JP2022112405A - Roll management device - Google Patents

Abstract

To provide a roll management device for determining a state of a rolling roll based on information on a state of a past rolling roll, and presenting an application method of the rolling roll.SOLUTION: A roll management device includes: a data collection part for collecting a physical quantity relating to a plurality of rolling rolls in rolling and rolling applicable condition data; a data storage part for storing the physical quantity and the rolling applicable condition data collected by the data collection part until the previous rolling; a state determination part for reading the relating physical quantity for the rolling applicable condition data that is the same as or similar to the rolling applicable condition data of the specific rolling roll used in rolling and is stored in the data storage part, and determining the state of the specific rolling roll on the basis of the relating physical quantity; and a recommendation application method determination part for presenting an application method recommended for the specific rolling roll on the basis of the state of the specific rolling roll determined by the state determination part.SELECTED DRAWING: Figure 2

Description

This disclosure relates to a role management device.

Patent Literature 1 discloses a roll management device. The roll management device can eliminate eccentricity of the rolling rolls.

Japanese Patent No. 5821527

However, the roll management device described in Patent Document 1 does not find the cause of the eccentricity of the rolling rolls. As a result, the rolling rolls cannot be properly applied at the next rolling opportunity.

The present disclosure has been made to solve the above problems. An object of the present disclosure is to provide a roll management device that can appropriately apply rolling rolls.

The roll management device according to the present disclosure includes a data collection unit that collects physical quantities and rolling application condition data regarding a plurality of rolling rolls during rolling, and the physical quantities and rolling application collected by the data collection unit until the previous rolling. a data storage unit for accumulating condition data; and for the applicable rolling condition data accumulated in the data storage unit that is the same as or similar to the applicable rolling condition data for a specific rolling roll used for rolling, reading the associated physical quantity; a state determining unit that determines the state of the specific rolling roll based on the related physical quantity; and an application recommended for the specific rolling roll based on the state of the specific rolling roll determined by the state determining unit. and a recommended application method determination unit that presents the method.

According to the present disclosure, the roll management system provides recommended application methods for a particular mill roll based on the condition of the particular mill roll. Therefore, rolling rolls can be applied appropriately.

1 is a configuration diagram of a role management system to which a role management device according to Embodiment 1 is applied; FIG. 1 is a configuration diagram of a role management device according to Embodiment 1; FIG. 5 is a graph showing an example of a roll physical quantity signal, material entry detection signal, material detachment detection signal, and material total length measurement signal of the roll management device according to Embodiment 1; 5 is a graph showing an example of unprocessed roll phenomenon data and preprocessed roll phenomenon data of the roll management device according to Embodiment 1; 4 is a diagram showing an example of a stratified phenomenon history database of the role management device according to the first embodiment; FIG. 4 is a diagram showing an example of a state determination threshold database of the role management device according to Embodiment 1; FIG. 4 is a diagram showing an example of a state mode database of the role management device according to Embodiment 1; FIG. 4 is a diagram showing an example of a recommended application method database of the role management device according to Embodiment 1; FIG. 4 is a flowchart for explaining an overview of the operation of the role management device according to Embodiment 1; 2 is a hardware configuration diagram of a role management device according to Embodiment 1; FIG. FIG. 10 is a configuration diagram of a role management device according to Embodiment 2; FIG. 11 is a configuration diagram of a role management device according to Embodiment 3; FIG. 12 is a configuration diagram of a role management device according to Embodiment 4; FIG. 11 is a configuration diagram of a role management device according to Embodiment 5; FIG. 12 is a configuration diagram of a role management device according to Embodiment 6; FIG. 21 is a configuration diagram of a role management device according to Embodiment 7;

Embodiments will be described with reference to the accompanying drawings. In addition, the same code|symbol is attached|subjected to the part which is the same or corresponds in each figure. Redundant description of the relevant part will be simplified or omitted as appropriate.

Embodiment 1.
FIG. 1 is a configuration diagram of a role management system to which a role management device according to Embodiment 1 is applied.

As shown in FIG. 1, the roll management system includes a rolling mill 11, a roll management device 1 and a process computer 12.

The rolling mill 11 includes an upper rolling roll 21 , a lower rolling roll 22 , a roll physical quantity sensor 31 , a material entry detection sensor 32 , a material separation detection sensor 33 , and a material total length measurement sensor 34 . For example, the rolling mill 11 rolls ferrous and non-ferrous materials.

The upper rolling roll 21 and the lower rolling roll 22 sandwich and roll the material. L is the total length of the material 42 after rolling. L1 is the middle position of the material 42 after rolling. L2 is the middle position of the material 42 after rolling.

The roll physical quantity sensor 31 is provided so as to measure a physical quantity related to the upper rolling roll 21 . For example, the physical quantity related to the upper roll 21 is the pressure applied to the upper roll 21 . For example, the physical quantity relating to the upper roll 21 is the displacement of the position of the upper roll 21 . For example, the physical quantity related to the upper roll 21 is the vibration value of the rolling load on the upper roll 21 . For example, the physical quantity relating to the upper roll 21 is the rolling tension in the upper roll 21 . The roll physical quantity sensor 31 transmits a roll physical quantity signal based on the physical quantity relating to the upper rolling roll 21 .

