Optimal control method and device for differential pressure and vibration of small vertical mill and computer equipment

Abstract

The invention relates to an optimal control method and device for differential pressure and vibration of a small vertical mill and computer equipment. The method comprises the following steps: acquiring real-time data of a mill; preprocessing the real-time data to generate a trend curve; generating trend control according to the change trend of the trend curve; adjusting trend control according to the change of the fan rotating speed parameter, and generating compensation control; according to the compensation control, current mill key variable parameters are obtained; and generating optimization control according to the key variable parameters of the mill and a preset differential pressure value. By the adoption of the method, calculation can be conducted through the preset model and the limiting conditions, corresponding control is driven, the production control process of the mill is more accurate, more timely, more reliable and more efficient, and conditions and guarantees are provided for long-term efficient and stable operation of the mill. The'edge clamping 'operation of main production indexes and quality indexes is realized; and the grinding efficiency of the mill system is improved, the electric energy loss of the mill system is reduced, and the benefits of enterprises are increased in a real sense.

Description

Technical Field

[0001] The present application relates to the field of advanced control technology, and in particular to a small mill optimization control method, device and computer equipment. Background Art

[0002] The grinding system is a nonlinear system with large hysteresis and strong coupling, and the variables affect each other. A controlled variable CV will be affected by several manipulated variables MV at the same time. For example, the mill differential pressure is affected by multiple parameters such as feed rate, grinding pressure, tail exhaust fan speed, powder concentrator speed and slag bucket lifting current.

[0003] Compared with conventional mills, small mill systems have the following characteristics:

[0004] (1) The grinding efficiency changes periodically with the use time of the grinding roller;

[0005] (2) The mill vibrates frequently;

[0006] (3) Due to factors such as roller wear and roller sleeve replacement, the grinding pressure needs to be frequently adjusted through a hydraulic device;

[0007] (4) Due to frequent changes in raw materials and mill operating conditions, operators need to regularly adjust process parameters.

[0008] In view of the above characteristics, if conventional control methods are used, the system cannot adapt to changes in working conditions, and it is difficult to capture abnormal situations in time and make adjustments. Usually, when formulating a mill control plan, a strategy is adopted to automatically adjust the feed into the mill based on the mill differential pressure, mill main current and tail exhaust fan current. However, for small mills, the mill main current itself has a large fluctuation range, and it will not change significantly with the adjustment of the feed amount into the mill. Therefore, from the perspective of system safety, it is difficult to use the mill main current as an important basis to directly adjust the mill output. Summary of the invention

[0009] Based on this, it is necessary to provide a small mill optimization control method, device, computer equipment, computer readable storage medium and computer program product that can adapt to various working conditions to address the above technical problems.

[0010] In a first aspect, the present application provides a small mill optimization control method. The method comprises:

[0011] Get real-time data of the mill;

[0012] Preprocessing the real-time data to generate a trend curve;

[0013] Generate trend control according to the changing trend of the trend curve;

[0014] Adjust trend control according to the change of fan speed parameters to generate compensation control;

[0015] According to the compensation control, obtaining current key variable parameters of the mill;

[0016] An optimized control is generated according to the key variable parameters of the mill and the preset differential pressure value.

[0017] In one embodiment, based on the control curve analysis method, the adjustment range of the controller is set, and the specific formula is as follows:

[0018]

[0019] Among them, u delta is the output adjustment range, ε is the deviation threshold; u range Adjust the amplitude for the controller;

[0020] According to the changing trend of the trend curve, a trend control is generated, and the specific formula is as follows:

[0021]

[0022] Among them, u con is the trend control output, △ delta The controller adjustment amplitude increment, pv i is the current value after filtering, pv i-1 It is the value of the previous control cycle after filtering.

[0023] In one of the embodiments, the trend control is adjusted according to the change of the fan speed parameter to generate the compensation control;

[0024] Wherein, the fan speed parameter includes the current tail exhaust fan speed setting value and the tail exhaust fan speed setting value of the previous control cycle;

[0025] When the current tail exhaust fan speed setting value is not equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output is zero, and compensation control is generated;

[0026] When the current tail exhaust fan speed setting value is equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output remains unchanged and a compensation control is generated;

[0027] The specific formula is as follows:

[0028]

[0029] Among them, wpzs i is the current tail exhaust fan speed setting value, wpzs i-1It is the speed setting value of the tail exhaust fan in the previous control cycle.

