A high-speed wire drawing machine lubricating oil cooling control method

Abstract

The present invention discloses a method for controlling lubricating oil cooling of a high-speed wire drawing machine, which specifically relates to the technical field of equipment cooling control, and comprises the following steps: by continuously collecting lubricating oil temperature and workload data within a preset sampling time window, dividing the sampling window into a plurality of sub-fluctuation time windows according to load changes, analyzing the cooling response index within each sub-fluctuation time window, and summarizing to form a cooling response data sequence; according to the fluctuation complexity of the data sequence, dividing the equipment state into abnormal fluctuation and normal fluctuation modes; in the abnormal fluctuation mode, analyzing the coolant flow rate and the lubricating oil heat exchange efficiency, inferring the abnormal level, determining whether to replace to a new cooling system and adjusting the sampling duration; by analyzing the fluctuation complexity of the cooling response data sequence, the present invention classifies the operating state of the high-speed wire drawing machine into two modes, namely, normal fluctuation and abnormal fluctuation, and judges whether the cooling level of the cooling system matches the working conditions of the current equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment cooling control, and more specifically, to a high-speed wire drawing machine lubricating oil cooling control method. Background Art

[0002] With the development of industrial automation and manufacturing technology, high-speed wire drawing machines have been widely used in the field of metal processing. However, during the operation of high-speed wire drawing machines, the equipment generates a lot of heat due to continuous high-speed operation. Especially under high load and long-term operation conditions, the lubrication system and cooling system must work effectively to ensure that the equipment is maintained within a reasonable temperature range. If the cooling system does not respond in time or the cooling effect is poor, it may cause the equipment to overheat, thereby affecting production efficiency, shortening the service life of the equipment, and may even cause safety accidents. Moreover, when the equipment load suddenly increases, the existing cooling system cannot respond in time, causing the equipment temperature to rise rapidly, and there is a risk of equipment overheating. The cooling system has a strong lag, and it is impossible to track the temperature changes of the equipment in real time and cannot be effectively adjusted. Therefore, a high-speed wire drawing machine lubricating oil cooling control method is proposed. Summary of the invention

[0003] To achieve the above object, the present invention provides the following technical solutions:

[0004] A high-speed wire drawing machine lubricating oil cooling control method comprises the following steps:

[0005] In a preset sampling time window, the temperature data of the lubricating oil and the workload data of the wire drawing machine are continuously collected, and the preset sampling time window is divided into a plurality of sub-fluctuation time windows according to the workload data of the wire drawing machine;

[0006] The temperature data of the lubricating oil in each sub-fluctuation time window is subjected to response analysis to obtain the cooling response index of the sub-fluctuation time window corresponding to the cooling system currently used by the high-speed wire drawing machine, and then the cooling response data sequence is obtained by summarizing the data.

[0007] According to the fluctuation complexity of the cooling response data sequence, the operating state of the high-speed wire drawing machine in this time window is classified into two modes: abnormal fluctuation and normal fluctuation.

[0008] For the high-speed wire drawing machine in abnormal fluctuation mode, the sub-fluctuation time window corresponding to the cooling response index with the maximum absolute value in the cooling response data sequence is selected, and the feature extraction operation is performed to analyze the changes in the coolant flow rate and the changes in the heat exchange efficiency of the lubricating oil. Then, the abnormal level of the high-speed wire drawing machine in abnormal fluctuation mode is inferred based on the analysis results.

[0009] According to the abnormal level of the high-speed wire drawing machine in the abnormal fluctuation mode and the cooling level corresponding to the cooling system currently used, determine the level of the new cooling system that needs to be replaced, and determine the sampling duration value of the next sampling time window;

[0010] According to the cooling level corresponding to the cooling system currently used by the high-speed wire drawing machine in the normal fluctuation mode, the sampling duration value of the next sampling time window is determined.

[0011] In a preferred embodiment, dividing the preset sampling time window into multiple sub-fluctuation time windows according to the workload data of the wire drawing machine means that: when there is a parameter change in the working parameter group corresponding to the workload data, the current sub-fluctuation time window ends and a new sub-fluctuation time window begins, and the corresponding working parameter group under each sub-fluctuation time window is the same.

[0012] In a preferred embodiment, the temperature data of the lubricating oil in each sub-fluctuation time window is subjected to response analysis, and the cooling response index of the sub-fluctuation time window corresponding to the cooling system currently used by the high-speed wire drawing machine is obtained, which refers to:

[0013] Get the temperature change of the lubricating oil in the target sub-fluctuation time window and mark it as , the change in ambient temperature and marked as , the temperature change caused by the equipment load and marked as , the length of the sampling period corresponding to the time window and marked as , the cooling efficiency of the current cooling system and marked as , and then substitute them into the cooling response index calculation formula:

[0014] ; k1, k2, k3, k4 are all preset adjustment coefficients and are not zero. Represents the cooling response index corresponding to the target sub-fluctuation time window.

[0015] In a preferred embodiment, the cooling efficiency of the current cooling system is The acquisition logic is:

[0016] Get the power consumption of the high-speed wire drawing machine under the current load condition, that is, the target sub-fluctuation time window , power conversion to heat loss coefficient , the quality of the lubricant used Specific heat capacity corresponding to the type of lubricant currently used , cooling efficiency The calculation formula is: .

[0017] In a preferred embodiment, according to the fluctuation complexity of the cooling response data sequence, the operation state of the high-speed wire drawing machine in the time window is classified into two modes: abnormal fluctuation and normal fluctuation. This means:

[0018] The cooling response data sequence is divided into a single positive data set and a single negative data set according to the positive and negative of the cooling response index, and the standard deviations of the single positive data set and the single negative data set are calculated respectively to obtain the single positive fluctuation standard deviation and the single negative fluctuation standard deviation, and then the single positive fluctuation standard deviation is compared with the preset fluctuation threshold one, and the single negative fluctuation standard deviation is compared with the preset fluctuation threshold two. If the single positive fluctuation standard deviation is less than or equal to the preset fluctuation threshold one and the single negative fluctuation standard deviation is less than or equal to the preset fluctuation threshold two, then the operation state of the high-speed wire drawing machine in this time window is the normal fluctuation mode. If the single positive fluctuation standard deviation is less than or equal to the preset fluctuation threshold one and the single negative fluctuation standard deviation is less than or equal to the preset fluctuation threshold two, then the operation state of the high-speed wire drawing machine in this time window is the abnormal fluctuation mode.