The material entry detection sensor 32 is provided so as to detect the entry of the pre-rolling material 41 . For example, the material entry detection sensor 32 detects that the pre-rolling material 41 has passed through its own detection range. For example, the material entry detection sensor 32 transmits a material entry detection signal when detecting entry of the pre-rolling material 41 . For example, the material entry detection sensor 32 transmits a material entry detection signal regarding passage of the pre-rolled material 41 within its own detection range. For example, the material entry detection sensor 32 transmits a material entry detection signal as a signal indicating whether or not the pre-rolling material 41 has been detected at its proximity position. For example, the material entry detection signal is a truth value. For example, the material entry detection signal indicates "1" when the material entry detection sensor 32 detects the pre-rolling material 41 at its close position. For example, the material entry detection signal indicates "0" when the material entry detection sensor 32 does not detect the pre-rolling material 41 at its close position.

A material detachment detection sensor 33 is provided so as to detect detachment of the rolled material 42 . For example, the material detachment detection sensor 33 detects that the rolled material 42 has passed through its own detection range. For example, the material detachment detection sensor 33 transmits a material detachment detection signal when detachment of the rolled material 42 is detected. For example, the material detachment detection sensor 33 transmits a material detachment detection signal regarding the passage of the rolled material 42 within its own detection range. For example, the material detachment detection signal is a truth value. For example, the material detachment detection signal indicates "1" when the material detachment detection sensor 33 detects the rolled material 42 at its close position. For example, the material entry detection signal indicates "0" when the material detachment detection sensor 33 does not detect the rolled material 42 at its close position.

For example, the material total length measurement sensor 34 detects that the tip of the rolled material 42 has passed through its own detection range. For example, the material total length measurement sensor 34 detects the time when the tip of the rolled material 42 passes through its own detection range. For example, the material total length measurement sensor 34 detects that the end of the rolled material 42 has passed through its own detection range. For example, the material total length measurement sensor 34 detects the time when the end of the rolled material 42 passes through its own detection range. The material total length measurement sensor 34 transmits a material total length measurement signal. For example, the material total length measurement signal is the length from the tip of the rolled material 42 to its own detection point at the time of measurement after the start of rolling. For example, if the rolling start time is time 0 and the rolling end time T, the material total length measurement signal at the rolling end time T indicates the total length L of the material 42 after rolling.

The roll management device 1 is provided so as to communicate with the rolling mill 11 . The role management device 1 is provided so as to communicate with the process computer 12 .

For example, process computer 12 is a general purpose computer. The process computer 12 is provided so as to receive rolling application condition data from a production control computer (not shown). For example, the applicable condition data are production instructions. For example, the applicable condition data are manufacturing specifications. For example, the application condition data is information such as the steel type, size, and temperature of the material to be rolled. The process computer 12 calculates rolling conditions based on the received information. Process computer 12 transmits the calculated value.

Next, the configuration of the role management device 1 will be described with reference to FIG.
FIG. 2 is a configuration diagram of a role management device according to the first embodiment.

As shown in FIG. 2 , the role management device 1 includes a data collection unit 2 , a data quantification unit 3 , a data storage unit 4 , a state determination unit 5 and a recommended application method determination unit 6 .

The data collection unit 2 receives from the rolling mill 11 a roll physical quantity signal, a material entry detection signal, a material detachment detection signal, and a material total length measurement signal. For example, the data acquisition unit 2 receives the roll physical quantity signal, the material entry detection signal, the material detachment detection signal, and the material total length measurement signal in synchronism. The data extraction unit 2 comprises a data extraction unit 2a and a data preprocessing unit 2b.

The data extraction unit 2 a extracts pre-processed roll phenomenon data from the signal received from the rolling mill 11 . The roll phenomenon data before processing is information about the upper rolling roll 21 . For example, the pre-treatment roll phenomenon data is information obtained by extracting the data within the range necessary for quantification from the information regarding the upper rolling roll 21 . For example, the pre-treatment roll phenomenon data is the rolling load vibration value. For example, the pre-treatment roll behavior data is the rolling tension value. For example, the pre-treatment roll phenomenon data is the displacement value of the rolling rolls. For example, the unprocessed roll phenomenon data includes a predetermined sampling period and a predetermined sampling time range. For example, the pre-process roll phenomenon data includes a suitable sampling period and a suitable sampling time range for quantifying mill roll related phenomena. An example of a specific sampling period is, if the vibration frequency of the roll eccentricity is about 2 Hz when collecting the data of the vibration of the roll eccentricity, consider the sampling theorem and the influence of noise, and set the sampling frequency to 4 times. do. In this case, a suitable sampling period is set to approximately 100 ms. For example, a suitable sampling time range is time timing such as after the start of rolling, in the middle of rolling, and at the end of rolling. For example, a suitable sampling time range is set based on the position of the measurement points along the length of the material. For example, the position of the measurement point in the entire length of the material is the position of the leading end in the entire length of the material, the middle position in the entire length of the material, the position of the rear end in the entire length of the material, and the like. The data extraction unit 2a transmits the unprocessed roll phenomenon data.

The data preprocessing unit 2b receives the preprocessed roll phenomenon data from the data extraction unit 2a. The data preprocessing unit 2b processes the preprocessed roll phenomenon data to obtain preprocessed roll phenomenon data. For example, the data preprocessing unit 2b filters the preprocessed roll phenomenon data. For example, the filters are low pass filters or high pass filters. The roll phenomenon data before processing and the roll phenomenon data after preprocessing are collectively referred to as roll phenomenon data.

