Upgrade management system and method for electric control system of sewing machine

Abstract

The embodiment of the invention relates to the field of industrial automation control, and discloses an upgrade management system and method for an electric control system of a sewing machine. The system comprises a cloud platform management module and an electric control system. The electric control system comprises an upgrading module, and the upgrading module establishes communication connection with the cloud platform management module through an HTTP protocol; the cloud platform management module is used for managing the firmware version of the electronic control system and sending an upgrading notification to the upgrading module through an HTTP protocol when the cloud platform newly receives the firmware version; the upgrading module is used for acquiring a firmware version from the cloud platform according to the upgrading notification to carry out upgrading operation, and sending an upgrading state to the cloud platform management module through an HTTP protocol; and the cloud platform management module is also used for determining an upgrading result according to the upgrading state. The technical problems that in the prior art, an electric control system and a gateway of the sewing machine need to be configured in advance, and in the upgrading process, the requirement for network conditions is high, the downloading speed is low, and even downloading fails are at least solved.

Description

Technical Field

[0001] The present application relates to the field of industrial automation control technology, and in particular to an upgrade management system and method for an electric control system of a sewing machine. Background Art

[0002] With the continuous advancement of intelligent manufacturing and industry, the electronic control system (i.e., electronic control system) of sewing machines is gradually developing in the direction of digitalization and intelligence. The upgrade of the electronic control system of a sewing machine mainly refers to the technical transformation of improving the performance, function, or adapting to modern production needs of the sewing machine by improving the software and hardware of the electronic control system of the sewing machine. This application mainly focuses on improving the software aspects of the electronic control system of a sewing machine.

[0003] Traditional upgrade solutions for the electronic control systems of sewing machines usually require manual operation or manual updates with the help of physical media such as USB, which results in inconvenient upgrade processes, low efficiency, and prone to errors. Especially in large-scale production scenarios, manual upgrades are not only time-consuming, but also difficult to ensure the synchronization of upgrades for the electronic control systems of various sewing machines. Some remote upgrade management solutions based on cloud platforms and HTTP communication can effectively solve the above problems.

[0004] However, the inventors found that there are at least the following technical problems in the related art:

[0005] The remote upgrade management solution based on cloud platform and HTTP communication requires the electronic control system and gateway of the sewing machine to be configured in advance. In addition, the network conditions are relatively high during the upgrade process. When the electronic control systems of multiple sewing machines share the same network for upgrade, it is easy to experience slow download speed or even download failure. Summary of the invention

[0006] One purpose of the present application is to provide an upgrade management system and method for the electronic control system of a sewing machine, at least to solve the technical problems in the related technology that the electronic control system and gateway of the sewing machine need to be configured in advance and during the upgrade process, the network conditions are relatively high, and the download speed is slow or even the download fails.

[0007] To achieve the above objectives, some embodiments of the present application provide the following aspects:

[0008] In a first aspect, some embodiments of the present application further provide an upgrade management system for an electronic control system of a sewing machine. The system includes a cloud platform management module and an electronic control system. The upgrade module is disposed in the electronic control system and establishes a communication connection with the cloud platform management module through the HTTP protocol. The cloud platform management module is configured to manage the firmware version of the electronic control system. When a new firmware version is received on the cloud platform, an upgrade notification is sent to the upgrade module through the HTTP protocol. The upgrade module is configured to obtain the firmware version from the cloud platform for an upgrade operation according to the upgrade notification and send the upgrade status to the cloud platform management module through the HTTP protocol. The cloud platform management module is further configured to determine an upgrade result according to the upgrade status.

[0009] In a second aspect, some embodiments of the present application further provide an upgrade method for an electronic control system of a sewing machine. The method is characterized in that the method is applied to the system as described above. The method includes: managing the firmware version of the electronic control system, and when a new firmware version is received, sending an upgrade notification to the electronic control system through the HTTP protocol; obtaining the firmware version from the cloud platform management module for an upgrade operation according to the upgrade notification, and sending the upgrade status to the cloud platform management module through the HTTP protocol; and determining an upgrade result according to the upgrade status.