[0030] In one embodiment, an optimization control is generated according to the key variable parameters of the mill and the preset differential pressure value. The specific formula is as follows:

[0031]

[0032] Among them, u i is the tail exhaust fan current, u j The current for the slag bucket, u k is the main mill current, x is the mill differential pressure setting value, Optimizing the set value for the mill differential pressure means optimizing control.

[0033] In one of the embodiments, detecting whether the vibration value is greater than a vibration threshold;

[0034] If the vibration value is less than or equal to the vibration threshold, detecting whether the fineness value is greater than the fineness threshold;

[0035] If the fineness value is less than or equal to the fineness threshold, a comprehensive control is generated according to the process parameters of the mill.

[0036] In one of the embodiments, if the vibration value is greater than a vibration threshold, grinding pressure control is performed;

[0037] If the fineness value is greater than the fineness threshold, fineness control is performed.

[0038] In a second aspect, the present application also provides a small mill optimization control device. The device comprises:

[0039] A data acquisition module is used to obtain real-time data of the mill;

[0040] A curve generating module, used for preprocessing the real-time data to generate a trend curve;

[0041] A trend control module, used for generating trend control according to the changing trend of the trend curve;

[0042] A compensation control module is used to adjust the trend control according to the change of the fan speed parameter and generate compensation control;

[0043] A parameter acquisition module, used for acquiring current key variable parameters of the mill according to the compensation control;

[0044] The optimization control module is used to generate optimization control according to the key variable parameters of the mill and the preset differential pressure value.

[0045] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0046] Get real-time data of the mill;

[0047] Preprocessing the real-time data to generate a trend curve;

[0048] Generate trend control according to the changing trend of the trend curve;

[0049] Adjust trend control according to the change of fan speed parameters to generate compensation control;

[0050] According to the compensation control, obtaining current key variable parameters of the mill;

[0051] An optimized control is generated according to the key variable parameters of the mill and the preset differential pressure value.

[0052] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0053] Get real-time data of the mill;

[0054] Preprocessing the real-time data to generate a trend curve;

[0055] Generate trend control according to the changing trend of the trend curve;

[0056] Adjust trend control according to the change of fan speed parameters to generate compensation control;

[0057] According to the compensation control, obtaining current key variable parameters of the mill;

[0058] An optimized control is generated according to the key variable parameters of the mill and the preset differential pressure value.

[0059] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0060] Get real-time data of the mill;

[0061] Preprocessing the real-time data to generate a trend curve;

[0062] Generate trend control according to the changing trend of the trend curve;

[0063] Adjust trend control according to the change of fan speed parameters to generate compensation control;

[0064] According to the compensation control, obtaining current key variable parameters of the mill;

[0065] An optimized control is generated according to the key variable parameters of the mill and the preset differential pressure value.

[0066] The above-mentioned small mill optimization control method, device and computer equipment obtain the real-time data of the mill; pre-process the real-time data to generate a trend curve; generate trend control according to the change trend of the trend curve; adjust the trend control according to the change of the fan speed parameter to generate compensation control; obtain the current mill key variable parameters according to the compensation control; generate optimization control according to the mill key variable parameters and the preset differential pressure value. In the present invention, the preset model and restriction conditions are used to calculate and drive the corresponding control, replacing the traditional conventional control method, so that the production control process of the mill is more accurate, more timely, more reliable and more efficient, providing conditions and guarantees for the long-term efficient and stable operation of the mill. The "edge card" operation of the main production indicators and quality indicators is realized; the grinding efficiency of the mill system is improved, and the power loss of the mill system is reduced, which truly improves the benefits for the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 A schematic flow chart of a small mill optimization control method in one embodiment;

[0068] Figure 2 A first strategy flow chart of a small mill optimization control method in one embodiment;

[0069] Figure 3 A second strategy flow chart of a small mill optimization control method in one embodiment;

[0070] Figure 4 It is a structural block diagram of a small mill optimization control device in one embodiment;

[0071] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0073] In one embodiment, Figure 1 As shown, a small mill optimization control method is provided, comprising the following steps:

[0074] Step 202, obtaining real-time data of the grinding mill.

[0075] Wherein, the real-time data includes vibration value and fineness value;

[0076] Specifically, it is detected whether the vibration value is greater than the vibration threshold; if the vibration value is less than or equal to the vibration threshold, it is detected whether the fineness value is greater than the fineness threshold; if the fineness value is less than or equal to the fineness threshold, a comprehensive control is generated according to the process parameters of the mill.

