Fault detection method, system and equipment for wire drawing machine

Abstract

The invention is suitable for the technical field of wire drawing machine detection, and particularly relates to a wire drawing machine fault detection method, system and equipment. Wherein the product defect information comprises defect items and occurrence frequency of the product subjected to wire drawing by the wire drawing machine; analyzing according to the defect items to obtain fault component information of the wire drawing machine; wherein the fault part information of the wire drawing machine is used for reflecting a fault part; and analyzing according to the occurrence frequency and the fault component information of the wire drawing machine to obtain the fault reason of the wire drawing machine. According to the method, the component with the fault can be quickly positioned through the specific product poor quality information, and the specific reason of the fault is further determined, so that the accuracy and efficiency of fault diagnosis are remarkably improved, the maintenance strategy is optimized, and the maintenance efficiency is improved.

Description

Technical Field

[0001] The present application belongs to the field of wire drawing machine detection technology, and in particular, relates to a wire drawing machine fault detection method, system and equipment. Background Art

[0002] In the metal wire processing industry, wire drawing machines are key equipment used to draw raw materials into wires of the required diameter. However, wire drawing machines may experience various faults during long-term operation, such as wire breakage, inconsistent sizes, surface scratches, and other problems. These problems not only affect product quality, but also lead to reduced production efficiency and increased production costs.

[0003] Traditional wire drawing machine fault detection often relies on manual experience for troubleshooting, which is time-consuming and inaccurate, making it difficult to detect and resolve equipment failures in a timely and effective manner. Summary of the invention

[0004] The embodiments of the present application provide a wire drawing machine fault detection method, system and device, which can solve the problem that traditional wire drawing machine fault detection often relies on manual experience for troubleshooting, which is time-consuming and inaccurate, and it is difficult to discover and solve equipment failures in a timely and effective manner.

[0005] In a first aspect, an embodiment of the present application provides a wire drawing machine fault detection method, comprising:

[0006] Obtaining product defect information; wherein the product defect information includes defect items and occurrence frequency of the product after being drawn by the wire drawing machine;

[0007] Analyze the defect items to obtain the wire drawing machine fault component information; wherein the wire drawing machine fault component information is used to reflect the faulty component;

[0008] The cause of the wire drawing machine failure is obtained by analyzing the occurrence frequency and the information of the wire drawing machine failure components.

[0009] The above technical solutions in the embodiments of the present application have at least the following technical effects:

[0010] The wire drawing machine fault detection method provided in the present application obtains product defect information including defect items and occurrence frequency of products after wire drawing by the wire drawing machine; then analyzes according to the defect items to obtain wire drawing machine fault component information used to reflect the faulty components; and then analyzes according to the occurrence frequency and wire drawing machine fault component information to obtain the cause of wire drawing machine failure. The method can quickly locate the faulty components through the specific information of poor product quality, and further determine the specific cause of the fault, thereby significantly improving the accuracy and efficiency of fault diagnosis, optimizing maintenance strategies, and thus improving maintenance efficiency.

[0011] In a possible implementation of the first aspect, analyzing according to the defect items to obtain the faulty component information of the wire drawing machine includes:

[0012] Analyze the defect items to obtain defect types; wherein the defect types include size type and appearance type;

[0013] Analyze according to the defect type to obtain component group information; wherein the component group information is used to reflect at least one component that may fail;

[0014] The component group information is analyzed to obtain the faulty component information of the wire drawing machine.

[0015] In a possible implementation manner of the first aspect, analyzing according to the component group information to obtain the faulty component information of the wire drawing machine includes:

[0016] Acquire maintenance information of each component in the component group information; wherein the maintenance information is used to reflect the repair and replacement records of each component;

[0017] Analyze the maintenance information to obtain the fault occurrence value of each component; wherein the fault occurrence value is used to reflect the probability of component failure;

[0018] The fault component information of the wire drawing machine is obtained by analyzing the multiple fault occurrence values.

[0019] In a possible implementation manner of the first aspect, the analyzing according to the maintenance information to obtain the fault occurrence value of each component includes:

[0020] Analyze the maintenance information to obtain a replacement factor, wherein the replacement factor is used to reflect the length of time since the last replacement of the component;

[0021] Analyze the maintenance information to obtain maintenance frequency; wherein the maintenance frequency is used to reflect the number and interval of component repair and replacement;

[0022] An analysis is performed based on the replacement factor and the maintenance frequency to obtain a failure occurrence value of each component.

