Quality data analysis method of multi-channel steel plate heat treatment unit, product and equipment

Abstract

The invention provides a quality data analysis method of a multi-channel steel plate heat treatment unit. The method comprises the following steps: according to position coordinates of process data acquisition points preset in a relational database and to-be-acquired process parameter information, respectively acquiring process parameters according to a preset acquisition frequency, transmitting the process parameters into a shared memory for time alignment, and establishing a corresponding relationship between the process parameters and acquisition time points; recording the time when the steel plate enters and exits from each section and the running speed in each acquisition period; determining an effective measurement time range of each acquisition point according to the starting point time, and determining corresponding process parameters; according to the running speed and the acquisition frequency of the steel plate, determining a length offset sequence of movement of the steel plate in each acquisition period, and establishing a corresponding relation between the length offset sequence and the process parameters. By means of the technical scheme, the technological parameters in the steel plate treatment process are aligned with the steel plate length, and data support is provided for follow-up waste judgment tracing, parameter optimization and quality control.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a quality data analysis method, product and equipment for a multi-channel steel plate heat treatment unit. Background Art

[0002] In the field of medium and thick plate heat treatment line production, with the continuous development of production lines and the increasing complexity of technology, the requirements for quality data analysis and processing have become increasingly stringent. However, the traditional quality data analysis and processing method has obvious drawbacks: it is difficult to accurately match the process parameters collected in the entire process section with the length of the steel plate, so it is impossible to clearly outline the correspondence between each process parameter and the length of the steel plate. On the one hand, when a problem occurs at a certain position of the finished steel plate, due to the lack of correspondence between the process parameters and the length of the steel plate, it is impossible to conduct an in-depth analysis of the process parameters at the problem position, so that in the subsequent heat treatment process of the steel plate, it is difficult to optimize the process parameters in a targeted manner according to the analysis results; on the other hand, if the heat treatment condition of the steel plate is good, it can be determined that the process curve of this heat treatment is appropriate, but due to the lack of correspondence between the process parameters and the length of the steel plate, these parameters cannot be used next time. Summary of the invention

[0003] In response to one or more of the technical problems existing in the above-mentioned prior art, an embodiment of the present invention provides a quality data analysis method, product and equipment for a multi-channel steel plate heat treatment unit.

[0004] In order to achieve the above object, on the one hand, a quality data analysis method of a multi-channel steel plate heat treatment unit is provided, comprising:

[0005] According to the position coordinates of the process data collection points pre-set in the predetermined relational database, the process parameter information to be collected, the message number of the collection message to which the collection point belongs, and the field offset address corresponding to the collection message, the process parameters of the collection points are collected respectively according to the predetermined collection frequency and transmitted to the shared memory for time alignment, and the corresponding relationship between the collected process parameters and the collection time points is established, wherein the sections involved in the process data include quenching, tempering, traverse, cooling bed, straightening and / or stacking, and the process parameters include temperature, fan speed, current and / or pressure;

[0006] Record the starting time when the steel plate enters the starting point of the corresponding process section and continuously obtain the process data of the steel plate in the corresponding section, wherein the process data includes the running speed of the steel plate and all collected process parameters;

[0007] Determine the effective measurement time range of the collection point in the corresponding section according to the starting time, and determine a plurality of effective collection time points and a plurality of process parameters corresponding to the plurality of effective collection time points included in the effective measurement time range for each process parameter, wherein the effective time range refers to the time range from the time when the head of the steel plate arrives at the collection point to the time when the tail of the steel plate leaves the collection point;

[0008] According to the running speed of the steel plate and the acquisition frequency, a length offset sequence of the steel plate movement in each acquisition cycle corresponding to the multiple process parameters is determined, and a corresponding relationship between the length offset sequence of the steel plate movement and the multiple process parameters is established, wherein the length offset of the steel plate movement is the length offset relative to the head of the steel plate.

