Cable production monitoring method and system based on Internet of Things

Abstract

The present invention discloses a cable production monitoring method and system based on the Internet of Things, which relates to the technical field of cable production. The method and system set a collection time interval, obtain the data of the cable core and the actual diameter data of the cable shell, judge whether the actual torsion angle data is the standard torsion angle data, obtain the standard twisting parameter data, judge whether the actual diameter data is within the standard diameter data range, obtain the standard shell processing data, input it into a twisting device and a shell processing device, input the standard twisting parameter data and the standard shell processing data into a preset parameter coding set, and establish a corresponding relationship. The present invention adopts the Internet of Things to monitor cable production, can collect and process key data in real time, optimize process parameters through intelligent analysis, ensure that production meets standards, reduce human errors, and improve production efficiency and product quality through real-time monitoring and data processing. At the same time, it enhances the control over the production process and promotes the intelligent and refined management of the production line.

Description

Technical Field

[0001] The present invention relates to the technical field of cable production, and in particular to a cable production monitoring method and system based on the Internet of Things. Background Art

[0002] In the cable production industry, cables are important carriers of power transmission and signal transmission. Their quality and performance directly affect the stability and safety of the entire power system. With the advancement of science and technology and the continuous development of industrial automation, the degree of automation of cable production lines is also gradually improving. On the cable production line, by precisely controlling the process parameters of each link, it can be ensured that the quality and performance of cable products meet the standard requirements. However, due to the shortcomings of existing technologies, traditional cable production lines face many challenges in real-time monitoring, data analysis, standardized production, flexible adjustment and information traceability.

[0003] At present, a Chinese invention patent with application number CN202010994411.2 discloses a cable production line monitoring system, including a cable production monitoring system. The cable production monitoring system includes an early warning adjustment module, an order tracking management system and a terminal monitoring module. The early warning adjustment module includes a real-time fault monitoring module, an alarm module and a rate adjustment module. The order tracking management system includes an order quantity tracking module, an order quantity feedback module and an order quantity statistics module. The terminal monitoring module includes a production line monitoring module, an order flow monitoring module, an order data backup module and an administrator client. Although the cable production line monitoring system can promptly issue an alarm for possible faults in the cable production process, thereby enabling on-site users to respond in a timely manner, it is difficult in the relevant technology to calculate and adjust the predicted torque parameters and standard shell processing data in real time based on the collected data, which affects the standardization of the finished cable products and makes it difficult to ensure the quality and consistency of the finished cable products. Summary of the invention

[0004] The technical problem solved by the present invention is that it is difficult in the related art to calculate and adjust the predicted torque parameters and standard shell processing data in real time based on the collected data, which affects the standardization of finished cable products and makes it difficult to ensure the quality and consistency of the finished cable products.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] The cable production monitoring method based on the Internet of Things includes the following steps:

[0007] Step S1, setting a collection time interval to obtain data of the cable core and actual diameter data of the cable casing;

[0008] Step S2, judging whether the actual torsion angle data is standard torsion angle data, outputting a first judgment result, analyzing the torsion situation according to the first judgment result, calculating the predicted torque parameter according to the torsion situation, inputting the predicted torque parameter into a preset standard twisting parameter data set, and obtaining the standard twisting parameter data;

[0009] Step S3, judging whether the actual diameter data is within the standard diameter data range, and outputting a second judgment result, obtaining the actual shell processing data according to the second judgment result, inputting the actual shell processing data into a preset standard shell processing data set, and obtaining the standard shell processing data;

[0010] Step S4, inputting the standard twisting parameter data and the standard shell processing data into the twisting device and the shell processing device;

[0011] Step S5, inputting the standard twisting parameter data and the standard shell processing data into a preset parameter coding set, obtaining the production information coding represented by the standard twisting parameter data and the standard shell processing data and establishing a corresponding relationship;

[0012] The step S1 includes the following sub-steps:

[0013] Step S101, collecting actual cable category data, inputting the cable category data into a collection parameter correspondence table, wherein the collection parameter correspondence table includes standard cable category data and corresponding collection time intervals, obtaining a collection time interval corresponding to the actual cable category, and inputting the collection time interval into a cable production device;

[0014] Step S102, acquiring actual torsion angle data of the cable core and actual diameter data of the cable housing according to a set collection time interval;

[0015] The step S2 includes the following sub-steps:

[0016] Step S201, inputting the actual cable category data into the standard library, searching for standard cable category data identical to the actual cable category data, obtaining standard torsion angle data corresponding to the standard cable category data, comparing the actual torsion angle data with the standard torsion angle data, and outputting a first judgment result;

[0017] Step S202, analyzing the torsion condition according to the first judgment result, wherein the torsion condition includes loose torsion and excessive torsion;

[0018] Step S203, calculating the torque according to the torsion condition and outputting it as a predicted torque parameter;

[0019] Step S204, inputting the predicted torque parameter into the standard twisting parameter data set, searching for standard twisting parameter data corresponding to the standard twisting parameter that is the same as the predicted twisting parameter, and outputting the standard twisting parameter data;

[0020] The first judgment result in step S201 includes that the actual torsion angle data is equal to the standard torsion angle data, the actual torsion angle data is greater than the standard torsion angle data, and the actual torsion angle data is less than the standard torsion angle data;

[0021] The step S202 analyzes the torsion situation according to the first judgment result as follows:

[0022] If the actual torsion angle data is greater than the standard torsion angle data, the torsion condition is excessive torsion;

[0023] If the actual torsion angle data is less than the standard torsion angle data, the torsion condition is loose torsion;

[0024] The step S203 calculates the torque according to the torsion condition as:

[0025] If the torsion condition is loose torsion, the actual cable category data is input into the preset torque data set, and the standard torque parameters corresponding to the standard cable category data that is the same as the actual cable category data are searched, and the output is the predicted torque parameters;

[0026] If the torsion condition is excessive torsion, input the actual cable category data into the preset torque data set, find the standard torque parameters corresponding to the standard cable category data that is the same as the actual cable category data, obtain the actual torque, and calculate the actual stiffness. The mathematical expression is:

[0027]

[0028] Among them, K T is the actual stiffness, T actual is the actual torque, θ actual is the actual torsion angle data;

[0029] Calculate the predicted torque parameter, the mathematical expression is:

[0030] T design =K T ×θ design

[0031] Among them, T design To predict the torque parameter, θ design To predict torsion parameters;

[0032] The step S3 includes the following sub-steps:

[0033] Step S301, inputting the actual diameter data into the standard library, obtaining the standard diameter data range corresponding to the standard cable category data, judging whether the actual diameter data is within the standard diameter data range, and outputting a second judgment result, wherein the second judgment result includes that the actual diameter data is within the standard diameter data range and the actual diameter data is not within the standard diameter data range;

[0034] Step S302, analyzing the second judgment result:

[0035] If the second judgment result is that the actual diameter data is within the standard diameter data range, no instruction is output;

[0036] If the second judgment result is that the actual diameter data is not within the standard diameter data range, the actual diameter data is input into the standard library to search for standard shell processing data corresponding to the standard diameter data closest to the actual diameter data.

[0037] Preferably, step S4 includes the following sub-steps:

[0038] Step S401, acquiring standard twisting parameter data and inputting the standard twisting parameter data into a twisting device;

[0039] Step S402, acquiring standard shell processing data and inputting the standard shell processing data into a shell processing device.

[0040] Preferably, step S5 includes the following sub-steps:

[0041] Step S501, inputting the standard twisting parameter data and the standard shell processing data into the parameter code set, respectively obtaining the production information codes represented by the standard twisting parameter data and the standard shell processing data, and merging the production information codes represented by the standard twisting parameter data and the standard shell processing data and outputting them as a production information code group;

[0042] Step S502, establishing and storing the corresponding relationship between the production information coding group, the actual cable category data and the batch information data.

[0043] The cable production monitoring system based on the Internet of Things is applied to any of the cable production monitoring methods based on the Internet of Things, and includes a data acquisition module, a monitoring adjustment module, an execution control module and a coding establishment module:

[0044] The data acquisition module is used to set an acquisition time interval, and obtain the actual torsion angle data of the cable core and the actual diameter data of the cable shell according to the acquisition time interval;

[0045] The monitoring and adjustment module is used to determine whether the actual torsion angle data is the standard torsion angle data, output a first judgment result, calculate the predicted torque parameter according to the first judgment result, input the predicted torque parameter into a preset standard twisting parameter data set, obtain the standard twisting parameter data, determine whether the actual diameter data is within the standard diameter data range and output a second judgment result, obtain the actual shell processing data according to the second judgment result, and obtain the standard shell processing data according to the actual shell processing data;

[0046] The execution control module is used to input the standard twisting parameter data and the standard shell processing data into the twisting device and the shell processing device;

[0047] The coding establishment module is used to input standard twisting parameter data and standard shell processing data into the parameter coding set, obtain the production information coding group and establish the corresponding relationship between the production information coding group, actual cable category data and batch information data.

