Method and system for collecting high-frequency data of hot-rolled strip at the same location for metallurgy

Abstract

The present invention provides a method and system for collecting high-frequency data from co-located points of hot-rolled steel strip for metallurgy, comprising: step S1: calculating the correspondence between slab positions and time points; step S2: obtaining required co-located point data based on the correspondence between slab positions and time points; and step S3: converting the co-located point data into equidistant co-located point data. Based on actual process conditions, the present invention sets the slab position interval (step size) as needed, calculates co-located point data (including important indicators such as temperature and rolling force), and then comprehensively assesses slab quality based on the co-located point data in combination with these important indicators, thereby improving hot rolling production efficiency.

Description

Technical Field

[0001] The present invention relates to high-frequency data acquisition technology for metallurgical hot rolling production lines, and more specifically, to a method and system for acquiring high-frequency data from the same point in a hot-rolled steel strip mill. In particular, the present invention relates to the acquisition of high-frequency data generated by a hot rolling mill during steel biting and casting. Background Art

[0002] High-frequency data at the same point in hot rolling is crucial to judging the quality of the slabs produced by hot rolling. Currently, there is no technology that can obtain high-frequency data at the same point, resulting in the inability to quickly judge the quality of the produced slabs and adjust the production parameters of the next slab in time.

[0003] Patent document CN101488907A discloses a method for collecting and transmitting high-frequency telegram signals. The method comprises: a data acquisition module collects high-frequency production signals, converts them into digital high-frequency telegram signals, and transmits them to a data transmission module; the data transmission module packages the high-frequency telegram signals and transmits them via a network to a data receiving module; and the data receiving module receives the packaged telegram signals and unpacks them for storage. Patent document CN101488907A describes a technique for converting high-frequency production signals into digital high-frequency telegram signals, thereby solving the problem of collecting and transmitting high-frequency data. The technique aims to increase data transmission frequency and reduce data loss.

[0004] However, no technical solution has been found in the prior art that can effectively obtain high-frequency data of the same position of hot-rolled strip through hardware acquisition technology. Summary of the Invention

[0005] In view of the defects in the prior art, the purpose of the present invention is to provide a method and system for collecting high-frequency data of hot-rolled strip at the same point in metallurgy.

[0006] According to the present invention, a method for collecting high-frequency data of hot-rolled strip at the same point in metallurgy is provided, comprising:

[0007] Step S1: Calculate the corresponding relationship between the slab position and the time point;

[0008] Step S2: acquiring required data and point data according to the corresponding relationship between the slab position and the time point;

[0009] Step S3: converting the simultaneous point data into equidistant co-location point data.

[0010] Preferably, in step S1:

[0011] Obtain the steel biting time T1 and steel throwing time T2 of the strip in the rolling mill;

[0012] According to the time interval [T1, T2], the time point data of strip speed or rolling mill linear speed are intercepted: (t1, y(Spd)1), (t2, y(Spd)2), ..., (t N ,y(Spd) N )t i ∈[T1,T2],i∈Z,N∈Z;

[0013] y(Spd) i represents the strip speed at the i-th moment;

[0014] Based on the above known speed data at each time point, the corresponding relationship between the slab position and the time point is calculated by integration:

[0015] (t1,y(LenOri)1),(t2,y(LenOri)2),……,(t N ,y(LenOri) N )t i ∈[T1,T2],i∈Z,N∈Z

[0016] y(LenOri) N represents the position of the slab at the i-th moment;

[0017] The slab length is multiplied by the slip coefficient fs to obtain the corresponding relationship between the adjusted slab position and the time point:

[0018] (t1,y(LenOri)1*fs),(t2,y(LenOri)2*fs),……,(t N ,y(LenOri) N *f s )t i ∈[T1,T2],i∈Z,N∈Z, abbreviated as:(t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z;

[0019] Among them, (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z is a set of simultaneous point data of the strip passing through the rolling mill;

[0020] t i represents the i-th moment;

[0021] y(Len) i represents the length of the strip passing through the rolling mill at the i-th moment;

[0022] T1 represents the moment when the strip bites the steel in the rolling mill;

[0023] T2 represents the time when the strip is thrown from the rolling mill;

[0024] Z represents the set of positive integers;

[0025] N represents the number of moments.

