Multi-wire saw wire bow angle control method and device based on compound control strategy

Abstract

This invention discloses a method and apparatus for controlling the bow angle of a multi-wire cutting machine based on a composite control strategy, relating to the field of cutting control. The method includes: calculating the feed speed of the multi-wire cutting machine for the next cycle using a feed speed theoretical control algorithm based on the bow angle and movement speed of each wire saw on the wire mesh in the current cycle; calculating the new wire feed amount for the wire mesh update in the next reciprocating cycle using a model predictive control algorithm based on the movement speed in the reciprocating motion, the number of reciprocating cycles, the total effective length of the wire saws participating in cutting in each reciprocating cycle, and the length of the new wire saw fed in each reciprocating cycle; and controlling the multi-wire cutting machine to adjust the feed speed and new wire feed amount within the minimum control cycle of the corresponding control quantities according to the feed speed of the multi-wire cutting machine in the next cycle and the new wire feed amount for the wire mesh update in the next reciprocating cycle, thereby controlling the bow angle within a preset bow angle range. This invention solves the problem that current bow angle control does not consider the influence of wear.

Description

Technical Field

[0001] This invention relates to the field of cutting control, and specifically to a method and apparatus for controlling the bow angle of a multi-line cutting line based on a composite control strategy. Background Technology

[0002] Wire sawing is a processing method used to cut hard and brittle materials, transforming a single piece of material into multiple thin sheets. During wire sawing, a wire bow phenomenon occurs. Furthermore, variations in wire saw wear, material dimensions, and processing techniques can alter the wire bow angle or tool deformation. The biggest difference between multi-wire cutting and single-wire cutting is that the wear on each wire is different, and this wear also affects the wire bow angle. Changes in the wire bow angle, in turn, affect the wear on each wire during multi-wire cutting. Due to the complexity of multi-wire cutting, simply adjusting the feed rate to control the wire bow angle is insufficient, as it fails to consider the impact of wire wear on the bow angle, potentially leading to inefficiency.

[0003] The patent with publication number CN112605843A uses bow sensors on both sides and a PID method to control the bow angle. However, this is only applicable to single-wire cutting and does not fully consider the impact of wear on the bow angle during multi-wire cutting.

[0004] Therefore, in the actual production process, it is necessary not only to control the wire bow angle by controlling the feed speed, but also to control the wear of each part, so as to control the wire bow angle without affecting the processing efficiency. Summary of the Invention

[0005] The purpose of this application is to propose a multi-line cutting line bow angle control method and device based on a composite control strategy to address the aforementioned technical problems.

[0006] In a first aspect, the present invention provides a method for controlling the bow angle of a multi-line cutting line based on a composite control strategy, comprising the following steps:

[0007] The system monitors in real time the wire bow angle, reciprocating speed, number of reciprocating cycles, total effective length of wire saws involved in cutting, and length of new wire feed for each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle. Based on the wire bow angle and reciprocating speed of each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle, the feed speed of the multi-wire cutting machine in the next cycle is calculated using a feed speed theoretical control algorithm.

[0008] The model predictive control algorithm is used to calculate the new wire feed amount for the wire mesh update in the next reciprocating cycle based on the motion speed, the number of reciprocating cycles, the total effective length of the wire saws involved in cutting in each reciprocating cycle, and the length of the new wire feed.

[0009] Based on the feed speed of the multi-wire cutting machine in the next cycle and the new wire feed amount of the wire mesh update in the next reciprocating cycle, the multi-wire cutting machine adjusts the feed speed and new wire feed amount within the minimum control cycle of the corresponding control amount, so that the wire bow angle of each wire saw on the wire mesh of the multi-wire cutting machine is controlled within the preset wire bow angle range.

[0010] Preferably, the feed rate of the multi-wire cutting machine for the next cycle is calculated using a feed rate theoretical control algorithm based on the wire bow angle and movement speed of each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle. Specifically, this includes:

[0011] The maximum line bow angle with the largest value among all wire saws on the online network in the current cycle is determined;

[0012] The feed rate of the multi-wire cutting machine for the next cycle can be calculated using a proportional control algorithm or a proportional-integral control algorithm with anti-saturation mechanism based on the maximum wire bow angle and the movement speed, or using a switching control algorithm based on the maximum wire bow angle.

[0013] As a preferred option, the proportional control algorithm proceeds as follows:

[0014] The maximum range of feed rate during the control process is calculated using the following formula:

[0015] ;

[0016] The minimum limit range of the feed rate during the control process is calculated using the following formula:

[0017] ;

[0018] in, This indicates the maximum limit of the feed rate. This indicates the minimum feed rate. Here, represents the preset line bow angle, F represents the tension, and a represents the workpiece width; vs represents the average absolute value of the motion speed; kf_min represents the minimum average sawing capability coefficient of the material at the cutting position throughout the entire cutting process; kf_max represents the maximum average sawing capability coefficient of the material at the cutting position throughout the entire cutting process; kf is the average sawing capability coefficient of the material at the cutting position, and its calculation formula is: assuming the material being cut contains k' types of materials, let the sawing capability coefficient of the i'th material be kf. i’ Its volume fraction as a percentage of the total volume removed is f.vi’ , i'=1,2,3,…,k'; the expression for the average sawing capacity coefficient of the material at the cutting position is:

[0019] ;

[0020] Set the maximum and minimum feed rates according to the range of maximum and minimum feed rates during the control process, and configure the proportional coefficient as follows: Where c is the proportional adjustment constant, K represents the system gain which can take any value, and satisfies ;

[0021] Calculate the difference between the preset line bow angle and the maximum line bow angle to obtain the deviation;

[0022] The proportional term P is calculated based on the deviation, as shown in the following formula:

[0023] ;

[0024] Where e represents deviation;

[0025] The following limiting logic is executed based on the proportional term:

[0026] When the ratio exceeds the set maximum or minimum limit, the feed speed of the multi-wire cutting machine in the next cycle will be limited to the corresponding maximum or minimum limit; when the ratio is within the range of the minimum and maximum limits, the ratio will be used as the feed speed of the multi-wire cutting machine in the next cycle.

[0027] The process of the proportional-integral control algorithm, which includes an anti-saturation mechanism, is as follows:

[0028] The deviation and proportional term are calculated using the same method as the proportional control algorithm, and an integral coefficient is set. K i ,satisfy K i If the value is greater than 0, the tentative control quantity is calculated based on the deviation, proportional term, and integral coefficient, as shown in the following formula:

[0029] temp_integral_e = integral_e + e·dt;

[0030] I= K i ·temp_integral_e;

[0031] vf_temp = P + I;

[0032] Where dt represents the control time interval, temp_integral_e represents the temporary integral variable, vf_temp represents the tentative control quantity, I represents the integral quantity, and integral_e represents the integral variable of the previous control time interval;

[0033] Execute anti-saturation logic based on conditional integrals according to the tentative control input:

[0034] When the trial control quantity triggers the set maximum or minimum limit, the feed speed of the multi-wire cutting machine in the next cycle is limited to the corresponding maximum or minimum limit. At the same time, if the sign of the deviation is consistent with the drive direction that causes saturation, the update of the integral variable for the next control time interval is frozen; if the sign of the deviation is opposite to the drive direction that causes saturation, the update of the integral variable for the next control time interval is allowed to achieve reverse exit from saturation.

[0035] When the trial control quantity is within the range of the minimum and maximum limits, the trial control quantity is used as the feed speed of the multi-wire cutting machine in the next cycle, and the temporary integral variable is updated to the integral variable of the next control time interval.

[0036] The specific process of the switch control algorithm is as follows:

[0037] When the maximum wire bow angle is less than the preset wire bow angle, the feed speed of the multi-wire cutting machine in the next cycle is the maximum limit.

[0038] When the maximum wire bow angle is greater than the preset wire bow angle, the feed speed of the multi-wire cutting machine in the next cycle is the minimum limit.

[0039] As a preferred approach, the process of the model predictive control algorithm is as follows:

[0040] Construct a relationship model between wear degree characterization quantities and actual wear conditions of the wire saw; based on the relationship model, convert the preset wear conditions into preset wear degree characterization quantities.

[0041] Taking the kth reciprocating cycle as the current reciprocating cycle, calculate the wear degree characterization of each wire saw at each processing position in different axes during the kth reciprocating cycle.