[0077] More specifically, if the vibration value is greater than the vibration threshold, grinding pressure control is performed; if the fineness value is greater than the fineness threshold, fineness control is performed.

[0078] In one embodiment, Figure 2 As shown in the figure, the hydraulic device is the power source of the mill, responsible for driving the grinding roller to grind the material on the grinding plate. In order to ensure the smooth operation of the system, the controller is designed according to the key threshold and expert experience to weaken the adverse effects of vibration on the system.

[0079] Detect whether the vibration value is greater than the vibration threshold; if the vibration value is greater than the vibration threshold, perform grinding pressure control. The specific formula is as follows:

[0080]

[0081] Among them, y is the grinding pressure setting value, δ is the deviation threshold, delta is the adjustment range, and v i is the vibration measurement value, v H is the upper limit of vibration, v t i me is the cumulative time for vibration to return to normal, v Ht i me The cumulative time limit.

[0082] Particle size is the core quality indicator in the production process. In order to maximize production efficiency and ensure product quality, when the production system is maintained in a relatively stable and controllable state, the particle size is closely tracked and adjusted through control means to detect the fineness value to maximize edge optimization.

[0083] Detect whether the fineness value is greater than the fineness threshold; if the fineness value is greater than the fineness threshold, perform fineness control. The specific formula is as follows:

[0084]

[0085] Among them, The margin of grinding pressure adjustment allowed, y1 is the fineness measurement value, y sp is the particle size setting value, n is the empirical constant, c △ Incremental output for the controller.

[0086] In addition, in order to respond to different production needs, starting from the device structure and production process flow, we look for process parameters that affect the output and smooth operation of the device to determine the control strategy.

[0087] If the fineness value is less than or equal to the fineness threshold, a comprehensive control is generated according to the process parameters of the mill. The specific formula is as follows:

[0088] Control target 1: output

[0089] J(yield max )=f(y,z max )+△ delta

[0090] Control Objective 2: Safety

[0091] J(safe max )=f(y,z min )-△ delta

[0092] Among them, J is the objective function, yield max To maximize production, safe max Safety first, max is the maximum control range allowed by differential pressure, z min is the acceptable minimum control range of mill differential pressure, △ delta The controller outputs increments. The control flow chart and effect diagram are shown below.

[0093] Step 204: pre-process the real-time data to generate a trend curve.

[0094] Specifically, in order to eliminate the data fluctuations caused by the on-site measuring instruments, the collected real-time data is preprocessed by continuous mean filtering to generate a trend curve. Under the premise of ensuring that the data is not distorted, the trend curve is made as stable as possible to highlight the change trend. The filtering function used is as follows:

[0095]

[0096] Among them, x i represents the value after filtering of the ith value; x j is the actual value of a parameter at a certain moment; n is the average value taken every n seconds.

[0097] Step 206: Generate trend control according to the changing trend of the trend curve.

[0098] Specifically, for the processing of mill output, when the differential pressure of the mill is too low or too high and exceeds the set threshold, it is necessary to quickly increase or decrease the feed amount so that the differential pressure of the mill quickly stabilizes.

[0099] Based on the control curve analysis method, the adjustment range of the controller is set. The specific formula is as follows:

[0100]

[0101] Among them, u delta is the output adjustment range, ε is the deviation threshold; u range Adjust the amplitude for the controller.

[0102] On the basis of the above, in order to maintain the flexibility and effectiveness of the controller and avoid overshoot and fluctuation, the operation of the system is defined according to the set value, control range and change trend of the variable. When the controller curve diverges, in order to achieve rapid increase and decrease of production and converge to the allowable range as soon as possible, the action strength of the controller is increased; when the control curve converges, in order to maintain high-yield operation for a long time and avoid fluctuations, the action strength of the controller is weakened and the convergence rate is suppressed.

[0103] According to the changing trend of the trend curve, a trend control is generated, and the specific formula is as follows:

[0104]

[0105] Among them, u con is the controller incremental output, △ delta The controller adjustment amplitude increment, pv i is the current value after filtering, pv i-1 It is the value of the previous control cycle after filtering.

[0106] Step 208, adjusting the trend control according to the change of the fan speed parameter to generate a compensation control.

[0107] The fan speed parameter includes a current tail exhaust fan speed setting value and a tail exhaust fan speed setting value in a previous control cycle.