[0048] The beneficial effects of the present invention are as follows: the present invention adopts the Internet of Things to monitor cable production, which can collect and process key data in real time, optimize process parameters through intelligent analysis, ensure that production meets standards, reduce human errors, and improve production efficiency and product quality through real-time monitoring and data processing. At the same time, it enhances the control over the production process and promotes the intelligent and refined management of the production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A flowchart of a method for monitoring cable production based on the Internet of Things provided by one embodiment of the present invention;

[0050] Figure 2 A system composition structure diagram of a cable production monitoring system based on the Internet of Things provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0051] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0052] Embodiment 1, refer to Figure 1 , provides a cable production monitoring method based on the Internet of Things, including the following steps:

[0053] Step S1, setting a collection time interval to obtain data of the cable core and actual diameter data of the cable casing.

[0054] Step S2, determine whether the actual torsion angle data is the standard torsion angle data, output a first judgment result, analyze the torsion situation according to the first judgment result, calculate the predicted torque parameter according to the torsion situation, input the predicted torque parameter into a preset standard twisting parameter data set, and obtain the standard twisting parameter data.

[0055] Step S3, judging whether the actual diameter data is within the standard diameter data range, and outputting a second judgment result, obtaining actual shell processing data according to the second judgment result, inputting the actual shell processing data into a preset standard shell processing data set, and obtaining standard shell processing data.

[0056] Step S4, inputting the standard twisting parameter data and the standard shell processing data into the twisting device and the shell processing device.

[0057] Step S5, inputting the standard twisting parameter data and the standard shell processing data into a preset parameter coding set, obtaining the production information coding represented by the standard twisting parameter data and the standard shell processing data and establishing a corresponding relationship.

[0058] Step S1 includes the following sub-steps:

[0059] Step S101, collect actual cable category data, input the cable category data into a collection parameter correspondence table, the collection parameter correspondence table includes standard cable category data and corresponding collection time intervals, obtain the collection time interval corresponding to the actual cable category, and input the collection time interval into the cable production device.

[0060] By collecting actual cable category data and matching it with the standard cable category data in the collection parameter correspondence table, the collection time interval suitable for the current cable category can be quickly and accurately obtained, realizing personalized customization of data collection, improving the pertinence and effectiveness of data collection, and inputting the obtained collection time interval into the cable production device to ensure that the production device can collect data at the predetermined time interval, avoiding the blindness and arbitrariness of data collection, and improving the standardization and accuracy of data collection.

[0061] Step S102, acquiring actual torsion angle data of the cable core and actual diameter data of the cable casing according to a set collection time interval.

[0062] According to the set collection time interval, the actual torsion angle data of the cable core and the actual diameter data of the cable casing are obtained in real time, ensuring the real-time and continuity of the data, providing a rich and comprehensive data source for subsequent data analysis and processing. By precisely controlling the collection time interval and collection method, the accuracy and reliability of data collection are improved, which helps to reduce production problems caused by data collection errors and improves the stability and controllability of the production process.

[0063] Step S1 uses intelligent means to set and obtain the key data collection time intervals in the cable production process, as well as the actual cable core torsion angle and shell diameter data, to provide accurate and timely data support for subsequent production monitoring and data analysis, ensuring the accuracy and timeliness of data collection, and laying the foundation for the effective operation of the entire production monitoring system.

[0064] Step S2 includes the following sub-steps:

[0065] Step S201, input the actual cable category data into the standard library, search for standard cable category data that is the same as the actual cable category data, obtain standard torsion angle data corresponding to the standard cable category data, compare the actual torsion angle data with the standard torsion angle data, and output a first judgment result.

[0066] The first judgment result in step S201 includes that the actual torsion angle data is equal to the standard torsion angle data, the actual torsion angle data is greater than the standard torsion angle data, and the actual torsion angle data is less than the standard torsion angle data.

[0067] Step S201 compares the actual cable category data with the data in the standard library, quickly finds the corresponding standard torsion angle data, and outputs the first judgment result by comparing the actual torsion angle with the standard torsion angle, which provides a direct basis for subsequent analysis of the torsion situation.