[0026] Preferably, in step S2:

[0027] Step 2: Calculate the same site data.

[0028] According to the corresponding relationship between the slab position and the time point (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z, intercept the required data and point the data at the same time:

[0029] (t21,y(Temp)1),(t22,y(Temp)2),……,(t2 M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,M∈Z

[0030] t2 i represents the i-th simultaneous point intercepted;

[0031] y(Temp) i represents the temperature at the i-th simultaneous point;

[0032] M represents the number of simultaneous points;

[0033] Among them, (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z get t2 by interpolation i i∈[0,M],t2 i y2(Len) corresponding to the time ∈[T1,T2] i i∈[0,M];

[0034] According to the above calculation results,

[0035] (t21,y(Temp)1),(t22,y(Temp)2),……,(t2 M ,y(Temp) M )t2i ∈[T1,T2],i∈Z,t2 in M∈Z i i∈[0,M],t2 i ∈[T1,T2] is replaced by y2(Len) i i∈[0,M]

[0036] That is, the same site data is obtained:

[0037] (y2(len)1,y(Temp)1),(y2(len)2,y(Temp)2),……,(y2(len) M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,M∈Z, abbreviated as:

[0038] (Len1,Temp1),(Len2,Temp2),……,(Len M ,Temp M )t2 i ∈[T1,T2],i∈Z,M∈Z.

[0039] Preferably, in step S3:

[0040] For (Len1, Temp1), (len2, Temp2), ..., (Len M ,Temp M )t2 i Len in ∈[T1,T2],i∈Z,M∈Z i i∈[0,M], interpolation is performed on the basis of the original co-location data to obtain equidistant co-location data.

[0041] Preferably, in step S3:

[0042] According to the total length of the slab Len M With a given step size Step>0, the slab length is divided into Q equal parts, where:

[0043]

[0044] Get vector A=(0,Step*1,Step*2,Step*3,……Step*Q)

[0045] TRUNC represents a function that truncates a date or number and returns a specified value.

[0046] The values in vector A are passed through (Len1, Temp1), (Len2, Temp2), ..., (Len M ,TempM )t2 i ∈[T1,T2],i∈Z,M∈Z interpolation, get the arithmetic difference and the same point data: (0,Temp0),(Step*1,Temp1),……,(Step*Q,Temp Q )in

[0047] According to the present invention, a system for collecting high-frequency data of hot-rolled strip steel at the same location in metallurgy is provided, comprising:

[0048] Module M1: Calculate the correspondence between slab position and time point;

[0049] Module M2: Acquire required data and point data according to the corresponding relationship between the slab position and the time point;

[0050] Module M3: converting the simultaneous point data into equidistant co-location point data.

[0051] Preferably, in the module M1:

[0052] Obtain the steel biting time T1 and steel throwing time T2 of the strip in the rolling mill;

[0053] According to the time interval [T1, T2], the time point data of strip speed or rolling mill linear speed are intercepted: (t1, y(Spd)1), (t2, y(Spd)2), ..., (t N ,y(Spd) N )t i ∈[T1,T2],i∈Z,N∈Z;

[0054] y(Spd) i represents the strip speed at the i-th moment;

[0055] Based on the above known speed data at each time point, the corresponding relationship between the slab position and the time point is calculated by integration:

[0056] (t1,y(LenOri)1),(t2,y(LenOri)2),……,(t N ,y(LdnOri) N )t i ∈[T1,T2],i∈Z,N∈Z

[0057] y(LenOri) N represents the position of the slab at the i-th moment;

[0058] The slab length is multiplied by the slip coefficient fs to obtain the corresponding relationship between the adjusted slab position and the time point:

[0059] (t1,y(LenOri)1*fs),(t2,y(LenOri)2*fs),……,(t N ,y(LenOri) N *fs)t i ∈[T1,T2],i∈Z,N∈Z, abbreviated as:(t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z;

[0060] Among them, (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z is a set of simultaneous point data of the strip passing through the rolling mill;

[0061] t i represents the i-th moment;

[0062] y(Len) i represents the length of the strip passing through the rolling mill at the i-th moment;

[0063] T1 represents the moment when the strip bites the steel in the rolling mill;

[0064] T2 represents the time when the strip is thrown from the rolling mill;

[0065] Z represents the set of positive integers;

[0066] N represents the number of moments.