For example, the data quantification unit 3 is a PLC. For example, the data quantification unit 3 is DCS. For example, the data quantification unit 3 is a general-purpose computer. The data quantification unit 3 receives preprocessed roll phenomenon data from the data collection unit 2 . The data quantification unit 3 generates state quantification data from the preprocessed roll phenomenon data. The state quantification data is data obtained by quantifying the state of the rolling rolls. The data quantification unit 3 transmits state quantification data. The data quantification section 3 includes a basic statistic calculation unit 3a.

The basic statistic calculation unit 3a calculates basic statistics from preprocessed roll phenomenon data to be subjected to data quantification, and generates state quantification data. For example, basic statistics are mean, median, maximum/minimum difference, standard deviation or variance. The basic statistic calculation unit 3a generates respective state quantification data for each of various roll phenomenon data. The basic statistic calculation unit 3a generates state quantified data for each of the material 41 before rolling and the material 42 after rolling.

The data storage unit 4 is provided so as to communicate with the data quantification unit 3 . The data storage unit 4 is provided so as to communicate with the process computer 12 . The data storage unit 4 receives state quantification data from the data quantification unit 3 . The data storage unit 4 receives state quantification data from the data quantification unit 3 for each of the plurality of rolling rolls. The data storage unit 4 stores state quantification data. The data storage unit 4 accumulates and stores previously received state quantification data. The data storage unit 4 receives values calculated by the process computer 12 and application condition data from the process computer 12 . The data storage unit 4 includes a data storage unit 4a, a stratified phenomenon history data reading unit 4b, and a stratified phenomenon history database 4c. The data storage unit 4 generates stratified phenomenon history data based on the application condition data and the stored data. For example, the layer-by-layer phenomenon history data is data recording items such as roll IDs, chocks supporting the rolls, production specifications such as the steel grade, size, and temperature of the material to be rolled, and rolling conditions for each layer. Note that the roll ID is a number for individually identifying a rolling roll.

The data storage unit 4a, the stratified phenomenon history data reading unit 4b, and the stratified phenomenon history database 4c are provided so as to be able to communicate with each other.

The data storage unit 4 a receives roll phenomenon data and state quantification data from the data quantification section 3 . The data storage unit 4a receives from the process computer 12 the relevant application condition data when applying a role. For example, applicable condition data related to rolling rolls includes roll IDs, chocks that support the rolls, production specifications such as the steel type, size, and temperature of the material to be rolled, rolling conditions, and the like. For example, the data storage unit 4a uses the role ID as a key and stores related data such as other applicable conditions.

The stratified phenomenon history data reading unit 4b reads stratified phenomenon history data based on an external request. The stratified phenomenon history data reading unit 4b receives a request from another device and reads stratified phenomenon history data. The stratified phenomenon history data reading unit 4b receives a request from another device and reads stratified phenomenon history data having the same application condition data. The stratified phenomenon history data reading unit 4b receives a request from another device and reads stratified phenomenon history data having similar application condition data. For example, the stratified phenomenon history data reading unit 4b reads stratified phenomenon history data based on a request from the process computer 12. FIG. The stratified phenomenon history data is arbitrarily selected from the data stored in the stratified phenomenon history database 4c, using the role ID as a key, and out of related data such as state quantification data and other linked application conditions. It is data generated by indexing stratified by item.

The stratified phenomenon history database 4c stores the data received by the data storage unit 4a and the acquisition time of each data in association with each other as stratified phenomenon history data.

The state determination unit 5 is provided so as to be communicable with the data storage unit 4 . State determination unit 5 receives state quantification data from data storage unit 4 . The state determination unit 5 reads stratified phenomenon history data from the data storage unit 4 . The state determination unit 5 determines the state mode of the rolling rolls based on the state quantification data and stratification phenomenon history data related to the rolling applicable condition data identical or similar to the rolling applicable condition data of the specific rolling rolls used for rolling. do. The state determination section 5 includes a state phenomenon database 5a and a state determination unit 5b.

The state phenomenon database 5a includes a state determination threshold database and a state mode database. For example, the state determination threshold database is a database listing state determination thresholds for determining whether the state is abnormal and the state level, which is the level of the state, for each state quantification data. The state determination threshold value is a value for determining whether or not the state of the roll is abnormal, and the state level. For example, the state determination threshold is set in advance. For example, the state determination threshold is semi-fixedly set. For example, the state determination threshold is calculated from the user's 7 past experience and knowledge of the plant. For example, the state mode is preset. For example, the state mode is set semi-permanently. For example, the status mode is calculated from the user's 7 past experience and knowledge of the plant.

When receiving application condition data of a specific roll used for rolling, the state determination unit 5b reads from the data storage unit 4 stratified phenomenon history data related to application condition data identical or similar to the application condition. For example, when the state determination unit 5b receives the rolling roll ID and the application condition related to the state quantification data, it reads out from the data storage unit 4 stratified phenomenon history data related to the rolling roll ID and the application condition. For example, when the state determination unit 5b receives the rolling roll ID and the application condition from the data storage section 4, it reads out from the data storage section 4 stratified phenomenon history data related to the rolling roll ID and the application condition. The state determination unit 5b compares the read stratified phenomenon history data with the data obtained from the state phenomenon database 5a to determine the state level and state mode of the state quantification data. The state determination unit 5b determines whether the state of the roll is abnormal and determines the state level based on the read stratified phenomenon history data and the state determination threshold obtained from the state phenomenon database 5a. The state determination unit 5b determines what kind of state mode it is for a combination of a data item that conflicts with the state determination threshold and its state level.