[0023] In a possible implementation manner of the first aspect, the analyzing according to the replacement factor and the maintenance frequency to obtain the failure occurrence value of each component includes:

[0024] Obtaining a replacement weight of the replacement factor and a frequency weight of the maintenance frequency;

[0025] The replacement weight is weighted for the replacement factor, the frequency weight is weighted for the maintenance frequency, and the sum is calculated to obtain the failure occurrence value of each component.

[0026] In a possible implementation of the first aspect, the analyzing according to the multiple fault occurrence values ​​to obtain the fault component information of the wire drawing machine includes:

[0027] Sorting the plurality of fault occurrence values ​​to obtain a first order digit and a second order digit;

[0028] Calculate the difference between the first sequence bit and the second sequence bit to obtain a fault difference value;

[0029] The fault difference value is analyzed to obtain the fault component information of the wire drawing machine.

[0030] In a possible implementation manner of the first aspect, the analyzing according to the fault difference value to obtain the fault component information of the wire drawing machine includes:

[0031] Compare the fault difference value with a preset difference value, and when the fault difference value is greater than or equal to the preset difference value, determine the component corresponding to the first sequence position as the fault component information of the wire drawing machine;

[0032] When the fault difference value is less than the preset difference value, the replacement factor corresponding to the first sequence bit and the replacement factor corresponding to the second sequence bit are compared, and the first sequence bit or the second sequence bit corresponding to the larger replacement factor is determined as the faulty component information of the wire drawing machine.

[0033] In a possible implementation of the first aspect, analyzing according to the occurrence frequency and the information of the faulty component of the wire drawing machine to obtain the fault cause of the wire drawing machine includes:

[0034] Analyze the faulty component information of the wire drawing machine to obtain a fault set; wherein the fault set includes all possible fault problems of the faulty component information of the wire drawing machine;

[0035] The correlation value between the occurrence frequency and the fault set is calculated, and the fault problem corresponding to the largest correlation value is determined as the cause of the wire drawing machine fault.

[0036] In a second aspect, an embodiment of the present application provides a wire drawing machine fault detection system, comprising:

[0037] An acquisition module, used to acquire product defect information; wherein the product defect information includes defect items and occurrence frequency of the product after being drawn by the wire drawing machine;

[0038] A first analysis module is used to analyze the defect items to obtain the wire drawing machine fault component information; wherein the wire drawing machine fault component information is used to reflect the faulty component;

[0039] The second analysis module is used to analyze the occurrence frequency and the information of the faulty parts of the wire drawing machine to obtain the cause of the wire drawing machine failure.

[0040] In a third aspect, an embodiment of the present application provides a wire drawing machine fault detection device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any one of the methods described in the first aspect when executing the computer program.

[0041] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of the above-mentioned first aspects is implemented.

[0042] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product runs on a wire drawing machine fault detection device, the wire drawing machine fault detection device enables the wire drawing machine fault detection device to execute the wire drawing machine fault detection method described in any one of the above-mentioned first aspects.

[0043] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 It is a flow chart of a wire drawing machine fault detection method provided in an embodiment of the present application;

[0046] Figure 2 It is a schematic diagram of the process structure of the wire drawing machine fault detection method provided in the embodiment of the present application;

[0047] Figure 3 It is a structural schematic diagram of a wire drawing machine fault detection system provided in an embodiment of the present application;

[0048] Figure 4 It is a structural schematic diagram of a wire drawing machine fault detection device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0050] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0051] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0052] As used in the specification of this application and the appended claims, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting" depending on the context. Similarly, the phrase "if it is determined" or "if the described condition or event is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce the described condition or event is detected" or "in response to detecting the described condition or event" depending on the context.

[0053] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0054] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0055] In the metal wire processing industry, wire drawing machines are key equipment used to draw raw materials into wires of the required diameter. However, wire drawing machines may experience various faults during long-term operation, such as wire breakage, inconsistent sizes, surface scratches, and other problems. These problems not only affect product quality, but also lead to reduced production efficiency and increased production costs.

[0056] Traditional wire drawing machine fault detection often relies on manual experience for troubleshooting, which is time-consuming and inaccurate, making it difficult to detect and resolve equipment failures in a timely and effective manner.