[0019] In a preferred embodiment, in the feature extraction operation, the extracted features include coolant flow rate change information and lubricating oil heat exchange efficiency change information, and a coolant flow rate anomaly index is generated after analyzing the coolant flow rate change, and a lubricating oil heat exchange efficiency anomaly index is generated after analyzing the lubricating oil heat exchange efficiency change. Then, fuzzy logic is used to infer the abnormality level of the high-speed wire drawing machine based on the coolant flow rate anomaly index and the lubricating oil heat exchange efficiency anomaly index.

[0020] In a preferred embodiment, the logic for obtaining the coolant flow rate abnormality index is:

[0021] Get the pressure change in the current cooling system , the length of the sampling period corresponding to the time window , Coolant quality , average acceleration of coolant , Temperature variables of high-speed wire drawing machines , and then substitute them into the calculation formula of coolant flow rate abnormality index:

[0022] ; It represents the preset lag time of the cooling system. r1, r2, r3 and r4 are all preset influence coefficients and are not zero. Indicates the coolant flow rate abnormality index.

[0023] In a preferred embodiment, the logic for obtaining the abnormal index of lubricating oil heat exchange efficiency is:

[0024] Capture heat removed by cooling system , heat transfer coefficient of cooling contact surface , cooling surface area , Temperature change of lubricating oil , Coolant temperature difference , Total heat absorbed by lubricating oil , the viscosity of lubricating oil , Average flow rate of lubricating oil , Thermal conductivity of lubricating oil , and substitute them into the calculation formula of the abnormal index of lubricating oil heat exchange efficiency:

[0025] ; w1, w2, w3, w4 are all preset proportional coefficients and are not zero. Indicates the abnormal index of lubricating oil heat exchange efficiency.

[0026] In a preferred embodiment, determining the sampling duration value of the next sampling time window refers to:

[0027] When the high-speed wire drawing machine is in abnormal fluctuation mode, the calculation formula for the sampling duration is:

[0028] ;

[0029] When the high-speed wire drawing machine is in normal fluctuation mode, the calculation formula for the sampling duration is:

[0030] ;

[0031] , are preset adjustment coefficients. Indicates the abnormal level of the high-speed wire drawing machine. Indicates the cooling level corresponding to the cooling system currently used by the high-speed wire drawing machine. Indicates the basic sampling duration, Indicates the sampling duration value of the next sampling time window.

[0032] Technical effects and advantages of the present invention:

[0033] The present invention divides the sampling time window into multiple sub-fluctuation time windows based on the workload data of the equipment. By performing response analysis on the lubricating oil temperature data in each sub-fluctuation time window, the cooling response index of the cooling system is calculated to form a cooling response data sequence. The data sequence can accurately reflect the operating response efficiency of the cooling system in different time periods.

[0034] The present invention classifies the operating status of the high-speed wire drawing machine into two modes: normal fluctuation and abnormal fluctuation, by analyzing the fluctuation complexity of the cooling response data sequence, which helps operation and maintenance personnel identify potential problems and prevent the risk of overheating or damage to the equipment due to insufficient response of the cooling system. For equipment in the abnormal fluctuation mode, the present invention can analyze according to the maximum absolute value of the cooling response index, accurately extract the characteristics of the coolant flow rate and the heat exchange efficiency of the lubricating oil, and infer the abnormal level of the equipment. According to the abnormal level and the cooling level of the current cooling system, the system can intelligently determine whether it is necessary to replace a more efficient cooling system, thereby improving the temperature control efficiency of the equipment and enhancing the responsiveness of the cooling system.

[0035] The present invention can dynamically adjust the duration of the next sampling time window according to the operating status of the equipment (normal fluctuation mode or abnormal fluctuation mode). In the abnormal fluctuation mode, the sampling duration will be shortened to ensure high-frequency monitoring of temperature fluctuations; in the normal fluctuation mode, the sampling duration can be appropriately extended to reduce the monitoring load and achieve efficient resource utilization. By real-time monitoring of equipment parameters such as workload, lubricating oil temperature, and coolant flow rate, the present invention can intelligently determine whether the cooling level of the cooling system matches the working conditions of the current equipment. In the case of insufficient cooling system level, it can promptly prompt to replace it with a more efficient cooling system to ensure that the equipment is always within a suitable operating temperature range. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0037] Figure 1 The schematic diagram is a high-speed wire drawing machine lubricating oil cooling control method in the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] Reference Figure 1 The following examples are obtained:

[0040] Embodiment 1: A high-speed wire drawing machine lubricating oil cooling control method comprises the following steps:

[0041] In the preset sampling time window, the temperature data of the lubricating oil and the workload data of the wire drawing machine are continuously collected, and the preset sampling time window is divided into multiple sub-fluctuation time windows according to the workload data of the wire drawing machine; this step is used to dynamically monitor the operation of the wire drawing machine, especially the temperature changes of the lubricating oil and the workload data, and refine the monitoring granularity by decomposing the time window. The purpose of dividing multiple sub-fluctuation time windows is to more finely capture the details of the temperature and load changes during the operation of the equipment, which helps to more accurately evaluate the cooling effect of the equipment at different time periods.

