main line data, calculating the lifting index of the motor speed data and the lifting index of the switch quantity of the slitting line system, the step characteristics of the motor speed data and the step characteristics of the switch quantity of the slitting line system;

[0112] Based on the motor speed data, the slitting line system switch quantity, the amplitude index of the motor speed data, the amplitude index of the slitting line system switch quantity, the step characteristics of the motor speed data and the step characteristics of the slitting line system switch quantity, the working conditions within the work order are divided through the work order recognition model to determine the working condition interval within each work order interval.

[0113] Optionally, within each work order division interval, the working condition is divided by combining the motor speed data of the slitting line equipment and the system switch quantity through a work order identification model.

[0114] Optionally, first set the motor speed data of the slitting line equipment ("unwinder motor speed" x_kj , “Slitting machine motor speed” x_zj, "Pinch roller motor speed" x_jg and "Winder motor speed" x_sj ) and slitting line system switch quantity x_zd Fit the main line, smooth and remove noise, and the third main line is recorded as M_kj, M_zj, M_jg, M_sj, M_zd ; Among them, the third main line is similar to the same formula (1), which will not be repeated in the embodiments of the present invention.

[0115] Optionally, calculate the motor speed data of the slitting line equipment ("unwinder motor speed" x_kj , “Slitting machine motor speed” x_zj , "Pinch roller motor speed" x_jg and "Winder motor speed" x_sj ) and the switch quantity of the slitting line system x_zd The amplitude index is used to obtain the fluctuation characteristics of the motor speed and switch quantity data. The obtained amplitude index is recorded as R_kj, R_zj, R_jg, R_sj, R_zd .

[0116] Optionally, the amplitude index refers to the average value of the larger half of the factors of the original value deviating from the main line within a certain interval, which is recorded as Range. The amplitude index calculation formula is:

[0117] (6);

[0118] Among them, range_itv is the set amplitude range, which is set to 4 here, mean() is the mean calculation function, and z is the amplitude index data length. Calculate according to the following formula:

[0119] (7);

[0120] Among them, sort() is a function for sorting from large to small. , refers to the amplitude factor, which indicates how much the original value deviates from the main line. X is the original sequence, and M is the main line fitted by formula (1);

[0121] Optionally, calculate the speed data of each motor of the slitting line equipment x_kj, x_zj, x_jg, x_sj And the switch quantity of the slitting line system x_zd The lifting index is used to obtain the step characteristics of the motor speed and switch quantity of each device. The lifting index is recorded as L_ kj、L_zj、L_jg、L_sj、L_zd The calculation of the lifting index is the same as formula (2), which will not be repeated in the embodiment of the present invention.

[0122] Optional, based on the speed data of each motor x_kj, x_zj, x_jg, x_sj , slitting line system switch quantity x_zd, Fluctuation characteristics and step characteristics are used to divide the working conditions within the work order:

[0123] The division of working conditions within a work order by using a work order recognition model includes:

[0124] Identify the working condition to which each sample point belongs;

[0125] A process inspection condition is identified from the conditions.

[0126] Optionally, identifying the working condition to which each sample point belongs in the implementation of the present invention means that in the process of judging the working condition, sampling is performed at specified intervals on a target time range where working condition identification is required, and working condition identification is performed on each sample point collected.

[0127] Optionally, the process inspection working condition in the implementation of the present invention refers to integrating the working condition of each sample point to obtain a timestamp for each working condition.

[0128] Specifically, for work orders The range is determined by the following formula to identify the working condition of each sample point. It is worth noting that arrive For sequential working conditions.

[0129] (8);

[0130] in, Indicates that the working condition is that the uncoiler passes the material to the slitting machine. Specifically, the uncoiler speed is greater than zero, the uncoiler amplitude index is greater than zero, and the slitting machine and the nip roller speeds are both zero. Indicates that the working condition is that the slitting machine passes the material to the nip roller, which is specifically manifested as the uncoiler speed is greater than zero, the uncoiler amplitude index is greater than zero, the slitting machine speed is greater than zero, the slitting machine amplitude index is greater than zero and the nip roller speed is zero. It indicates that the working condition is from the nip roller threading to continuous shearing, which is specifically manifested as the speed of the uncoiler, slitting machine, and nip roller are all greater than zero, and the amplitude index of the uncoiler, slitting machine, and nip roller are all greater than zero. It indicates that the working condition is continuous shearing and process inspection, which is specifically manifested as the slitting machine speed is greater than zero and the system is in automatic state.

