A system and encryption method for remote maintenance of sewing equipment

Abstract

The present invention discloses a system and encryption method for remote maintenance of sewing equipment. In order to overcome the problem that the prior art lacks confidentiality of the equipment data transmission process and confidentiality of partner data; the system of the present invention includes: a sewing factory, which associates and maps product data into equipment data, and encrypts the equipment data and uploads it to a cloud database; or directly sends a maintenance request to a sewing equipment manufacturer; a cloud database, which stores the encrypted data uploaded by the sewing factory; the sewing equipment manufacturer, which obtains the corresponding encrypted equipment parameters from the cloud database regularly or after receiving the maintenance request, matches the maintenance method after decryption, and issues maintenance instructions. The encrypted transmission of equipment data between the sewing factory and the sewing equipment manufacturer prevents others from intercepting the parameters and ensures information security. After the product data is mapped into equipment data and uploaded to the cloud database, the possibility of confidentiality is reduced and the privacy data between partners is protected.

Description

Technical Field

[0001] The invention relates to the field of equipment maintenance, and in particular to a system and an encryption method for remote maintenance of sewing equipment. Background Art

[0002] Manufacturers of sewing equipment have the obligation to maintain and repair the sewing equipment they sell, but they also want to be able to manage these sewing equipment remotely, which eliminates the need for on-site participation and saves human resources.

[0003] The current intelligent sewing equipment has networking function, which can upload the equipment's own parameters to the factory's gateway for equipment maintenance and other operations. For example, a "sewing equipment maintenance management system" disclosed in Chinese patent documents, with announcement number CN105785884B, includes a main control module of the sewing machine and a client wirelessly connected to the main control module, the client is connected to the display terminal and the monitoring terminal, the main control module collects the operating data of the sewing equipment and transmits it to the display terminal through the client, which is classified and displayed according to a preset method, and the monitoring terminal monitors the operating data in real time and issues an alarm prompt through the display terminal. However, this solution does not take into account the confidentiality of data.

[0004] On the one hand, the sewing equipment manufacturer remotely operates and maintains the equipment in the factory based on the equipment parameters fed back by monitoring; because the parameters involve corporate secrets, it is necessary to prevent others from intercepting the parameters during the data transmission process to ensure information security.

[0005] On the other hand, since the equipment manufacturer and the factory may be different companies, the parameter monitoring of operation and maintenance may involve product data, including the product's design pattern and shape, which the factory does not want the equipment manufacturer to know, which involves confidentiality issues of the partners. Summary of the invention

[0006] The present invention mainly solves the problem that the prior art lacks confidentiality of the device data transmission process and the data confidentiality of the partners; it provides a system and encryption method for remote maintenance of sewing equipment to prevent the device data from being intercepted by outsiders, and protect the privacy data between partners while maintaining the equipment itself.

[0007] The above technical problems of the present invention are mainly solved by the following technical solutions:

[0008] A system for remote maintenance of sewing equipment, comprising:

[0009] Sewing factories map product data to equipment data, encrypt the equipment data and upload it to the cloud database; or send maintenance requests directly to the sewing equipment manufacturer;

[0010] A cloud database that stores encrypted data uploaded by sewing factories;

[0011] Sewing equipment manufacturers obtain the corresponding encrypted equipment parameters from the cloud database regularly or after receiving a maintenance request, decrypt them, match the maintenance method, and issue maintenance instructions.

[0012] The encrypted device data is uploaded to the cloud database. The encrypted transmission of device data between the sewing factory and the sewing equipment manufacturer prevents others from intercepting the parameters and ensures information security. The product data is mapped to the device data and uploaded to the cloud database to reduce the possibility of confidentiality and protect the privacy data between partners.

[0013] Preferably, the sewing factory comprises:

[0014] A product database storing set product data for each product;

[0015] Product identification module, which obtains product data produced by sewing equipment at each stage;

[0016] The data judgment module compares the acquired product data with the corresponding set product data. If the product data error is greater than the set threshold, the product data is mapped into device parameters and a maintenance request is sent;

[0017] The product data mapping module associates product data with equipment parameters, completes quantitative mapping through time alignment, and retains mapping flags.