[0042] The temperature data of the lubricating oil in each sub-fluctuation time window is analyzed for response, and the cooling response index of the sub-fluctuation time window corresponding to the cooling system currently used by the high-speed wire drawing machine is obtained, and then summarized to obtain a cooling response data sequence; by analyzing the temperature change of each sub-fluctuation time window, the cooling response index of the cooling system in this time window is calculated, and the working efficiency of the current cooling system can be quantified. These response indices can be summarized to form a cooling response data sequence, which is further used to analyze the operating stability of the equipment and the performance of the cooling system.

[0043] According to the fluctuation complexity of the cooling response data sequence, the operating status of the high-speed wire drawing machine in this time window is classified into two modes: abnormal fluctuation and normal fluctuation; the fluctuation complexity of the cooling response data sequence reflects the stability of the lubricating oil temperature and equipment load. By analyzing the amplitude and frequency of the fluctuation, it can be determined whether the current working state of the wire drawing machine is stable (normal fluctuation) or unstable (abnormal fluctuation). This classification can help operation and maintenance personnel identify potential problems and take further analysis and repair operations in the abnormal fluctuation mode.

[0044] For high-speed wire drawing machines in abnormal fluctuation mode, the sub-fluctuation time window corresponding to the cooling response index with the maximum absolute value in the cooling response data sequence is selected for feature extraction, and the changes in coolant flow rate and lubricant heat exchange efficiency are analyzed. Then, the abnormal level of the high-speed wire drawing machine in abnormal fluctuation mode is inferred based on the analysis results. In the abnormal fluctuation mode, finding the sub-fluctuation time window corresponding to the most extreme cooling response index can help locate the most serious cooling problem. The feature extraction operation deeply analyzes the coolant flow rate and the heat exchange efficiency of the lubricant to further understand the specific problems of the cooling system. The abnormal level inference provides a basis for the subsequent cooling system replacement decision strategy.

[0045] It should be noted that by selecting the cooling response index with the maximum absolute value, the abnormal fluctuations caused by temperature rise and fall can be covered at the same time. Whether it is a sharp rise in temperature or a sharp drop in temperature caused by overcooling, it can be effectively captured. The absolute maximum value can reflect the most extreme temperature fluctuations in the system. Whether it is a positive value (temperature rise) or a negative value (temperature drop), it can represent the strongest response demand of the cooling system during this period. Abnormal fluctuations may come from two aspects: one is that the system temperature rises too fast and the cooling system does not respond enough; the other is that the system temperature drops too fast and the cooling system cools too much. If you only focus on the positive response index, you may ignore the abnormalities caused by overcooling. Selecting the absolute maximum value can ensure that the most critical problems of the cooling system are captured. Whether the problem is insufficient cooling or overcooling, it can be reflected by the maximum change in the absolute value. At this time, the cooling response index with the maximum value is replaced by the absolute maximum value, which can not only take into account the different situations brought by positive and negative values, but also consider the overall operation performance of the cooling system through a wider range of data.

[0046] According to the abnormal level of the high-speed wire drawing machine in the abnormal fluctuation mode and the cooling level corresponding to the currently used cooling system, determine the level of the new cooling system that needs to be replaced, and determine the sampling duration value of the next sampling time window; when the equipment is in abnormal fluctuation mode, determining the abnormal level of the cooling system helps to determine whether the cooling system needs to be upgraded or adjusted. By replacing a new cooling system that adapts to the abnormal level, the stability of the equipment can be improved. In addition, dynamically adjusting the duration of the next sampling time window can enable more flexible monitoring according to the operating status of the equipment.

[0047] According to the cooling level corresponding to the cooling system currently used by the high-speed wire drawing machine in normal fluctuation mode, the sampling duration value of the next sampling time window is determined. When the equipment is in normal fluctuation mode, it means that the cooling system is relatively stable. In this case, the sampling frequency can be appropriately reduced and the sampling time window can be extended, thereby reducing the load and data processing pressure of the monitoring system and achieving more efficient equipment monitoring.

[0048] Dividing the preset sampling time window into multiple sub-fluctuation time windows according to the workload data of the wire drawing machine means that when there is a parameter change in the working parameter group corresponding to the workload data, the current sub-fluctuation time window ends and a new sub-fluctuation time window begins, and the corresponding working parameter group under each sub-fluctuation time window is the same.

[0049] The workload of high-speed wire drawing machines (such as material drawing speed, tension, etc.) changes dynamically, and the load changes will directly affect the working state and cooling requirements of the equipment. By dividing the sub-fluctuation time window, a new sub-fluctuation time window is restarted every time the workload parameters change, which can ensure that the system response at each load change moment is accurately captured. When the workload changes significantly, if the same sampling time window continues to be used, some key load changes may be ignored. By dynamically dividing the sub-fluctuation time window, ensuring that the workload parameters in each sub-window remain consistent, it helps to capture the key responses of the system in load changes.

[0050] The same working parameter group in each sub-fluctuation time window means that the load conditions of the system's operating state remain stable during this time period. This can eliminate the uncertainty caused by load changes during analysis and more accurately analyze the response behavior of the cooling system under the same load conditions. If the load parameters change frequently and are not distinguished, the analysis results may be affected by complex mixed factors. Using the load change moment as the boundary of the sub-fluctuation window ensures that the working conditions within each sub-window are relatively stable, which helps to simplify the analysis of system behavior.

[0051] The workload parameters of the wire drawing machine are usually directly related to the material drawing speed, tension, motor power, etc. in the production process. By linking the workload data with the sub-fluctuation time window, the operating status of the equipment can be better reflected and abnormal fluctuations can be monitored. When the workload changes, a new sub-fluctuation time window is immediately divided. This can accurately locate the specific moment when the load change occurs, and analyze the temperature, coolant flow rate, etc. of the equipment before and after the load change, to help identify potential anomalies or optimization opportunities. Further dividing a larger sampling time window into multiple sub-fluctuation time windows can effectively reduce the complexity of data processing and make the analysis more targeted. The data in each sub-fluctuation window is easier to process and analyze due to the consistency of conditions.