[0009] Preferably, the quality data analysis method further comprises, after recording the starting time:

[0010] Recording the end time when the tail of the steel plate leaves the corresponding section;

[0011] According to the number n of sections included in the steel plate heat treatment unit, the acquisition frequency f s , the starting time T 1i and the end time T 2i The total number of time series data items m is calculated, wherein the calculation formula of the total number of time series data items m is:

[0012] When the number of time series data in a section is greater than a preset threshold, the data processing of the section is stopped, and it is determined that the steel plate has an abnormal stay phenomenon in the section.

[0013] Preferably, the quality data analysis method further comprises, after time alignment:

[0014] The process parameters of each section are transmitted to the shared memory in the form of messages at their pre-agreed transmission frequencies for centralized caching. After that, the shared memory outputs a piece of the latest updated data of all process parameters and the data at the current time point to a predetermined time series database at a pre-set frequency, wherein the input and output of the shared memory run independently, and the output time is recorded as the collection time point of the current set of process parameters.

[0015] Preferably, the quality data analysis method, the step of determining the effective measurement time range of the collection point in the corresponding section according to the starting time comprises:

[0016] The following formula is used to determine the number of collection cycles n1 that the head of the steel plate passes from the starting point of the corresponding section to the time when it reaches the collection point and the number of collection cycles n2 that the head of the steel plate passes from the starting point of the corresponding section to the time when the tail of the steel plate leaves the collection point:

[0017]

[0018] Where, l is the length of the finished steel plate, l o is the position offset of the finished steel plate on the raw steel plate, l x is the distance between the acquisition point and the starting point of the corresponding section, f s is the acquisition frequency, v i is the running speed of the steel plate;

[0019] Determine the effective starting time T' of the effective measurement time range 1x and effective end time T′ 2x , and according to the effective starting time T′ 1x and the effective end time T′ 2x Determine the effective measurement time range (T′ 1x , T′ 2x ),in:

[0020] T′ 1x =T 1i +n1*f s ;

[0021] T′ 2x =T 1i +n2*f s ;

[0022] T 1i is the starting time.

[0023] Preferably, the quality data analysis method comprises the step of determining the length offset sequence of the steel plate movement in each acquisition cycle corresponding to the process parameter according to the running speed of the steel plate and the acquisition frequency:

[0024] The acquisition period is calculated according to the acquisition frequency, wherein the calculation formula of the acquisition period is: T is the acquisition period, f s is the acquisition frequency;

[0025] The length offset of the steel plate corresponding to the corresponding effective process parameters is calculated according to the acquisition cycle and the running speed of the steel plate, wherein the calculation formula of the length offset of the steel plate is: l1=l2+v i×T, l1 is the length offset of the steel plate corresponding to the process parameter, l2 is the length offset of the steel plate movement corresponding to the corresponding process parameter in the previous acquisition cycle, v i is the running speed of the steel plate;

[0026] The steel plate length offset corresponding to each of the process parameter acquisition values ​​is calculated in a loop according to the acquisition cycle and the running speed of the steel plate.

[0027] Preferably, the quality data analysis method further comprises:

[0028] Single value calculation and / or array sequence calculation are performed based on the measurement value sequence of the process parameters and the length offset sequence of the steel plate movement, wherein the single value calculation includes extreme value calculation, standard deviation calculation and / or average value calculation for the collection item; wherein, when the single value calculation is extreme value calculation, it also includes calculating the position corresponding to the extreme value.

[0029] Preferably, the quality data analysis method further comprises, before performing array sequence calculation according to the process parameters and the length offset sequence of the steel plate movement:

[0030] Determine a unit length according to a predetermined analysis accuracy, and aggregate the process parameter value into the unit length according to a length offset sequence of the steel plate movement;

[0031] An average of the process parameter values ​​within the unit length is calculated.

[0032] Preferably, in the quality data analysis method, the unit length satisfies Where l3 is the unit length, v i is the running speed of the steel plate, f s is the acquisition frequency.