[0068] Step S202: analyzing the torsion condition according to the first judgment result, where the torsion condition includes loose torsion and excessive torsion.

[0069] Step S202 analyzes the torsion situation according to the first judgment result:

[0070] If the actual torsion angle data is greater than the standard torsion angle data, the torsion condition is excessive torsion.

[0071] If the actual torsion angle data is smaller than the standard torsion angle data, the torsion condition is loose torsion.

[0072] Step S202 clarifies the torsion condition of the cable core according to the first judgment result, provides important information for subsequent torque calculation and twisting parameter adjustment, and ensures the pertinence and effectiveness of the adjustment measures.

[0073] Step S203, calculating the torque according to the torsion condition, and outputting it as a predicted torque parameter.

[0074] Step S203 calculates the torque according to the torsion condition as:

[0075] If the torsion condition is loose torsion, the actual cable category data is input into the preset torque data set, and the standard torque parameters corresponding to the standard cable category data that is the same as the actual cable category data are found, and the output is the predicted torque parameters.

[0076] If the torsion condition is excessive torsion, input the actual cable category data into the preset torque data set, find the standard torque parameters corresponding to the standard cable category data that is the same as the actual cable category data, obtain the actual torque, and calculate the actual stiffness. The mathematical expression is:

[0077]

[0078] Among them, K T is the actual stiffness, T actual is the actual torque, θ actual is the actual torsion angle data. The mathematical expression for calculating the predicted torque parameter is:

[0079] T design =K T ×θ design

[0080] Among them, T design To predict the torque parameter, θ design To predict the torsion parameters.

[0081] Step S203 uses different methods to calculate the predicted torque parameters for different torsion conditions. For loose torsion conditions, the standard torque parameters are directly referenced. For excessive torsion conditions, the predicted values ​​are obtained by calculating the actual stiffness and predicting the torque parameters, thereby ensuring the accuracy and scientificity of the torque calculation and providing a reliable basis for the subsequent adjustment of the twisting parameters.

[0082] Step S204, input the predicted torque parameter into the standard twisting parameter data set, search for the standard twisting parameter data corresponding to the standard twisting parameter that is the same as the predicted twisting parameter, and output the standard twisting parameter data, wherein the standard twisting parameter data set includes a standard twisting parameter threshold and corresponding standard twisting parameter data.

[0083] Step S204 matches the predicted torque parameters with the standard twisting parameter data set, searches for and outputs the standard twisting parameters applicable to the current cable category, and realizes intelligent adjustment and optimization of the cable production process, ensuring that the produced cable products meet the quality requirements.

[0084] Step S2 analyzes the torsion situation by comparing the actual cable torsion angle with the standard torsion angle, and calculates and predicts the torque parameters accordingly, and finally outputs the standard twisting parameters suitable for the current cable category, thereby realizing real-time monitoring and precise adjustment of the torsion link in the cable production process, ensuring the torsion quality of the cable core, and improving production efficiency and product quality.

[0085] Step S3 includes the following sub-steps:

[0086] Step S301, input the actual diameter data into the standard library, obtain the standard diameter data range corresponding to the standard cable category data, determine whether the actual diameter data is within the standard diameter data range, and output a second judgment result, the second judgment result includes the actual diameter data is within the standard diameter data range and the actual diameter data is not within the standard diameter data range.

[0087] Step S301 compares the actual diameter data with the standard diameter data range in the standard library to quickly draw a conclusion on whether the actual diameter data meets the standard requirements, thereby ensuring the accuracy and timeliness of the data comparison. Based on the comparison result, a second judgment result is output, namely, whether the actual diameter data is within the standard diameter data range, which provides a direct basis for subsequent analysis and adjustment.

[0088] Step S302, analyzing the second judgment result:

[0089] If the second judgment result is that the actual diameter data is within the standard diameter data range, no instruction is output.

[0090] If the second judgment result is that the actual diameter data is not within the standard diameter data range, the actual diameter data is input into the standard library to search for standard shell processing data corresponding to the standard diameter data closest to the actual diameter data.

[0091] Step S302 performs targeted analysis and processing based on the second judgment result. If the actual diameter data is within the standard range, it means that the current processing state of the cable jacket is good and no adjustment is required. Therefore, no instructions are output, avoiding unnecessary operations and waste of resources. If the actual diameter data is not within the standard range, the corresponding standard jacket processing data is obtained by finding the standard diameter data closest to the actual diameter data, which provides specific data support for subsequent processing adjustments, helps to quickly and accurately correct the diameter problem of the cable jacket and ensure the stability of product quality.