[0057] To solve the above problems, the embodiments of the present application provide a wire drawing machine fault detection method, system and device. In this method, by obtaining product defect information including defect items and occurrence frequency of products after wire drawing by a wire drawing machine; then analyzing according to the defect items, obtaining wire drawing machine fault component information used to reflect the faulty components; and then analyzing according to the occurrence frequency and wire drawing machine fault component information, obtaining the cause of the wire drawing machine failure. This method can quickly locate the faulty components through specific information on poor product quality, and further determine the specific cause of the fault, thereby significantly improving the accuracy and efficiency of fault diagnosis, optimizing maintenance strategies, and thus improving maintenance efficiency.

[0058] The wire drawing machine fault detection method provided in the embodiment of the present application can be applied to a wire drawing machine fault detection device. At this time, the wire drawing machine fault detection device is the executor of the wire drawing machine fault detection method provided in the embodiment of the present application. The embodiment of the present application does not impose any restrictions on the specific type of the wire drawing machine fault detection device.

[0059] For example, the wire drawing machine fault detection device can be on terminal devices such as mobile phones, tablet computers, laptops, ultra-mobile personal computers (UMPC), netbooks, personal digital assistants (PDA), desktop computers, smart large screens, smart TVs, handheld devices with wireless communication functions, computing devices or other processing devices connected to wireless modems, Internet of Things terminals, computers, laptops, handheld communication devices, handheld computing devices, satellite wireless devices, wireless modem cards, TV set top boxes (set top boxes, STB), customer premise equipment (customer premise equipment, CPE) and / or other devices used to communicate on wireless systems and next-generation communication systems, such as mobile terminals in 5G networks or mobile terminals in future evolved public land mobile networks (Public Land Mobile Network, PLMN), etc.

[0060] In order to better understand the wire drawing machine fault detection method provided in the embodiment of the present application, the specific implementation process of the wire drawing machine fault detection method provided in the embodiment of the present application is exemplarily introduced below.

[0061] Figure 1 and Figure 2 A schematic flow chart of a wire drawing machine fault detection method provided in an embodiment of the present application is shown, and the wire drawing machine fault detection method includes:

[0062] S100, obtaining product defect information; wherein the product defect information includes defect items and occurrence frequency of the product after being drawn by a wire drawing machine.

[0063] It can be understood that defective items may include wire drawing size deviation, wire breakage and surface scratches, etc. The frequency of occurrence refers to the number of times a defective item of a wire drawing product occurs within a preset time. The preset time is a pre-set value, which can be 10 minutes, 0.5 hours, 1 hour, etc., but is not limited to this. The preset time can be manually input by humans, or obtained from a wire drawing database, etc., but is not limited to this. The wire drawing database refers to a database containing preset times corresponding to different wire drawing products. These data can be obtained through laboratory experiments, on-site measurements and monitoring, and past experience. After obtaining, the collected data will be sorted, classified and archived, useful information and rules will be extracted, and the relevant data will be saved in the database to form a wire drawing database. Product defect information can be manually input by humans, or obtained by obtaining images of wire drawing products after drawing for analysis, but is not limited to this. Images of wire drawing products after drawing can be obtained through cameras or other imaging devices.

[0064] S200, analyzing the defective items to obtain the faulty component information of the wire drawing machine; wherein the faulty component information of the wire drawing machine is used to reflect the faulty component.

[0065] It can be understood that when various parts of the wire drawing machine fail, the defects caused to the wire drawing product may be different, and the reasons for the failure of the same part are different, and the defects caused to the wire drawing product may also be different. For example, when the defective item of the wire drawing product is wire breakage, the failed part may be a wire take-up wheel, a damaged mold, a damaged tension sensor, etc. If the failed part is a wire take-up wheel failure, the wire drawing product may have surface scratches due to the wear of the wire take-up wheel, or the wire drawing size deviation or wire breakage may be caused by the unstable wire take-up speed of the wire take-up wheel. In other words, for the same defective item, the failed part is uncertain. The corresponding multiple possible faulty parts can be obtained by first obtaining the category of the defective item, and then analyzing the multiple possible faulty parts to finally obtain the faulty parts; the defective items can also be input into the learning model, and the learning model then outputs the corresponding wire drawing machine faulty part information, etc., but not limited to this. The learning model is trained by multiple sets of training data. The learning model is repeatedly trained by using detailed defective items and the defective items as training data, and the trained defective items cover all possible defects.

[0066] As an optional embodiment of this application, please refer to Figure 2 In step S200, the defective items are analyzed to obtain the faulty parts information of the wire drawing machine, including:

[0067] S210, analyzing the defect items to obtain defect types; wherein the defect types include size type and appearance type.