[0108] Specifically, in order to respond to production plans, on-site operators usually adjust the speed of the tail exhaust fan frequently and irregularly. As the main power source for the air circulation of the mill system, frequent adjustments of the tail exhaust fan will inevitably cause abnormal fluctuations in the mill differential pressure. In order to offset the adverse effects of this abnormal situation on the control system, the following auxiliary control strategy is adopted.

[0109] According to the change of the fan speed parameter, the trend control is adjusted to generate the compensation control; when the current tail exhaust fan speed setting value is not equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output is zero, and the compensation control is generated; when the current tail exhaust fan speed setting value is equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output remains unchanged, and the compensation control is generated; the specific formula is as follows:

[0110]

[0111] Among them, wpzs i is the current tail exhaust fan speed setting value, wpzs i-1 It is the speed setting value of the tail exhaust fan in the previous control cycle.

[0112] Step 210: Obtain current key variable parameters of the mill according to the compensation control.

[0113] Among them, the key variable parameters of the mill include the tail exhaust fan current, the slag bucket lifting current, and the mill main machine current.

[0114] Step 212, generating an optimized control according to the key variable parameters of the mill and the preset differential pressure value.

[0115] Specifically, through the analysis of the process flow, in order to achieve the goal of reducing the labor intensity of operators and improving the mill production capacity, an optimization control strategy is adopted with the tail exhaust fan current and slag bucket lifting current as the main control and the mill main current as the auxiliary control. The target optimization function can be expressed as:

[0116] According to the key variable parameters of the mill and the preset differential pressure value, the optimization control is generated, and the specific formula is as follows:

[0117]

[0118] Among them, u i is the tail exhaust fan current, u j The current for the slag bucket, u k is the main mill current, x is the mill differential pressure setting value, Optimize setpoint for mill differential pressure.

[0119] Furthermore, from a safety perspective, combined with the actual conditions of equipment operation and production scheduling, when the equipment is in some special states, the output of the optimization controller is restricted.

[0120]

[0121] Among them, case 1 is the grinding mill startup state, case 2 is the multi-feeding belt scale switching state, case 3 is the operator manual intervention state; case 4 is the grinding mill host tripping and restarting state.

[0122] In the above-mentioned small mill optimization control method, the real-time data of the mill is obtained; the real-time data is preprocessed to generate a trend curve; according to the change trend of the trend curve, a trend control is generated; according to the change of the fan speed parameter, the trend control is adjusted to generate a compensation control; according to the compensation control, the current mill key variable parameters are obtained; according to the mill key variable parameters and the preset differential pressure value, an optimization control is generated. In the present invention, the preset model and restriction conditions are used to calculate and drive the corresponding control, replacing the traditional conventional control method, so that the production control process of the mill is more accurate, more timely, more reliable and more efficient, providing conditions and guarantees for the long-term efficient and stable operation of the mill. The "edge card" operation of the main production indicators and quality indicators is realized; the grinding efficiency of the mill system is improved, and the power loss of the mill system is reduced, which truly improves the benefits for the enterprise.

[0123] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0124] Based on the same inventive concept, the embodiment of the present application also provides a small mill optimization control device for implementing the small mill optimization control method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more small mill optimization control device embodiments provided below can refer to the limitations of the small mill optimization control method above, and will not be repeated here.

[0125] In one embodiment, Figure 4 As shown, a small mill optimization control device is provided, including: a data acquisition module 410, a curve generation module 420, a trend control module 430, a compensation control module 440, a parameter acquisition module 450 and an optimization control module 460, wherein:

[0126] Data acquisition module 410, used to obtain real-time data of the mill.

[0127] The curve generating module 420 is used to pre-process the real-time data to generate a trend curve.

[0128] The trend control module 430 is used to generate trend control according to the change trend of the trend curve.

[0129] The compensation control module 440 is used to adjust the trend control according to the change of the fan speed parameter and generate the compensation control.

[0130] The parameter acquisition module 450 is used to acquire the current key variable parameters of the mill according to the compensation control.

[0131] The optimization control module 460 is used to generate optimization control according to the key variable parameters of the mill and the preset differential pressure value.

[0132] The trend control module 430 is also used to set the adjustment range of the controller based on the control curve analysis method. The specific formula is as follows:

[0133]

[0134] Among them, u delta is the output adjustment range, ε is the deviation threshold; u range Adjust the amplitude for the controller;

[0135] According to the changing trend of the trend curve, a trend control is generated, and the specific formula is as follows:

[0136]

[0137] Among them, u con is the trend control output, △ delta The controller adjustment amplitude increment, pv i is the current value after filtering, pv i-1 It is the value of the previous control cycle after filtering.