[0010] Compared with the related art, in the solution provided by the embodiments of the present application, the system includes a cloud platform management module and an electric control system; the upgrade module is arranged in the electric control system. By setting such a system architecture, the functions and collaboration relationships of each part can be clarified, thereby avoiding to a certain extent the problem of complex configuration caused by unclear system structure in the related art solutions and reducing the dependence on the pre-complex configured electric control system and gateway; the upgrade module establishes a communication connection with the cloud platform management module through the HTTP protocol; the cloud platform management module is used to manage the firmware version of the electric control system. When a new firmware version is received on the cloud platform, an upgrade notification is sent to the upgrade module through the HTTP protocol. In this way, the upgrade process can be made more orderly. Since the upgrade module of each electric control system independently receives the notification from the cloud platform management module, it is possible to avoid the chaos caused by multiple electric control systems sharing the network for upgrade in the same network. The upgrade module is used to obtain the firmware version from the cloud platform for upgrade operations according to the upgrade notification and send the upgrade status to the cloud platform management module through the HTTP protocol; the cloud platform management module is further used to determine the upgrade result according to the upgrade status. By means of this real-time feedback of the upgrade status, problems occurring during the upgrade process can be timely discovered and processed. Compared with the situation in the related art where multiple sewing machines share the network and may experience download failures but cannot be timely aware of and handle them, it can better ensure the smooth progress of the upgrade and reduce the probability of download failures. At the same time, since the upgrade module of each electric control system independently interacts with the cloud platform, it can also reduce the competition for network bandwidth among multiple electric control systems during simultaneous upgrades and avoid the problem of slow download speed to a certain extent. In addition, this system can also perform remote operations through the network to realize the automatic upgrade of the sewing machine electric control system, which can not only greatly improve the upgrade efficiency, reduce the labor cost, but also ensure the consistent upgrade effect of each sewing machine and guarantee the stability and reliability of the upgrade process. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] One or more embodiments are exemplarily illustrated by pictures in the corresponding drawings. These exemplary illustrations do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings are represented as similar elements, unless otherwise stated, and the drawings in the figures do not constitute a scale limitation.

[0012] Figure 1 FIG. is an exemplary schematic diagram of an upgrade management system for an electric control system of a sewing machine according to some embodiments of the present application;

[0013] Figure 2 FIG. is an exemplary flowchart of an upgrade management method for an electric control system of a sewing machine according to some embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0014] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the accompanying drawings in the embodiments of this application. Apparently, the described embodiments are some, but not all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this application without creative efforts shall fall within the scope of protection of this application.

[0015] First Embodiment

[0016] The first embodiment of this application relates to an upgrade management system for the electronic control system of a sewing machine. As Figure 1 shown, the system may include: a cloud platform management module and an upgrade module; the upgrade module is provided in the electronic control system and establishes a communication connection with the cloud platform management module through the HTTP protocol.

[0017] The cloud platform management module is used to manage the firmware version of the electronic control system. When a new firmware version is received on the cloud platform, an upgrade notice is sent to the upgrade module through the HTTP protocol.

[0018] The upgrade module is used to obtain the firmware version from the cloud platform for upgrade operations according to the upgrade notice, and send the upgrade status to the cloud platform management module through the HTTP protocol.

[0019] The cloud platform management module is further used to determine the upgrade result according to the upgrade status.

[0020] Among them, the upgrade module may be built-in with a network communication module (such as a Wi-Fi or Ethernet module). When the sewing machine is connected to the network, the network communication module can establish a communication connection with the cloud platform management module through the HTTP protocol.

[0021] Among them, a cloud platform is built in this application. The cloud platform integrates the cloud platform management module and is used to manage the firmware version of the electronic control system. Exemplarily, an administrator can upload the latest firmware version of the electronic control system through the cloud platform, so that the firmware version is stored on the cloud platform.

[0022] When a new firmware version is received on the cloud platform, the cloud platform management module can send an upgrade notice to the upgrade module through the HTTP protocol, thereby triggering the upgrade module to perform firmware upgrade operations. It can also automatically distribute these latest firmware versions to the electronic control systems corresponding to the sewing machines that need to be upgraded.

[0023] Exemplarily, the upgrade module can automatically download and install the latest firmware from the cloud platform according to the upgrade notification to complete the upgrade operation, and the whole process requires no manual intervention. For example, if the upgrade module determines that the version of the firmware of the electric control system is lower than that of the firmware of the cloud platform management module, it sends a firmware acquisition request to the cloud platform management module through the HTTP protocol.