[0052] The temperature data of the lubricating oil in each sub-fluctuation time window is analyzed, and the cooling response index of the sub-fluctuation time window corresponding to the cooling system currently used by the high-speed wire drawing machine is obtained. It means: the temperature change of the lubricating oil in the target sub-fluctuation time window is obtained and marked as , which reflects the temperature fluctuation of the lubricating oil within the sub-fluctuation time window, is the core variable that needs to be adjusted in the cooling system and directly affects the workload of the cooling system; the ambient temperature change is marked as ,The fluctuation of ambient temperature has a direct impact on the efficiency of the cooling system. A higher ambient temperature may increase the burden of the cooling system, conversely, a lower ambient temperature may reduce the system load; the temperature variation caused by the equipment load is marked as , when the device load increases, the heat generated increases, and stronger cooling is required to cope with the temperature rise. This parameter reflects the impact of device load on cooling requirements. The length of the sampling period corresponding to the time window is marked as , is the time span of the evaluation time window, ensuring that the cooling system can respond to different load and temperature changes under fluctuations in different time periods. The cooling efficiency of the current cooling system is marked as , reflects the efficiency of the cooling system in this time window, taking into account the coolant flow rate of the cooling system, the heat exchange capacity of the lubricating oil, etc. If the cooling system works efficiently, then Larger, otherwise smaller.

[0053] Then substitute them into the cooling response index calculation formula: ; k1, k2, k3, k4 are all preset adjustment coefficients and are not zero. Represents the cooling response index corresponding to the target sub-fluctuation time window.

[0054] The lubricating oil temperature change, ambient temperature change, temperature change caused by equipment load and the adjustment capacity of the cooling system are comprehensively considered. By introducing factors such as weighting and time length, the response performance analysis of the cooling system is more comprehensive and accurate. The formula combines multiple key factors (such as lubricating oil temperature, ambient temperature, equipment load, etc.) to comprehensively evaluate the performance of the cooling system under different working conditions. Through different weight coefficients, the impact of each factor on the cooling response index can be flexibly adjusted and optimized according to specific system requirements. The introduction of the time window length allows the evaluation to adjust the response index according to the length of the time period to ensure the dynamic nature of the evaluation results.

[0055] It should be noted that the following considerations are made in the cooling response index process corresponding to the target sub-fluctuation time window:

[0056] If the sign of the temperature change has a physical impact on the regulation of the system, retain the direction of the temperature change. If you only care about the magnitude of the temperature change and not its direction, you can add an absolute value. In a cooling system, rising and falling temperatures often have different effects on the regulation of cooling demand. For example, a rise in lubricating oil temperature will increase cooling demand; a drop in ambient temperature may reduce cooling demand. If an absolute value is added, it will not be possible to distinguish the positive and negative directions of these changes, and only the magnitude of the temperature change can be seen, which may mask the true response of the system to the temperature change. The responsiveness of the cooling system depends not only on the magnitude of the change, but also on the direction of the temperature change (i.e., whether it is heating up or cooling down). Similarly, the demand for cooling is different when the equipment load increases or decreases. If you do not add an absolute value, you can directly evaluate the different effects of increasing or decreasing load on the cooling system. If you use an absolute value, you cannot distinguish between load increases and load decreases. Therefore, in order to more accurately evaluate the responsiveness of the cooling system and fully consider the different effects of the direction of temperature and load changes on the system, keep the positive and negative signs of temperature and load changes in order to more clearly reflect the response characteristics of the system under different operating conditions.

[0057] A positive response index indicates that the lubricating oil temperature has risen significantly, and the cooling system may need to respond more actively to reduce the temperature relative to changes in ambient temperature and equipment load. This usually means that the temperature has risen and the system needs to increase cooling. A negative response index indicates that the lubricating oil temperature has dropped significantly, or the equipment load has decreased significantly, and the response demand of the cooling system has decreased relative to changes in ambient temperature. This usually reflects that the cooling system does not require significant intervention, and may even need to reduce the cooling intensity to avoid overcooling. Even without adding an absolute value, the responsiveness of the cooling system can still be judged by the size of the response index: A large response index indicates that the system is facing large temperature fluctuations (increases or decreases), whether positive or negative. A positive number indicates that cooling needs to be strengthened, and a negative number indicates that the cooling demand has decreased or there may be overcooling. A response index close to zero indicates that the system is in a stable state, the temperature changes are small, and the cooling system may not need to make major adjustments.

[0058] The cooling efficiency of the current cooling system The acquisition logic is:

[0059] Get the power consumption of the high-speed wire drawing machine under the current load condition, that is, the target sub-fluctuation time window , power conversion to heat loss coefficient , the quality of the lubricant used Specific heat capacity corresponding to the type of lubricant currently used , cooling efficiency The calculation formula is: . Indicates the power consumption of the high-speed wire drawing machine under the current load conditions. It is the total power consumed by the equipment and is used to measure the heat generated when the equipment is working. The mass of the lubricating oil is used to calculate the cooling efficiency of the cooling system in the lubricating oil. The specific heat capacity of the lubricating oil indicates the heat required for the lubricating oil to increase or decrease by one degree per unit mass. This formula is based on the energy balance principle of thermodynamics and is designed to calculate how the cooling system converts the power consumption PH of the equipment into heat in the lubricating oil and dissipates heat through cooling. Power consumption is the main source of heat generated by the equipment during operation, while the mass and specific heat capacity of the lubricating oil determine the ability of the lubricating oil to absorb or dissipate heat. The power consumption reflects the heat generated by the equipment: it represents the power consumption of the equipment under the current load conditions. The power consumed by the equipment is converted into heat and taken away by the cooling system. This power consumption is the heat load that the cooling system needs to cope with, so it is the core variable in the formula. The power consumption multiplied by the mass of the lubricating oil reflects the heat absorption capacity of the lubricating oil, that is, how much heat the lubricating oil can absorb per unit time and dissipate heat through cooling.