[0067] Preferably, in the module M2:

[0068] Step 2: Calculate the same site data.

[0069] According to the corresponding relationship between the slab position and the time point (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z, intercept the required data and point the data at the same time:

[0070] (t21,y(Temp)1),(t22,y(Temp)2),……,(t2 M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,M∈Z

[0071] t2i represents the i-th simultaneous point intercepted;

[0072] y(Temp) i represents the temperature at the i-th simultaneous point;

[0073] M represents the number of simultaneous points;

[0074] Among them, (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z get t2 by interpolation i i∈[0,M],t2 i y2(Len) corresponding to the time ∈[T1,T2] i i∈[0,M];

[0075] According to the above calculation results,

[0076] (t21,y(Temp)1),(t22,y(Temp)2),……,(t2 M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,t2 in M∈Z i i∈[0,M],t2 i ∈[T1,T2] is replaced by y2(Len) i i∈[0,M]

[0077] That is, the same site data is obtained:

[0078] (y2(len)1,y(Temp)1),(y2(len)2,y(Temp)2),……,(y2(len) M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,M∈Z, abbreviated as:

[0079] (Len1,Temp1),(Len2,Temp2),……,(Len M ,Temp M )t2 i ∈[T1,T2],i∈Z,M∈Z.

[0080] Preferably, in the module M3:

[0081] For (Len1, Temp1), (Len2, Temp2), ..., (Len M ,TempM )t2 i Len in ∈[T1,T2],i∈Z,M∈Z i i∈[0,M], interpolation is performed on the basis of the original co-location data to obtain equidistant co-location data.

[0082] Preferably, in the module M3:

[0083] According to the total length of the slab Len M With a given step size Step>0, the slab length is divided into Q equal parts, where:

[0084]

[0085] Get vector A=(0,Step*1,Step*2,Step*3,……Step*Q)

[0086] TRUNC represents a function that truncates a date or number and returns a specified value.

[0087] The values in vector A are passed through (Len1, Temp1), (Len2, Temp2), ..., (Len M ,Temp M )t2 i ∈[T1,T2],i∈Z,M∈Z interpolation, get the arithmetic difference and the same point data: (0,Temp0),(Step*1,Temp1),……,(Step*Q,Temp Q )in

[0088] Compared with the prior art, the present invention has the following beneficial effects:

[0089] 1. The present invention combines the actual process conditions and, under the condition of known simultaneous points, sets the slab position interval (step length) as needed, calculates the slab equal interval position data (including important indicators such as temperature and rolling force), and then comprehensively judges the quality of the slab through the slab equal position data in combination with important indicators to improve the hot rolling production efficiency.

[0090] 2. The present invention obtains high-frequency data of the same point through high-frequency data of the same point, so as to quickly judge the quality of the produced slab and improve the overall production efficiency of the hot rolling unit.

[0091] 3. The calculation process of the present invention is time-saving and the calculation results are accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0093] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0094] The present invention will be described in detail below with reference to specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those skilled in the art, several changes and improvements can be made without departing from the scope of the present invention. These all fall within the scope of protection of the present invention.

[0095] According to the present invention, a method for collecting high-frequency data of hot-rolled strip at the same point in metallurgy is provided, comprising the following steps:

[0096] Step 1: Calculate the length data. Calculating the same point data requires a set of simultaneous point data of the strip passing through the rolling mill, i.e. (t1,y(Len)1), (t2,y(Len)2), ..., (t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z can be used to obtain the length data by integrating the velocity over time.

[0097] t i represents the i-th moment;

[0098] y(Len) i represents the length of the strip passing through the rolling mill at the i-th moment;

[0099] T1 represents the moment when the strip bites the steel in the rolling mill;

[0100] T2 represents the time when the strip is thrown from the rolling mill;

[0101] Z represents the set of positive integers;

[0102] N represents the number of moments.