[0024] Furthermore, the upgrade module can also send the upgrade status to the cloud platform management module through the HTTP protocol after the upgrade operation is completed. Further, the cloud platform management module may further include an upgrade verification module. The upgrade verification module can be used to determine the upgrade result according to the upgrade status. The upgrade result is used to indicate whether the upgrade is successful, including successful upgrade and failed upgrade, and provides necessary subsequent processing measures.

[0025] Exemplarily, the upgrade module can record an upgrade log. If the upgrade fails, it can automatically retry; if the retry is still unsuccessful, it can send an error report to the cloud platform for subsequent processing.

[0026] Optionally, in some embodiments, the system may further include a remote management module: the cloud platform may further include a remote management module to implement the functions of remote monitoring and management of the cloud platform through the remote management module. For example, an administrator can view the versions, upgrade histories, etc. of the electric control systems of all sewing machines on the cloud platform, and can also remotely start or stop the upgrade operation of the sewing machines. For another example, the remote management module can also communicate through the HTTP protocol to periodically check whether the firmware version is updated; after the firmware version is updated, the upgrade module of the electric control system obtains the new version of the firmware from the cloud platform management module, and after determining whether the electric control system is currently in an idle state, obtains the new version of the firmware from the cloud platform management module.

[0027] Optionally, in some embodiments, the electric control system may further be built-in with a timing check module for triggering a timing task to periodically request firmware update from the cloud platform. In this way, since the upgrade task is triggered by the timing task and executed in the background, independent of the production operation of the sewing machine, during the upgrade process, the sewing machine can continue to operate normally without disturbing the normal work process of the sewing machine or interrupting the production process due to the upgrade.

[0028] Optionally, in some embodiments, the system can perform a security verification before each upgrade to ensure the legality and integrity of the firmware version, preventing illegal or damaged firmware from being downloaded and installed. This verification process can effectively prevent illegal or damaged firmware from being downloaded and installed into the electric control system. By checking the legality and integrity of the firmware, security issues such as system failures and data loss caused by using malicious or damaged firmware can be avoided, ensuring the stable operation of the sewing machine electric control system and the security of production data.

[0029] It is not difficult to find that, compared with the related art, in the solution provided by the embodiment of the present application, an upgrade management system for the electric control system of a sewing machine is provided. The system includes a cloud platform management module and an electric control system; the upgrade module is set in the electric control system. Through such a system architecture setting, the functions and cooperation relationships of each part can be clarified, thereby avoiding to a certain extent the configuration complexity problem caused by unclear system structure in the solution of the related art and reducing the dependence on the pre-complex configured electric control system and gateway; the upgrade module establishes a communication connection with the cloud platform management module through the HTTP protocol; the cloud platform management module is used to manage the firmware version of the electric control system. When a new firmware version is received on the cloud platform, an upgrade notice is sent to the upgrade module through the HTTP protocol. In this way, the upgrade process can be made more orderly. Since the upgrade module of each electric control system independently receives the notice from the cloud platform management module, chaos caused by multiple electric control systems sharing the network for upgrade in the same network can be avoided. The upgrade module is used to obtain the firmware version from the cloud platform for upgrade operations according to the upgrade notice and send the upgrade status to the cloud platform management module through the HTTP protocol; the cloud platform management module is also used to determine the upgrade result according to the upgrade status. Through this way of real-time feedback of the upgrade status, problems occurring during the upgrade process can be discovered and processed in a timely manner. Compared with the situation in the related art where multiple sewing machines share the network and may experience download failures but cannot be informed and processed in a timely manner, it can better ensure the smooth progress of the upgrade and reduce the probability of download failures. At the same time, since the upgrade module of each electric control system interacts with the cloud platform independently, competition for network bandwidth caused by multiple electric control systems upgrading simultaneously can also be reduced, avoiding the problem of slow download speed to a certain extent. In addition, the system can also perform remote operation through the network to achieve automatic upgrade of the sewing machine electric control system. This can not only greatly improve the upgrade efficiency and reduce the labor cost, but also ensure that the upgrade effect of each sewing machine is consistent and guarantee the stability and reliability of the upgrade process.

[0030] In summary, compared with the related art, the solution provided by the embodiment of the present application has at least the following beneficial effects:

[0031] 1. Improve the upgrade efficiency: Through the cloud platform and HTTP communication technology, the electronic control system can receive upgrade notifications in real time, automatically download and install the upgrade package, significantly improving the upgrade efficiency.