[0060] The quality of the lubricant directly affects the ability of the cooling system. More lubricant means more heat can be absorbed, increasing the cooling system's ability to dissipate heat. The specific heat capacity of the lubricant refers to the amount of heat required to raise or lower the temperature by one degree. The greater the specific heat capacity, the more heat the lubricant can absorb with less temperature change, indicating a higher cooling efficiency. This formula measures the overall efficiency of the cooling system by comparing the power consumption generated by the equipment to the heat absorption capacity of the lubricant. The higher the PL value, the more effectively the cooling system can convert the power consumption into heat in the lubricant and dissipate it.

[0061] According to the fluctuation complexity of the cooling response data sequence, the operating state of the high-speed wire drawing machine in this time window is classified into two modes: abnormal fluctuation and normal fluctuation.

[0062] The cooling response data sequence is divided into a single positive data set and a single negative data set according to the positive and negative of the cooling response index, and the standard deviations of the single positive data set and the single negative data set are calculated respectively to obtain the single positive fluctuation standard deviation and the single negative fluctuation standard deviation, and then the single positive fluctuation standard deviation is compared with the preset fluctuation threshold one, and the single negative fluctuation standard deviation is compared with the preset fluctuation threshold two. If the single positive fluctuation standard deviation is less than or equal to the preset fluctuation threshold one and the single negative fluctuation standard deviation is less than or equal to the preset fluctuation threshold two, then the operation state of the high-speed wire drawing machine in this time window is the normal fluctuation mode. If the single positive fluctuation standard deviation is less than or equal to the preset fluctuation threshold one and the single negative fluctuation standard deviation is less than or equal to the preset fluctuation threshold two, then the operation state of the high-speed wire drawing machine in this time window is the abnormal fluctuation mode.

[0063] Positive response index: usually indicates that the system temperature rises, the cooling demand increases, and the cooling system needs to work more actively to reduce the temperature. This type of data reflects the active response needs of the cooling system. Negative response index: usually indicates that the system temperature drops, which may be overcooling or the equipment load decreases, and the cooling demand decreases. Negative data reflects the situation of overcooling or unnecessary cooling of the system. In actual operation, positive and negative responses may indicate different fluctuation reasons and system requirements, so considering positive and negative data types separately can help to more clearly understand the cooling behavior of the system.

[0064] Complexity of positive fluctuations: High positive fluctuations mean that the temperature of the system fluctuates violently, and the cooling system must constantly increase its work to keep the temperature stable. This situation requires careful analysis to determine whether it is caused by equipment load, ambient temperature changes, or other reasons. Complexity of negative fluctuations: High negative fluctuations may mean that the cooling system is overworking within a specific period of time, causing the system temperature to drop sharply. This may be a sign that the cooling system is not sensitive enough or is not adjusted in time, and the cooling intensity may need to be reduced. The analysis of fluctuation complexity can be considered separately through the complexity of both the positive fluctuation sequence and the negative fluctuation sequence to determine the different states of the system. This helps to more accurately distinguish whether the system has problems caused by insufficient cooling or excessive cooling.

[0065] If positive and negative data are directly mixed for fluctuation complexity analysis, important details may be obscured. For example: high positive fluctuations and high negative fluctuations exist at the same time: the cooling system may be adjusting frequently, resulting in unstable temperature control. If positive and negative fluctuations are not distinguished, this situation may be regarded as normal fluctuations, but in fact there is a hidden danger of unstable regulation. Single positive or negative fluctuations are dominant: If only positive or negative fluctuations are large, the root cause of the system problem will be different. Large positive fluctuations may indicate insufficient cooling, while large negative fluctuations may indicate excessive cooling or large changes in equipment load.

[0066] By considering positive and negative fluctuations separately, abnormal fluctuations can be identified more effectively. For example, high positive complexity may mean that the cooling system is not responding enough when the equipment is operating in a high temperature environment, while high negative complexity may mean that the system is overcooled and the temperature drops significantly.

[0067] In the feature extraction operation, the extracted features include the coolant flow rate change information and the lubricating oil heat exchange efficiency change information. After analyzing the coolant flow rate change, a coolant flow rate anomaly index is generated. After analyzing the lubricating oil heat exchange efficiency change, a lubricating oil heat exchange efficiency anomaly index is generated. Then, fuzzy logic is used to infer the anomaly level of the high-speed wire drawing machine based on the coolant flow rate anomaly index and the lubricating oil heat exchange efficiency anomaly index.

[0068] The coolant flow rate abnormality index and the lubricant heat exchange efficiency abnormality index are defined as fuzzy variables, and their values ​​are divided into different fuzzy sets. In general, these abnormality indices can be divided into three levels: low, medium, and high. For example: the coolant flow rate abnormality index can be expressed as abnormally low flow rate, abnormally medium flow rate, and abnormally high flow rate. The lubricant heat exchange efficiency abnormality index can be expressed as abnormally low heat exchange, abnormally medium heat exchange, and abnormally high heat exchange. Fuzzy rules are used to define the relationship between the coolant flow rate abnormality index and the lubricant heat exchange efficiency abnormality index, as well as their impact on the abnormality level of the high-speed wire drawing machine. It can be described by the following rules: If the coolant flow rate is abnormally low and the lubricant heat exchange is abnormally low, the abnormality level of the equipment is low. If the coolant flow rate is abnormally high and the lubricant heat exchange is abnormally high, the abnormality level of the equipment is high. If the coolant flow rate is abnormally medium and the lubricant heat exchange is abnormally medium, the abnormality level of the equipment is medium. If the coolant flow rate is abnormally high but the lubricant heat exchange is abnormally low, the abnormality level of the equipment can be medium or high, depending on the situation. If the coolant flow rate is abnormally low, but the lubricant heat exchange is abnormally high, the abnormal level of the equipment can be medium or high, depending on the situation. Through these rules, the fuzzy logic system can handle abnormal indexes under different combinations and infer the abnormal level of the equipment. The specific values ​​of the coolant flow rate abnormal index and the lubricant heat exchange efficiency abnormal index are input into the fuzzy logic system. The fuzzy reasoning process is carried out through the following steps: the coolant flow rate abnormal index and the lubricant heat exchange efficiency abnormal index are converted into fuzzy sets. For example, if the coolant flow rate abnormal index is a specific value, it can be partially attributed to the three fuzzy sets of low, medium and high, and the degree of attribution is determined according to its value. According to the fuzzy rules, the system will calculate the input fuzzy sets to determine the possible abnormal levels under these input conditions. Through the defuzzification process, the result of fuzzy reasoning is converted into a specific abnormal level. This abnormal level can be a specific value among low, medium and high, representing the abnormal degree of the equipment. After fuzzy reasoning and defuzzification, an abnormal level will be output to indicate the abnormal degree of the high-speed wire drawing machine under the current working conditions.