[0042] In the kth reciprocating cycle, based on the wiring method of the multi-wire cutting machine and the processing position involved in multi-wire cutting, the wear degree characterization of the wire saws at each processing position of the multiple wire saws in different axes is superimposed to obtain the wear degree characterization of the whole wire saw in the kth reciprocating cycle.

[0043] Based on the wear characteristics of the wire saw at each processing position in the k-th reciprocating cycle, the wear characteristics of the entire wire saw, and the wear influence factors at each processing position, the MPC control method is used to calculate the wear characteristics of the wire saw at each processing position and the wear characteristics of the entire wire saw in the next h reciprocating cycles under different new wire feed rates. The wear characteristics of the entire wire saw in the next h reciprocating cycles under different new wire feed rates are then back-calculated and aggregated to obtain the wear characteristics of the wire saw at all processing positions in the next h reciprocating cycles under different new wire feed rates.

[0044] Based on the wear degree characterization of the wire saw at all processing positions in the next h reciprocating cycles under different new wire feed rates and the preset wear degree characterization, a cost function for the next h reciprocating cycles under different new wire feed rates is constructed. The new wire feed rate corresponding to the minimum value of the cost function for the next h reciprocating cycles is selected as the new wire feed rate for wire mesh update in the next reciprocating cycle.

[0045] Preferably, the wear characteristics of each wire saw at various processing positions along different axes in each reciprocating cycle are calculated, specifically including:

[0046] In the initialization phase, assuming that all wire saws on the wire mesh of the multi-wire cutting machine are not involved in processing, the entire wire mesh consisting of multiple wire saws is discretized to obtain discrete wire saw units. An initial matrix is ​​then constructed to represent the wear degree of different wire saw units in the entire wire mesh during the initialization phase. Where L represents the length of the entire wire saw, and ds is the length of the discrete wire saw unit;

[0047] In the processing stage of the first half of the i-th reciprocating cycle, a wear characteristic of the wire saw at the j-th processing position in the first half of the i-th reciprocating cycle is constructed based on the initial matrix. As shown in the following formula:

[0048] ;

[0049] Where i = 1, 2, ..., k, k represents the total number of reciprocating cycles, j = 1, 2, ..., N, N represents the total number of processing positions, P j Let LL be the wire saw interval length from the j-th processing position to the 1st processing position. i LLL represents the total effective length of the wire saw involved in cutting during the i-th reciprocating cycle. i z represents the length of the new wire feed in the i-th reciprocating cycle. i,jThe wear influence factor is the j-th processing position in the i-th reciprocating cycle. The wear influence factor is calculated by the wire bow angle or based on the average motion speed of the corresponding reciprocating cycle, the reciprocating cycle time, the total effective length of the wire saws involved in the cutting, the length of the new wire feed, the material removal coefficient, and the wire bow angle corresponding to that reciprocating cycle. Represents a matrix of all 1s;

[0050] In the processing stage of the second half of the i-th reciprocating cycle, a wear characteristic of the wire saw at the j-th processing position in the second half of the i-th reciprocating cycle is constructed based on the initial matrix. As shown in the following formula:

[0051] ;

[0052] The wear level of the wire saw at the j-th processing position in the i-th reciprocating cycle is calculated using the following formula. :

[0053] ;

[0054] The wear degree characterization quantity of the whole wire saw in the kth reciprocating cycle is: .

[0055] As a preferred method, the MPC control method proceeds as follows:

[0056] Establish a new linear feed sequence for regulation. , ,in Indicates the first A new line feed rate , This represents the total feed rate of the new line.

[0057] Based on the wear degree characterization of the whole wire saw in the k-th reciprocating cycle, combined with the first value in the new wire feed sequence... The calculation of the wear influence factor of the new feed rate and the j-th machining position in the k-th reciprocating cycle is performed in the first cycle. The wear characteristic of the wire saw at the j-th machining position in the m-th reciprocating cycle under a new linear feed rate. As shown in the following formula:

[0058] ;

[0059] in, , This represents the total number of future h repetition cycles. Indicates the first The wear degree of the wire saw at the j-th processing position in the first half of the m-th reciprocating cycle under a new wire feed rate is characterized by the following expression: ; Indicates the first The wear degree of the wire saw at the j-th processing position in the second half of the m-th reciprocating cycle under a new feed rate is characterized by the following expression: , This represents the wear influence factor at the j-th processing position in the k-th reciprocating cycle;

[0060] The wear degree characterization of the whole wire saw in the k-th reciprocating cycle is calculated by superimposing the values ​​to obtain the wear degree characterization of the k-th reciprocating cycle. Wear characteristics of the entire wire saw over the next h reciprocating cycles at a new wire feed rate. As shown in the following formula

[0061] ;

[0062] The inverse calculation and aggregation process is as follows:

[0063] Delete in reverse order There are columns containing consecutive zero elements. The remaining columns are retained to obtain the first target wear degree characterization matrix. The flip function is used to flip the first target wear degree characterization matrix to obtain the second target wear degree characterization matrix.

[0064] By truncating the elements of the second target wear degree characterization matrix, the third target wear degree characterization matrix is ​​obtained, as shown in the following formula:

[0065] ;

[0066] in, The matrix representing the wear degree of the second target is... The matrix representing the wear degree of the third target. Indicates the first Elements of column n to nth The elements of each column are extracted, and N' represents the total number of wire saws involved in the processing, which is equal to the total number of processing positions.

[0067] Aggregate the wear degree characterization matrix of the third target to obtain the result at the 1st The wear degree characterization of the wire saw passing through the j-th processing position in the next h reciprocating cycles under a new linear feed rate. As shown in the following formula:

[0068] ;

[0069] in, For data aggregation operators;

[0070] The construction is obtained in the first Wear characterization matrix of N machining positions over the next h reciprocating cycles under a new linear feed rate. As shown in the following formula:

[0071] ;

[0072] For the first The wear characterization matrix of each machining position under a new linear feed rate for the next h reciprocating cycles is aggregated to obtain the wear characterization matrix of the first h-cycle cycle. Wear characterization of all machining positions over the next h reciprocating cycles under a new feed rate. As shown in the following formula:

[0073] ;

[0074] The expression for the cost function is: ,in, This represents the preset wear level characterization quantity.

[0075] Secondly, the present invention provides a multi-line cutting line bow angle control device based on a composite control strategy, comprising:

[0076] The feed rate calculation module is configured to monitor in real time the wire bow angle, reciprocating speed, number of reciprocating cycles, total effective length of wire saws participating in cutting and length of new wire feed for each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle; and calculate the feed rate of the multi-wire cutting machine for the next cycle using a feed rate theoretical control algorithm based on the wire bow angle and reciprocating speed of each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle.

[0077] The new wire feed calculation module is configured to calculate the new wire feed for the next reciprocating cycle based on the motion speed in the reciprocating motion, the number of reciprocating cycles, the total effective length of the wire saws involved in cutting in each reciprocating cycle, and the length of the new wire feed wire saws using a model predictive control algorithm.

[0078] The adjustment control module is configured to control the multi-wire cutting machine to adjust the feed speed and new wire feed amount within the minimum control cycle of the corresponding control amount according to the feed speed of the multi-wire cutting machine in the next cycle and the new wire feed amount of the wire mesh update in the next reciprocating cycle, so that the wire bow angle of each wire saw on the wire mesh of the multi-wire cutting machine is controlled within the preset wire bow angle range.

[0079] Thirdly, the present invention provides an electronic device including one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any implementation of the first aspect.

[0080] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any of the implementations of the first aspect.

[0081] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the method as described in any of the implementations in the first aspect.

[0082] Compared with the prior art, the present invention has the following beneficial effects:

[0083] (1) The multi-wire cutting bow angle control method based on composite control strategy mentioned in this invention controls the new wire feed amount by using model predictive control algorithm to accurately control the wear degree of the whole wire saw within the set threshold to avoid excessive fatigue of the wire, realize the full utilization of diamond wire, reduce wire loss, save wire cost, make the wear of the whole wire saw more uniform, and make the bow angle difference between each wire of the whole wire smaller.