The recommended application method determination unit 6 is provided so as to be communicable with the data storage unit 4 . The recommended application method determination unit 6 is provided so as to be communicable with the state determination unit 5 . The recommended application method determination unit 6 receives from the state determination unit 5 the data item that conflicts with the state determination threshold value and the state mode determined by the state determination unit 5 . The recommended application method determination unit 6 determines the recommended application method of the rolling rolls and stratified phenomenon history data. The recommended application method determination unit 6 externally displays the recommended application method of the rolling rolls and stratified phenomenon history data. The recommended application method determination unit 6 presents the recommended application method of the rolling rolls and stratified phenomenon history data to the user 7 . The recommended application method determination unit 6 includes a recommended application method database 6a and a recommended application method determination unit 6b.

The recommended application method database 6a stores values for determining the recommended application method of the rolling rolls. For example, the value for determining the recommended application method of the mill roll is the value for determining the recommended application method for the state mode combination. The recommended application method is the recommended mill roll application method for the state mode. For example, a recommended application method is to avoid roll application by roll change. For example, the recommended application method is to change the rolling conditions by reducing the roll load.

When a rolling roll ID and an application condition are given, the recommended application method determination unit 6b receives the stratification phenomenon history data related to the roll ID and the application condition and the stratification phenomenon history data from the state determination unit 5b. Get state mode. The recommended application method determination unit 6b obtains the appropriate recommended application method from the recommended application method database 6a for the received state mode. The recommended application method determination unit 6b externally displays the recommended application method of the rolling rolls and stratified phenomenon history data. For example, the recommended application method determination unit 6b presents the user 7 with the recommended application method of the rolling rolls and stratified phenomenon history data. For example, the recommended application method determination unit 6b provides the user 7 with a display on a display device. For example, the recommended application method determination unit 6b presents it to the user 7 by means of sound from a sound output device.

Next, with reference to FIG. 3, an example of processing performed by the data extraction unit 2a until the pre-rolling material 41 is rolled by the distance L after the start of rolling will be described.
3A and 3B are diagrams showing examples of a roll physical quantity signal, a material entry detection signal, a material separation detection signal, and a material total length measurement signal of the roll management device according to Embodiment 1. FIG.

The uppermost graph is a graph showing the roll physical quantity signal. The second graph from the top is a graph showing the material entry detection signal. The third graph from the top is a graph showing the material detachment detection signal. The lowermost graph is a graph showing a material total length measurement signal.

Time T0 is the time when the material bites into the upper roll 21 and the lower roll 22 . Time T is the time when the material has been rolled by length L. Time T1 is the time when the rolled material 42 is rolled from the tip to the position of L1. Time T2 is the time when the rolled material 42 is rolled from the tip to the position of L2.

For example, the data extraction unit 2a (not shown) extracts the roll physical quantity signal in a time range based on the elapsed time after the start of rolling. Specifically, the data extracting unit 2a extracts the roll phenomenon data related to the upper roll 21 from the start of rolling to the time L is rolled by setting the cut-out time range from time T0 to time T. The data extraction unit 2a extracts the roll phenomenon data related to the upper roll 21 from the start of rolling to the distance L1 by setting the cut-out time range from time T0 to time T1.

For example, the data extraction unit 2a collects roll phenomenon data during rolling of appropriate portions from the portions of the material 42 after rolling. Specifically, the data extraction unit 2a obtains the time range from time T1 to T2 by referring to the material total length measurement signal as the timing corresponding to the time range corresponding to the intermediate portions L1 to L2 of the rolled material 42. . The data extraction unit 2a extracts the roll physical quantity signal in the time range from time T1 to time T2. As a result, the data extracting unit 2a collects roll phenomenon data during rolling from L1 to L2 of the post-rolling material 42 .

Next, an example of roll phenomenon data before processing and roll phenomenon data after preprocessing will be described with reference to FIG.
FIG. 4 is a graph showing an example of unprocessed roll phenomenon data and preprocessed roll phenomenon data of the roll management device according to the first embodiment.

The upper graph in FIG. 4 is a graph showing pre-treatment roll phenomenon data relating to the vibration of the rolling rolls collected by the data extraction unit 2a. The lower graph in FIG. 4 is a graph showing the preprocessed roll phenomenon data processed by the data preprocessing unit 2b. As shown in FIG. 4, the unprocessed roll phenomenon data contains noise. The noise includes instantaneous noise and low-frequency noise with large undulations. Filtering removes noise from the preprocessed roll phenomenon data.

Next, an example of the stratified phenomenon history database will be described with reference to FIG.
FIG. 5 is a diagram showing an example of the stratified phenomenon history database of the role management device according to the first embodiment.

As shown in FIG. 5, the layered phenomenon history data records rolling material ID, roll ID, check ID, rolling material type, rolling material dimensions, rolling conditions, data acquisition time, and state quantification data as items. . For example, in the stratified phenomenon history data, the data is recorded separately for each item such as data record 1, data record 2, and data record 3 at the time of data acquisition and for each stratum.

Next, an example of the state determination threshold database will be described with reference to FIG.
6 is a diagram illustrating an example of a state determination threshold database of the role management device according to Embodiment 1. FIG.

As shown in FIG. 6, a plurality of state determination thresholds are set for each state quantification data in the state determination threshold database. For example, in the example shown in FIG. 6, in the case of the threshold value X1 for the state quantification data A, the state level is "level 1".