[0068] It can be understood that the defect type is used to reflect the category of the defect item. The defect item can be input into the defect database for matching to obtain the defect type corresponding to the defect item; the defect type to which the defect item belongs can also be directly identified based on the characteristics of the defect item, etc., but not limited thereto. The defect database refers to a database that includes all defect items classified into size categories or appearance categories.

[0069] In a possible implementation, in step S210, defect items are analyzed to obtain defect types, including:

[0070] S211, analyzing the defect items to obtain a defect degree value; wherein the defect degree value is used to reflect the damage degree of the wire drawing product.

[0071] It is understandable that the degree of defects caused by the same defect item may be different. For example, the depth of scratches on the same surface may be different. At the same time, for wire drawing products with different quality requirements, even if the scratches are the same depth, the corresponding defect degree value is larger for wire drawing products with higher quality requirements. The defect degree value can be obtained by matching the acquired defective product image in the defect database; or by inputting the specification requirements and defect items of the wire drawing product into the learning model, and the learning model outputs the corresponding defect degree value, etc., but not limited to this.

[0072] S212, analyzing according to the defect degree value to obtain a rework rate; wherein the rework rate is used to reflect the success rate of rework and repair of the defective item.

[0073] It can be understood that the higher the defect level value, the lower the rework rate; the lower the defect level value, the greater the rework rate. The defect level value can be matched in the defect database to obtain the corresponding rework rate; the specification requirements and defect level value of the wire drawing product can also be input into the learning model, and the learning model outputs the corresponding rework rate, etc., but not limited to this.

[0074] S213, analyzing based on the rework rate to obtain defect types.

[0075] For example, the rework rate can be compared with a preset rework rate. If the rework rate is less than the preset rework rate, it is determined to be a size class, and if the rework rate is greater than the preset rework rate, it is determined to be an appearance class. The preset rework rate is a preset value, which can be manually input by humans or obtained from a defect database, etc., but is not limited thereto. The rework rate can also be matched in the defect database to obtain the corresponding defect type, etc., but is not limited thereto.

[0076] So configured, this method allows for refined management of defects in wire drawing products, reflecting the actual impact of different defects through specific defect severity values, thereby more accurately determining the severity of quality issues, and enabling more comprehensive and accurate determination of defect types through analysis of defect severity and rework rate.

[0077] S220, analyzing according to the defect type to obtain component group information; wherein the component group information is used to reflect at least one component that may fail.

[0078] It can be understood that the component group information includes multiple components of the wire drawing machine. The size category and the appearance category each correspond to a component group information. The corresponding component group information can be obtained by inputting the defect type into the defect database for matching; the component group information can also be obtained by matching each component of the wire drawing machine with the corresponding defect type, etc., but not limited to this.

[0079] S230, analyzing according to the component group information to obtain the faulty component information of the wire drawing machine.

[0080] Exemplarily, by performing statistical analysis on the maintenance information of each component in the component group information, the component most likely to fail, i.e., the faulty component information of the wire drawing machine, can be calculated; or by summarizing the actual operating conditions of each component in the component group information and monitoring them, the operating data can be analyzed, and the components with abnormal operating data can be analyzed to obtain the faulty component information of the wire drawing machine, etc., but not limited to this.

[0081] With such an arrangement, the analysis scope of faulty parts of the wire drawing machine can be narrowed down through the types of defects in the wire drawing products, thereby significantly improving the accuracy and efficiency of fault diagnosis.

[0082] In a possible implementation, in step S230, analyzing the component group information to obtain the faulty component information of the wire drawing machine includes:

[0083] S231, obtaining maintenance information of each component in the component group information; wherein the maintenance information is used to reflect the repair and replacement records of each component.

[0084] For example, the maintenance information can be obtained from the equipment operation records in the MES system; the maintenance information can also be obtained by manual input, etc., but not limited to this. The MES system includes the operation information of each device and the repair, replacement and maintenance records of each device.

[0085] S232, analyzing the maintenance information to obtain a fault occurrence value of each component; wherein the fault occurrence value is used to reflect the probability of a component failure.

[0086] For example, the replacement records in the maintenance information and the overall maintenance records in the equipment life cycle can be analyzed, and the fault occurrence value can be obtained based on the weights of the replacement records and maintenance records; the maintenance information can also be input into the learning model, and the learning model outputs the corresponding fault occurrence value, etc., but not limited to this. The learning model is trained with a large number of historical maintenance records and fault occurrence situations and corresponding fault occurrence values.