[0084] (2) The multi-line cutting bow angle control method based on composite control strategy mentioned in this invention uses the feed speed theoretical control algorithm to control the feed speed, avoids the risk of large sudden changes in the bow angle during the processing, eliminates abnormal wire breakage faults from the source, and greatly reduces the loss of waste material during downtime.

[0085] (3) The multi-line cutting line bow angle control method based on the composite control strategy mentioned in this invention achieves intelligent closed-loop adjustment of process parameters based on the feedback of the wire network status by composite control of the feed speed and the new line feed amount, which improves the adaptive processing efficiency of the equipment for complex hard stone and realizes intelligent closed-loop control of efficient processing of stone and low tool wear. Attached Figure Description

[0086] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0087] Figure 1This is a flowchart illustrating a multi-line cutting line bow angle control method based on a composite control strategy, as an embodiment of this application.

[0088] Figure 2 The image shows the results of feed rate control using a proportional-derivative (PDC) control algorithm during the wire sawing of marble. Figure 2 (a) in the diagram represents a marble. Figure 2 (b) in the figure represents a comparison between the simulated line bow angle and the line bow angle obtained using the proportional-derivative control algorithm. Figure 2 (c) in the graph represents the feed rate variation using the proportional-derivative control algorithm;

[0089] Figure 3 The diagram shows the results of feed rate control using the feed rate theoretical control algorithm of this invention during the wire sawing of marble. Figure 3 (a) in the diagram represents a marble. Figure 3 (b) in the figure represents a comparison between the simulated line bow angle and the line bow angle using the feed rate theoretical control algorithm of this invention. Figure 3 (c) in the figure represents the feed rate variation diagram using the feed rate theoretical control algorithm of the present invention;

[0090] Figure 4 The diagram shows the results of feed rate control using the feed rate theoretical control algorithm of this invention during the wire sawing of marble. Figure 4 (a) in the diagram represents a marble. Figure 4 (b) in the figure represents a comparison between the simulated line bow angle and the line bow angle using the feed rate theoretical control algorithm of this invention. Figure 4 In the diagram, (c) represents the feed rate variation graph using the feed rate theory control algorithm of this invention; and Figure 3 The difference is, Figure 4 The minimum and maximum feed rates set in the settings are 0 mm / s and 0.003 mm / s, respectively.

[0091] Figure 5 The diagram shows the results of feed rate control using the feed rate theoretical control algorithm of this invention during the wire sawing of marble. Figure 5 (a) in the diagram represents a marble. Figure 5 (b) in the figure represents a comparison between the simulated line bow angle and the line bow angle using the feed rate theoretical control algorithm of this invention. Figure 5 In the diagram, (c) represents the feed rate variation graph using the feed rate theory control algorithm of this invention; and Figure 3 The difference is, Figure 5 The minimum and maximum feed rates set in the settings are 0.008 mm / s and 0.03 mm / s, respectively.

[0092] Figure 6 This is a diagram showing the results of using the model predictive control algorithm of this invention to control the feed rate of a new line during multi-line machining. Figure 6 (a) in the graph represents the changes in wear influencing factors. Figure 6 (b) in the figure represents a comparison of the effects of using MPC-controlled new feed rate versus using a constant new feed rate on the wear characterization parameters. Figure 6 (c) in the figure represents the change of the new line feed rate with machining time when the new line feed rate is controlled by MPC and when the new line feed rate is constant.

[0093] Figure 7 This is a comparison chart showing the results of wear degree characterization metrics for controlling the new line feed rate using the model predictive control algorithm of the embodiments of this application and without using the model predictive control algorithm of the embodiments of this application during multi-line machining. Figure 7 (a) in the figure represents the change of the wear characterization quantity of multiple wire saws with processing time due to the use of a constant new wire feed rate. Figure 7 (b) in the figure represents the change of the wear degree characterization quantity of multiple wire saws as a function of processing time due to the use of MPC to control the new wire feed rate;

[0094] Figure 8 This is a schematic diagram of a multi-line cutting line bow angle control device based on a composite control strategy, as an embodiment of this application.

[0095] Figure 9 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0096] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0097] Figure 1 The present application illustrates an embodiment of a multi-line cutting line bow angle control method based on a composite control strategy, comprising the following steps:

[0098] S1 monitors in real time the wire bow angle, reciprocating speed, number of reciprocating cycles, total effective length of wire saws participating in cutting, and length of new wire feed for each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle; based on the wire bow angle and reciprocating speed of each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle, the feed speed of the multi-wire cutting machine in the next cycle is calculated using the feed speed theoretical control algorithm.

[0099] Specifically, in the embodiments of this application, the wire bow angle, movement speed in reciprocating motion, number of reciprocating cycles, and total effective length of the wire saws participating in cutting and the length of the new wire feed are monitored in real time for each wire saw on the wire mesh of the multi-wire cutting machine during the current cycle. The number of reciprocating cycles is the total number of reciprocating cycles. In the embodiments of this application, the cycle mentioned in the feed speed refers to the control cycle of the feed speed, while the reciprocating cycle represents the periodic time of one reciprocating motion in the cutting process. The method of monitoring the wire bow angle in the embodiments of this application is not specifically limited.

[0100] In a specific embodiment, the feed rate of the multi-wire cutting machine for the next cycle is calculated using a feed rate theoretical control algorithm based on the wire bow angle and movement speed of each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle. Specifically, this includes:

[0101] The maximum line bow angle with the largest value among all wire saws on the online network in the current cycle is determined;

[0102] The feed rate of the multi-wire cutting machine for the next cycle can be calculated using a proportional control algorithm or a proportional-integral control algorithm with anti-saturation mechanism based on the maximum wire bow angle and the movement speed, or using a switching control algorithm based on the maximum wire bow angle.

[0103] Specifically, embodiments of this application further determine the maximum wire bow angle in the wire mesh by monitoring the wire bow angle of each wire saw in the current cycle. Then, combining the maximum wire bow angle with the movement speed, or directly using the maximum wire bow angle, a feed rate theoretical control algorithm is employed to calculate the feed rate of the multi-wire cutting machine for the next cycle. This feed rate theoretical control algorithm mainly utilizes pre-set minimum and maximum limits to limit the feed rate. Several methods exist, including proportional control algorithms, proportional-integral control algorithms with anti-saturation mechanisms, and on / off control algorithms. The specific processes of these three algorithms are described below.

[0104] In a specific embodiment, the proportional control algorithm proceeds as follows:

[0105] The maximum range of feed rate during the control process is calculated using the following formula:

[0106] ;

[0107] The minimum limit range of the feed rate during the control process is calculated using the following formula:

[0108] ;

[0109] in, This indicates the maximum limit of the feed rate. This indicates the minimum feed rate. Here, represents the preset line bow angle, F represents the tension, and a represents the workpiece width; vs represents the average absolute value of the motion speed; kf_min represents the minimum average sawing capability coefficient of the material at the cutting position throughout the entire cutting process; kf_max represents the maximum average sawing capability coefficient of the material at the cutting position throughout the entire cutting process; kf is the average sawing capability coefficient of the material at the cutting position, and its calculation formula is: assuming the material being cut contains k' types of materials, let the sawing capability coefficient of the i'th material be kf. i’ Its volume fraction as a percentage of the total volume removed is f. vi’ , i'=1,2,3,…,k'; the expression for the average sawing capacity coefficient of the material at the cutting position is:

[0110] ;

[0111] Set the maximum and minimum feed rates according to the range of maximum and minimum feed rates during the control process, and configure the proportional coefficient as follows: Where c is the proportional adjustment constant, K represents the system gain which can take any value, and satisfies ;

[0112] Calculate the difference between the preset line bow angle and the maximum line bow angle to obtain the deviation;

[0113] The proportional term P is calculated based on the deviation, as shown in the following formula:

[0114] ;

[0115] Where e represents deviation;

[0116] The following limiting logic is executed based on the proportional term:

[0117] When the ratio exceeds the set maximum or minimum limit, the feed speed of the multi-wire cutting machine in the next cycle will be limited to the corresponding maximum or minimum limit; when the ratio is within the range of the minimum and maximum limits, the ratio will be used as the feed speed of the multi-wire cutting machine in the next cycle.