Next, an example of the state mode database will be described with reference to FIG.
7 is a diagram illustrating an example of a state mode database of a role management device according to Embodiment 1. FIG.

As shown in FIG. 7, in the state mode database, a state mode to be determined is set for each combination of a data item that violates the state determination threshold and its state level. For example, in the example shown in FIG. 7, the data item that conflicts with the state determination threshold is state quantified data A, the state level is 2, and the data item that conflicts with the state determination threshold is state quantified data B, and the state If the level is 2, the state mode is determined to be "possible state mode X".

Next, an example of the recommended application method database will be described with reference to FIG.
8 is a diagram illustrating an example of a recommended application method database of the role management device according to Embodiment 1. FIG.

As shown in FIG. 8, the recommended application method for the determined state mode is set in the recommended application method database. For example, in the example shown in FIG. 9, when it is determined that there is a possibility of state mode X, the recommended legal method is "load reduction".

Next, the operation of the role management device 1 will be described using FIG.
FIG. 9 is a flow chart for explaining an overview of the operation of the role management device according to the first embodiment.

In step S1, the rolling mill 11 starts rolling the material. After that, the data collecting unit 2 performs the operation of step S2.

In step S2, the data collection unit 2 collects roll phenomenon data. After that, the data quantification unit 3 performs the operation of step S3.

In step S3, the data quantification unit 3 generates state quantification data. After that, the data storage unit 4 performs the operation of step S4.

In step S4, the data storage unit 4 stores state quantification data. Next, the data storage unit 4 reads stratified phenomenon history data based on the input from the process computer 12 . After that, the state determination unit 5 performs the operation of step S5.

In step S5, the state determination unit 5 determines the state mode of the rolling rolls based on the stratified phenomenon history data. After that, the recommended application method determination unit 6 performs the operation of step S6.

In step S6, the recommended application method determination unit 6 determines a recommended legal method based on the state mode. After that, the role management device 1 performs the operation of step S7.

In step S7, the role management device 1 displays the recommended legal method to the outside. After that, the role management device 1 ends the flow.

Next, an example of the role management device 1 will be described using FIG.
FIG. 10 is a hardware configuration diagram of the role management device according to the first embodiment.

Each function of the role management device 1 can be realized by a processing circuit. For example, the processing circuitry comprises at least one processor 100a and at least one memory 100b. For example, the processing circuitry comprises at least one piece of dedicated hardware 200 .

When the processing circuit includes at least one processor 100a and at least one memory 100b, each function of the role management device 1 is realized by software, firmware, or a combination of software and firmware. At least one of software and firmware is written as a program. At least one of software and firmware is stored in at least one memory 100b. At least one processor 100a realizes each function of the role management device 1 by reading and executing a program stored in at least one memory 100b. The at least one processor 100a is also referred to as a central processing unit, processing unit, arithmetic unit, microprocessor, microcomputer, DSP. For example, the at least one memory 100b is a nonvolatile or volatile semiconductor memory such as RAM, ROM, flash memory, EPROM, EEPROM, magnetic disk, flexible disk, optical disk, compact disk, mini disk, DVD, or the like.

Where the processing circuitry comprises at least one piece of dedicated hardware 200, the processing circuitry may be implemented, for example, in single circuits, multiple circuits, programmed processors, parallel programmed processors, ASICs, FPGAs, or combinations thereof. be. For example, each function of the monitoring device 9 is implemented by a processing circuit. For example, each function of the role management device 1 is collectively realized by a processing circuit.

A part of each function of the role management device 1 may be realized by dedicated hardware 200 and the other part may be realized by software or firmware. For example, the functions of the data sampling unit 2 are realized by a processing circuit as dedicated hardware 200, and the functions other than the functions of the data sampling unit 2 are implemented by at least one processor 100a and a program stored in at least one memory 100b. may be implemented by reading and executing

Thus, the processing circuit implements each function of the role management device 1 with hardware 200, software, firmware, or a combination thereof.

According to Embodiment 1 described above, the roll management device 1 presents a recommended application method for a specific rolling roll based on the state of the specific rolling roll. Therefore, rolling rolls can be applied appropriately.

In addition, the roll management device 1 can suppress abnormalities in the rolling rolls. Therefore, it is possible to systematically produce the rolled material.

Moreover, the roll management device 1 can suppress breakage of the rolling rolls. Therefore, it is possible to reduce the influence of failure of the rolling mill on equipment other than the rolling mill.

Further, the role management device 1 automatically performs data quantification. Therefore, the user 7 does not need to perform data quantification work.

The roll management device 1 also records a plurality of data regarding rolling. Therefore, there is no need to integrate multiple pieces of rolling data.

In addition, the roll management device 1 presents to the user 7 the recommended application method of the rolling rolls and stratified phenomenon history data. Therefore, the user 7 can determine how the rolling rolls applied to the rolling mill 11 should be applied to rolling based on his/her own experience and knowledge.

The role management device 1 also includes a state determination threshold database. Therefore, the determination accuracy for each rolling position is improved.

The roll management device 1 also quantifies the roll phenomenon data to generate state quantified data. Therefore, the roll state can be quantitatively grasped.

Also, the role management device 1 collects only the data of the timing corresponding to the required time range. Therefore, the amount of data to be collected can be reduced. As a result, the data processing time can be shortened, the calculation load can be reduced, and the processing accuracy can be improved. As a result, the roll phenomenon data before processing can be processed using a general-purpose computer.