[0033] On the other hand, a computer program product is also provided, comprising a computer program, wherein when the computer program is executed by a processor, the steps of any of the quality data analysis methods described above are implemented.

[0034] On the other hand, an electronic device is provided, comprising a memory and a processor, wherein the memory stores at least one program, and the at least one program is executed by the processor to implement the steps of any of the quality data analysis methods described above.

[0035] The above technical solution has the following technical effects:

[0036] The technical solution of the embodiment of the present invention is to set the position coordinates of the process data collection points and the process parameter information to be collected in the relational database in advance, and collect the process parameters of each collection point according to the predetermined collection frequency and transfer them to the shared memory for time alignment. There are dozens of collection messages to be transmitted by the multi-channel heat treatment unit. The embodiment of the present invention synchronizes the shared memory so that the collected process parameters can be quickly aligned to a time axis, so that all can be carried using one data table and one time field;

[0037] Furthermore, by recording the time when the steel plate enters and exits each section and the running speed in each collection cycle; determining the effective measurement time range of each collection point according to the starting time, and determining the corresponding process parameters; determining the length offset sequence of the steel plate movement in each collection cycle according to the running speed of the steel plate and the collection frequency, and establishing the correspondence between the length offset sequence and the process parameters, the real-time process parameters of different equipment in the processing of the steel plate can be aligned with the length of the steel plate, providing data support for subsequent scrap tracing, parameter optimization and quality control, reducing the scrap rate, ensuring product quality and improving production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flow chart of a quality data analysis method of a multi-channel steel plate heat treatment unit according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] To further illustrate the various embodiments, the present invention provides drawings. These drawings are part of the disclosure of the present invention, which are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, a person of ordinary skill in the art should be able to understand other possible implementations and advantages of the present invention. The components in the figures are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0040] The present invention will now be further described with reference to the accompanying drawings and specific implementation methods.

[0041] Embodiment 1:

[0042] Figure 1 FIG. 1 is a flow chart of a quality data analysis method of a multi-channel steel plate heat treatment unit according to an embodiment of the present invention. Figure 1 The quality data analysis method based on the steel plate heat treatment unit in this example includes the following steps:

[0043] Step 1: According to the position coordinates of the process data collection points pre-set in the predetermined relational database, the process parameter information to be collected, the message number of the collection message to which the collection point belongs, and the field offset address corresponding to the collection message, the process parameters of the collection points are collected according to the predetermined collection frequency and transmitted to the shared memory for time alignment, wherein the sections involved in the process data include quenching, tempering, traverse, cooling bed, straightening and / or stacking, and the process parameters include temperature, fan speed, current and / or pressure, etc.;

[0044] In a specific implementation, the process data is recorded in a relational database or a relational data table as a retrieval directory for process parameters. The process data also includes the name of the collection point, the range of the collection value, the unit of the collection value, the unit conversion factor, the storage accuracy, the physical relative position of the collection point, the message number corresponding to the collection point, and the starting offset address of the name of the collection point in the message body.

[0045] In a specific implementation, it also includes:

[0046] The process parameters of each section are transmitted to the shared memory in the form of messages at their pre-agreed transmission frequencies for centralized caching. After that, the shared memory outputs a piece of the latest updated data of all process parameters and the data at the current time point to a predetermined time series database at a pre-set frequency, wherein the input and output of the shared memory run independently, and the output time is recorded as the collection time point of the current set of process parameters.

[0047] In a specific implementation, a data structure including floating-point numbers is defined in advance through a data dictionary management tool as a data transmission channel between a message receiving channel and the shared memory and a data carrier within the shared memory. In a specific implementation, a data structure including multiple, for example, 200 floating-point numbers is defined within the shared memory.

[0048] In a specific implementation, the process parameters collected at each collection point are ranked according to the order preset in the relational database, and are stored in sequence in a data structure including floating-point numbers in the shared memory.