[0118] The process of the proportional-integral control algorithm, which includes an anti-saturation mechanism, is as follows:

[0119] The deviation and proportional term are calculated using the same method as the proportional control algorithm, and an integral coefficient is set. K i ,satisfy K i If the value is greater than 0, the tentative control quantity is calculated based on the deviation, proportional term, and integral coefficient, as shown in the following formula:

[0120] temp_integral_e = integral_e + e·dt;

[0121] I= K i ·temp_integral_e;

[0122] vf_temp = P + I;

[0123] Where dt represents the control time interval, temp_integral_e represents the temporary integral variable, vf_temp represents the tentative control quantity, I represents the integral quantity, and integral_e represents the integral variable of the previous control time interval;

[0124] Execute anti-saturation logic based on conditional integrals according to the tentative control input:

[0125] When the trial control quantity triggers the set maximum or minimum limit, the feed speed of the multi-wire cutting machine in the next cycle is limited to the corresponding maximum or minimum limit. At the same time, if the sign of the deviation is consistent with the drive direction that causes saturation, the update of the integral variable for the next control time interval is frozen; if the sign of the deviation is opposite to the drive direction that causes saturation, the update of the integral variable for the next control time interval is allowed to achieve reverse exit from saturation.

[0126] When the trial control quantity is within the range of the minimum and maximum limits, the trial control quantity is used as the feed speed of the multi-wire cutting machine in the next cycle, and the temporary integral variable is updated to the integral variable of the next control time interval.

[0127] The specific process of the switch control algorithm is as follows:

[0128] When the maximum wire bow angle is less than the preset wire bow angle, the feed speed of the multi-wire cutting machine in the next cycle is the maximum limit.

[0129] When the maximum wire bow angle is greater than the preset wire bow angle, the feed speed of the multi-wire cutting machine in the next cycle is the minimum limit.

[0130] Specifically, the proportional control algorithm mentioned in the embodiments of this application multiplies the deviation by the proportional coefficient to obtain a proportional term. This proportional term, along with the minimum and maximum limits, is used for amplitude limiting. If the proportional term is within the range of the minimum and maximum limits, it is taken as the feed speed of the multi-wire cutting machine in the next cycle. If the proportional term exceeds the range of the minimum and maximum limits, the feed speed of the multi-wire cutting machine in the next cycle is taken as either the minimum or maximum limit, thus limiting the range of the feed speed of the multi-wire cutting machine in the next cycle to within the range of the minimum and maximum limits. Here, the proportional term is used as a control variable, and its judgment logic is: vf=max(min(vf_temp, max_vf), min_vf), where vf represents the feed speed of the multi-wire cutting machine in the next cycle, vf_temp represents the control variable, max_vf represents the maximum limit, min_vf represents the minimum limit, min indicates taking the minimum value, and max indicates taking the maximum value. The proportional gain is calculated using the system gain and the proportional adjustment coefficient. The proportional adjustment coefficient ranges from [0.5, 2.0]. As long as the maximum and minimum feed rates satisfy the ranges of the maximum and minimum feed rates respectively, the system gain can be arbitrarily chosen, as long as it meets the following conditions. If the maximum and minimum feed speed limits set do not meet the range of the maximum or minimum feed speed limits, the bow angle cannot be stably controlled to be near the preset bow angle.

[0131] The proportional-integral control algorithm with anti-saturation mechanism used in the embodiments of this application performs integral accumulation calculation only when the trial control quantity does not trigger the amplitude limit cutoff, or when the current error change trend is conducive to exiting the amplitude limit cutoff state. First, the deviation and proportional term are calculated in the same way as in the proportional control algorithm, and an integral coefficient is set. K i ,satisfy K i >0. A temporary integral variable, temp_integral_e = integral_e + e * dt, is calculated using the deviation. This temporary integral variable is then used to calculate the integral quantity I. The sum of the integral quantity I and the proportional term P is used as the control quantity vf_temp. Conditional integral-based anti-saturation logic is then executed: when the control quantity triggers the set maximum or minimum limit, the feed rate of the multi-wire cutting machine in the next cycle is limited to the corresponding maximum or minimum limit. Simultaneously, if the sign of the deviation e is consistent with the driving direction causing saturation, the accumulation of the current integral variable is frozen; if the sign of the deviation e is opposite to the driving direction causing saturation, the integral variable is allowed to accumulate and update, thus achieving reverse exit from saturation. Specifically:

[0132] Case 1: If the control variable vf_temp is greater than the set maximum limit value max_vf, then the feed speed vf of the multi-wire cutting machine for the next cycle is output as vf = max_vf; if the feed speed of the multi-wire cutting machine for the next cycle that is output has reached the maximum limit value, and the error still requires an increase in output, then stop accumulating the integral variable, that is, if e > 0, then the integral variable new_integral_e for the next control time interval is equal to integral_e; keep the integral variable of the previous control time interval unchanged; otherwise, the integral variable new_integral_e for the next control time interval is equal to temp_integral_e; allow reverse exit from saturation; the temporary integral variable is used as an intermediate variable for updating the integral variable to the next control time interval.

[0133] Case 2: If the control variable vf_temp is less than the set minimum limit value min_vf, then the feed speed vf of the multi-wire cutting machine for the next cycle is output as vf = min_vf; if the feed speed of the multi-wire cutting machine for the next cycle that is output has dropped to the minimum limit value, and the error still requires a decrease in output, then stop accumulating the integral variable;

[0134] If e < 0, then the integral variable new_integral_e for the next control time interval is equal to integral_e; keep the integral variable of the previous control time interval unchanged; otherwise, the integral variable new_integral_e for the next control time interval is equal to temp_integral_e; allow reverse exit from saturation.

[0135] Case 3: If the control variable vf_temp is within the normal range, that is, min_vf < vf_temp < max_vf, the output is not limited, and the integral variable is normally accumulated. At this time, the actual feed speed vf of the multi-wire cutting machine for the next cycle is vf = vf_temp; the integral variable new_integral_e for the next control time interval is equal to temp_integral_e.

[0136] For the switch control algorithm, the decision logic is: when the monitored wire bow angle is less than the preset wire bow angle, the feed speed of the multi-wire cutting machine for the next cycle is directly output as the maximum limit value max_vf; when the monitored wire bow angle is greater than the preset wire bow angle, the output is the minimum limit value min_vf.

[0137] S2. Calculate the new wire feed amount for the wire mesh update in the next reciprocating cycle by using the model predictive control algorithm based on the moving speed, the number of reciprocating cycles, the total effective length of the wire saws participating in cutting in each reciprocating cycle, and the length of the wire saws for new wire feeding during the reciprocating motion.

[0138] In a specific embodiment, the model predictive control algorithm proceeds as follows:

[0139] Construct a relationship model between wear degree characterization quantities and actual wear conditions of the wire saw; based on the relationship model, convert the preset wear conditions into preset wear degree characterization quantities.

[0140] Taking the kth reciprocating cycle as the current reciprocating cycle, calculate the wear degree characterization of each wire saw at each processing position in different axes during the kth reciprocating cycle.

[0141] In the kth reciprocating cycle, based on the wiring method of the multi-wire cutting machine and the processing position involved in multi-wire cutting, the wear degree characterization of the wire saws at each processing position of the multiple wire saws in different axes is superimposed to obtain the wear degree characterization of the whole wire saw in the kth reciprocating cycle.

[0142] Based on the wear characteristics of the wire saw at each processing position in the k-th reciprocating cycle, the wear characteristics of the entire wire saw, and the wear influence factors at each processing position, the MPC control method is used to calculate the wear characteristics of the wire saw at each processing position and the wear characteristics of the entire wire saw in the next h reciprocating cycles under different new wire feed rates. The wear characteristics of the entire wire saw in the next h reciprocating cycles under different new wire feed rates are then back-calculated and aggregated to obtain the wear characteristics of the wire saw at all processing positions in the next h reciprocating cycles under different new wire feed rates.

[0143] Based on the wear degree characterization of the wire saw at all processing positions in the next h reciprocating cycles under different new wire feed rates and the preset wear degree characterization, a cost function for the next h reciprocating cycles under different new wire feed rates is constructed. The new wire feed rate corresponding to the minimum value of the cost function for the next h reciprocating cycles is selected as the new wire feed rate for wire mesh update in the next reciprocating cycle.