[0018] Map product data to device data and upload it to the cloud database to reduce the possibility of confidentiality and protect the privacy of data between partners. Through time alignment, quantitative mapping of product data and device parameters is completed, and the corresponding device parameters are obtained through the error time period of product data.

[0019] Preferably, the sewing equipment manufacturers include:

[0020] The historical fault database, including the equipment fault database and the product error database, matches the decrypted equipment parameters with the corresponding data in the historical fault database according to the mapping mark;

[0021] Equipment fault database, which stores historical equipment fault problems, corresponding equipment parameter performance and solutions;

[0022] The product error library stores the relationship between equipment parameters and product data and historical solutions.

[0023] The presence or absence of mapping marks can be used to determine whether it is a device problem or a product error, and the device parameters need to be adjusted. Solutions to the problems can be obtained by matching historical data. This is more targeted, and even if the same parameters are present, different problems can be analyzed, and product errors can be identified under normal operation of the equipment.

[0024] Preferably, the sewing factory further comprises:

[0025] An image encryption module encrypts the monitored device data or the mapped device data into image data and uploads it to the cloud database;

[0026] The sewing equipment manufacturers also include:

[0027] The image decryption module restores the image data obtained from the cloud database into device data for maintenance judgment;

[0028] Maintenance requests and maintenance instructions between the sewing factory and the sewing equipment manufacturer are encrypted using a symmetric algorithm.

[0029] The data interaction and instruction interaction are encrypted respectively through different encryption methods to enhance the security of information.

[0030] An encryption method for remote maintenance of sewing equipment comprises the following steps:

[0031] S1: The sewing factory monitors the equipment data of the sewing equipment and the product data of each stage in real time, and encrypts the equipment data and uploads it to the cloud database;

[0032] S2: If it is determined that the error of the product data exceeds the threshold, the product data is mapped into equipment parameters, and a maintenance request is sent to the sewing equipment manufacturer after retaining the mapping mark;

[0033] S3: After receiving the maintenance request or at a fixed time, the sewing equipment manufacturer obtains the corresponding equipment data from the cloud database, decrypts it, matches the maintenance method in the corresponding historical database, and issues maintenance instructions.

[0034] The encrypted device data is uploaded to the cloud database. The encrypted transmission of device data between the sewing factory and the sewing equipment manufacturer prevents others from intercepting the parameters and ensures information security. The product data is mapped to the device data and uploaded to the cloud database to reduce the possibility of confidentiality and protect the privacy data between partners.

[0035] Preferably, the device data encryption is image encryption; the specific process of image encryption is:

[0036] Construct a pixel matrix with time as the horizontal axis and object as the vertical axis;

[0037] The device parameters are converted into binary numbers;

[0038] With eight binary numbers as one pixel bit, the device parameters are converted into three pixel bits representing RGB values ​​in sequence, and zeros are added to the front if the number is insufficient.

[0039] According to the converted RGB values, the corresponding color blocks are generated and filled into the corresponding positions of the pixel matrix.

[0040] Through the process of this solution, the equipment parameters are systematically encrypted into image data. The encryption rules are only set between the sewing factory and the sewing equipment manufacturer. Only the two parties know the objects represented by the vertical axis and the time represented by the horizontal axis, avoiding data leakage due to interception by a third party during the transmission process and ensuring data security.

[0041] Preferably, the specific process of step S2 is as follows:

[0042] Subtract the product data obtained through monitoring from the preset product data in the product database to obtain the product data error;

[0043] Compare whether the product data error is greater than the set threshold. If so, map the product data to the corresponding device parameters and retain the mapping flag. Otherwise, continue monitoring and judging.

[0044] The mapped device parameter image is encrypted and uploaded to the cloud database together with the mapping mark.

[0045] The mapping flag is reserved to distinguish whether the device parameter is used to determine whether it is an inherent problem of the device or a parameter configuration problem in the product production process.