[0069] The logic for obtaining the coolant flow rate abnormality index is:

[0070] Get the pressure change in the current cooling system , which is the main driving force of the coolant flow rate. The greater the pressure change, the more likely the coolant flow rate will fluctuate, so it has a greater impact on the coolant flow rate abnormality. The length of the sampling time period corresponding to the time window , indicating the influence of pressure changes and other parameters during this time period. The longer the time, the greater the fluctuation of flow rate may be, so the degree of flow rate abnormality should be measured by time. Coolant quality The greater the mass of the coolant, the smaller the fluctuations in flow rate are likely to be, because a fluid with a larger mass is less susceptible to pressure changes. The average acceleration of the coolant The greater the average acceleration, the higher the possibility of abnormal flow rate. Therefore, the average acceleration of the coolant is also an important factor affecting the abnormal coolant flow rate index. The more drastic the equipment temperature change is, the higher the cooling demand is, which may cause the coolant flow rate to fluctuate. Therefore, the equipment temperature change is also a key factor affecting the flow rate abnormality. Then substitute them into the coolant flow rate abnormality index calculation formula:

[0071] ; Represents the preset lag time of the cooling system, reflecting the reaction speed of the cooling system in the face of temperature changes and cooling needs. The larger the lag time, the slower the cooling system, and the less timely the flow rate adjustment may be, which may lead to abnormal flow rate. r1, r2, r3, and r4 are all preset influence coefficients and are not zero. They are used to adjust the influence of various factors on the coolant flow rate abnormality index. By adjusting these coefficients, the weight of certain factors can be increased or decreased according to the actual system situation to optimize the calculation results of the flow rate abnormality index. The formula calculates the abnormality of the coolant flow rate by comprehensively considering key factors such as the pressure change of the cooling system, the acceleration of the coolant, and the temperature change of the equipment. Each parameter reflects a different aspect of the coolant flow. The pressure change is the main driving force of the flow rate, the quality and acceleration of the coolant affect the flow of the fluid, and the temperature change of the equipment affects the cooling demand. By combining these factors, the formula can evaluate whether the coolant flow rate is significantly different from the expected flow rate under normal operating conditions. Indicates the coolant flow rate abnormality index. The larger the coolant flow rate abnormality index, the greater the deviation between the coolant flow rate and the system expected value, and the more drastic the flow rate fluctuation. This usually indicates that the cooling system has a problem when adjusting the coolant flow rate, and may not be able to respond to changes in equipment load, temperature, etc. in a timely manner.

[0072] The logic for obtaining the abnormal index of lubricating oil heat exchange efficiency is as follows:

[0073] Capture heat removed by cooling system , is the total amount of heat removed by the cooling system through heat exchange, reflecting the actual cooling effect of the system. The more heat removed by the cooling system, the stronger the cooling capacity of the system, but if too little heat is removed, it means that the cooling efficiency is low. The heat transfer coefficient of the cooling contact surface , which indicates the heat transfer capacity of the lubricant and coolant when they are in contact. The higher the heat transfer coefficient, the faster the heat can be transferred from the lubricant to the coolant. If the heat transfer coefficient is low, the heat may not be transferred in time, affecting the cooling effect. The area of ​​the cooling surface The larger the contact area between the lubricant and the coolant, the higher the efficiency of heat exchange. A larger contact area can speed up heat transfer and help the lubricant cool down quickly. , which indicates the temperature change of the lubricating oil in a period of time. The greater the temperature change, the greater the cooling demand. If the lubricating oil temperature fails to drop in time, it may mean that the heat exchange efficiency is poor. The temperature difference of the coolant reflects its heat dissipation capacity. When the coolant temperature is low, it can absorb more heat; when the coolant temperature is high, it may limit the heat dissipation efficiency of the lubricant. The total heat absorbed by the lubricant , which is the total amount of heat absorbed by the lubricant during operation, and is usually related to the equipment workload. The greater the total heat, the greater the burden on the cooling system. The viscosity of the lubricating oil affects its fluidity, thus affecting the efficiency of heat transfer. When the viscosity is high, the flow rate of the lubricating oil slows down, which may lead to a decrease in heat transfer efficiency. The average flow rate of the lubricating oil The faster the average flow rate of the lubricating oil, the faster it can transfer heat. If the average flow rate is slower, the heat may not be transferred from the lubricating oil to the coolant in time. The thermal conductivity of the lubricating oil , is the ability of lubricating oil to transfer heat. The greater the thermal conductivity, the better the lubricating oil performs in the heat exchange process and the higher the cooling efficiency. Substitute them into the calculation formula of the abnormal index of lubricating oil heat exchange efficiency:

[0074] ; w1, w2, w3, and w4 are all preset proportional coefficients and are not zero. They are used to adjust the influence weight of each variable on the abnormal index of lubricating oil heat exchange efficiency, ensuring that the influence of different factors in the formula can be adjusted according to specific circumstances. Indicates the abnormal index of lubricating oil heat exchange efficiency. The abnormal index of lubricating oil heat exchange efficiency is used to evaluate the abnormality of the cooling system when exchanging heat between lubricating oil and coolant. By calculating this index, it can be determined whether the cooling system effectively transfers the heat generated by the equipment to the coolant during operation, thereby maintaining the temperature stability of the equipment. The higher the index, the greater the deviation of the heat exchange effect between the lubricating oil and the coolant from the expected one, which may mean poor cooling efficiency or other problems.