[0131] Because from arrive The working condition is in order, so the starting point of the above state is taken as the starting point of the working condition through formula (9). The operating range is modified and the timings belonging to the same operating condition are integrated:

[0132] (9);

[0133] because Continuous cutting and process inspection may be alternating, not continuous, so it is necessary to Special Identification Ticket Continuous shear and process inspection Working condition, two working conditions appear alternately, when the system is in automatic shearing, it is continuous shearing, and when the system is in manual, it is the process inspection state in the shearing diagram:

[0134] (10);

[0135] In the above embodiment, parameters such as amplitude index and lifting index are introduced into the identification of the working condition interval through the motor speed data and the switch quantity of the slitting line system, thereby improving the accuracy of the working condition identification.

[0136] Please refer to Figure 2 and Figure 3 Optionally, the determining of the working condition interval within each work order interval further includes:

[0137] Determining a work order execution efficiency index for the work order interval based on the working condition interval within the work order interval, wherein the work order execution efficiency index includes at least one of the following: work order tool change time, work order start-up rate, and work order cutting speed;

[0138] Based on the work order execution efficiency index, the work order execution efficiency of the work order interval is determined.

[0139] Optional, for work orders , based on the working condition range obtained in the above embodiment, the tool change time is calculated according to formula (11): , calculate the startup rate according to formula (12) , according to formula (13) calculate the cutting speed :

[0140] (11);

[0141] (12);

[0142] (13);

[0143] Through the above embodiments, by carefully dividing the working condition intervals within the work order interval and calculating the work order execution efficiency indicators (such as the work order tool change time, the work order start-up rate and the work order cutting speed) based on this, the work order efficiency can be comprehensively evaluated, and the automated real-time monitoring and adjustment can be realized, the production management can be optimized, the resource utilization efficiency can be improved, and reliable data support can be provided for management decisions, thereby improving the production efficiency and system stability as a whole. Furthermore, the present invention can obtain standard man-hours by accurately dividing multiple working condition intervals within the work order of complex equipment and calculating the work order execution efficiency from multiple dimensions. Man-hours are generated based on a large amount of production data, avoiding the drawbacks of insufficient man-hour data in the conventional lean means of manually calculating man-hours with a stopwatch, and have guiding significance for the production department to improve production efficiency. This not only helps to accurately identify production bottlenecks, optimize equipment utilization and workflow, but also provides reliable data support for scientific decision-making and performance evaluation. Therefore, the implementation of the above-mentioned improvement measures can significantly improve the level of production management and operational efficiency.

[0144] The present invention uses two indicators, the lifting index and the amplitude index, to analyze the characteristics of the actual production time series data, and uses the fitting main line to filter out the noise of the original production data, thereby realizing the distinction of the work orders of the longitudinal shearing line equipment and the subdivision of each production stage, including the threading stage that is not controlled by the switch quantity; multiple parameters are considered in combination, not affected by the fixed threshold, and the problems of false touch and abnormality are eliminated; the tool change time between adjacent work orders is calculated through data performance. The present invention solves the problems in the prior art that the test knife and the cutting of the material cannot be distinguished, the threading cannot be subdivided, the analysis failure caused by the false touch of the switch quantity, and the dependence on the switch quantity and the threshold value, and realizes the distinction of all states of the longitudinal shearing line equipment and the time consumption statistics of each stage. At the same time, the work order information does not rely on MES acquisition, and is not affected by information misreporting and the inconsistency between production and actual tasks. Further, the work order and state are distinguished by the characteristics of production data, and the threading is subdivided to realize lean production management, which has the characteristics of zero code, more refinement, and high accuracy.

[0145] Please refer to Figure 4 The embodiment of the present invention further provides a slitting line system working condition confirmation system 20, comprising:

[0146] An acquisition module 21 is used to acquire equipment data of the slitting line system within a target time range, wherein the equipment data includes: motor speed data, slitting line system switch quantity, slitting line feeding data, and slitting line discharging data;

[0147] A steel coil module 22, for determining a plurality of steel coil intervals within a target time range based on the equipment data;

[0148] A work order module 23, configured to identify work order intervals based on the equipment data and the steel coil intervals, and determine a plurality of work order intervals for each of the steel coil intervals;

[0149] The working condition module 24 is used to identify the working condition based on the equipment data and the work order interval, and determine the working condition interval within each work order interval.