[0103] Specifically, the strip biting time T1 and the strip throwing time T2 of the rolling mill are obtained; according to the time interval [T1, T2], the time point data of the strip speed or the rolling mill linear speed are intercepted from the self-developed real-time product iHyperDB: (t1, y(Spd)1), (t2, y(Spd)2), ..., (t N ,y(Spd) N )t i ∈[T1,T2],i∈Z,N∈Z;

[0104] y(Spd) i represents the strip speed at the i-th moment;

[0105] Based on the above known speed data at each time point, the corresponding relationship between the slab position and the time point is calculated by integration:

[0106] (t1,y(LenOri)1),(t2,y(LenOri)2),……,(t N ,y(LenOri) N )t i ∈[T1,T2],i∈Z,N∈Z

[0107] y(LenOri) N represents the position of the slab at the i-th moment;

[0108] The slab length is multiplied by the forward slip coefficient (fs for short) to obtain a more accurate correspondence between the slab position and the time point: (t1,y(LenOr*)1*fs),(t2,y(LenOri)2*fs),……,(t N ,y(LenOri) N *fs)t i ∈[T1,T2],i∈Z,N∈Z, abbreviated as:(t1,y(Len)1),(t2,y(Len)2),……,(tN,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z

[0109] Step 2: Calculate the same site data.

[0110] Here we take the calculation of the temperature data of the same point of the slab as an example. According to the relationship between the time and the slab position obtained in the first step (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z, intercept the required data from iHyperDB and click the data at the same time:

[0111] (t21,y(Temp)1),(t22,y(Temp)2),……,(t2 M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,M∈Z

[0112] t2 i represents the i-th simultaneous point intercepted;

[0113] y(Temp) i represents the temperature at the i-th simultaneous point;

[0114] M represents the number of simultaneous points;

[0115] Specifically, (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z get t2 by interpolation i i∈[0,M],t2 i y2(Len) corresponding to the time ∈[T1,T2] i i∈[0,M];

[0116] According to the above calculation results, (t21,y(Temp)1),(t22,y(Temp)2),……,(t2 M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,t2 in M∈Z i i∈[0,M],t2 i ∈[T1,T2] is replaced by y2(Len) i i∈[0,M]

[0117] You can get the same site data:

[0118] (y2(len)1,y(Temp)1),(y2(len)2,y(Temp)2),……,(y2(len) M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,M∈Z, abbreviated as:

[0119] (Len1,Temp1),(Len2,Temp2),……,(Len M ,Temp M )t2 i ∈[T1,T2],i∈Z,M∈Z

[0120] Step 3: Calculate the same site data. Convert the result data into equal difference same site data

[0121] (Len1,Temp1),(Len2,Temp2),……,(Len M ,Temp M )t2 i Len in ∈[T1,T2],i∈Z,M∈Z i i∈[0,M] is calculated by interpolation. The length differences between adjacent data are different. Interpolation can be performed on the basis of the original co-located data to obtain equidistant co-located data, including the frequently used 1-meter data.

[0122] Specifically, according to the total length of the slab Len M With a given step size Step>0, the slab length can be divided into Q equal parts, where:

[0123]

[0124] Get vector A=(0,Step*1,Step*2,Step*3,……Step*Q)

[0125] TRUNC represents a function that truncates a date or number and returns a specified value, similar to the INT function.

[0126] The values in vector A are passed through (Len1, Temp1), (Len2, Temp2), ..., (Len M ,Temp M )t2 i ∈[T1,T2],i∈Z,M∈Z

[0127] Find interpolation

[0128] You can get the arithmetic and position data: (0, Temp0), (Step*1, Temp1), ..., (Step*Q, Temp Q )in

[0129] The present invention also provides a system for collecting high-frequency data of the same position of hot-rolled strip for metallurgy. Those skilled in the art can notify the step flow of executing the method for collecting high-frequency data of the same position of hot-rolled strip for metallurgy to realize the system for collecting high-frequency data of the same position of hot-rolled strip for metallurgy, that is, the method for collecting high-frequency data of the same position of hot-rolled strip for metallurgy can be understood as an optimal implementation of the system for collecting high-frequency data of the same position of hot-rolled strip for metallurgy.

[0130] According to the present invention, a system for collecting high-frequency data of hot-rolled strip steel at the same location in metallurgy is provided, comprising:

[0131] Module M1: Calculate the correspondence between slab position and time point;

[0132] Module M2: Acquire required data and point data according to the corresponding relationship between the slab position and the time point;

[0133] Module M3: converting the simultaneous point data into equidistant co-location point data.