[0049] In a specific implementation, although the acquisition frequencies of each segment and / or each acquisition point are different, the data collected by each segment and / or each acquisition point in the shared memory are output at a preset frequency by default. In a specific implementation, if the frequency of data collection of a segment and / or a certain acquisition point is less than the preset frequency, when the data is output according to the preset frequency, if the data of a segment and / or a certain acquisition point is not updated, the data output of the segment and / or the acquisition point in the previous cycle will continue to be output.

[0050] In a specific implementation, the pre-set frequency needs to be adjusted on-site to balance performance and data authenticity.

[0051] Step 2: Record the starting time when the steel plate enters the starting point of the corresponding process section and continuously obtain the process data of the steel plate in the corresponding section, wherein the process data includes the running speed of the steel plate and all collected process parameters;

[0052] In a specific implementation, after recording the starting time, the following is further included:

[0053] Record the end time when the tail of the steel plate leaves the corresponding section;

[0054] According to the number of sections n and the acquisition frequency f of the steel plate heat treatment unit s , starting time T 1i and the end time T 2i The total number of time series data items m is calculated, where the calculation formula for the total number of time series data items m is:

[0055] From the perspective of the protection system, when the number of time series data in a section is greater than the preset threshold, the data processing of the section is stopped; and it is determined that the steel plate has an abnormal stay phenomenon in the section or area.

[0056] In a specific implementation, the process data of the steel plate in the corresponding section is obtained through a service program, wherein the service program includes a processing module for processing messages sent by basic automation, a scanning module for actively and regularly scanning the internal DB blocks of the basic automation PLC, and a communication module for actively and regularly reading the external database.

[0057] Step 3: Determine the effective measurement time range of each collection point in the corresponding section according to the starting time, and determine the multiple effective collection time points and corresponding process parameter values ​​contained in the effective measurement time range for each process parameter, wherein the effective time range refers to the time range from the time when the head of the steel plate arrives at the collection point to the time when the tail of the steel plate leaves the collection point;

[0058] In a specific implementation, according to the correspondence between the process parameters and the acquisition time points, a set of process parameters in the time series data table that is within the effective measurement time range is found.

[0059] In a specific implementation, the step of determining the effective measurement time range of the collection point in the corresponding section according to the starting time includes:

[0060] The following formula is used to determine the number of collection cycles n1 that the head of the steel plate goes through from the starting point of the corresponding section to the time it reaches the collection point, and the number of collection cycles n2 that the head of the steel plate goes through from the starting point of the corresponding section to the time the tail of the steel plate leaves the collection point:

[0061]

[0062] Where, l is the length of the finished steel plate, l o is the position offset of the finished steel plate on the raw steel plate, l x is the distance between the acquisition point and the starting point of the corresponding section, f s is the acquisition frequency, v i is the running speed of the steel plate;

[0063] Determine the effective starting time T′ of the effective measurement time range 1x and effective end time T′ 2x , and according to the effective starting time T′ 1x and effective end time T′ 2x Determine the effective measurement time range (T′ 1x , T′ 2x ),in:

[0064] T′ 1x =T 1i +n1*f s ;

[0065] T′ 2x =T 1i +n2*f s ;

[0066] T 1i The starting time.

[0067] In a specific implementation, the effective measurement time range includes (n2-n1+1) groups of effective acquisition time points and effective process parameters corresponding to the effective acquisition time points.

[0068] Step 4: Determine the length offset sequence of the steel plate movement in each acquisition cycle corresponding to the process parameter value based on the running speed of the steel plate and the acquisition frequency, and establish a corresponding relationship between the length offset sequence of the steel plate movement and the process parameter value, wherein the length offset of the steel plate movement is the position offset relative to the head of the steel plate.

[0069] In a specific implementation, when establishing the corresponding relationship between the length offset of the steel plate movement and the process parameters, the process parameters remain unchanged.

[0070] In a specific implementation, after the raw steel plate is produced by the steel plate heat treatment unit, it is determined whether the processed finished steel plate is cut during the production process. If cutting occurs, the finished steel plate needs to be mapped to the raw steel plate when aligning the process parameters in the production process to the length of the finished steel plate.