[0150] Optionally, the slitting line system working condition confirmation system 20 further includes:

[0151] An efficiency module, used to determine a work order execution efficiency index of the work order interval based on a working condition interval within the work order interval, wherein the work order execution efficiency index includes at least one of the following: work order tool change time, work order start-up rate, and work order cutting speed;

[0152] Based on the work order execution efficiency index, the work order execution efficiency of the work order interval is determined.

[0153] Optionally, the steel coil module 22 includes:

[0154] The steel coil module is used to fit the actual data curve according to the slitting line feeding data to obtain the first main line data;

[0155] Based on the first main line data, calculating the lifting index of the slitting line feeding data, and determining the step characteristics of the slitting line feeding data;

[0156] Based on the slitting line feeding data, the slitting line system switching quantity and the step characteristics of the slitting line feeding data, the steel coil interval is divided through the steel coil recognition model to determine multiple steel coil intervals within the target time range.

[0157] Optionally, the work order module 23 includes:

[0158] A work order submodule is used to fit the actual data curve according to the discharge data of the slitting line for each of the steel coil sections to obtain the second main line data;

[0159] Based on the second main line data, calculating the rise and fall index of the slitting line discharge data, and determining the step characteristics of the slitting line discharge data;

[0160] Based on the discharging data of the slitting line, the switching quantity of the slitting line system and the step characteristics of the discharging data of the slitting line, the work order intervals are divided through the work order recognition model to determine multiple work order intervals for each of the steel coil intervals.

[0161] Optionally, the operating condition module 24 includes:

[0162] A working condition submodule is used to fit an actual data curve according to the motor speed data and the switch quantity of the slitting line system in each work order interval to obtain the third main line data;

[0163] Based on the third main line data, determining the amplitude index of the motor speed data and the amplitude index of the switching quantity of the slitting line system;

[0164] Based on the third main line data, calculating the lifting index of the motor speed data and the lifting index of the switch quantity of the slitting line system, the step characteristics of the motor speed data and the step characteristics of the switch quantity of the slitting line system;

[0165] Based on the motor speed data, the slitting line system switch quantity, the amplitude index of the motor speed data, the amplitude index of the slitting line system switch quantity, the step characteristics of the motor speed data and the step characteristics of the slitting line system switch quantity, the working conditions within the work order are divided through the work order recognition model to determine the working condition interval within each work order interval.

[0166] Optionally, the slitting line system working condition confirmation system 20 further includes:

[0167] A preprocessing module is used to preprocess the device data, wherein the preprocessing includes at least one of the following: timestamp alignment, outlier processing, and missing value filling.

[0168] The slitting line system working condition confirmation system provided by the embodiment of the present invention can realize Figure 1 The various processes implemented by the method embodiment and achieving the same technical effect are not described here to avoid repetition.

[0169] The embodiment of the present invention provides an electronic device 30, see Figure 5 As shown, Figure 5 The electronic device 30 of the embodiment of the present invention includes a processor 31, a memory 32 and a program or instruction stored in the memory 32 and executable on the processor 31. When the program or instruction is executed by the processor, any step in the method for confirming the working condition of the longitudinal shearing line system of the present invention is implemented.

[0170] An embodiment of the present invention provides a readable storage medium, on which programs or instructions are stored. When the programs or instructions are executed by a processor, the various processes of an embodiment of a method for confirming the operating condition of a longitudinal shearing line system as described above are implemented, and the same technical effect can be achieved. To avoid repetition, they will not be described here.

[0171] Computer readable media include permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0172] The embodiment of the present invention also provides a computer program product, including computer instructions, which, when executed by a processor, implement the above Figure 1 The various processes of any of the embodiments of the method for confirming the operating condition of the longitudinal shearing line system shown can achieve the same technical effect. To avoid repetition, they will not be described here.

[0173] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0174] It should be noted that the collection, collection, updating, analysis, processing, use, transmission, storage and other aspects of user personal information involved in the technical solution of this disclosure are in compliance with the provisions of relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken for user personal information to prevent illegal access to user personal information data and maintain the security of user personal information and network security.