[0138] The compensation control module 440 is also used to adjust the trend control according to the change of the fan speed parameter and generate the compensation control;

[0139] When the current tail exhaust fan speed setting value is not equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output is zero, and compensation control is generated;

[0140] When the current tail exhaust fan speed setting value is equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output remains unchanged and a compensation control is generated;

[0141] The specific formula is as follows:

[0142]

[0143] Among them, wpzs iis the current tail exhaust fan speed setting value, wpzs i-1 It is the speed setting value of the tail exhaust fan in the previous control cycle.

[0144] The optimization control module 460 is also used to generate optimization control according to the key variable parameters of the mill and the preset differential pressure value. The specific formula is as follows:

[0145]

[0146] Among them, u i is the tail exhaust fan current, u j The current for the slag bucket, u k is the main mill current, x is the mill differential pressure setting value, Optimizing the set value for the mill differential pressure means optimizing control.

[0147] The data acquisition module 410 is also used to detect whether the vibration value is greater than a vibration threshold;

[0148] If the vibration value is less than or equal to the vibration threshold, detecting whether the fineness value is greater than the fineness threshold;

[0149] If the fineness value is less than or equal to the fineness threshold, a comprehensive control is generated according to the process parameters of the mill.

[0150] The data acquisition module 410 is also used to perform grinding pressure control if the vibration value is greater than a vibration threshold;

[0151] If the fineness value is greater than the fineness threshold, fineness control is performed.

[0152] Each module in the above-mentioned small mill optimization control device can be implemented in whole or in part by software, hardware and their combination. Each module can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0153] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 5As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store optimization control data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a small mill optimization control method is implemented.

[0154] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0155] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, any one of the small mill optimization control methods in the above embodiments is implemented.

[0156] Get real-time data of the mill;

[0157] Preprocessing the real-time data to generate a trend curve;

[0158] Generate trend control according to the changing trend of the trend curve;

[0159] Adjust trend control according to the change of fan speed parameters to generate compensation control;

[0160] According to the compensation control, obtaining current key variable parameters of the mill;

[0161] An optimized control is generated according to the key variable parameters of the mill and the preset differential pressure value.

[0162] In one embodiment, when the processor executes the computer program, the following steps are further implemented: based on the control curve analysis method, the adjustment range of the controller is set, and the specific formula is as follows:

[0163]

[0164] Among them, u delta is the output adjustment range, ε is the deviation threshold; u range Adjust the amplitude for the controller;

[0165] According to the changing trend of the trend curve, a trend control is generated, and the specific formula is as follows:

[0166]

[0167] Among them, u con is the trend control output, △ delta The controller adjustment amplitude increment, pv i is the current value after filtering, pv i-1 It is the value of the previous control cycle after filtering.

[0168] In one embodiment, when the processor executes the computer program, the following steps are further implemented: adjusting the trend control according to the change of the fan speed parameter to generate a compensation control;

[0169] Wherein, the fan speed parameter includes the current tail exhaust fan speed setting value and the tail exhaust fan speed setting value of the previous control cycle;

[0170] When the current tail exhaust fan speed setting value is not equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output is zero, and compensation control is generated;

[0171] When the current tail exhaust fan speed setting value is equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output remains unchanged and a compensation control is generated;

[0172] The specific formula is as follows:

[0173]

[0174] Among them, wpzs i is the current tail exhaust fan speed setting value, wpzs i-1 It is the speed setting value of the tail exhaust fan in the previous control cycle.

[0175] In one embodiment, when the processor executes the computer program, the following steps are further implemented: generating an optimization control according to the key variable parameters of the mill and the preset differential pressure value, and the specific formula is as follows:

[0176]

[0177] Among them, u i is the tail exhaust fan current, u j The current for the slag bucket, u k is the main mill current, x is the mill differential pressure setting value, Optimizing the set value for the mill differential pressure means optimizing control.

[0178] In one embodiment, when the processor executes the computer program, the following steps are further implemented: detecting whether the vibration value is greater than a vibration threshold;

[0179] If the vibration value is less than or equal to the vibration threshold, detecting whether the fineness value is greater than the fineness threshold;

[0180] If the fineness value is less than or equal to the fineness threshold, a comprehensive control is generated according to the process parameters of the mill.