[0046] Preferably, the mapping process is:

[0047] Set association parameters to associate device data that affects the same product data with the product data;

[0048] When the error of the product data is greater than a threshold, the product data is mapped to the corresponding associated device data of the stage.

[0049] Map product data into device data and upload it to the cloud database to reduce the possibility of confidentiality and protect the privacy data between partners.

[0050] Preferably, the specific process of step S3 is as follows:

[0051] After receiving a maintenance request or at a fixed time, the corresponding equipment data is obtained from the cloud database;

[0052] Reversely convert the encrypted image data into device data corresponding to the time and object;

[0053] Determine whether the device data has a mapping mark, if so, match the device data with the data in the product error library; otherwise, match the data with the data in the device fault library;

[0054] If the match is successful, the corresponding solution is obtained, a maintenance instruction is generated, and it is encrypted and sent to the sewing factory. Otherwise, an expert request is sent.

[0055] The presence or absence of the mapping mark is matched to the corresponding historical database to distinguish the device parameters and determine whether it is an inherent problem of the device or a parameter configuration problem in the product production process.

[0056] The beneficial effects of the present invention are:

[0057] 1. Upload the encrypted device data to the cloud database. The encrypted transmission of device data between the sewing factory and the sewing equipment manufacturer prevents others from intercepting the parameters and ensures information security.

[0058] 2. Map product data into device data and upload it to the cloud database to reduce the possibility of confidentiality and protect the privacy data between partners.

[0059] 3. The presence or absence of the mapping mark is matched to the corresponding historical database to distinguish whether the device parameters are used to determine whether they are inherent problems of the device or parameter configuration problems in the product production process.

[0060] 4. Encrypt data interaction and instruction interaction separately through different encryption methods to enhance information security.

[0061] 5. Encrypt device parameters into image data in an orderly manner to avoid leakage caused by third-party interception during data transmission and ensure data security. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a data transmission schematic diagram of the equipment remote maintenance system of the present invention.

[0063] Figure 2 It is a flow chart of the encryption algorithm for remote maintenance of equipment of the present invention.

[0064] In the figure, 1. Sewing factory, 1-1. Product database, 1-2. Product identification library, 1-3. Data judgment module, 1-4. Product data mapping module, 1-5. Image encryption module, 2. Cloud database, 3. Sewing equipment manufacturer, 3-1. Historical fault library, 3-2. Image decryption module, 3-3. Equipment fault library, 3-4 Product error library. DETAILED DESCRIPTION

[0065] The technical solution of the present invention is further specifically described below through embodiments and in conjunction with the accompanying drawings.

[0066] Example:

[0067] A system for remote maintenance of sewing equipment in this embodiment, such as Figure 1 As shown, it includes a sewing factory 1, a cloud database 2 and a sewing equipment manufacturer 3.

[0068] Sewing Factory 1 purchases sewing equipment for the production of products, including sewing of clothing.

[0069] The sewing machine manufacturer 3 manufactures sewing machines, sells the sewing machines to the sewing factory 1, and has the obligation to maintain and repair the sewing machines.

[0070] The sewing factory 1 maps the product data into equipment data, encrypts the equipment data image and uploads it to the cloud database 2. Or the sewing factory 1 directly sends an encrypted maintenance request to the sewing equipment manufacturer 3.

[0071] The sewing factory 1 includes a product database 1-1, a product identification module 1-2, a data judgment module 1-3, a product data mapping module 1-4 and an image encryption module 1-5.

[0072] The product database 1-1 stores the set product data of each product, and stores the ideal product data of each stage of the product in advance, such as setting the parameters such as the shape, size, position and stitch density of the pattern in the stage of embroidery of clothes.

[0073] The product recognition module 1-2 obtains product data produced by the sewing equipment at each stage, including but not limited to cameras and pressure sensors.

[0074] For example, a camera can be used to photograph semi-finished products at each stage, and product data can be obtained through image recognition. For example, product data corresponding to the position, size, and stitch density of clothing patterns after the embroidery stage can be obtained.

[0075] The data judgment module 1-3 compares the acquired product data with the corresponding set product data. If the product data error is greater than the set threshold, the product data is mapped into device parameters and a maintenance request is sent.