[0144] Specifically, the embodiments of this application first utilize data analysis algorithms to fit and construct a relationship model between the wear degree characterization quantity and the actual wear condition of the wire saw, based on the actual wear conditions obtained from a large number of experiments and the wear degree characterization quantity calculated under the same working conditions. The data analysis algorithms here include, but are not limited to, data fitting, regression analysis, neural networks, machine learning, or deep learning. The data involved in the actual wear condition of the wire saw includes, but is not limited to, wire saw diameter, wear amount at wire saw diameter, exposed height of wire saw abrasive grains, wear amount at exposed height of wire saw abrasive grains, number of abrasive grains per unit length of wire saw, number of abrasive grains lost per unit length of wire saw, number of broken abrasive grains, cutting capacity of the wire saw, loss of cutting capacity of the wire saw, number of reciprocating strokes per unit length of wire saw, torsion condition of the wire saw, and fatigue life of the wire saw. Furthermore, this relationship model is used to convert the preset wear condition into a preset wear degree characterization quantity.

[0145] In a specific embodiment, the wear degree characterization of each wire saw at various processing positions along different axes in each reciprocating cycle is calculated, specifically including:

[0146] In the initialization phase, assuming that all wire saws on the wire mesh of the multi-wire cutting machine are not involved in processing, the entire wire mesh consisting of multiple wire saws is discretized to obtain discrete wire saw units. An initial matrix is ​​then constructed to represent the wear degree of different wire saw units in the entire wire mesh during the initialization phase. Where L represents the length of the entire wire saw, and ds is the length of the discrete wire saw unit;

[0147] In the processing stage of the first half of the i-th reciprocating cycle, a wear characteristic of the wire saw at the j-th processing position in the first half of the i-th reciprocating cycle is constructed based on the initial matrix. As shown in the following formula:

[0148] ;

[0149] Where i = 1, 2, ..., k, k represents the total number of reciprocating cycles, j = 1, 2, ..., N, N represents the total number of processing positions, P j Let LL be the wire saw interval length from the j-th processing position to the 1st processing position. i LLL represents the total effective length of the wire saw involved in cutting during the i-th reciprocating cycle. i z represents the length of the new wire feed in the i-th reciprocating cycle. i,j The wear influence factor is the j-th processing position in the i-th reciprocating cycle. The wear influence factor is calculated by the wire bow angle or based on the average motion speed of the corresponding reciprocating cycle, the reciprocating cycle time, the total effective length of the wire saws involved in the cutting, the length of the new wire feed, the material removal coefficient, and the wire bow angle corresponding to that reciprocating cycle. Represents a matrix of all 1s;

[0150] In the processing stage of the second half of the i-th reciprocating cycle, a wear characteristic of the wire saw at the j-th processing position in the second half of the i-th reciprocating cycle is constructed based on the initial matrix. As shown in the following formula:

[0151] ;

[0152] The wear level of the wire saw at the j-th processing position in the i-th reciprocating cycle is calculated using the following formula. :

[0153] ;

[0154] The wear degree characterization quantity of the whole wire saw in the kth reciprocating cycle is: .

[0155] Specifically, assuming all wire saws are not involved in processing, the entire wire saw network is discretized by discretizing the wire saw length. Based on the real-time wire bow angle, movement speed, and effective cutting length of the wire saw, an initial matrix of wear degree characterization for each discrete unit is calculated. Based on this initial matrix, and combining the i-th reciprocating cycle, j-th processing position, total effective length of the wire saws involved in cutting, length of the new wire feed, and wear influence factor, a wear degree characterization for the j-th processing position in the first half of the i-th reciprocating cycle and a wear degree characterization for the j-th processing position in the second half of the i-th reciprocating cycle are constructed. These two are added together to obtain the wear degree characterization for the j-th processing position in the i-th reciprocating cycle. The wear degree characterizations on all wire saws in the k-th cycle across N processing positions are spatiotemporally superimposed to obtain the wear degree characterization for the entire wire saw network. .

[0156] In a specific embodiment, the MPC control method proceeds as follows:

[0157] Establish a new linear feed sequence for regulation. , ,in Indicates the first A new line feed rate , This represents the total feed rate of the new line.

[0158] Based on the wear degree characterization of the whole wire saw in the k-th reciprocating cycle, combined with the first value in the new wire feed sequence... The calculation of the wear influence factor of the new feed rate and the j-th machining position in the k-th reciprocating cycle is performed in the first cycle. The wear characteristic of the wire saw at the j-th machining position in the m-th reciprocating cycle under a new linear feed rate. As shown in the following formula:

[0159] ;

[0160] in, , This represents the total number of future h repetition cycles. Indicates the first The wear degree of the wire saw at the j-th processing position in the first half of the m-th reciprocating cycle under a new wire feed rate is characterized by the following expression: ; Indicates the first The wear degree of the wire saw at the j-th processing position in the second half of the m-th reciprocating cycle under a new feed rate is characterized by the following expression: , This represents the wear influence factor at the j-th processing position in the k-th reciprocating cycle;

[0161] The wear degree characterization of the whole wire saw in the k-th reciprocating cycle is calculated by superimposing the values ​​to obtain the wear degree characterization of the k-th reciprocating cycle. Wear characteristics of the entire wire saw over the next h reciprocating cycles at a new wire feed rate. As shown in the following formula

[0162] ;

[0163] The inverse calculation and aggregation process is as follows:

[0164] Delete in reverse order There are columns containing consecutive zero elements. The remaining columns are retained to obtain the first target wear degree characterization matrix. The flip function is used to flip the first target wear degree characterization matrix to obtain the second target wear degree characterization matrix.

[0165] By truncating the elements of the second target wear degree characterization matrix, the third target wear degree characterization matrix is ​​obtained, as shown in the following formula:

[0166] ;

[0167] in, The matrix representing the wear degree of the second target is... The matrix representing the wear degree of the third target. Indicates the first Elements of column n to nth The elements of each column are extracted, and N' represents the total number of wire saws involved in the processing, which is equal to the total number of processing positions.

[0168] Aggregate the wear degree characterization matrix of the third target to obtain the result at the 1st The wear degree characterization of the wire saw passing through the j-th processing position in the next h reciprocating cycles under a new linear feed rate. As shown in the following formula:

[0169] ;

[0170] in, For data aggregation operators;

[0171] The construction is obtained in the first Wear characterization matrix of N machining positions over the next h reciprocating cycles under a new linear feed rate. As shown in the following formula:

[0172] ;

[0173] For the first The wear characterization matrix of each machining position under a new linear feed rate for the next h reciprocating cycles is aggregated to obtain the wear characterization matrix of the first h-cycle cycle. Wear characterization of all machining positions over the next h reciprocating cycles under a new feed rate. As shown in the following formula:

[0174] ;

[0175] The expression for the cost function is: ,in, This represents the preset wear level characterization quantity.

[0176] Specifically, the embodiments of this application utilize the MPC control method to calculate the wear degree characterization of each processing position and the wear degree characterization of the entire wire saw in the next h reciprocating cycles under different new wire feed rates, based on the wear degree characterization of the current cycle, the wear degree characterization of the entire wire saw, and the wear influence factor of each processing position on the wire saw. The calculation process involves establishing a series of multiple new wire feed rates, and for each new wire feed rate, calculating the wear degree characterization of each processing position and the wear degree characterization of the entire wire saw in the next h reciprocating cycles. It is assumed that the wear influence factor of each processing position in the subsequent future cycles is the same as the wear influence factor of the processing position corresponding to the current cycle, i.e. The wear influence factor z is used to characterize the severity of wear conditions at the interface between the wire saw and the workpiece. It is determined by at least one of the following parameters: (1) the physical load acting on the interface between the wire saw and the workpiece (such as normal force, wire bow angle); (2) the amount of geometric damage at the interface between the wire saw and the workpiece (such as the amount of material removed from the workpiece); (3) the degree of torsion or the number of reciprocating motions of the wire saw. The calculation formula selected in actual production practice is as follows: (Equal to the line arch angle) or (Equal to the sine of the line bow angle) or (Equal to the magnitude of the interaction force between the workpiece and the wire saw along the workpiece feed direction) or (Material removal per micro-element per cycle) or (Equal to the reciprocating frequency corresponding to the reciprocating motion cycle). Where T is the time length of a single reciprocating cycle. The arc angle of the wire saw at the j-th processing position in the i-th reciprocating cycle is represented by vs. i,j kf represents the average absolute value of the motion speed of the wire saw at the j-th processing position in the i-th reciprocating cycle.i,j The material removal coefficient or wire saw cutting capability at the j-th processing position in the i-th reciprocating cycle is represented by , and U represents the reciprocating frequency corresponding to the reciprocating motion cycle. It should be noted that although the numerical magnitudes of the wear influence factors obtained using the above three calculation methods may differ, they are equivalent in characterizing the physical law of "wear trend caused by the wear influence factor." In practical applications, technicians can also choose any of the above methods to quantify this parameter based on specific indirect parameters (such as spindle power, spindle torque, spindle motor current, etc.), which does not deviate from the technical concept of this invention.