[0134] Preferably, in the module M1:

[0135] Obtain the steel biting time T1 and steel throwing time T2 of the strip in the rolling mill;

[0136] According to the time interval [T1, T2], the time point data of strip speed or rolling mill linear speed are intercepted: (t1, y(Spd)1), (t2, y(Spd)2), ..., (t N ,y(Spd) N )t i ∈[T1,T2],i∈Z,N∈Z;

[0137] y(Spd) i represents the strip speed at the i-th moment;

[0138] Based on the above known speed data at each time point, the corresponding relationship between the slab position and the time point is calculated by integration:

[0139] (t1,y(LenOri)1),(t2,y(LenOri)2),……,(t N ,y(LenOri) N )t i ∈[T1,T2],i∈Z,N∈Z

[0140] y(LenOri) N represents the position of the slab at the i-th moment;

[0141] The slab length is multiplied by the slip coefficient fs to obtain the corresponding relationship between the adjusted slab position and the time point:

[0142] (t1,y(LenOri)1*fs),(t2,y(LenOri)2*fs),……,(tN,y(LenOri) N *fs)ti∈[T1,T2],i∈Z,N∈Z, abbreviated as:(t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z;

[0143] Among them, (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z is a set of simultaneous point data of the strip passing through the rolling mill;

[0144] t i represents the i-th moment;

[0145] y(Len) i represents the length of the strip passing through the rolling mill at the i-th moment;

[0146] T1 represents the moment when the strip bites the steel in the rolling mill;

[0147] T2 represents the time when the strip is thrown from the rolling mill;

[0148] Z represents the set of positive integers;

[0149] N represents the number of moments.

[0150] Preferably, in the module M2:

[0151] Step 2: Calculate the same site data.

[0152] According to the corresponding relationship between the slab position and the time point (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z, intercept the required data and point the data at the same time:

[0153] (t21,y(Temp)1),(t22,y(Temp)2),……,(t2 M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,M∈Z

[0154] t2 i represents the i-th simultaneous point intercepted;

[0155] y(Temp) i represents the temperature at the i-th simultaneous point;

[0156] M represents the number of simultaneous points;

[0157] Among them, (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z get t2 by interpolation i i∈[0,M],t2 i y2(Len) corresponding to the time ∈[T1,T2] i i∈[0,M];

[0158] According to the above calculation results, (t21,y(Temp)1),(t22,y(Temp)2),……,(t2 M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,t2 in M∈Z ii∈[0,M],t2 i ∈[T1,T2] is replaced by y2(Len) i i∈[0,M]

[0159] That is, the same site data is obtained:

[0160] (y2(len)1,y(Temp)1),(y2(len)2,y(Temp)2),……,(y2(len) M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,M∈Z, abbreviated as:

[0161] (Len1,Temp1),(Len2,Temp2),……,(Len M ,Temp M )t2 i ∈[T1,T2],i∈Z,M∈Z.

[0162] Preferably, in the module M3:

[0163] For (Len1, Temp1), (Len2, Temp2), ..., (Len M ,Temp M )t2 i Len in ∈[T1,T2],i∈Z,M∈Z i i∈[0,M], interpolation is performed on the basis of the original co-location data to obtain equidistant co-location data.

[0164] Preferably, in the module M3:

[0165] According to the total length of the slab Len M With a given step size Step>0, the slab length is divided into Q equal parts, where:

[0166]

[0167] Get vector A=(0,Step*1,Step*2,Step*3,……Step*Q)

[0168] TRUNC represents a function that truncates a date or number and returns a specified value.

[0169] The values in vector A are passed through (Len1, Temp1), (Len2, Temp2), ..., (Len M ,Temp M )t2 i∈[T1,T2],i∈Z,M∈Z interpolation, get the arithmetic difference and the same point data: (0,Temp0),(Step*1,Temp1),……,(Step*Q,Temp Q )in

[0170] Those skilled in the art will appreciate that, in addition to implementing the system, device, and various modules provided by the present invention in purely computer-readable program code, it is entirely possible to implement the same program in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, embedded microcontrollers, and the like by logically programming the method steps. Therefore, the system, device, and various modules provided by the present invention can be considered a hardware component, and the modules included therein for implementing various programs can also be considered structures within the hardware component; the modules for implementing various functions can also be considered both software programs for implementing the method and structures within the hardware component.