[0175] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0176] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a service classification device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0177] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for confirming the working condition of a slitting line system, characterized in that: include: Acquire equipment data of the slitting line system within the target time range, the equipment data including: motor speed data, slitting line system switch quantity, slitting line feeding data and slitting line discharging data; Based on the equipment data, multiple steel coil intervals within the target time range are determined; including: determining corresponding step characteristics according to the slitting line feeding data; dividing the steel coil intervals based on the slitting line feeding data, the slitting line system switch quantity and the step characteristics of the slitting line feeding data, and determining multiple steel coil intervals within the target time range; the steel coil intervals include: an initial steel coil interval, a normal shearing interval and an abnormal shearing interval; Based on the equipment data and the steel coil interval, work order interval identification is performed to determine multiple work order intervals for each of the steel coil intervals; including: determining corresponding step characteristics according to the slitting line discharge data; dividing the work order intervals based on the slitting line discharge data, the slitting line system switch quantity and the step characteristics of the slitting line discharge data, and determining multiple work order intervals for each of the steel coil intervals; Based on the equipment data and the work order interval, the working condition is identified to determine the working condition interval in each work order interval; including: determining the step characteristics of the motor speed data and the step characteristics of the slitting line system switch quantity according to the motor speed data and the slitting line system switch quantity; based on the motor speed data, the slitting line system switch quantity, the step characteristics of the motor speed data and the step characteristics of the slitting line system switch quantity, the working condition is divided within the work order to determine the working condition interval in each work order interval; the working condition interval includes threading from the uncoiler to the slitting machine, threading from the slitting machine to the clamping roller, threading from the clamping roller to continuous shearing, continuous shearing and process inspection.

2. The method according to claim 1, characterized in that The determining of the working condition interval within each work order interval further includes: Determining a work order execution efficiency index for the work order interval based on the working condition interval within the work order interval, wherein the work order execution efficiency index includes at least one of the following: work order tool change time, work order start-up rate, and work order cutting speed; Based on the work order execution efficiency index, the work order execution efficiency of the work order interval is determined.

3. The method according to claim 1, characterized in that Determine the corresponding step characteristics according to the slitting line feeding data; divide the steel coil intervals based on the slitting line feeding data, the slitting line system switch quantity and the step characteristics of the slitting line feeding data, and determine multiple steel coil intervals within the target time range, including: Fitting an actual data curve according to the slitting line feeding data to obtain first main line data; Based on the first main line data, calculating the lifting index of the slitting line feeding data, and determining the step characteristics of the slitting line feeding data; Based on the slitting line feeding data, the slitting line system switch quantity and the step characteristics of the slitting line feeding data, the steel coil interval is divided by a steel coil recognition model to determine multiple steel coil intervals within a target time range; the steel coil recognition model includes: determining a rising step signal of the slitting line feeding data; Based on the rising step signal of the slitting line feeding data, an initial steel coil interval is obtained; Determine the descending step signal of the slitting line feed data; Based on the descending step signal of the slitting line feeding data and the switching value of the slitting line system, the normal shearing range and the abnormal shearing range are obtained; The steel coil interval is determined based on the initial steel coil interval, the normal shear interval and the abnormal shear interval.

4. The method according to claim 1, characterized in that: Determine the corresponding step characteristics according to the slitting line discharge data; divide the work order intervals based on the slitting line discharge data, the slitting line system switch quantity and the step characteristics of the slitting line discharge data, and determine that multiple work order intervals for each of the steel coil intervals include: For each of the steel coil sections, an actual data curve is fitted according to the discharge data of the slitting line to obtain second main line data; Based on the second main line data, calculating the rise and fall index of the slitting line discharge data, and determining the step characteristics of the slitting line discharge data; Based on the slitting line discharge data, the slitting line system switch quantity and the step characteristics of the slitting line discharge data, the work order interval is divided through the work order recognition model to determine multiple work order intervals for each of the steel coil intervals; the work order recognition model includes: determining a descending step signal of the slitting line discharge data; obtaining an initial work order interval based on the descending step signal of the slitting line discharge data; determining a descending step signal of the slitting line system switch quantity data; correcting the work order start time based on the descending step signal of the slitting line system switch quantity data; and dividing the work order interval based on the initial work order interval and the corrected work order start time.