[0177] The wear level characterization s of the entire wire saw in the k-th reciprocating cycle is obtained. k Then, feed the new line sequence respectively. The wear influence factor z for each new line feed and the kth reciprocating cycle. k,j Calculate the wear characteristic of the wire saw at the j-th processing position in the m-th reciprocating cycle. Continue in this s k On the basis of superimposed calculation A measure of the wear degree of the entire wire saw after h reciprocating cycles under a new wire feed rate. , for A measure of the wear degree of the entire wire saw after h reciprocating cycles under a new wire feed rate. Perform the reverse calculation. Delete this. The column where the latter part is all 0, Columns with zeros at the end of the matrix represent wire saws that were not processed and are not of research value. These are deleted to obtain the first target wear degree characterization matrix. The first target wear degree characterization matrix is ​​then flipped using the `flip` function to obtain the second target wear degree characterization matrix. The `flip` function flips the positions of elements in the matrix, moving elements from the beginning to the end. Further truncation of the elements in the second target wear degree characterization matrix yields the third target wear degree characterization matrix. Aggregation processing of the third target wear degree characterization matrix provides more detailed feature values ​​that better reflect the wear condition of a wire saw segment. The wear degree characteristic value of N' wire saws participating in the processing through the j-th processing position in the next h reciprocating cycles under a new wire feed rate is aggregated. The aggregation process uses data aggregation operators to convert matrix data into single numerical values. The data aggregation operators used in the embodiments of this application include, but are not limited to, calculating the average and minimum values. Further utilization in... The characteristic values ​​of the wear degree characterization quantity of N' wire saws participating in the processing through all processing positions in the next h reciprocating cycles under a new wire feed rate are constructed in... The wear characterization matrix for each machining position in the next h reciprocating cycles under a new feed rate. Then, for... The wear characterization matrix of each machining position under a new linear feed rate for the next h reciprocating cycles is aggregated to obtain the following... The wear level characteristics of all machining positions in the next h reciprocating cycles are determined by a new feed rate. A cost function is constructed based on the preset wear level characteristics. The new feed rate that minimizes the cost function is selected and applied to the (k+1)th reciprocating cycle. Therefore, the wear level characteristics in the (k+1)th reciprocating cycle can be controlled to be near the preset wear level characteristics, thus achieving the required system control performance. In the embodiments of this application, the MPC control calculation frequency is once per reciprocating cycle.

[0178] S3, based on the feed speed of the multi-wire cutting machine in the next cycle and the new wire feed amount of the wire mesh update in the next reciprocating cycle, controls the multi-wire cutting machine to adjust the feed speed and new wire feed amount within the minimum control cycle of the corresponding control amount, so that the wire bow angle of each wire saw on the wire mesh of the multi-wire cutting machine is controlled within the preset wire bow angle range.

[0179] Specifically, in the embodiments of this application, the cycle used to control the feed speed is the feed speed adjustment cycle. This feed speed adjustment cycle overlaps with the subsequent reciprocating cycle, meaning that while controlling the feed speed of the multi-wire cutting machine in the next cycle is in progress, the adjustment of the new wire feed amount for the next reciprocating cycle's wire mesh update also occurs. The feed speed adjustment cycle is much shorter than a reciprocating cycle, and multiple feed speed adjustment cycles may exist within a single reciprocating cycle. The embodiments of this application control the multi-wire cutting machine to adjust the feed speed and new wire feed amount within the minimum control cycle corresponding to the control amount, respectively, for the feed speed of the multi-wire cutting machine in the next cycle and the new wire feed amount for the next reciprocating cycle. That is, the minimum control cycle for the feed speed corresponds to one feed speed adjustment cycle, and the minimum control cycle for the new wire feed amount corresponds to one reciprocating cycle. Through the combined control of feed speed and new wire feed amount, the overall wear of the wire mesh is kept below a preset level, and the feed speed is controlled to keep the maximum wire bow angle near the preset wire bow angle. Both control the wire bow angle during the multi-wire cutting process.

[0180] The embodiments of this application are based on Simulink or a simulation environment with equivalent functionality to simulate the experimental effects of existing algorithms and the methods proposed in the embodiments of this application. The results are as follows: Figures 2 to 7 As shown, where, Figure 2 and Figure 3The same marble was used, and the sawability parameters of different materials within the marble were the same. Except for the feed speed, all other machine tool parameters and test settings were the same. Based on the preset line bow angle of 0.18° and the material parameters, the maximum feed speed calculated according to the corresponding formula was 0.01 mm / s, and the minimum feed speed was 0.0045 mm / s. Figures 2 to 5 The simulation parameters are the same except for the new line feed rate. The minimum control cycle is the machine tool running cycle, which is set to 20 seconds in the simulation.

[0181] Figure 2 The method involves using existing proportional-derivative (PD) control algorithms to control the feed rate and thus the arc angle during the wire sawing of marble. Simulation results show that this control method is not ideal and exhibits significant errors. Figure 2 The minimum and maximum feed rates set in the system are 0 mm / s and 0.01 mm / s, respectively, which meet the conditions for the maximum and minimum feed rates.

[0182] Figure 3 The feed rate control algorithm of this invention is used to control the feed rate during the wire sawing of marble, thereby controlling the wire bow angle. Simulation results show that this control method achieves ideal control performance. Figure 3 The minimum and maximum feed rates set in the system are 0 mm / s and 0.01 mm / s, respectively, which meet the conditions for the maximum and minimum feed rates.

[0183] Figure 4 The feed rate control algorithm of this invention is used to control the feed rate during the wire sawing of marble. Figure 4 The minimum and maximum feed rates set in the configuration are 0 mm / s and 0.003 mm / s, respectively; the maximum feed rate is less than... The condition of setting the feed rate to the maximum limit is not met. When the line angle corresponding to the maximum feed rate is less than the preset line angle, the output feed rate is always at the maximum limit, and it is still impossible to control the line angle to be near the preset line angle.

[0184] Figure 5 The feed rate control algorithm of this invention is used to control the feed rate during the wire sawing of marble. Figure 5 The minimum and maximum feed rates set in the system are 0.008 mm / s and 0.03 mm / s, respectively; the minimum feed rate is greater than... The minimum feed rate requirement is not met. At this point, the angle of the line cut corresponding to the minimum feed rate is greater than the preset angle of the line cut. During the control process, the output feed rate is always the minimum value, yet the angle of the line cut cannot be controlled to be near the preset angle of the line cut.

[0185] Figure 6 The model predictive control algorithm of this invention is used to control the new line feed rate during multi-line machining. Regarding disturbances during machining (such as sudden material changes), compared to a constant new line feed rate, the multi-line wear condition after using the model predictive control algorithm mentioned in the embodiments of this application can be controlled to near a preset value. Its response speed is faster than constant new line control, and its overshoot is smaller than that of constant new line feed rate control.

[0186] Figure 7 In multi-wire machining, the model predictive control algorithm mentioned in the embodiments of this application is used to control the feed rate of the new wire. The control effect on each wire is better than that of constant new wire control. While the model predictive control controls the feed rate of the new wire, the feed rate in the multi-wire machining process is also controlled, thereby decoupling the influence of wear and feed parameters on the wire bow angle. Figure 6 and Figure 7 The wear characterization quantity in the text is adopted .

[0187] This invention decouples the effects of feed rate and new wire feed amount on the wire bow angle through composite control. It controls the feed rate to keep the maximum wire bow angle in the wire mesh near a preset bow angle, preventing wire breakage during multi-wire sawing due to any wire exceeding the preset bow angle. Simultaneously, it ensures that the wear degree of each wire is less than a preset level, preventing a decrease in sawing efficiency due to neglecting wear. Therefore, this control method is of great significance for achieving safe and efficient multi-wire cutting.