[0087] In a possible implementation, in step S230, analyzing the maintenance information to obtain the fault occurrence value of each component includes:

[0088] S2321, analyzing the maintenance information to obtain a replacement factor; wherein the replacement factor is used to reflect the length of time since the last replacement of the component.

[0089] It can be understood that the replacement factor = the date of failure occurrence - the date of last replacement. The larger the replacement factor, the longer the time since the last replacement of the component, and the greater the possibility of failure.

[0090] S2322, analyzing the maintenance information to obtain maintenance frequency; wherein the maintenance frequency is used to reflect the number and interval of component repair and replacement.

[0091] It can be understood that maintenance frequency = time interval ÷ (number of repairs + number of replacements). The maintenance frequency can be calculated by the number of maintenances in the entire use cycle, or by the number of maintenances in a preset cycle, etc., but is not limited to this. The preset cycle is a pre-set cycle value, which can be within one year, three years, etc., but is not limited to this. The preset cycle can be manually input by humans, or it can be obtained from the fault database, etc., but is not limited to this. The smaller the maintenance frequency, the more times the component is repaired and replaced during this period, and the greater the possibility of a fault.

[0092] S2323, analyzing based on the replacement factor and maintenance frequency to obtain the failure occurrence value of each component.

[0093] Exemplarily, the fault occurrence value can be obtained by weighted summing the replacement factor and the maintenance frequency; the replacement factor and the maintenance frequency can also be input into a learning model to output the corresponding fault occurrence value, etc., but not limited to this.

[0094] This setting can provide a scientific basis for equipment management and maintenance by quantifying the possibility of failure of each component. It can quickly determine which components have a higher risk of failure, so as to prioritize inspection and maintenance and avoid unnecessary downtime.

[0095] In a possible implementation, in step S2323, an analysis is performed based on the replacement factor and the maintenance frequency to obtain the failure occurrence value of each component, including:

[0096] S23231, obtain the replacement weight of the replacement factor and the frequency weight of the maintenance frequency.

[0097] It can be understood that the replacement weight and frequency weight are pre-set weight values, which can be manually input by humans or obtained from a fault database, etc., but are not limited to this.

[0098] S23232, weight the replacement factor by the replacement weight, weight the maintenance frequency by the frequency weight, and sum them up to obtain the failure occurrence value of each component.

[0099] It can be understood that the fault occurrence value = replacement factor × replacement weight + maintenance frequency × maintenance weight. For example, assuming that the replacement weight is 0.6, the maintenance weight is 0.4, the replacement time of components A, B, and C is June 1, 2024, April 10, 2024, and August 1, 2024, respectively, and the maintenance times of components A, B, and C in the past year are 5 times, 3 times, and 4 times, respectively. The current time is September 19, 2024, then the fault occurrence value of component A = 110 × 0.6 + 73 × 0.4 = 95.2, the fault occurrence value of component B = 162 × 0.6 + 121.7 × 0.4 = 145.9, the fault occurrence value of component C = 50 × 0.6 + 91.3 × 0.4 = 66.5, and so on.

[0100] With this setting, the failure occurrence value of each component can be obtained through weighted analysis of replacement factors and maintenance frequency, which can provide quantitative data for subsequent analysis processes and quickly determine which components have a higher risk of failure.

[0101] S233, analyzing the multiple fault occurrence values ​​to obtain the fault component information of the wire drawing machine.

[0102] Exemplarily, multiple fault occurrence values ​​of each component can be sorted, and further analyzed according to the sorted order to obtain the wire drawing machine fault component information; each fault occurrence value can also be input into a learning model, and the learning model then outputs the wire drawing machine fault component information, etc., but not limited thereto. The learning model is trained by multiple sets of training data, and each set of training data in the multiple sets of training data includes the fault occurrence value of each component and the corresponding wire drawing machine fault component information.

[0103] In this way, the fault occurrence value of each component is obtained by analyzing the previous maintenance information of each component, thereby obtaining the fault component information of the wire drawing machine, and the components that may fail can be identified more accurately. This method is more scientific and objective than traditional manual experience judgment.

[0104] In a possible implementation, in step S233, analysis is performed based on multiple fault occurrence values ​​to obtain fault component information of the wire drawing machine, including:

[0105] S2331, sort the multiple fault occurrence values ​​to obtain a first sequence digit and a second sequence digit.