5. The method according to claim 1, characterized in that: Determine the step characteristics of the motor speed data and the step characteristics of the slitting line system switch quantity according to the motor speed data and the slitting line system switch quantity; divide the working conditions within the work order based on the motor speed data, the slitting line system switch quantity, the step characteristics of the motor speed data and the step characteristics of the slitting line system switch quantity, and determine that the working condition interval within each work order interval includes: For each work order interval, an actual data curve is fitted according to the motor speed data and the switch quantity of the slitting line system to obtain the third main line data; Based on the third main line data, determining the amplitude index of the motor speed data and the amplitude index of the switching quantity of the slitting line system; Based on the third main line data, calculating the lifting index of the motor speed data and the lifting index of the switch quantity of the slitting line system, the step characteristics of the motor speed data and the step characteristics of the switch quantity of the slitting line system; Based on the motor speed data, the switching quantity of the slitting line system, the amplitude index of the motor speed data, the amplitude index of the switching quantity of the slitting line system, the step characteristics of the motor speed data and the step characteristics of the switching quantity of the slitting line system, the working conditions within the work order are divided to determine the working condition intervals within each work order interval.

6. The method according to claim 5, characterized in that The method of dividing the working conditions within the work order based on the motor speed data, the slitting line system switch quantity, the amplitude index of the motor speed data, the amplitude index of the slitting line system switch quantity, the step characteristics of the motor speed data and the step characteristics of the slitting line system switch quantity, and determining the working condition interval within each work order interval includes: The uncoiler speed is greater than zero, the uncoiler amplitude index is greater than zero, and the slitting machine and the pinch roller speed are both zero, and the working condition is determined to be the uncoiler passing the material to the slitting machine; The uncoiler speed is greater than zero, the uncoiler amplitude index is greater than zero, the slitting machine speed is greater than zero, the slitting machine amplitude index is greater than zero and the nip roller speed is zero, and the working condition is determined to be the slitting machine passing the material to the nip roller; The speeds of the uncoiler, slitting machine and nip roller are all greater than zero, and the amplitude indexes of the uncoiler, slitting machine and nip roller are all greater than zero, and the working condition is determined to be from nip roller threading to continuous shearing; The speed of the slitting machine is greater than zero and the system is in automatic state, and the working condition is determined to be continuous shearing or process inspection.

7. A slitting line system working condition confirmation system, characterized in that: include: An acquisition module is used to acquire equipment data of the slitting line system within a target time range, wherein the equipment data includes: motor speed data, slitting line system switch quantity, slitting line feeding data, and slitting line discharging data; A steel coil module, for determining multiple steel coil intervals within a target time range based on the equipment data; including: determining corresponding step characteristics according to the slitting line feeding data; dividing the steel coil intervals based on the slitting line feeding data, the slitting line system switch quantity and the step characteristics of the slitting line feeding data, and determining multiple steel coil intervals within the target time range; the steel coil intervals include initial steel coil intervals, normal shearing intervals and abnormal shearing intervals; a work order module, for identifying work order intervals based on the equipment data and the steel coil intervals, and determining multiple work order intervals for each of the steel coil intervals; including: determining corresponding step characteristics according to the slitting line discharging data; dividing the work order intervals based on the slitting line discharging data, the slitting line system switch quantity and the step characteristics of the slitting line discharging data, and determining multiple work order intervals for each of the steel coil intervals; The working condition module is used to identify the working condition based on the equipment data and the work order interval, and determine the working condition interval within each work order interval; including: determining the step characteristics of the motor speed data and the step characteristics of the slitting line system switch quantity according to the motor speed data and the slitting line system switch quantity; dividing the working conditions within the work order based on the motor speed data, the slitting line system switch quantity, the step characteristics of the motor speed data and the step characteristics of the slitting line system switch quantity, and determining the working condition interval within each work order interval; the working condition interval includes threading from the uncoiler to the slitting machine, threading from the slitting machine to the clamping roller, threading from the clamping roller to continuous shearing, continuous shearing and process inspection.

8. An electronic device, characterized in that: include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein when the program is executed by the processor, the steps of the method for confirming the operating condition of a longitudinal shearing line system as described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium, characterized in that: A computer program is stored on a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method for confirming the operating condition of a slitting line system as described in any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that It comprises computer instructions, which, when executed by a processor, implement the steps of the method for confirming the working condition of a slitting line system as described in any one of claims 1 to 6.

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