[0171] The above describes specific embodiments of the present invention. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art may make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. The embodiments of this application and the features in the embodiments may be combined with each other in any manner unless there is a conflict.

Claims

1. A method for collecting high-frequency data of hot-rolled strip steel at the same point in metallurgy, characterized in that: include: Step S1: Calculate the corresponding relationship between the slab position and the time point; Step S2: acquiring required data and point data according to the corresponding relationship between the slab position and the time point; Step S3: converting the simultaneous point data into equidistant co-location data; In step S1: Obtain the steel biting time T1 and steel throwing time T2 of the strip in the rolling mill; According to the time interval [T1, T2], the time point data of strip speed or rolling mill linear speed are intercepted: (t1, y(Spd)1), (t2, y(Spd)2), ..., (t N ,y(Spd) n )t i ∈[T1,T2],i∈Z,N∈Z; y(Spd) i represents the strip speed at the i-th moment; Based on the above known speed data at each time point, the corresponding relationship between the slab position and the time point is calculated by integration: (t1,y(LenOri)1),(t2,y(LenOri)2),……,(t N ,y(LenOri) N )t i ∈[T1,T2],i∈Z,N∈Zy(LenOri) N represents the position of the slab at the i-th moment; The slab length is multiplied by the slip coefficient fs to obtain the corresponding relationship between the adjusted slab position and the time point: (t1, y(LenOri)1*fs), (t2, y(LenOri)2*fs), ……, (t N , y(LenOri) N *fs)t i ∈[T1, T2], i∈Z, N∈Z, briefly denoted as: (t1, y(Len)1), (t2, y(Len)2), ……, (t N , y(Len) N )t i ∈[T1, T2], i∈Z, N∈Z; Among them, (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z is a set of simultaneous point data of the strip passing through the rolling mill; t i represents the i-th moment; y(Len) i represents the length of the strip passing through the rolling mill at the i-th moment; T1 represents the moment when the strip bites the steel in the rolling mill; T2 represents the time when the strip is thrown from the rolling mill; Z represents the set of positive integers; N represents the number of moments; In step S2: Step 2: Calculate the same site data, According to the corresponding relationship between the slab position and the time point (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z, intercept the required data and point the data at the same time: (t21,y(Temp)1),(t22,y(Temp)2),……,(t2 M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,M∈Z t2 i represents the i-th simultaneous point intercepted; y(Temp) i represents the temperature at the i-th simultaneous point; M represents the number of simultaneous points; Among them, (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z get t2 by interpolation i i∈[0,M],t2 i y2(Len) corresponding to the time ∈[T1,T2] i i∈[0,M]; According to the above calculation results, (t21,y(Temp)1),(t22,y(Temp)2),……,(t2 M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,t2 in M∈Z i i∈[0,M],t2 i ∈[T1,T2] is replaced by y2(Len) i i∈[0,M] That is, the same site data is obtained: (y2(len)1,y(Temp)1),(y2(len)2,y(Temp)2),……,(y2(len) M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,M∈Z, abbreviated as: (Len1,Temp1),(Len2,Temp2),……,(Len M ,Temp M )t2 i ∈[T1,T2],i∈Z,M∈Z; In step S3: For (Len1, Temp1), (Len2, Temp2), ..., (Len M ,Temp M )t2 i Len in ∈[T1,T2],i∈Z,M∈Z i i∈[0,M], interpolation is performed on the basis of the original co-location data to obtain equidistant co-location data.

2. The method for collecting high-frequency data of hot-rolled strip steel at the same location for metallurgy according to claim 1, characterized in that: In step S3: According to the total length of the slab Len M With a given step size Step>0, the slab length is divided into Q equal parts, where: Q=TRUNC(Len M / Step) Get vector A=(0,Step*1,Step*2,Step*3,……Step*Q) TRUNC represents a function that truncates a date or number and returns a specified value. The values in vector A are passed through (Len1, Temp1), (Len2, Temp2), ..., (Len M ,Temp M )t2 i ∈[T1,T2],i∈Z,M∈Z interpolation, get the arithmetic difference and the same point data: (0,Temp0),(Step*1,Temp1),……,(Step*Q,Temp Q )where Q=TRUNC(Len M / Step),Step>0.