[0188] Further reference Figure 8 As an implementation of the methods shown in the above figures, this application provides an embodiment of a multi-line cutting line bow angle control device based on a composite control strategy. This device embodiment is similar to... Figure 1 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.

[0189] This application provides a multi-line cutting line bow angle control device based on a composite control strategy, including:

[0190] The feed rate calculation module 1 is configured to monitor in real time the wire bow angle, reciprocating speed, number of reciprocating cycles, total effective length of wire saws participating in cutting and length of new wire feed for each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle; and calculate the feed rate of the multi-wire cutting machine for the next cycle using a feed rate theoretical control algorithm based on the wire bow angle and reciprocating speed of each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle.

[0191] The new wire feed calculation module 2 is configured to calculate the new wire feed for the next reciprocating cycle based on the motion speed in the reciprocating motion, the number of reciprocating cycles, the total effective length of the wire saws involved in cutting in each reciprocating cycle, and the length of the new wire feed wire saws using a model predictive control algorithm.

[0192] The adjustment control module 3 is configured to control the multi-wire cutting machine to adjust the feed speed and new wire feed amount within the minimum control cycle of the corresponding control amount according to the feed speed of the multi-wire cutting machine in the next cycle and the new wire feed amount of the wire mesh update in the next reciprocating cycle, so that the wire bow angle of each wire saw on the wire mesh of the multi-wire cutting machine is controlled within the preset wire bow angle range.

[0193] Figure 9 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention. For example... Figure 9 As shown, the electronic device in this embodiment includes a processor 901 and a memory 902; wherein the memory 902 is used to store computer execution instructions; and the processor 901 is used to execute the computer execution instructions stored in the memory to implement the various steps performed by the electronic device in the above embodiment. For details, please refer to the relevant descriptions in the foregoing method embodiments.

[0194] Alternatively, the memory 902 can be either standalone or integrated with the processor 901.

[0195] When the memory 902 is set up independently, the electronic device also includes a bus 903 for connecting the memory 902 and the processor 901.

[0196] This invention also provides a computer storage medium storing computer execution instructions, which, when executed by processor 901, implement the above method.

[0197] This invention also provides a computer program product, including a computer program that, when executed by a processor 901, implements the above-described method.

[0198] In the embodiments provided by this invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0199] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0200] Furthermore, the functional modules in the various embodiments of this invention can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit formed by the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0201] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor 901 to execute some steps of the methods of the various embodiments of this application.

[0202] It should be understood that the processor 901 described above can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor, or the processor 901 can be any conventional processor 901. The steps of the method disclosed in this invention can be directly manifested as execution by the hardware processor 901, or execution by a combination of hardware and software modules within the processor 901.

[0203] The memory 902 may include high-speed RAM memory, and may also include non-volatile memory NVM, such as at least one disk storage device, and may also be a USB flash drive, portable hard drive, read-only memory, disk or optical disc, etc.

[0204] Bus 903 can be an Industry Standard Architecture (ISA), a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Bus 903 can be divided into address bus, data bus, control bus, etc. For ease of illustration, the bus 903 in the accompanying drawings of this application is not limited to only one bus 903 or one type of bus 903.

[0205] The aforementioned storage medium can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium accessible to general-purpose or special-purpose computers.

[0206] An exemplary storage medium is coupled to a processor 901, enabling the processor 901 to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor 901. The processor 901 and the storage medium can reside in an application-specific integrated circuit (ASIC). Alternatively, the processor 901 and the storage medium can exist as discrete components in an electronic device or a host device.

[0207] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0208] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the bow angle of a multi-line cutting line based on a composite control strategy, characterized in that, Includes the following steps: The system monitors in real time the wire bow angle, reciprocating speed, number of reciprocating cycles, total effective length of wire saws involved in cutting, and length of new wire feed for each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle. Based on the wire bow angle and reciprocating speed of each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle, the feed speed of the multi-wire cutting machine in the next cycle is calculated using a feed speed theoretical control algorithm. The model predictive control algorithm is used to calculate the new wire feed amount for the wire mesh update in the next reciprocating cycle based on the motion speed, the number of reciprocating cycles, the total effective length of the wire saws involved in cutting in each reciprocating cycle, and the length of the new wire feed. Based on the feed speed of the multi-wire cutting machine in the next cycle and the new wire feed amount of the wire mesh update in the next reciprocating cycle, the multi-wire cutting machine adjusts the feed speed and the new wire feed amount within the minimum control cycle of the corresponding control amount, so that the wire bow angle of each wire saw on the wire mesh of the multi-wire cutting machine is controlled within the preset wire bow angle range.

2. The multi-line cutting line bow angle control method based on a composite control strategy according to claim 1, characterized in that, Based on the wire bow angle and movement speed of each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle, the feed speed of the multi-wire cutting machine in the next cycle is calculated using a feed speed theoretical control algorithm, specifically including: The maximum line bow angle with the largest value among all wire saws on the online network in the current cycle is determined; The feed rate of the multi-wire cutting machine for the next cycle is calculated using a proportional control algorithm or a proportional-integral control algorithm with an anti-saturation mechanism based on the maximum wire bow angle and the movement speed, or using a switching control algorithm based on the maximum wire bow angle.

3. The multi-line cutting line bow angle control method based on a composite control strategy according to claim 2, characterized in that, The proportional control algorithm process is as follows: The maximum range of feed rate during the control process is calculated using the following formula: ； The minimum limit range of the feed rate during the control process is calculated using the following formula: ； in, This indicates the maximum limit of the feed rate. This indicates the minimum feed rate. Here, represents the preset line bow angle, F represents the tension, and a represents the workpiece width; vs represents the average absolute value of the motion speed; kf_min represents the minimum average sawing capability coefficient of the material at the cutting position throughout the entire cutting process; kf_max represents the maximum average sawing capability coefficient of the material at the cutting position throughout the entire cutting process; kf is the average sawing capability coefficient of the material at the cutting position, and its calculation formula is: assuming the material being cut contains k' types of materials, let the sawing capability coefficient of the i'th material be kf. i’ Its volume fraction as a percentage of the total volume removed is f. vi’ , i'=1,2,3,…,k'; the expression for the average sawing capacity coefficient of the material at the cutting position is: ； Set the maximum and minimum feed rates according to the range of maximum and minimum feed rates during the control process, and configure the proportional coefficient as follows: Where c is the proportional adjustment constant, K represents the system gain which can take any value, and satisfies ; Calculate the difference between the preset line bow angle and the maximum line bow angle to obtain the deviation; The proportional term P is calculated based on the aforementioned deviation, as shown in the following formula: ； Where e represents deviation; The following limiting logic is executed based on the aforementioned ratio term: When the ratio exceeds the set maximum or minimum limit, the feed speed of the multi-wire cutting machine in the next cycle is limited to the corresponding maximum or minimum limit; when the ratio is within the range of the minimum and maximum limits, the ratio is used as the feed speed of the multi-wire cutting machine in the next cycle. The proportional-integral control algorithm, which includes an anti-saturation mechanism, is as follows: The deviation and proportional term are calculated in the same way as the proportional control algorithm, and an integral coefficient is set. K i ,satisfy K i If the value is greater than 0, the tentative control quantity is calculated based on the deviation, proportional term, and integral coefficient, as shown in the following formula: temp_integral_e = integral_e + e·dt; I= K i ·temp_integral_e; vf_temp = P + I; Where dt represents the control time interval, temp_integral_e represents the temporary integral variable, vf_temp represents the tentative control quantity, I represents the integral quantity, and integral_e represents the integral variable of the previous control time interval; Execute conditional integral-based anti-saturation logic based on the tentative control value: When the tentative control quantity triggers the set maximum or minimum limit, the feed speed of the multi-wire cutting machine in the next cycle is limited to the corresponding maximum or minimum limit. At the same time, if the sign of the deviation is consistent with the drive direction that causes saturation, the update of the integral variable for the next control time interval is frozen; if the sign of the deviation is opposite to the drive direction that causes saturation, the update of the integral variable for the next control time interval is allowed to achieve reverse exit from saturation. When the tentative control quantity is within the range of the minimum and maximum limits, the tentative control quantity is used as the feed speed of the multi-wire cutting machine in the next cycle, and the temporary integral variable is updated to the integral variable of the next control time interval. The specific process of the switch control algorithm is as follows: When the maximum wire bow angle is less than the preset wire bow angle, the feed speed of the multi-wire cutting machine in the next cycle is the maximum limit. When the maximum wire bow angle is greater than the preset wire bow angle, the feed speed of the multi-wire cutting machine in the next cycle is the minimum limit.