[0092] Step S3 is mainly responsible for monitoring and evaluating the actual diameter of the cable sheath. By comparing it with the standard diameter data range in the standard library, it is determined whether the diameter of the cable sheath meets the requirements. If the actual diameter is within the standard range, no adjustment is made. If the actual diameter exceeds the standard range, the corresponding standard sheath processing data is obtained by finding the closest standard diameter data for subsequent adjustment or correction, thereby ensuring the accuracy and consistency of the cable sheath diameter and improving the overall quality of the product.

[0093] Step S4 includes the following sub-steps:

[0094] Step S401, acquiring standard twisting parameter data and inputting the standard twisting parameter data into a twisting device.

[0095] Step S401 accurately transmits the standard twisting parameter data to the twisting device, ensuring that the twisting device can work according to the predetermined parameters. Through accurate parameter setting, it can be ensured that the twisting tightness, uniformity and other indicators of the wire core meet the requirements.

[0096] Step S402, acquiring standard shell processing data and inputting the standard shell processing data into a shell processing device.

[0097] Step S402 inputs the standard shell processing data into the shell processing device, providing accurate data support for the shell processing. Through automated data input and device control, it can ensure that the shell processing parameters are consistent with standard requirements, thereby improving the shell processing accuracy and consistency. In addition, it also helps to reduce errors and waste in the processing process, and improve production efficiency and resource utilization.

[0098] Step S4 is an important link in the cable production process. It is responsible for inputting the standard twisting parameters and standard shell processing data calculated or found in the previous steps into the twisting device and the shell processing device respectively, ensuring that each link in the production process can be carried out according to the predetermined standards and parameters, thereby ensuring the quality and consistency of the cable products. Through automated data input and device control, production efficiency and accuracy are improved, and human errors are reduced.

[0099] Step S5 includes the following sub-steps:

[0100] Step S501, input standard twisting parameter data and standard shell processing data into a parameter coding set, obtain production information codes represented by the standard twisting parameter data and the standard shell processing data respectively, and combine the production information codes represented by the standard twisting parameter data and the standard shell processing data and output them as a production information coding group.

[0101] Step S501 inputs the standard twisting parameter data and the standard shell processing data into the parameter coding set, obtains the production information codes represented by each through coding conversion, realizes the standardization and digitization of production data, facilitates subsequent information processing and storage, merges the two production information codes and outputs them as a production information coding group, closely links the twisting parameters and shell processing information, forms a complete production information unit, and provides convenience for subsequent information query and traceability.

[0102] Step S502, establishing and storing the corresponding relationship between the production information coding group, the actual cable category data and the batch information data.

[0103] Establishing the correspondence between the production information coding group, actual cable category data and batch information data, this process ensures the accuracy and completeness of the production information. By clarifying the relationship between the data, the production details of each batch of cables can be clearly traced, providing strong support for product quality control and production optimization. The established correspondence will be stored for subsequent query and use. Through an effective storage mechanism, key information in the production process can be retained for a long time, providing valuable data resources for the company's continuous improvement and decision-making analysis.

[0104] Step S5 is a key step in information integration and recording during the cable production process. By integrating standard twisting parameter data, standard shell processing data, actual cable category data and batch information data into a production information coding group, and establishing a corresponding relationship between them for storage, comprehensive and accurate recording of production information is achieved, which not only improves the transparency and traceability of production management, but also provides an important basis for subsequent product quality traceability, production data analysis, etc.

[0105] The cable production monitoring method based on the Internet of Things has significantly improved the automation and intelligence level of cable production, reduced human intervention and errors, ensured the stability and controllability of the production process, and through real-time monitoring and data analysis, it can promptly detect and correct deviations in production, ensuring the quality and consistency of cable products. At the same time, it also enhances the transparency and traceability of production information, providing strong support for the company's production management, quality control and continuous improvement.

[0106] Example 2, refer to Figure 2 , provides a cable production monitoring system based on the Internet of Things, including data acquisition module, monitoring adjustment module, execution control module and coding establishment module:

[0107] The data acquisition module is used to set the acquisition time interval, and obtain the actual torsion angle data of the cable core and the actual diameter data of the cable shell according to the acquisition time interval.