[0076] The product data obtained by each sensor is subtracted from the corresponding preset product data in the product database to obtain the product data error, which is compared with the set error threshold. If it is greater than the error threshold, it means that the parameter error is too large and needs to be adjusted.

[0077] For example, the acquired position of the pattern on the clothes is compared with the preset position of the pattern. If the deviation exceeds the error threshold of 5 cm, it is determined that the parameters need to be adjusted.

[0078] The product data mapping modules 1-4 associate product data with equipment parameters, complete quantitative mapping through time alignment, and retain mapping flags.

[0079] Map the product parameters to the device parameters, retain the mapping mark and send the encrypted maintenance request.

[0080] For example, the product parameter of pattern position is associated with equipment parameters such as needle insertion time, transfer speed, and initial needle drop position. Therefore, the relevant equipment data of the embroidery stage is associated with the product parameter of pattern position, and the product parameter of pattern position is mapped to the corresponding equipment parameter. The time of the corresponding equipment data takes all the equipment data of the embroidery stage.

[0081] The image encryption module 1-5 encrypts the monitored device data or the mapped device data into image data and uploads it to the cloud database.

[0082] The specific process of image encryption is:

[0083] A pixel matrix is ​​constructed with time as the horizontal axis and the object as the vertical axis.

[0084] The device parameters are converted to binary numbers.

[0085] With eight binary numbers as one pixel bit, the device parameters are converted into three pixel bits representing RGB values ​​in sequence, and zeros are added to the front if the bits are insufficient.

[0086] According to the converted RGB values, the corresponding color blocks are generated and filled into the corresponding positions of the pixel matrix.

[0087] The equipment parameters are systematically encrypted into image data. The encryption rules are only set between the sewing factory and the sewing equipment manufacturer. Only the two parties know the objects represented by the vertical axis and the time represented by the horizontal axis, avoiding data leakage due to third-party interception during transmission and ensuring data security.

[0088] The cloud database 2 stores the encrypted data uploaded by the sewing factory 1 and cleans it up regularly.

[0089] The sewing equipment manufacturer 3 obtains the corresponding encrypted equipment parameters from the cloud database 2 at regular intervals or after receiving a maintenance request, matches the maintenance method after decryption, and issues a maintenance instruction.

[0090] The sewing equipment manufacturer 3 includes a historical fault library 3-1 and an image decryption module 3-2.

[0091] The image decryption module 3 - 2 restores the image data obtained from the cloud database 2 into device data and performs maintenance judgment.

[0092] The restoration process of image data is the reverse process of image encryption. The RGB data is converted into binary numbers in sequence. The horizontal axis corresponds to time, and the vertical axis corresponds to the object.

[0093] The corresponding original data of the equipment parameters are obtained through binary conversion.

[0094] The historical fault library 3-1 includes an equipment fault library 3-3 and a product error library 3-4, and the decrypted equipment parameters are matched with the corresponding data in the historical fault library 3-1 according to the mapping mark.

[0095] The equipment fault library 3-3 stores historical equipment fault problems, corresponding equipment parameter performances and solutions. For example, the fault problem is that a certain component lacks wheel skating oil; the corresponding equipment parameters are that the action execution time of the component is prolonged and the temperature rises; the solution is to add wheel skating oil.

[0096] The product error library 3-4 stores the association between equipment parameters and product data and historical solutions.

[0097] The presence or absence of mapping marks can be used to determine whether it is a device problem or a product error, and the device parameters need to be adjusted. Solutions to the problems can be obtained by matching historical data. This is more targeted, and even if the same parameters are present, different problems can be analyzed, and product errors can be identified under normal operation of the equipment.

[0098] In this embodiment, the maintenance request and maintenance instruction between the sewing factory and the sewing equipment manufacturer are encrypted by a symmetric algorithm. The symmetric encryption algorithm includes but is not limited to the DES algorithm, 3DES algorithm, TDEA algorithm, Blowfish algorithm, RC5 algorithm and IDEA algorithm.