3. A system for collecting high-frequency data of hot-rolled strip steel at the same point in metallurgy, characterized in that: include: Module M1: Calculate the correspondence between slab position and time point; Module M2: Acquire required data and point data according to the corresponding relationship between the slab position and the time point; Module M3: converting the simultaneous point data into equidistant co-location data; In the module M1: Obtain the steel biting time T1 and steel throwing time T2 of the strip in the rolling mill; According to the time interval [T1, T2], the time point data of strip speed or rolling mill linear speed are intercepted: (t1, y(Spd)1), (t2, y(Spd)2), ..., (t N ,y(Spd) N )t i ∈[T1,T2],i∈Z,N∈Z; y(Spd) i represents the strip speed at the i-th moment; Based on the above known speed data at each time point, the corresponding relationship between the slab position and the time point is calculated by integration: (p1,y(LenOri)1),(p2,y(LenOri)2),……,(t N ,y(LenOri) N ) p i ∈[T1,T2],i∈Z,N∈Z y(LenOri) N represents the position of the slab at the i-th moment; The slab length is multiplied by the previous slip coefficient fs to obtain the corresponding relationship between the adjusted slab position and the time point: (t1,y(LenOri)1*fs),(t2,y(LenOri)2*fs),……,(t N ,y(LenOri) N *fs)t i ∈[T1,T2],i∈Z,N∈Z, abbreviated as:(t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z; Among them, (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Lne) N )t i ∈[T1,T2],i∈Z,N∈Z is a set of simultaneous point data of the strip passing through the rolling mill; t i represents the i-th moment; y(Len) i represents the length of the strip passing through the rolling mill at the i-th moment; T1 represents the moment when the strip bites the steel in the rolling mill; T2 represents the time when the strip is thrown from the rolling mill; Z represents the set of positive integers; N represents the number of moments; In the module M2: Step 2: Calculate the same site data, According to the corresponding relationship between the slab position and the time point (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z, intercept the required data and point the data at the same time: (t21,y(Temp)1),(t22,y(Temp)2),……,(t2 M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,M∈Z t2 i represents the i-th simultaneous point intercepted; y(Temp) i represents the temperature at the i-th simultaneous point; M represents the number of simultaneous points; Among them, (t1,y(Len)1),(t2,y(Len)2),……,(t N ,y(Len) N )t i ∈[T1,T2],i∈Z,N∈Z get t2 by interpolation i i∈[0,M],t2 i y2(Len) corresponding to the time ∈[T1,T2] i i∈[0,M]; According to the above calculation results, (t21,y(Temp)1),(t22,y(Temp)2),……,(t2 M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,t2 in M∈Z i i∈[0,M],t2 i ∈[T1,T2] is replaced by y2(Len) i i∈[0,M] That is, the same site data is obtained: (y2(len)1,y(Temp)1),(y2(len)2,y(Temp)2),……,(y2(len) M ,y(Temp) M )t2 i ∈[T1,T2],i∈Z,M∈Z, abbreviated as: (Len1,Temp1),(Len2,Temp2),……,(Len M ,Temp M )t2 i ∈[T1,T2],i∈Z,M∈Z; In the module M3: For (Len1, Temo1), (Len2, Temp2), ... ..., (Len M ,Temp M )t2 i Len in ∈[T1,T2],i∈Z,M∈Z i i∈[0,M], interpolation is performed on the basis of the original co-location data to obtain equidistant co-location data.

4. The hot-rolled strip co-location high-frequency data acquisition system for metallurgy according to claim 3, characterized in that: In the module M3: According to the total length of the slab Len M With a given step size Step>0, the slab length is divided into Q equal parts, where: Q=TRUNC(Len M / Step) Get vector A=(0,Step*1,Step*2,Step*3,……Step*Q) TRUNC represents a function that truncates a date or number and returns a specified value. The values in vector A are passed through (Len1, Temp1), (Len2, Temp2), ..., (Len M ,Temp M )t2 i ∈[T1,T2],i∈Z,M∈Z interpolation, get the arithmetic difference and the same point data: (0,Temp0),(Step*1,Temp1),……,(Step*Q,Temp Q )where Q=TRUNC(Len M / Step),Step>0.

Images