[0106] It can be understood that the first order bit is the maximum value of the fault occurrence value. The second order bit is the order bit of the fault occurrence value other than the first order bit that is greater than the preset threshold. The preset threshold is a preset value, which can be manually input by humans, or obtained from a fault database, etc., but is not limited to this. For example, the fault occurrence value of component A is 87.5, the fault occurrence value of component B is 114.0, the fault occurrence value of component C is 61.3, the fault occurrence value of component D is 42.9, and the fault occurrence value of component E is 31.5. The preset threshold is 50, then the first order bit is 114.0, and the second order bit includes 87.5, 61.3, and so on.

[0107] S2332, calculate the difference between the first sequence bit and the second sequence bit to obtain a fault difference value.

[0108] It can be understood that the fault difference value=the fault occurrence value of the first order bit-the fault occurrence value of the second order bit.

[0109] S2333, analyzing according to the fault difference value to obtain the fault component information of the wire drawing machine.

[0110] Exemplarily, the size of the fault difference value can be analyzed to determine the possibility of failure of the first and second order bits, thereby determining the faulty component information of the wire drawing machine; each fault difference value can also be input into a learning model to obtain the faulty component information of the wire drawing machine, etc., but is not limited to this.

[0111] With this setting, by sorting and calculating the fault difference value, the faulty component can be quickly located, reducing the troubleshooting time. At the same time, through the fault difference value analysis, potential faulty components can be discovered in time, so that a more reasonable preventive maintenance plan can be formulated to reduce unplanned downtime.

[0112] In a possible implementation, in step S2333, analyzing the fault difference value to obtain the fault component information of the wire drawing machine includes:

[0113] S23331a, compare the fault difference value with the preset difference value, and when the fault difference value is greater than or equal to the preset difference value, determine the component corresponding to the first sequence digit as the fault component information of the wire drawing machine.

[0114] It can be understood that the preset difference value is a preset value, which can be manually input or obtained from a fault database, etc., but is not limited thereto. When the fault difference value is greater than or equal to the preset difference value, it means that the possibility of the component corresponding to the first order position failing is much greater than the possibility of other components failing, and it can be determined as a faulty component.

[0115] S23331A, when the fault difference value is less than the preset difference value, the replacement factor corresponding to the first sequence digit and the replacement factor corresponding to the second sequence digit are compared, and the first sequence digit or the second sequence digit corresponding to the larger replacement factor is determined as the faulty component information of the wire drawing machine.

[0116] It can be understood that when the fault difference value is less than the preset difference value, it means that the probability of the component corresponding to the second order position to fail is high as that of the component corresponding to the first order position to fail. It is impossible to accurately locate the fault only by the fault occurrence value. At this time, it is necessary to further compare the replacement factor to determine the more likely faulty component. The larger the replacement factor, the longer the time since the last replacement of the component. The component may have been worn or has a large functional consumption. If the replacement factor corresponding to the first order position is large, the component corresponding to the first order position is more likely to be a faulty component. If the replacement factor corresponding to the second order position is large, the component corresponding to the second order position is more likely to be a faulty component, and so on.

[0117] With this arrangement, by comparing the fault difference value with the preset difference value, the component with a higher possibility of failure can be quickly determined. Combined with the replacement factor, the faulty component can be located more accurately, thereby improving the diagnostic efficiency.

[0118] S300: Analyze the occurrence frequency and the information of the faulty parts of the wire drawing machine to obtain the fault cause of the wire drawing machine.

[0119] Exemplarily, after determining the faulty component of the wire drawing machine, an analysis can be performed based on the frequency of occurrence of poor quality problems in the wire drawing products to determine the component failure problem corresponding to the cause of the failure; the frequency of occurrence and the information on the faulty components of the wire drawing machine can also be input into a learning model, and the learning model outputs the corresponding cause of the wire drawing machine failure, etc., but is not limited to this.

[0120] In a possible implementation, in step S300, the failure cause of the wire drawing machine is obtained by analyzing the occurrence frequency and the failure component information of the wire drawing machine, including:

[0121] S310, analyzing the wire drawing machine fault component information to obtain a fault set; wherein the fault set includes all possible fault problems that may occur in the wire drawing machine fault component information.

[0122] It is understandable that each faulty component may have multiple fault problems, such as poor quality of lubricating fluid in the lubrication mechanism, insufficient lubricating fluid, lubrication pump failure, etc., improper tension adjustment of the wire storage device, tension sensor failure, tension controller failure, etc.