[0108] The data acquisition module regularly obtains the actual torsion angle data of the cable core and the actual diameter data of the cable casing by setting a reasonable collection time interval. The accurate data collection provides a reliable basis for subsequent monitoring and adjustment, ensuring real-time monitoring and precise control of the production process.

[0109] The monitoring and adjustment module is used to determine whether the actual torsion angle data is the standard torsion angle data, output a first judgment result, calculate the predicted torque parameter based on the first judgment result, input the predicted torque parameter into a preset standard twisting parameter data set, obtain the standard twisting parameter data, determine whether the actual diameter data is within the standard diameter data range and output a second judgment result, obtain the actual shell processing data based on the second judgment result, and obtain the standard shell processing data based on the actual shell processing data.

[0110] The monitoring and adjustment module is responsible for in-depth analysis of the actual data collected and comparing it with the standard data. First, it determines whether the actual torsion angle data is the standard value, outputs the first judgment result, and calculates the predicted torque parameters based on this, and then obtains the standard twisting parameter data. Secondly, it determines whether the actual diameter data is within the standard range, outputs the second judgment result, and obtains the standard shell processing data based on this, realizing real-time monitoring and adjustment of key parameters of cable production, ensuring product quality and consistency.

[0111] The execution control module is used to input the standard twisting parameter data and the standard shell processing data into the twisting device and the shell processing device.

[0112] The execution control module directly inputs the standard twisting parameter data and standard shell processing data calculated or obtained by the monitoring and adjustment module into the twisting device and shell processing device, realizing the automatic control of the production process, reducing human intervention and errors, and improving production efficiency and stability.

[0113] The coding establishment module is used to input standard twisting parameter data and standard shell processing data into the parameter coding set, obtain the production information coding group and establish the corresponding relationship between the production information coding group, actual cable category data and batch information data.

[0114] The coding establishment module inputs the standard twisting parameter data and standard shell processing data into the parameter coding set, generates a production information coding group, and establishes a corresponding relationship with the production batch and the actual cable category, thereby realizing the standardization and digital management of production information, and providing important support for the company's production management, quality control and continuous improvement. At the same time, coding establishment also enhances the traceability of production information, facilitating subsequent product quality traceability and production data analysis.

[0115] The cable production monitoring system based on the Internet of Things establishes multiple functional modules by integrating data collection, monitoring adjustment, execution control and coding, realizing comprehensive, real-time and accurate monitoring and management of the cable production process. It not only improves production efficiency and product quality, but also enhances the transparency and traceability of production information, providing strong support for the company's intelligent transformation and continuous improvement.