Further, the roll management device 1 collects pre-processing roll phenomenon data at appropriate sampling intervals. Therefore, the amount of data to be collected can be reduced. As a result, the data processing time can be shortened, the calculation load can be reduced, and the processing accuracy can be improved. As a result, the roll phenomenon data before processing can be processed using a general-purpose computer.

Further, the roll management device 1 collects the entire pre-processing roll phenomenon data within an appropriate sampling time range. Therefore, the unprocessed roll phenomenon data can be processed using a general-purpose computer.

In addition, the roll management device 1 sets the leading end of the entire length of the material, the middle of the entire length of the material, and the trailing end of the entire length of the material as appropriate sampling time ranges. Therefore, the determination accuracy for each rolling position is improved.

Note that the role management device 1 does not have to include the data quantification unit 3 . In this case, the data storage unit 4 receives preprocessed roll phenomenon data from the data collection unit 2 . As a result, the roll management device 1 determines the recommended application method of the rolling rolls based on the preprocessed roll phenomenon data.

In the description of the first embodiment, the data extraction unit 2a has exemplified the method of collecting data at the timing corresponding to the required time range, but other means for obtaining appropriate timing may be substituted.

Further, the roll management device 1 generates preprocessed roll phenomenon data by applying a filter to the unprocessed roll phenomenon data. Therefore, it is possible to shorten the data processing time, reduce the calculation load, and improve the processing accuracy.

It should be noted that the execution of the preprocessing of the roll phenomenon data before processing in the data collecting means may be accompanied by data cleansing such as complementation of missing data or normalization of different data formats.

Note that the roll management device 1 does not need to perform filter processing and data cleansing on unprocessed roll phenomenon data.

Note that the data quantification unit 3 may be integrated with the data collection unit 2 .

Although the upper rolling roll 21 has been described as a target to be managed, the lower rolling roll 22 may be a target to be managed. In this case, the roll physical quantity sensor 31 may measure the physical quantity of the lower roll 22 .

Although the upper rolling roll 21 has been described as being managed, both the upper rolling roll 21 and the lower rolling roll 22 may be managed. In this case, the roll physical quantity sensor 31 may measure the physical quantity of the upper rolling roll 21 and the lower rolling roll 22 respectively.

When the recommended application method determination unit 6b reads data related to application conditions given for determining a recommended application method from the data storage unit 4, it reads out data that matches all the data items that make up the application conditions. may

When the recommended application method determination unit 6b reads data related to application conditions given for determining a recommended application method from the data storage unit 4, data whose partial data items match may be read.

Embodiment 2.
FIG. 11 is a configuration diagram of a role management device according to the second embodiment. The same reference numerals are given to the same or corresponding parts as those of the first embodiment. Description of this part is omitted.

The data quantification unit 3 in the second embodiment includes a frequency analysis unit 3b.

The frequency analysis unit 3b performs frequency analysis on preprocessed roll phenomenon data to be subjected to data quantification, and converts the data into frequency domain data such as signal strength for each frequency component. The frequency analysis unit 3b generates state quantification data based on the transformed frequency domain data. For example, the frequency analysis is a known analysis method such as Fourier transform, discrete Fourier transform, or wavelet transform that converts roll phenomenon data expressed in the time domain into data expressed in the frequency domain, such as signal strength for each frequency component.

According to the second embodiment described above, it is possible to generate state quantified data that quantifies what kind of frequency components are included in roll phenomenon data and how much. Therefore, it is possible to increase the types of state quantification data items to be subjected to state determination. As a result, it is possible to improve the accuracy of specifying the state mode. Furthermore, it is possible to present the user 7 with a useful recommended method of use and judgment basis data.

Embodiment 3.
FIG. 12 is a configuration diagram of a role management device according to the third embodiment. The same reference numerals are given to the same or corresponding parts as those of the second embodiment. Description of this part is omitted.

The quantification unit 3 in Embodiment 3 includes a data model estimation unit 3c. The data model estimation unit 3c analyzes the preprocessed roll phenomenon data to be subjected to data quantification based on the data model to generate state quantification data. A data model is a known model such as a probability density function model, an autoregressive model or a neural network model.

According to the third embodiment described above, the parameters of the data model can be used as quantification means. Therefore, it is possible to increase the types of state quantification data items to be subjected to state determination. As a result, it is possible to improve the accuracy of specifying the state mode. Furthermore, it is possible to present the user 7 with a useful recommended method of use and judgment basis data.

Note that the quantification unit 3 in the third embodiment does not have to include the frequency analysis unit 3b.

Embodiment 4.
FIG. 13 is a configuration diagram of a role management device according to the fourth embodiment. The same reference numerals are given to the same or corresponding parts as those of the third embodiment. Description of this part is omitted.

The data quantification section 3 in Embodiment 4 includes a quantification data manual input unit 3d. The quantified data manual input unit 3d accepts input of externally quantified data. For example, externally quantified data is data quantified by the user 7 based on his/her own experience and knowledge. Specifically, the externally quantified data is data based on events discovered by the operator. For example, the data based on the events discovered by the operator includes rolling unstable events such as material meandering and lateral slippage during rolling, rolling failure events such as product defects and product shape defects, and material and roll rolls. Rolling facility state events such as collisions, rolling roll state vibrations, rolling roll overloads, and rolling roll flaws, the number of occurrences of these, evaluation points, or the number of occurrences and evaluation points.