[0099] The data interaction and instruction interaction are encrypted respectively through different encryption methods to enhance the security of information.

[0100] An encryption method for remote maintenance of sewing equipment in this embodiment, such as Figure 2 As shown, the following steps are included:

[0101] S1: The sewing factory monitors the equipment data of the sewing equipment and the product data of each stage in real time, and encrypts the equipment data and uploads it to the cloud database. The equipment data encryption is image encryption.

[0102] The specific process of image encryption is:

[0103] A pixel matrix is ​​constructed with time as the horizontal axis and the object as the vertical axis.

[0104] The device parameters are converted to binary numbers.

[0105] With eight binary numbers as one pixel bit, the device parameters are converted into three pixel bits representing RGB values ​​in sequence, and zeros are added to the front if the bits are insufficient.

[0106] According to the converted RGB values, the corresponding color blocks are generated and filled into the corresponding positions of the pixel matrix.

[0107] Through the process of this solution, the equipment parameters are systematically encrypted into image data. The encryption rules are only set between the sewing factory and the sewing equipment manufacturer. Only the two parties know the objects represented by the vertical axis and the time represented by the horizontal axis, avoiding data leakage due to interception by a third party during the transmission process and ensuring data security.

[0108] S2: If it is determined that the error of the product data exceeds a threshold, the product data is mapped into equipment parameters, and a maintenance request is sent to the sewing equipment manufacturer after retaining the mapping mark.

[0109] The product data obtained by monitoring is subtracted from the preset product data in the product database to obtain the product data error.

[0110] Compare whether the product data error is greater than the set threshold. If so, map the product data to the corresponding device parameters and retain the mapping mark. Otherwise, continue monitoring and judging.

[0111] The mapping process is:

[0112] Set association parameters to associate device data that affects the same product data with the product data;

[0113] When the error of the product data is greater than a threshold, the product data is mapped to the corresponding associated device data of the stage.

[0114] Map product data into device data and upload it to the cloud database to reduce the possibility of confidentiality and protect the privacy data between partners.

[0115] The mapped device parameter image is encrypted and uploaded to the cloud database together with the mapping mark.

[0116] The mapping flag is reserved to distinguish whether the device parameter is used to determine whether it is an inherent problem of the device or a parameter configuration problem in the product production process.

[0117] S3: After receiving the maintenance request or at a fixed time, the sewing equipment manufacturer obtains the corresponding equipment data from the cloud database, decrypts it, matches the maintenance method in the corresponding historical database, and issues maintenance instructions.

[0118] After receiving a maintenance request or at a scheduled time, the corresponding device data is obtained from the cloud database.

[0119] The encrypted image data is reversely converted into device data corresponding to the time and object.

[0120] Determine whether the device data has a mapping mark. If so, match the device data with the data in the product error library; otherwise, match the data with the data in the device fault library.

[0121] If the match is successful, the corresponding solution is obtained, a maintenance instruction is generated, and it is encrypted and sent to the sewing factory. Otherwise, an expert request is sent.

[0122] The presence or absence of the mapping mark is matched to the corresponding historical database to distinguish the device parameters and determine whether it is an inherent problem of the device or a parameter configuration problem in the product production process.

[0123] The solution of this embodiment uploads the encrypted device data to the cloud database. The encrypted transmission of device data between the sewing factory and the sewing equipment manufacturer prevents others from intercepting the parameters and ensures information security. The product data is mapped into device data and uploaded to the cloud database to reduce the possibility of confidentiality and protect the privacy data between partners.

[0124] It should be understood that the embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope limited by the appended claims of the application.