[0116] It should be understood by those skilled in the art that the embodiments of the present invention can be provided as methods, systems or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. Among them, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0117] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A cable production monitoring method based on the Internet of Things, characterized in that: The steps include: Step S1, setting a collection time interval to obtain data of the cable core and actual diameter data of the cable casing; Step S2, judging whether the actual torsion angle data is standard torsion angle data, outputting a first judgment result, analyzing the torsion situation according to the first judgment result, calculating the predicted torque parameter according to the torsion situation, inputting the predicted torque parameter into a preset standard twisting parameter data set, and obtaining the standard twisting parameter data; Step S3, judging whether the actual diameter data is within the standard diameter data range, and outputting a second judgment result, obtaining the actual shell processing data according to the second judgment result, inputting the actual shell processing data into a preset standard shell processing data set, and obtaining the standard shell processing data; Step S4, inputting the standard twisting parameter data and the standard shell processing data into the twisting device and the shell processing device; Step S5, inputting the standard twisting parameter data and the standard shell processing data into a preset parameter coding set, obtaining the production information coding represented by the standard twisting parameter data and the standard shell processing data and establishing a corresponding relationship; The step S1 includes the following sub-steps: Step S101, collecting actual cable category data, inputting the cable category data into a collection parameter correspondence table, wherein the collection parameter correspondence table includes standard cable category data and corresponding collection time intervals, obtaining a collection time interval corresponding to the actual cable category, and inputting the collection time interval into a cable production device; Step S102, acquiring actual torsion angle data of the cable core and actual diameter data of the cable housing according to a set collection time interval; The step S2 includes the following sub-steps: Step S201, inputting the actual cable category data into the standard library, searching for standard cable category data identical to the actual cable category data, obtaining standard torsion angle data corresponding to the standard cable category data, comparing the actual torsion angle data with the standard torsion angle data, and outputting a first judgment result; Step S202, analyzing the torsion condition according to the first judgment result, wherein the torsion condition includes loose torsion and excessive torsion; Step S203, calculating the torque according to the torsion condition and outputting it as a predicted torque parameter; Step S204, inputting the predicted torque parameter into the standard twisting parameter data set, searching for standard twisting parameter data corresponding to the standard twisting parameter that is the same as the predicted twisting parameter, and outputting the standard twisting parameter data; The first judgment result in step S201 includes that the actual torsion angle data is equal to the standard torsion angle data, the actual torsion angle data is greater than the standard torsion angle data, and the actual torsion angle data is less than the standard torsion angle data; The step S202 analyzes the torsion situation according to the first judgment result as follows: If the actual torsion angle data is greater than the standard torsion angle data, the torsion condition is excessive torsion; If the actual torsion angle data is less than the standard torsion angle data, the torsion condition is loose torsion; The step S203 calculates the torque according to the torsion condition as: If the torsion condition is loose torsion, the actual cable category data is input into the preset torque data set, and the standard torque parameters corresponding to the standard cable category data that is the same as the actual cable category data are searched, and the output is the predicted torque parameters; If the torsion condition is excessive torsion, input the actual cable category data into the preset torque data set, find the standard torque parameters corresponding to the standard cable category data that is the same as the actual cable category data, obtain the actual torque, and calculate the actual stiffness. The mathematical expression is: Among them, K T is the actual stiffness, T actual is the actual torque, θ actual is the actual torsion angle data; Calculate the predicted torque parameter, the mathematical expression is: T design =K T ×θ design Among them, T design To predict the torque parameter, θ design To predict torsion parameters; The step S3 includes the following sub-steps: Step S301, inputting the actual diameter data into the standard library, obtaining the standard diameter data range corresponding to the standard cable category data, judging whether the actual diameter data is within the standard diameter data range, and outputting a second judgment result, wherein the second judgment result includes that the actual diameter data is within the standard diameter data range and the actual diameter data is not within the standard diameter data range; Step S302, analyzing the second judgment result: If the second judgment result is that the actual diameter data is within the standard diameter data range, no instruction is output; If the second judgment result is that the actual diameter data is not within the standard diameter data range, the actual diameter data is input into the standard library to search for standard shell processing data corresponding to the standard diameter data closest to the actual diameter data.

2. The cable production monitoring method based on the Internet of Things according to claim 1, characterized in that: The step S4 includes the following sub-steps: Step S401, acquiring standard twisting parameter data and inputting the standard twisting parameter data into a twisting device; Step S402, acquiring standard shell processing data and inputting the standard shell processing data into a shell processing device.

3. The cable production monitoring method based on the Internet of Things according to claim 2, characterized in that: The step S5 includes the following sub-steps: Step S501, inputting the standard twisting parameter data and the standard shell processing data into the parameter code set, respectively obtaining the production information codes represented by the standard twisting parameter data and the standard shell processing data, and merging the production information codes represented by the standard twisting parameter data and the standard shell processing data and outputting them as a production information code group; Step S502, establishing and storing the corresponding relationship between the production information coding group, the actual cable category data and the batch information data.

4. A cable production monitoring system based on the Internet of Things, which is applied to the cable production monitoring method based on the Internet of Things as described in any one of claims 1 to 3, characterized in that: It includes data acquisition module, monitoring and adjustment module, execution control module and coding establishment module: The data acquisition module is used to set an acquisition time interval, and obtain the actual torsion angle data of the cable core and the actual diameter data of the cable housing according to the acquisition time interval; The monitoring and adjustment module is used to determine whether the actual torsion angle data is the standard torsion angle data, output a first judgment result, calculate the predicted torque parameter according to the first judgment result, input the predicted torque parameter into a preset standard twisting parameter data set, obtain the standard twisting parameter data, determine whether the actual diameter data is within the standard diameter data range and output a second judgment result, obtain the actual shell processing data according to the second judgment result, and obtain the standard shell processing data according to the actual shell processing data; The execution control module is used to input the standard twisting parameter data and the standard shell processing data into the twisting device and the shell processing device; The coding establishment module is used to input standard twisting parameter data and standard shell processing data into the parameter coding set, obtain the production information coding group and establish the corresponding relationship between the production information coding group, actual cable category data and batch information data.

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