[0123] S320, calculating the correlation value between the occurrence frequency and the fault set, and determining the fault problem corresponding to the largest correlation value as the fault cause of the wire drawing machine.

[0124] It can be understood that there is a certain relationship between the frequency of occurrence of poor quality of drawn products and the various fault problems of faulty components, and there is an associated value between different occurrence frequencies and different fault problems in the fault set. The associated value can be a statistical correlation coefficient, Pearson correlation coefficient, Spearman rank correlation coefficient, etc., that is, through statistical analysis of historical fault data and maintenance data, when a certain defective item occurs in a certain drawn product, the cause of the fault of the faulty component is statistically analyzed by the number of fault causes and the number of occurrences of the defective item to obtain the associated value; the associated value can also be obtained through a mathematical model, the occurrence frequency and each fault problem in the fault set are input into the mathematical model, and the corresponding associated value is output, etc., but not limited to this.

[0125] With this setting, by combining the frequency of occurrence and the faulty component information, the specific cause of the fault can be located more accurately, the accuracy of fault diagnosis can be improved, and through scientific quantitative analysis methods, ineffective maintenance work caused by misdiagnosis can be reduced, thereby improving work efficiency.

[0126] It should be understood that the size of the serial numbers of the steps in the above embodiments 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.

[0127] Corresponding to the wire drawing machine fault detection method described in the above embodiment, the embodiment of the present application also provides a wire drawing machine fault detection system, and each module of the system can implement each step of the wire drawing machine fault detection method. Figure 3 A structural block diagram of a wire drawing machine fault detection system provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0128] Reference Figure 3 , the wire drawing machine fault detection system includes:

[0129] The acquisition module is used to obtain product defect information; wherein the product defect information includes defect items and occurrence frequency of the product after being drawn by the wire drawing machine.

[0130] The first analysis module is used to analyze according to the defect items to obtain the faulty component information of the wire drawing machine; wherein the faulty component information of the wire drawing machine is used to reflect the faulty components.

[0131] The second analysis module is used to analyze the failure cause of the wire drawing machine according to the occurrence frequency and the failure component information of the wire drawing machine.

[0132] It should be noted that the information interaction, execution process and other contents between the above-mentioned modules are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0133] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above modules is used as an example for illustration. In practical applications, the above functions can be assigned to different modules as needed, that is, the internal structure of the system can be divided into different modules to complete all or part of the functions described above. The modules in the embodiment can be integrated into a processing unit, or each module can exist physically alone, or two or more modules can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the modules are only for the convenience of distinguishing from each other, and are not used to limit the scope of protection of this application. The specific working process of the modules in the above system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0134] The present application also provides a wire drawing machine fault detection device, Figure 4 This is a schematic diagram of the structure of a wire drawing machine fault detection device 6 provided in one embodiment of the present application. Figure 4 As shown, the wire drawing machine fault detection device 6 of this embodiment includes: at least one processor 60 ( Figure 4 Only one is shown), at least one memory 61 ( Figure 4 Only one is shown) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, the wire drawing machine fault detection device 6 implements the steps in any of the above-mentioned wire drawing machine fault detection method embodiments, or implements the functions of the modules in the above-mentioned system embodiments.

[0135] Exemplarily, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 62 in the wire drawing machine fault detection device 6.

[0136] The wire drawing machine fault detection device 6 can be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The wire drawing machine fault detection device can include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art can understand that Figure 4 It is only an example of the wire drawing machine fault detection device 6 and does not constitute a limitation of the wire drawing machine fault detection device 6. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, buses, etc.

[0137] The processor 60 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0138] In some embodiments, the memory 61 may be an internal storage unit of the wire drawing machine fault detection device 6, such as a hard disk or memory of the wire drawing machine fault detection device 6. In other embodiments, the memory 61 may also be an external storage device of the wire drawing machine fault detection device 6, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the wire drawing machine fault detection device 6. Further, the memory 61 may also include both the internal storage unit of the wire drawing machine fault detection device 6 and an external storage device. The memory 61 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program, etc. The memory 61 may also be used to temporarily store data that has been output or is to be output.

[0139] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0140] An embodiment of the present application provides a computer program product. When the computer program product runs on a wire drawing machine fault detection device, the wire drawing machine fault detection device implements the steps in any of the above-mentioned method embodiments.

[0141] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying the computer program code to the wire drawing machine fault detection device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk.

[0142] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0143] 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.