[0075] Determining the sampling duration value of the next sampling time window means: when the high-speed wire drawing machine is in abnormal fluctuation mode, the sampling duration value calculation formula is: ; When the high-speed wire drawing machine is in normal fluctuation mode, the calculation formula for the sampling duration value is: ; , are preset adjustment coefficients. The abnormality level of the high-speed wire drawing machine is used to measure the current abnormality of the equipment. The higher the abnormality level, the more serious the system fluctuation is, and the sampling time needs to be shortened accordingly to speed up the sampling frequency. Indicates the cooling level corresponding to the cooling system currently used by the high-speed wire drawing machine. Indicates the basic sampling duration, which indicates the default sampling interval when there are no special circumstances. Represents the sampling duration value of the next sampling time window. The purpose is to dynamically adjust the sampling time according to the current working mode of the high-speed wire drawing machine (abnormal fluctuation mode or normal fluctuation mode). The adjustment of the sampling duration enables the present invention to flexibly respond to different working conditions, not only to obtain data in time when the equipment fluctuates abnormally, but also to reduce the sampling frequency and save resources during normal operation. By adjusting the sampling duration, the state changes of the high-speed wire drawing machine can be effectively monitored to avoid frequent sampling interference or data lag caused by too sparse sampling. At the same time, this adjustment can ensure that in abnormal situations, the cooling system and equipment status can be quickly detected and processed.

[0076] The abnormality level is an indicator used to measure the degree of fluctuation in the working state of the high-speed wire drawing machine. The higher the abnormality level, the more severe the fluctuation of the equipment and the greater the temperature fluctuation, which means that the heat generated by the equipment is difficult to be quickly removed by the cooling system. This is usually caused by excessive equipment workload, failure of the lubrication system, or insufficient response of the cooling system. The abnormality level is used to determine whether the existing cooling system can meet the cooling needs of the current equipment. If the abnormality level is very high and the existing cooling system cannot effectively cope with it, then it is necessary to consider replacing a more efficient cooling system to ensure the normal operation of the equipment and prevent the equipment from overheating or failure.

[0077] The cooling level is an assessment of the cooling system's capabilities, indicating its responsiveness to parameters such as coolant flow rate and heat exchange efficiency. The higher the cooling level, the faster and more efficiently the cooling system can handle the heat generated by the equipment and keep the equipment temperature stable. The cooling level directly determines the cooling system's ability to cope with the heat generated by the equipment when it is working. The cooling level of the current cooling system indicates its ability to handle the specific heat load generated by the equipment. When the equipment load or temperature fluctuations intensify, a low-level cooling system may not be able to meet the needs, and it is necessary to replace it with a higher-level cooling system.

[0078] The level of cooling system replacement is usually based on the following factors: Severity of the abnormality level: If the abnormality level is high, it means that the current equipment load and temperature fluctuations are large, and the existing cooling system may not be sufficient to cope with this situation. The cooling level of the current cooling system: If the cooling level is low and the abnormality level is high, you may need to replace it with a more efficient cooling system. The preset strategy for changing to a new cooling system is as follows: If the abnormality level is high and the current cooling level is low, you should change to a higher level or even two levels of cooling system to ensure that the cooling effect can meet the operating needs of the equipment. If the abnormality level is medium or low, and the cooling system level is high enough, there is no need to replace it and continue to use the current cooling system. When the abnormality level increases significantly and the current cooling system cannot quickly reduce the temperature or responds insufficiently, it is necessary to select a cooling system with a higher cooling level to enhance the cooling effect and quickly adjust the temperature of the equipment. This means that a higher cooling level has a faster coolant circulation speed and a more efficient heat exchange system that can quickly handle the heat fluctuations generated by the equipment to prevent the equipment from overheating.

[0079] Matching of cooling level and abnormality level: The higher the cooling level, the faster the cooling system can adjust the coolant flow rate and the temperature of the lubricating oil to ensure that the equipment operates within a stable temperature range. Therefore, when the abnormality level is higher, a higher level cooling system is required to cope with the heat load caused by equipment fluctuations. Replacement basis: The replacement cooling system level usually needs to meet the following conditions: When the abnormality level reaches a medium or high level, a cooling level one level higher than the current cooling system should be selected. When the abnormality level reaches a very high level, a cooling level two levels higher than the current system should be selected. Example of changing the cooling system level: For example, the current cooling system is a two-level cooling system, and the abnormality level of the equipment reaches a high level (for example, level 3), then it should be replaced with a three-level or four-level cooling system to ensure that the system has sufficient cooling capacity.