According to the fourth embodiment described above, externally quantified data are accepted. Therefore, it is possible to increase the types of state quantification data items to be subjected to state determination. As a result, it is possible to improve the accuracy of specifying the state mode. Furthermore, it is possible to present the user 7 with a useful recommended method of use and judgment basis data.

Note that the quantification unit 3 in the fourth embodiment does not have to include the frequency analysis unit 3b.

Note that the quantification unit 3 in the fourth embodiment does not have to include the data model estimation unit 3c.

Embodiment 5.
FIG. 14 is a configuration diagram of a role management device according to the fifth embodiment. The same reference numerals are given to the same or corresponding parts as those of the first embodiment. Description of this part is omitted.

The state determination section 5 in Embodiment 5 includes a state determination threshold calculation unit 5c.

The state determination threshold calculation unit 5c dynamically calculates the state determination threshold from the state quantification data. The state determination threshold calculation unit 5c sets the calculated state determination threshold. For example, when a rolling roll ID and application conditions are given, the state determination threshold calculation unit 5c applies a method of calculating a state judgment threshold such as Hotelling theory to state quantification data related to the rolling roll ID. As a result, the state determination threshold calculation unit 5c dynamically calculates the state determination threshold.

According to the fifth embodiment described above, the state determination threshold is dynamically calculated by the state determination threshold calculation unit 5c. Therefore, when an unexpected situation occurs, the state determination unit 5 can change the state determination threshold value according to the situation. As a result, it is possible to improve the accuracy of specifying the state mode. Furthermore, it is possible to present the user 7 with a useful recommended method of use and judgment basis data.

Embodiment 6.
FIG. 15 is a configuration diagram of a role management device according to the sixth embodiment. The same reference numerals are given to the same or corresponding parts as those of the fifth embodiment. Description of this part is omitted.

The state determination section 5 in the sixth embodiment includes a state determination logic estimation unit 5d.

The state determination logic estimating unit 5d builds a causal relationship model from the rolling roll ID, stratified phenomenon history data, and application condition data. The state determination logic estimating unit 5d compares the constructed causality model with the application condition data during rolling, and sets logic for determining the state mode. For example, the causality model is a non-statistical causality model such as a statistical causality model, a decision tree, or a neural network. The state determination logic estimation unit 5d sets the logic for determining the state mode for the combination of the data item that violates the state determination threshold and the state level based on the causality model. The state determination unit 5 determines the state mode based on the logic.

According to the sixth embodiment described above, the state determination unit 5 determines the state mode based on the logic. Therefore, it is possible to improve the accuracy of specifying the state mode. Furthermore, it is possible to present the user 7 with a useful recommended method of use and judgment basis data.

It should be noted that the state determination section 5 in Embodiment 6 does not have to include the state determination threshold calculation unit 5c.

Modification.
The role management device 1 in the modified example has the same configuration as the role management device 1 in the first embodiment.
The recommended application method determination unit 6b in Embodiment 7 may estimate the recommended application method under the application condition of the rolling roll ID from the state modes under the same application condition regarding other rolling roll IDs.

When a roll ID and an application condition are given, the recommended application method determination unit 6b uses the applicable condition as a key regardless of the roll ID to determine the stratified phenomenon history data related to the applicable condition and the stratified A state mode determined by the state determining device by executing processing on the phenomenon history data is obtained.

For example, when given a rolling roll ID and an application condition, the recommended application method determination unit 6b determines the same stratification phenomenon history data and the stratification phenomenon history data that are the same as the application condition regardless of the rolling roll ID. The state mode determined by the state determination device is obtained. Specifically, the recommended application method determination unit 6b, when rolling a soft material and wide material with a certain roll, stratified phenomenon history data when rolling a soft material and wide material with respect to other rolls Then, the status mode determined by the status determination device is obtained by executing the process on the stratified phenomenon history data.

For example, when a certain rolling roll ID and application conditions are given, the recommended application method determination unit 6b determines the stratification phenomenon history data similar to the applicable conditions regardless of the rolling roll ID and the stratification phenomenon history data. The state mode determined by the state determination device is obtained. The recommended application method determination unit 6b is used for rolling a soft material and a wide material with a certain roll, regardless of the hardness of the material with respect to other rolls. Then, the status mode determined by the status determination device is obtained by executing the process on the stratified phenomenon history data.

According to the variant described above, the recommended application method determination unit 6b obtains the status mode regardless of the roll ID. Therefore, the roll management device 1 can determine the recommended application method for data related to the same rolling conditions. As a result, the role management device 1 can perform a wide range of determinations, and can improve determination accuracy.

Embodiment 7.
FIG. 16 is a configuration diagram of a role management device according to the seventh embodiment. The same reference numerals are given to the same or corresponding parts as those of the first embodiment. Description of this part is omitted.

The state determination unit 5 in the eighth embodiment includes a state occurrence prediction unit 5e.

The state occurrence prediction unit 5 e transmits state mode data based on inference based on prior knowledge to the recommended application method determination unit 6 . Specifically, the reasoning by prior knowledge is that for a certain state mode: P, if a certain roll ID: X occurs under the applicable condition: A, a different roll ID: Y and a different applicable condition: If there is an inference that a similar state mode can occur under B, the recommended application method determination unit 6 performs the following operations. The recommended application method determination unit 6 tried to obtain the state mode related to the rolling roll ID: Y and the applicable condition: B when the state mode: P occurred under the rolling roll ID: X and the applicable condition: A. At this time, the estimated state mode data indicating that the state mode P can occur is transmitted to the recommended application method determination unit 6 .