[0144] In the embodiments provided in the present application, it should be understood that the disclosed wire drawing machine fault detection device and system can be implemented in other ways. For example, the wire drawing machine fault detection system embodiment described above is only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0145] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0146] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A wire drawing machine fault detection method, characterized in that: include: Obtaining product defect information; wherein the product defect information includes defect items and occurrence frequency of the product after being drawn by the wire drawing machine; Analyze the defect items to obtain the wire drawing machine fault component information; wherein the wire drawing machine fault component information is used to reflect the faulty component; The cause of the wire drawing machine failure is obtained by analyzing the occurrence frequency and the information of the wire drawing machine failure components.

2. The wire drawing machine fault detection method according to claim 1, characterized in that: The analysis based on the defect items to obtain the faulty parts information of the wire drawing machine includes: Analyze the defect items to obtain defect types; wherein the defect types include size type and appearance type; Analyze according to the defect type to obtain component group information; wherein the component group information is used to reflect at least one component that may fail; The component group information is analyzed to obtain the faulty component information of the wire drawing machine.

3. The wire drawing machine fault detection method according to claim 2, characterized in that: The analyzing according to the component group information to obtain the fault component information of the wire drawing machine includes: Acquire maintenance information of each component in the component group information; wherein the maintenance information is used to reflect the repair and replacement records of each component; Analyze the maintenance information to obtain the fault occurrence value of each component; wherein the fault occurrence value is used to reflect the probability of component failure; The fault component information of the wire drawing machine is obtained by analyzing the multiple fault occurrence values.

4. The wire drawing machine fault detection method according to claim 3, characterized in that: The analyzing according to the maintenance information to obtain the fault occurrence value of each component includes: Analyze the maintenance information to obtain a replacement factor, wherein the replacement factor is used to reflect the length of time since the last replacement of the component; Analyze the maintenance information to obtain maintenance frequency; wherein the maintenance frequency is used to reflect the number and interval of component repair and replacement; An analysis is performed based on the replacement factor and the maintenance frequency to obtain a failure occurrence value of each component.

5. The wire drawing machine fault detection method according to claim 4, characterized in that: The analyzing according to the replacement factor and the maintenance frequency to obtain the failure occurrence value of each component includes: Obtaining a replacement weight of the replacement factor and a frequency weight of the maintenance frequency; The replacement weight is weighted for the replacement factor, the frequency weight is weighted for the maintenance frequency, and the sum is calculated to obtain the failure occurrence value of each component.

6. The wire drawing machine fault detection method according to claim 5, characterized in that: The analyzing according to the plurality of fault occurrence values ​​to obtain the fault component information of the wire drawing machine includes: Sorting the plurality of fault occurrence values ​​to obtain a first order digit and a second order digit; Calculate the difference between the first sequence bit and the second sequence bit to obtain a fault difference value; The fault difference value is analyzed to obtain the fault component information of the wire drawing machine.

7. The wire drawing machine fault detection method according to claim 6, characterized in that: The analyzing according to the fault difference value to obtain the fault component information of the wire drawing machine includes: Compare the fault difference value with a preset difference value, and when the fault difference value is greater than or equal to the preset difference value, determine the component corresponding to the first sequence position as the fault component information of the wire drawing machine; When the fault difference value is less than the preset difference value, the replacement factor corresponding to the first sequence bit and the replacement factor corresponding to the second sequence bit are compared, and the first sequence bit or the second sequence bit corresponding to the larger replacement factor is determined as the faulty component information of the wire drawing machine.

8. The wire drawing machine fault detection method according to claim 1, characterized in that: The analyzing according to the occurrence frequency and the wire drawing machine fault component information to obtain the wire drawing machine fault cause includes: Analyze the faulty component information of the wire drawing machine to obtain a fault set; wherein the fault set includes all possible fault problems of the faulty component information of the wire drawing machine; The correlation value between the occurrence frequency and the fault set is calculated, and the fault problem corresponding to the largest correlation value is determined as the cause of the wire drawing machine fault.

9. A wire drawing machine fault detection system, characterized in that: include: An acquisition module, used to acquire product defect information; wherein the product defect information includes defect items and occurrence frequency of the product after being drawn by the wire drawing machine; A first analysis module is used to analyze the defect items to obtain the wire drawing machine fault component information; wherein the wire drawing machine fault component information is used to reflect the faulty component; The second analysis module is used to analyze the occurrence frequency and the information of the faulty parts of the wire drawing machine to obtain the cause of the wire drawing machine failure.

10. A wire drawing machine fault detection device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 8 when executing the computer program.

Images