[0071] In a specific implementation, it is assumed that the steel plate moves at a uniform speed within the same acquisition cycle, and the steps of determining the offset sequence of the steel plate movement corresponding to the process parameter value according to the running speed of the steel plate and the acquisition frequency include:

[0072] The collection period is calculated according to the collection frequency, where the calculation formula of the collection period is: T is the acquisition period, f s is the acquisition frequency;

[0073] According to the acquisition cycle and the running speed of the steel plate, the length offset sequence of the steel plate movement corresponding to the corresponding process parameter value is calculated, wherein the calculation formula of the length offset of the steel plate movement is: l1 = l2 + v i ×T, l1 is the length offset of the steel plate movement corresponding to the corresponding effective process parameters, l2 is the length offset of the steel plate movement corresponding to the corresponding process parameters in the previous acquisition cycle, v i is the running speed of the steel plate;

[0074] The loop is executed to calculate the length offset of the steel plate movement corresponding to multiple effective process parameters according to the acquisition cycle and the running speed of the steel plate.

[0075] In a specific implementation, it also includes:

[0076] Single value calculation and / or array sequence calculation are performed according to the process parameters and the length offset of the steel plate movement, wherein the single value calculation includes extreme value calculation, standard deviation calculation and / or average value calculation for the acquisition item; wherein, when the single value calculation is extreme value calculation, it also includes calculating the position corresponding to the extreme value. In the specific implementation, the array sequence calculation result is converted into a process data curve of the steel plate length.

[0077] In a specific implementation, before performing array sequence calculation according to the process parameters and the length offset sequence of the steel plate movement, the method further includes:

[0078] Determine the unit length according to a predetermined analysis accuracy, and aggregate the process parameter values ​​into the unit length according to the length offset sequence of the steel plate movement;

[0079] Calculate the average of the process parameter values ​​within a unit length.

[0080] In a specific implementation, after the steel plate is produced by a heat treatment unit, the length of the finished steel plate is divided into areas of the same length according to the required analysis accuracy, and the same number of storage space entries are created according to the number of divided areas. Finally, the process parameters collected at each collection point are aggregated into the divided areas in a superimposed manner according to the length offset of the steel plate movement corresponding to the process parameters. The process parameters corresponding to the area are the average of the superimposed process parameters in the area.

[0081] In one specific implementation, the unit length satisfies Among them, l3 is the unit length, v i is the running speed of the steel plate, f sis the acquisition frequency. In the specific implementation, the unit length l3 is much larger than

[0082] In a specific implementation, the analyzed and processed data is stored in a database, wherein the data to be stored includes: finished steel plate data, single value calculation results and / or array sequence calculation results, wherein the finished steel plate data includes size, production time, and position mapping relationship between the finished steel plate and the raw steel plate.

[0083] The technical solution of the embodiment of the present invention transmits collected data by means of internal messages to improve compatibility, and adopts a centralized storage method based on shared memory to speed up the reading speed. At the same time, the measured value is aligned with the material length by relying on the section running speed. In the process of analyzing the measured value, only a small number of iterative cycles are required to align the time series data to the steel plate, thus avoiding the storage and calculation of a large amount of tracking data, having strong adaptability and faster data processing speed.

[0084] A specific application example of an embodiment of the present invention is given below.

[0085] Application environment: Continuous heat treatment line of a hot rolling mill of a steel company, steel plate thickness 3mm-12mm, width 900mm-2000mm. Varieties include: structural steel, wear-resistant steel, tempered plate, etc.