According to the seventh embodiment described above, the role management device 1 determines the recommended application method based on inference based on prior knowledge indicating inference. Therefore, even if the state mode has not been determined in the past for a certain rolling roll ID and a certain application condition, the recommended application method can be determined.

1 role management device, 2 data collection unit, 2a data extraction unit, 2b data preprocessing unit, 3 data quantification unit, 3a basic statistics calculation unit, 3b frequency analysis unit, 3c data model estimation unit, 3d manual quantification data input unit 4 data storage unit 4a data storage unit 4b stratified phenomenon history data reading unit 4c stratified phenomenon history database 5 state determination unit 5a state phenomenon database 5b state determination unit 5c state determination threshold calculation unit 5d state determination logic estimation unit 5e state occurrence prediction unit 6 recommended application method determination unit 6a recommended application method database 6b recommended application method determination unit 7 user 11 rolling mill 12 process computer 21 upper rolling roll , 22 lower rolling roll, 31 roll physical quantity sensor, 32 material entry detection sensor, 33 material detachment detection sensor, 34 material total length measurement sensor, 41 material before rolling, 42 material after rolling, 100a processor, 100b memory, 200 hardware

Claims (17)

a data collection unit for collecting physical quantities and rolling application condition data relating to a plurality of rolling rolls during rolling;
a data storage unit for accumulating physical quantities and rolling application condition data collected by the data collection unit up to the previous rolling;
With respect to the applicable rolling condition data of the specific rolling roll used for rolling, which is identical or similar to the applicable rolling condition data accumulated in the data storage unit, the related physical quantity is read, and the specific rolling is performed based on the related physical quantity. a state determination unit that determines the state of the roll;
A recommended application method determination unit that presents a recommended application method for the specific rolling roll based on the state of the specific rolling roll determined by the state determining unit;
A roll management device with The state determination unit reads a physical quantity associated with the applicable rolling condition data for the specific rolling roll accumulated in the data storage unit identical or similar to the applicable rolling condition data for the specific rolling roll, and 2. A roll management device according to claim 1, wherein the state of said specific rolling roll is determined based on related physical quantities. The state determination unit reads a physical quantity associated with the applicable rolling condition data for the other rolls accumulated in the data storage unit that is the same as or similar to the applicable rolling condition data for the specific roll, and reads the related physical quantity. 2. The roll management device according to claim 1, wherein the state of the specific rolling roll is determined based on the physical quantity. 4. The roll management device according to any one of claims 1 to 3, wherein the data collection unit collects the physical quantity based on a predetermined sampling period. 5. The roll management device according to any one of claims 1 to 4, wherein the data collection unit collects physical quantities based on a predetermined sampling time range. The roll management device according to any one of claims 1 to 5, wherein the data collection unit filters or cleanses the collected physical quantities relating to the plurality of rolling rolls during rolling. The data storage unit accumulates a plurality of physical quantities and a plurality of rolling application condition data for each material to be rolled in chronological order by layer,
The state determination unit determines the applicable rolling condition data for the roll ID of the specific rolling roll accumulated in the data storage unit that is identical or similar to the rolling applicable condition data for the specific rolling roll, and determines the relevant physical quantity. and determines the state of the specific rolling roll based on the related physical quantity. The data storage unit accumulates a plurality of physical quantities and a plurality of rolling application condition data for each material to be rolled in chronological order by layer,
The state determination unit builds a causal relationship model for the plurality of physical quantities and the plurality of rolling application condition data accumulated in the data storage unit,
8. The roll management device according to any one of claims 1 to 7, wherein the state of the specific rolling roll is determined by comparing applicable condition data of rolling of the specific rolling roll with a causality model. A data quantification unit that generates state quantification data obtained by quantifying the physical quantity,
The data storage unit accumulates state quantification data generated by the data quantification unit up to the previous rolling,
The state judging section reads the relevant state quantification data for the rolling applicable condition data identical or similar to the rolling applicable condition data of the specific rolling roll and accumulated in the data storage section, and reads the relevant state quantification data. The roll management device according to any one of claims 1 to 8, wherein the state of the specific rolling roll is determined based on quantified data. 10. The roll management device according to claim 9, wherein the data quantification unit quantifies the physical quantity using a basic statistic to generate state quantification data. 10. The roll management device according to claim 9, wherein the data quantification unit quantifies the physical quantity by frequency analysis to generate state quantification data. 10. The roll management device according to claim 9, wherein the data quantification unit analyzes the physical quantity based on a data model to generate state quantification data. 13. The state determination unit according to any one of claims 9 to 12, wherein the state determination unit includes a state determination threshold database that records a state determination threshold that is a threshold for determining the state of the specific rolling roll for the state quantification data. The roll management device according to item 1. The role management device according to claim 13, wherein the state determination unit dynamically calculates the threshold. The state determination unit determines a state level when the rolling roll is applied based on state quantification data related to rolling application condition data accumulated in the data storage unit for the roll ID that is the same as the roll ID of the specific rolling roll. judge,
15. The recommended application method determination unit according to any one of claims 9 to 14, wherein the recommended application method for the specific rolling roll is determined based on the state level determined by the state determination unit. Roll management device. 16. The roll management device according to any one of claims 9 to 15, wherein the state determination unit determines the state of the specific rolling roll based on state quantification data input from the outside. 17. The roll management device according to any one of claims 1 to 16, wherein the state determination unit determines the state of the specific rolling roll based on inference based on prior knowledge.

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