Claims

1. A system for remote maintenance of sewing equipment, characterized in that: include: In the sewing factory, the product data with errors exceeding the threshold are mapped into equipment data, and the equipment data is encrypted and uploaded to the cloud database; A cloud database that stores encrypted data uploaded by sewing factories; The sewing equipment manufacturer obtains the corresponding encrypted equipment data from the cloud database at regular intervals or after receiving the maintenance request directly sent by the sewing factory to the sewing equipment manufacturer, decrypts it and matches the maintenance method, and issues maintenance instructions; The sewing factory includes: a product data mapping module that associates product data with equipment data, completes quantitative mapping through time alignment, and retains mapping marks; an image encryption module that encrypts real-time monitored equipment data or mapped equipment data into image data and uploads it to the cloud database; The sewing equipment manufacturer includes: a historical fault library, including an equipment fault library and a product error library, and the decrypted equipment data is matched with the data in the corresponding historical fault library according to the mapping mark; the equipment fault library stores historical equipment fault problems, corresponding equipment data performances and solutions; the product error library stores the association between equipment data and product data and historical solutions; matching the decrypted equipment data with the data in the corresponding historical fault library according to the mapping mark is specifically as follows: judging whether the equipment data has a mapping mark, if so, matching the equipment data with the data in the product error library; otherwise, matching the equipment data with the data in the equipment fault library; the equipment data is obtained by inverse conversion of the encrypted image data.

2. A system for remote maintenance of sewing equipment according to claim 1, characterized in that: The sewing factory comprises: A product database storing set product data for each product; Product identification module, which obtains product data produced by sewing equipment at each stage; The data judgment module compares the acquired product data with the corresponding set product data. If the product data error is greater than the set threshold, the product data is mapped into device data and a maintenance request is sent.

3. A system for remote maintenance of sewing equipment according to claim 1 or 2, characterized in that: The sewing equipment manufacturers also include: The image decryption module restores the image data obtained from the cloud database into device data for maintenance judgment; Maintenance requests and maintenance instructions between the sewing factory and the sewing equipment manufacturer are encrypted using a symmetric algorithm.

4. An encryption method for remote maintenance of sewing equipment, using a system for remote maintenance of sewing equipment as claimed in any one of claims 1 to 3, characterized in that: include: S1: The sewing factory monitors the equipment data of the sewing equipment and the product data of each stage in real time; encrypts the equipment data and uploads it to the cloud database; S2: If it is determined that the error of the product data exceeds the threshold, the product data is mapped to the equipment data, and a maintenance request is sent to the sewing equipment manufacturer after retaining the mapping mark; S2 includes: subtracting the product data obtained by monitoring from the preset product data in the product database to obtain the product data error; comparing whether the product data error is greater than a set threshold, if so, mapping the product data to the corresponding device data and retaining the mapping mark, otherwise, continuing monitoring and judging; The mapped device data image is encrypted and uploaded to the cloud database together with the mapping mark; S3: After receiving the maintenance request or at a fixed time, the sewing equipment manufacturer obtains the corresponding equipment data from the cloud database, decrypts it, matches the maintenance method in the corresponding historical database, and issues maintenance instructions; S3 includes: obtaining corresponding equipment data from a cloud database after receiving a maintenance request or at a fixed time; Reversely convert the encrypted image data into device data corresponding to the time and object; Determine whether the device data has a mapping mark, if so, match the device data with the data in the product error library; otherwise, match the data with the data in the device fault library; If the match is successful, the corresponding solution is obtained, a maintenance instruction is generated, and it is encrypted and sent to the sewing factory. Otherwise, an expert request is sent.

5. The encryption method for remote maintenance of sewing equipment according to claim 4, characterized in that: The device data encryption is image encryption; the specific process of image encryption is: Construct a pixel matrix with time as the horizontal axis and object as the vertical axis; The device data is converted into binary numbers; With eight binary numbers as one pixel bit, the device data is converted into three pixel bits representing RGB values ​​in sequence, and zeros are added to the front if the number is insufficient. According to the converted RGB values, the corresponding color blocks are generated and filled into the corresponding positions of the pixel matrix.

6. The encryption method for remote maintenance of sewing equipment according to claim 4, characterized in that: The mapping process includes: Set association parameters to associate device data that affects the same product data with the product data.

7. The encryption method for remote maintenance of sewing equipment according to claim 4, characterized in that: The mapping process also includes: When the error of the product data is greater than a threshold, the product data is mapped to the corresponding associated device data of the stage.

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