[0181] In one embodiment, when the processor executes the computer program, the following steps are also implemented: if the vibration value is greater than the vibration threshold, grinding pressure control is performed; if the fineness value is greater than the fineness threshold, fineness control is performed.

[0182] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, any one of the small mill optimization control methods in the above embodiments is implemented.

[0183] Get real-time data of the mill;

[0184] Preprocessing the real-time data to generate a trend curve;

[0185] Generate trend control according to the changing trend of the trend curve;

[0186] Adjust trend control according to the change of fan speed parameters to generate compensation control;

[0187] According to the compensation control, obtaining current key variable parameters of the mill;

[0188] An optimized control is generated according to the key variable parameters of the mill and the preset differential pressure value.

[0189] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: based on the control curve analysis method, the adjustment range of the controller is set, and the specific formula is as follows:

[0190]

[0191] Among them, u delta is the output adjustment range, ε is the deviation threshold; u range Adjust the amplitude for the controller;

[0192] According to the changing trend of the trend curve, a trend control is generated, and the specific formula is as follows:

[0193]

[0194] Among them, u con is the trend control output, △ delta The controller adjustment amplitude increment, pv i is the current value after filtering, pv i-1It is the value of the previous control cycle after filtering.

[0195] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: adjusting the trend control according to the change of the fan speed parameter to generate a compensation control;

[0196] Wherein, the fan speed parameter includes the current tail exhaust fan speed setting value and the tail exhaust fan speed setting value of the previous control cycle;

[0197] When the current tail exhaust fan speed setting value is not equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output is zero, and compensation control is generated;

[0198] When the current tail exhaust fan speed setting value is equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output remains unchanged and a compensation control is generated;

[0199] The specific formula is as follows:

[0200]

[0201] Among them, wpzs i is the current tail exhaust fan speed setting value, wpzs i-1 It is the speed setting value of the tail exhaust fan in the previous control cycle.

[0202] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: wherein the key variable parameters of the mill include the tail exhaust fan current, the slag bucket lifting current, and the mill main machine current;

[0203] According to the key variable parameters of the mill and the preset differential pressure value, the optimization control is generated, and the specific formula is as follows:

[0204]

[0205] Among them, u i is the tail exhaust fan current, u j The current for the slag bucket, u k is the main mill current, x is the mill differential pressure setting value, Optimizing the set value for the mill differential pressure means optimizing control.

[0206] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: detecting whether the vibration value is greater than a vibration threshold;

[0207] If the vibration value is less than or equal to the vibration threshold, detecting whether the fineness value is greater than the fineness threshold;

[0208] If the fineness value is less than or equal to the fineness threshold, a comprehensive control is generated according to the process parameters of the mill.

[0209] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: if the vibration value is greater than the vibration threshold, grinding pressure control is performed;

[0210] If the fineness value is greater than the fineness threshold, fineness control is performed.

[0211] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0212] Get real-time data of the mill;

[0213] Preprocessing the real-time data to generate a trend curve;

[0214] Generate trend control according to the changing trend of the trend curve;

[0215] Adjust trend control according to the change of fan speed parameters to generate compensation control;

[0216] According to the compensation control, obtaining current key variable parameters of the mill;

[0217] An optimized control is generated according to the key variable parameters of the mill and the preset differential pressure value.

[0218] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: based on the control curve analysis method, the adjustment range of the controller is set, and the specific formula is as follows:

[0219]

[0220] Among them, u delta is the output adjustment range, ε is the deviation threshold; u range Adjust the amplitude for the controller;

[0221] According to the changing trend of the trend curve, a trend control is generated, and the specific formula is as follows:

[0222]

[0223] Among them, u con is the trend control output, △ delta The controller adjustment amplitude increment, pv i is the current value after filtering, pv i-1 It is the value of the previous control cycle after filtering.

[0224] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: adjusting the trend control according to the change of the fan speed parameter to generate a compensation control;

[0225] Wherein, the fan speed parameter includes the current tail exhaust fan speed setting value and the tail exhaust fan speed setting value of the previous control cycle;

[0226] When the current tail exhaust fan speed setting value is not equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output is zero, and compensation control is generated;

[0227] When the current tail exhaust fan speed setting value is equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output remains unchanged and a compensation control is generated;

[0228] The specific formula is as follows:

[0229]

[0230] Among them, wpzs i is the current tail exhaust fan speed setting value, wpzs i-1 It is the speed setting value of the tail exhaust fan in the previous control cycle.