[0080] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0081] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0082] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0083] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0084] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A high-speed wire drawing machine lubricating oil cooling control method, characterized in that: The following steps are involved: In a preset sampling time window, the temperature data of the lubricating oil and the workload data of the wire drawing machine are continuously collected, and the preset sampling time window is divided into a plurality of sub-fluctuation time windows according to the workload data of the wire drawing machine; The temperature data of the lubricating oil in each sub-fluctuation time window is subjected to response analysis to obtain the cooling response index of the sub-fluctuation time window corresponding to the cooling system currently used by the high-speed wire drawing machine, and then the cooling response data sequence is obtained by summarizing the data. According to the fluctuation complexity of the cooling response data sequence, the operation status of the high-speed wire drawing machine in the time window corresponding to the cooling response data sequence is classified into two modes: abnormal fluctuation and normal fluctuation. For the high-speed wire drawing machine in abnormal fluctuation mode, the sub-fluctuation time window corresponding to the cooling response index with the maximum absolute value in the cooling response data sequence is selected, and the feature extraction operation is performed to analyze the changes in the coolant flow rate and the changes in the heat exchange efficiency of the lubricating oil. Then, the abnormal level of the high-speed wire drawing machine in abnormal fluctuation mode is inferred based on the analysis results. According to the abnormal level of the high-speed wire drawing machine in the abnormal fluctuation mode and the cooling level corresponding to the cooling system currently used, determine the level of the new cooling system that needs to be replaced, and determine the sampling duration value of the next sampling time window; Determine the sampling duration value of the next sampling time window according to the cooling level corresponding to the cooling system currently used by the high-speed wire drawing machine in the normal fluctuation mode; Dividing the preset sampling time window into a plurality of sub-fluctuation time windows according to the workload data of the wire drawing machine means that when there is a parameter change in the working parameter group corresponding to the workload data, the current sub-fluctuation time window ends and a new sub-fluctuation time window begins, and the working parameter group corresponding to each sub-fluctuation time window is the same; The temperature data of the lubricating oil in each sub-fluctuation time window is analyzed for response, and the cooling response index of the sub-fluctuation time window corresponding to the cooling system currently used in the high-speed wire drawing machine is: Get the temperature change of the lubricating oil in the target sub-fluctuation time window and mark it as , the change in ambient temperature and marked as , the temperature change caused by the equipment load and marked as , the length of the sampling period corresponding to the time window and marked as , the cooling efficiency of the current cooling system and marked as , and then substitute them into the cooling response index calculation formula: ; k1, k2, k3, k4 are all preset adjustment coefficients and are not zero. Represents the cooling response index corresponding to the target sub-fluctuation time window.

2. A high-speed wire drawing machine lubricating oil cooling control method according to claim 1, characterized in that: The cooling efficiency of the current cooling system The acquisition logic is: Get the power consumption of the high-speed wire drawing machine under the current load condition, that is, the target sub-fluctuation time window , power conversion to heat loss coefficient , the quality of the lubricant used Specific heat capacity corresponding to the type of lubricant currently used , cooling efficiency The calculation formula is: .

3. A high-speed wire drawing machine lubricating oil cooling control method according to claim 2, characterized in that: According to the fluctuation complexity of the cooling response data sequence, the operating state of the high-speed wire drawing machine in this time window is classified into two modes: abnormal fluctuation and normal fluctuation. The cooling response data sequence is divided into a single positive data set and a single negative data set according to the positive and negative of the cooling response index, and the standard deviations of the single positive data set and the single negative data set are calculated respectively to obtain the single positive fluctuation standard deviation and the single negative fluctuation standard deviation, and then the single positive fluctuation standard deviation is compared with the preset fluctuation threshold one, and the single negative fluctuation standard deviation is compared with the preset fluctuation threshold two. If the single positive fluctuation standard deviation is less than or equal to the preset fluctuation threshold one and the single negative fluctuation standard deviation is less than or equal to the preset fluctuation threshold two, then the operation state of the high-speed wire drawing machine in this time window is the normal fluctuation mode. If the single positive fluctuation standard deviation is less than or equal to the preset fluctuation threshold one and the single negative fluctuation standard deviation is less than or equal to the preset fluctuation threshold two, then the operation state of the high-speed wire drawing machine in this time window is the abnormal fluctuation mode.

4. A high-speed wire drawing machine lubricating oil cooling control method according to claim 3, characterized in that: In the feature extraction operation, the extracted features include the coolant flow rate change information and the lubricating oil heat exchange efficiency change information. After analyzing the coolant flow rate change, a coolant flow rate anomaly index is generated. After analyzing the lubricating oil heat exchange efficiency change, a lubricating oil heat exchange efficiency anomaly index is generated. Then, fuzzy logic is used to infer the anomaly level of the high-speed wire drawing machine based on the coolant flow rate anomaly index and the lubricating oil heat exchange efficiency anomaly index.

5. A high-speed wire drawing machine lubricating oil cooling control method according to claim 4, characterized in that: The logic for obtaining the coolant flow rate abnormality index is: Get the pressure change in the current cooling system , the length of the sampling period corresponding to the time window , Coolant quality , average acceleration of coolant , Temperature variables of high-speed wire drawing machines , and then substitute them into the calculation formula of coolant flow rate abnormality index: ; It represents the preset lag time of the cooling system. r1, r2, r3 and r4 are all preset influence coefficients and are not zero. Indicates the coolant flow rate abnormality index.

6. A high-speed wire drawing machine lubricating oil cooling control method according to claim 5, characterized in that: The logic for obtaining the abnormal index of lubricating oil heat exchange efficiency is as follows: Capture heat removed by cooling system , heat transfer coefficient of cooling contact surface , cooling surface area , Temperature change of lubricating oil , Coolant temperature difference , Total heat absorbed by lubricating oil , the viscosity of lubricating oil , Average flow rate of lubricating oil , Thermal conductivity of lubricating oil , and substitute them into the calculation formula of the abnormal index of lubricating oil heat exchange efficiency: ； w1, w2, w3, w4 are all preset proportional coefficients and are not zero. Indicates the abnormal index of lubricating oil heat exchange efficiency.

7. A high-speed wire drawing machine lubricating oil cooling control method according to claim 6, characterized in that: Determining the sampling duration value of the next sampling time window refers to: When the high-speed wire drawing machine is in abnormal fluctuation mode, the calculation formula for the sampling duration is: ； When the high-speed wire drawing machine is in normal fluctuation mode, the calculation formula for the sampling duration is: ; , are preset adjustment coefficients. Indicates the abnormal level of high-speed wire drawing machine, Indicates the cooling level corresponding to the cooling system currently used by the high-speed wire drawing machine. Indicates the basic sampling duration, Indicates the sampling duration value of the next sampling time window.

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