[0086] Taking the heat treatment furnace of this project as an example for analysis, it is required to collect and analyze the temperature changes of each section in the furnace during the heating process of each steel plate in the heat treatment furnace to provide data support for subsequent pattern analysis. During the on-site inspection, it was learned that the instrument layout of the furnace evenly divides the furnace area into 32 areas, each area has a corresponding instrument. First, the physical distance of the entrance and exit of the furnace area and the length of the heating furnace are set (assuming that the total length of the heating furnace is 120m). After taking the entrance of the heating furnace as the starting point for collection, fill in the reference physical distance of each measuring instrument, and then transmit the heating furnace temperature data to the collection program once per second through a message for time alignment, and continue to write it into the timing table at a rate of once per second (f s =1), and then according to the time when the steel plate enters the furnace and the running speed per second in the furnace (assuming that the heating time in the furnace is set to 45min and the running speed in the furnace is 2.6m / min), the temperature measurement value sequence of each finished steel plate heated in the furnace can be obtained first, and then the temperature measurement value sequence of each finished steel plate can be calculated accurately to each meter of steel plate according to the requirements. The unit length can be set to 1m to obtain the corresponding single value result and numerical trend of the measurement, and accurately depict the temperature running trajectory of the steel plate in the furnace.

[0087] Embodiment 2:

[0088] The present invention also provides a computer program product, comprising a computer program, characterized in that when the computer program is executed by a processor, the steps of any of the quality data analysis method embodiments described above are implemented.

[0089] Embodiment three:

[0090] The present invention also provides an electronic device, comprising a processor, a memory, a bus, and a computer program stored in the memory and executable on the processor, wherein the processor comprises one or more processing cores, the memory is connected to the processor via a bus, the memory is used to store program instructions, and the processor implements the steps in the above-mentioned method embodiment of the first embodiment of the present invention when executing the computer program.

[0091] Further, as an executable solution, the electronic device may be a computer unit, and the computer unit may be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The computer unit may include, but is not limited to, a processor and a memory. Those skilled in the art may understand that the composition structure of the above-mentioned computer unit is only an example of a computer unit and does not constitute a limitation on the computer unit, and may include more or less components than the above-mentioned, or a combination of certain components, or different components. For example, the computer unit may also include input and output devices, network access devices, buses, etc., which are not limited in the embodiments of the present invention.

[0092] Further, as an executable solution, the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the computer unit, and various interfaces and lines are used to connect the various parts of the entire computer unit.

[0093] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the computer unit by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required for a function; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0094] Although the present invention has been specifically shown and described in conjunction with the preferred embodiments, it should be understood by those skilled in the art that various changes may be made to the present invention in form and details without departing from the spirit and scope of the present invention as defined by the appended claims, all of which are within the scope of protection of the present invention.

Claims

1. A quality data analysis method for a multi-channel steel plate heat treatment unit, characterized in that: include: According to the position coordinates of the process data collection points pre-set in the predetermined relational database, the process parameter information to be collected, the message number of the collection message to which the collection point belongs, and the field offset address corresponding to the collection message, the process parameters of each collection point are collected respectively according to the predetermined collection frequency and are transferred to the shared memory for time alignment, wherein the sections involved in the process data include quenching, tempering, traverse, cooling bed, straightening and / or stacking, and the process parameters include temperature, fan speed, current and / or pressure; Record the starting time when the steel plate enters the starting point of the corresponding process section and continuously obtain the process data of the steel plate in the corresponding section, wherein the process data includes the running speed of the steel plate and all collected process parameters; Determine the effective measurement time range of each collection point in the corresponding section according to the starting time, and determine a plurality of effective collection time points and corresponding process parameter values ​​included in the effective measurement time range for each process parameter, wherein the effective time range refers to the time range from the time when the head of the steel plate arrives at the collection point to the time when the tail of the steel plate leaves the collection point; According to the running speed of the steel plate and the acquisition frequency, a length offset sequence of the steel plate movement in each acquisition cycle corresponding to the process parameter value is determined, and a corresponding relationship between the length offset sequence of the steel plate movement and the process parameter value is established, wherein the length offset of the steel plate movement is a position offset relative to the head of the steel plate.