4. The multi-line cutting line bow angle control method based on a composite control strategy according to claim 1, characterized in that, The process of the model predictive control algorithm is as follows: Construct a relationship model between wear degree characterization quantities and actual wear conditions of the wire saw; convert the preset wear conditions into preset wear degree characterization quantities based on the relationship model; Taking the kth reciprocating cycle as the current reciprocating cycle, calculate the wear degree characterization of each wire saw at each processing position in different axes during the kth reciprocating cycle. In the kth reciprocating cycle, based on the wiring method of the multi-wire cutting machine and the processing position involved in multi-wire cutting, the wear degree characterization of the wire saws at each processing position of the multiple wire saws in different axes is superimposed to obtain the wear degree characterization of the whole wire saw in the kth reciprocating cycle. Based on the wear characteristics of the wire saw at each processing position in the k-th reciprocating cycle, the wear characteristics of the entire wire saw, and the wear influence factors at each processing position, the MPC control method is used to calculate the wear characteristics of the wire saw at each processing position and the wear characteristics of the entire wire saw in the next h reciprocating cycles under different new wire feed rates. The wear characteristics of the entire wire saw in the next h reciprocating cycles under different new wire feed rates are then back-calculated and aggregated to obtain the wear characteristics of the wire saw at all processing positions in the next h reciprocating cycles under different new wire feed rates. Based on the wear degree characterization of the wire saw at all processing positions in the next h reciprocating cycles under different new wire feed rates and the preset wear degree characterization, a cost function for the next h reciprocating cycles under different new wire feed rates is constructed. The new wire feed rate corresponding to the minimum value of the cost function for the next h reciprocating cycles is selected as the new wire feed rate for wire mesh update in the next reciprocating cycle.

5. The multi-line cutting line bow angle control method based on a composite control strategy according to claim 4, characterized in that, Calculate the wear characteristics of each wire saw at various machining positions along different axes for each reciprocating cycle, specifically including: In the initialization phase, assuming that all wire saws on the wire mesh of the multi-wire cutting machine are not involved in processing, the entire wire mesh consisting of multiple wire saws is discretized to obtain discrete wire saw units. An initial matrix is ​​then constructed to represent the wear degree of different wire saw units in the entire wire mesh during the initialization phase. Where L represents the length of the entire wire saw, and ds is the length of the discrete wire saw unit; During the processing phase of the first half of the i-th reciprocating cycle, a wear characterization quantity for the wire saw at the j-th processing position of the first half of the i-th reciprocating cycle is constructed based on the initial matrix. As shown in the following formula: ； Where i = 1, 2, ..., k, k represents the total number of reciprocating cycles, j = 1, 2, ..., N, N represents the total number of processing positions, P j Let LL be the wire saw interval length from the j-th processing position to the 1st processing position. i LLL represents the total effective length of the wire saw involved in cutting during the i-th reciprocating cycle. i z represents the length of the new wire feed in the i-th reciprocating cycle. i,j The wear influence factor is the wear factor at the j-th processing position in the i-th reciprocating cycle. The wear influence factor is calculated by the wire bow angle or based on the average motion speed of the corresponding reciprocating cycle, the reciprocating cycle time, the total effective length of the wire saws involved in the cutting, the length of the wire saw with the new wire feed, the material removal coefficient, and the wire bow angle corresponding to that reciprocating cycle. Represents a matrix of all 1s; In the processing stage of the second half of the i-th reciprocating cycle, a wear characteristic of the wire saw at the j-th processing position of the second half of the i-th reciprocating cycle is constructed based on the initial matrix. As shown in the following formula: ； The wear level of the wire saw at the j-th processing position in the i-th reciprocating cycle is calculated using the following formula. : ； The wear degree characterization quantity of the whole wire saw in the kth reciprocating cycle is: .

6. The multi-line cutting line bow angle control method based on a composite control strategy according to claim 5, characterized in that, The process of the MPC control method is as follows: Establish a new linear feed sequence for regulation. , ,in Indicates the first A new line feed rate , This represents the total feed rate of the new line. Based on the wear degree characterization of the whole wire saw in the k-th reciprocating cycle, combined with the first value in the new wire feed sequence... The calculation of the wear influence factor of the new feed rate and the j-th machining position in the k-th reciprocating cycle is performed in the first cycle. The wear characteristic of the wire saw at the j-th machining position in the m-th reciprocating cycle under a new linear feed rate. As shown in the following formula: ； in, , This represents the total number of future h repetition cycles. Indicates the first The wear degree of the wire saw at the j-th processing position in the first half of the m-th reciprocating cycle under a new wire feed rate is characterized by the following expression: ; Indicates the first The wear degree of the wire saw at the j-th processing position in the second half of the m-th reciprocating cycle under a new feed rate is characterized by the following expression: , This represents the wear influence factor at the j-th processing position in the k-th reciprocating cycle; The wear degree characterization of the whole wire saw in the k-th reciprocating cycle is calculated by superimposing the values ​​to obtain the wear degree characterization of the k-th reciprocating cycle. Wear characteristics of the entire wire saw over the next h reciprocating cycles at a new wire feed rate. As shown in the following formula ； The inverse calculation and aggregation process is as follows: Delete in reverse order There are columns containing consecutive zero elements. The remaining columns are retained to obtain the first target wear degree characterization matrix. The flip function is used to flip the first target wear degree characterization matrix to obtain the second target wear degree characterization matrix. By truncating elements of the second target wear degree characterization matrix, the third target wear degree characterization matrix is ​​obtained, as shown in the following formula: ； in, The matrix representing the wear degree of the second target is... The matrix representing the wear degree of the third target. Indicates the first Elements of column n to nth The elements of each column are extracted, and N' represents the total number of wire saws involved in the processing, which is equal to the total number of processing positions. The wear degree characterization matrix of the third target is aggregated to obtain the result at the first target. The wear degree characterization of the wire saw passing through the j-th processing position in the next h reciprocating cycles under a new linear feed rate. As shown in the following formula: ； in, For data aggregation operators; The construction is obtained in the first Wear characterization matrix of N machining positions over the next h reciprocating cycles under a new linear feed rate. As shown in the following formula: ； For the first The wear characterization matrix of each machining position under a new linear feed rate for the next h reciprocating cycles is aggregated to obtain the wear characterization matrix of the first h-cycle cycle. Wear characterization of all machining positions over the next h reciprocating cycles under a new feed rate. As shown in the following formula: ； The expression for the cost function is: ,in, This represents the preset wear level characterization quantity.

7. A multi-line cutting line bow angle control device based on a composite control strategy, characterized in that, include: The feed rate calculation module is configured to monitor in real time the wire bow angle, reciprocating speed, number of reciprocating cycles, total effective length of wire saws participating in cutting and length of new wire feed for each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle; and calculate the feed rate of the multi-wire cutting machine for the next cycle using a feed rate theoretical control algorithm based on the wire bow angle and reciprocating speed of each wire saw on the wire mesh of the multi-wire cutting machine in the current cycle. The new wire feed calculation module is configured to calculate the new wire feed for the next reciprocating cycle based on the motion speed in the reciprocating motion, the number of reciprocating cycles, the total effective length of the wire saws involved in cutting in each reciprocating cycle, and the length of the new wire feed wire saws using a model predictive control algorithm. The adjustment control module is configured to control the multi-wire cutting machine to adjust its feed speed and new wire feed amount within the minimum control period of the corresponding control amount, based on the feed speed of the multi-wire cutting machine in the next cycle and the new wire feed amount of the wire mesh update in the next reciprocating cycle, so that the wire bow angle of each wire saw on the wire mesh of the multi-wire cutting machine is controlled within the preset wire bow angle range.

8. An electronic device, comprising: One or more processors; A storage device for storing one or more programs, characterized in that, when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-6.

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