[0231] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: generating an optimization control according to the key variable parameters of the mill and the preset differential pressure value, and the specific formula is as follows:

[0232]

[0233] Among them, u i is the tail exhaust fan current, u j The current for the slag bucket, u k is the main mill current, x is the mill differential pressure setting value, Optimizing the set value for the mill differential pressure means optimizing control.

[0234] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: detecting whether the vibration value is greater than a vibration threshold;

[0235] If the vibration value is less than or equal to the vibration threshold, detecting whether the fineness value is greater than the fineness threshold;

[0236] If the fineness value is less than or equal to the fineness threshold, a comprehensive control is generated according to the process parameters of the mill.

[0237] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: if the vibration value is greater than the vibration threshold, grinding pressure control is performed;

[0238] If the fineness value is greater than the fineness threshold, fineness control is performed.

[0239] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0240] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0241] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0242] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A small mill optimization control method, characterized in that: The method comprises: Get real-time data of the mill; Preprocessing the real-time data to generate a trend curve; Generate trend control according to the changing trend of the trend curve; Adjust trend control according to the change of fan speed parameters to generate compensation control; According to the compensation control, obtaining current key variable parameters of the mill; An optimized control is generated according to the key variable parameters of the mill and the preset differential pressure value.

2. The method according to claim 1, characterized in that The generating trend control according to the changing trend of the trend curve comprises: Based on the control curve analysis method, the adjustment range of the controller is set. The specific formula is as follows: Among them, u delta is the output adjustment range, ε is the deviation threshold; u range Adjust the amplitude for the controller; According to the changing trend of the trend curve, a trend control is generated, and the specific formula is as follows: Among them, u con is the trend control output, △ delta The controller adjustment amplitude increment, pv i is the current value after filtering, pvi -1 It is the value of the previous control cycle after filtering.

3. The method according to claim 2, characterized in that The adjusting trend control according to the change of the fan speed parameter to generate the compensation control comprises: Adjust trend control according to the change of fan speed parameters to generate compensation control; Wherein, the fan speed parameter includes the current tail exhaust fan speed setting value and the tail exhaust fan speed setting value of the previous control cycle; When the current tail exhaust fan speed setting value is not equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output is zero, and compensation control is generated; When the current tail exhaust fan speed setting value is equal to the tail exhaust fan speed setting value of the previous control cycle, the controller increment output remains unchanged and a compensation control is generated; The specific formula is as follows: Among them, wpzsi is the current tail exhaust fan speed setting value, wpzsi -1 It is the speed setting value of the tail exhaust fan in the previous control cycle.

4. The method according to claim 3, characterized in that: The optimization control is generated according to the key variable parameters of the mill and the preset differential pressure value. include: Among them, the key variable parameters of the mill include tail exhaust fan current, slag bucket lifting current, and mill main machine current; According to the key variable parameters of the mill and the preset differential pressure value, the optimization control is generated, and the specific formula is as follows: Among them, u i is the tail exhaust fan current, uj is the slag bucket lifting current, uk is the main mill current, x is the mill differential pressure setting value, Optimizing the set point for the mill differential pressure optimizes the control output.

5. The method according to claim 1, characterized in that: The real-time data of the mill is obtained include: Wherein, the real-time data includes vibration value and fineness value; Detecting whether the vibration value is greater than a vibration threshold; If the vibration value is less than or equal to the vibration threshold, detecting whether the fineness value is greater than the fineness threshold; If the fineness value is less than or equal to the fineness threshold, a comprehensive control is generated according to the process parameters of the mill.

6. The method according to claim 5, characterized in that The method further comprises: If the vibration value is greater than the vibration threshold, grinding pressure control is performed; If the fineness value is greater than the fineness threshold, fineness control is performed.

7. A small mill optimization control device, characterized in that: The device comprises: A data acquisition module is used to obtain real-time data of the mill; A curve generating module, used for preprocessing the real-time data to generate a trend curve; A trend control module, used for generating trend control according to the changing trend of the trend curve; A compensation control module is used to adjust the trend control according to the change of the fan speed parameter and generate compensation control; A parameter acquisition module, used for acquiring current key variable parameters of the mill according to the compensation control; The optimization control module is used to generate optimization control according to the key variable parameters of the mill and the preset differential pressure value.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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