2. The quality data analysis method according to claim 1, characterized in that: After recording the starting time, the method further includes: Recording the end time when the tail of the steel plate leaves the corresponding section; According to the number n of sections included in the steel plate heat treatment unit, the acquisition frequency f s , the starting time T 1i and the end time T 2i The total number of time series data items m is calculated, wherein the calculation formula of the total number of time series data items m is: When the number of time series data in a section is greater than a preset threshold, the data processing of the section is stopped, and it is determined that the steel plate has an abnormal stay phenomenon in the section.

3. The quality data analysis method according to claim 1, characterized in that: After time alignment, it also includes: The process parameters of each section are transmitted to the shared memory in the form of messages at their pre-agreed transmission frequencies for centralized caching. After that, the shared memory outputs a piece of the latest updated data of all process parameters and the data at the current time point to a predetermined time series database at a pre-set frequency, wherein the input and output of the shared memory run independently, and the output time is recorded as the collection time point of the current set of process parameters.

4. The quality data analysis method according to claim 1, characterized in that: The step of determining the effective measurement time range of the acquisition point in the corresponding section according to the starting time includes: The following formula is used to determine the number of collection cycles n1 that the head of the steel plate passes from the starting point of the corresponding section to the time when it reaches the collection point and the number of collection cycles n2 that the head of the steel plate passes from the starting point of the corresponding section to the time when the tail of the steel plate leaves the collection point: Where, l is the length of the finished steel plate, l o is the position offset of the finished steel plate on the raw steel plate, l x is the distance between the acquisition point and the starting point of the corresponding segment, f s is the acquisition frequency, v i is the running speed of the steel plate; Determine the effective starting time T' of the effective measurement time range 1x and effective end time T′ 2x , and according to the effective starting time T′ 1x and the effective end time T′ 2x Determine the effective measurement time range (T′ 1x , T′ 2x ),in: T′ 1x =T 1i +n1*f s ; T′ 2x =T 1i +n2*f s ; T 1i is the starting time.

5. The quality data analysis method according to claim 1, characterized in that: The step of determining the length offset sequence of the steel plate movement in each acquisition cycle corresponding to the process parameter according to the running speed of the steel plate and the acquisition frequency comprises: The acquisition period is calculated according to the acquisition frequency, wherein the calculation formula of the acquisition period is: T is the acquisition period, f s is the acquisition frequency; The length offset of the steel plate movement corresponding to the corresponding process parameters is calculated according to the acquisition cycle and the running speed of the steel plate, wherein the calculation formula of the length offset of the steel plate movement is: l1=l2+v i ×T, l1 is the length offset of the steel plate movement corresponding to the process parameter, l2 is the length offset of the steel plate movement corresponding to the corresponding process parameter in the previous acquisition cycle, v i is the running speed of the steel plate; The loop is executed to calculate the length offset of the movement of the steel plate corresponding to each of the process parameter collection values ​​according to the collection period and the running speed of the steel plate.

6. The quality data analysis method according to claim 1, characterized in that: Also includes: Single value calculation and / or array sequence calculation are performed based on the measurement value sequence of the process parameters and the length offset sequence of the steel plate movement, wherein the single value calculation includes extreme value calculation, standard deviation calculation and / or average value calculation for the collection item; wherein, when the single value calculation is extreme value calculation, it also includes calculating the position corresponding to the extreme value.

7. The quality data analysis method according to claim 6, characterized in that: Before performing array sequence calculation according to the process parameters and the length offset sequence of the steel plate movement, the method further includes: Determine a unit length according to a predetermined analysis accuracy, and aggregate the process parameter value into the unit length according to a length offset sequence of the steel plate movement; An average of the process parameter values ​​within the unit length is calculated.

8. The quality data analysis method according to claim 7, characterized in that: The unit length satisfies Where l3 is the unit length, v i is the running speed of the steel plate, f s is the acquisition frequency.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the quality data analysis method according to any one of claims 1 to 8 are implemented.

10. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores at least one program, and the at least one program is executed by the processor to implement the steps of the quality data analysis method according to any one of claims 1 to 8.

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