[0032] 2. Reduce manual intervention: Through remote control and automated upgrade processes, manual operation steps can be reduced, lowering the possibility of human errors.

[0033] 3. Save costs: Abandoning the traditional method of manual upgrade via physical media such as USB can save a large amount of labor costs.

[0034] 4. Ensure upgrade consistency: All sewing machines can synchronously upgrade the electronic control system, ensuring the consistency and stability of the upgrade effect.

[0035] 5. Facilitate remote management: Administrators can remotely monitor the upgrade status of all sewing machines, and in real time understand the versions of the electronic control systems of each sewing machine, effectively avoiding production problems caused by inconsistent versions.

[0036] Second Embodiment

[0037] The second embodiment of this application relates to an upgrade management system for the electronic control system of a sewing machine. The second embodiment is an improvement based on the first embodiment. The specific improvement lies in: In this embodiment, the upgrade process of the electronic control system of the sewing machine is controlled by the device ID, and the upgrade management system can achieve flexible and precise upgrade management to meet different upgrade requirements.

[0038] Optionally, in some embodiments, the firmware version includes multiple device IDs; the device ID is used to control the upgrade process of the electronic control system of a single sewing machine;

[0039] The cloud platform management module is specifically configured to, when a new firmware version is received on the cloud platform, add the device ID to the newly received firmware version to obtain a target device ID;

[0040] The cloud platform management module is further configured to determine the upgrade mode; the upgrade mode includes at least one of the following: batch upgrade, selective upgrade, and separate upgrade of faulty devices;

[0041] The upgrade module is specifically configured to select the corresponding control system to perform the upgrade operation according to the upgrade notification, the upgrade mode, and the target device ID.

[0042] That is to say, before upgrading the electronic control system through the upgrade module, the device ID to be upgraded can be selected on the cloud platform by means of the upgrade management system. The cloud platform can add the device ID to the newly received firmware version to obtain the target device ID, so that the corresponding firmware version can be obtained according to the target device ID. Subsequently, the upgrade module can execute the upgrade operation on the electronic control system corresponding to the target device ID included in the firmware version according to the firmware version.

[0043] For example, assume that a garment manufacturing enterprise has 100 sewing machines, and each sewing machine is equipped with a corresponding electronic control system. The enterprise adopts the upgrade management system provided in this application to uniformly manage and upgrade the electronic control systems of all sewing machines. The firmware versions stored in the cloud platform management module include multiple device IDs, and each device ID corresponds to the electronic control system of a specific sewing machine. For example, the device IDs of these 100 sewing machines are S001 - S100 respectively. When the cloud platform newly receives a firmware version, it will add these device application IDs to this new firmware version to obtain the target device application ID. For example, if the new firmware version is to optimize the sewing speed control function of the sewing machine, the cloud platform will add the device application IDs S001 - S100 to this new firmware version to form a firmware version containing the target device application ID application.

[0044] Furthermore, the cloud platform management module needs to determine the upgrade mode, which is described in the following three cases:

[0045] Case 1: Batch upgrade

[0046] Suppose the enterprise decides to upgrade the electronic control systems of all 100 sewing machines to uniformly improve the performance of all sewing machines. The cloud platform management module determines that the upgrade mode is batch upgrade. At this time, the cloud platform sends an upgrade notice to the upgrade modules of all 100 sewing machines through the HTTP protocol.

[0047] After each sewing machine's upgrade module receives the notice, since the upgrade mode is batch upgrade and the target device ID includes all device IDs from S001 - S100, each sewing machine's upgrade module will find the corresponding upgrade process from the firmware version according to the device ID information stored in itself. For example, the upgrade module of the sewing machine with the device ID S025 will select the upgrade process corresponding to S025 from the firmware version and then perform the upgrade operation according to this process to upgrade the electronic control system to the new version and optimize the sewing speed control function.

[0048] Case 2: Selective upgrade

[0049] The enterprise discovers that some sewing machines (such as 10 sewing machines with equipment IDs from S001 to S010) need to be upgraded with special functions, such as adding new sewing patterns, while other sewing machines do not require it for the time being. The cloud platform management module determines that the upgrade mode is selective upgrade.

[0050] The cloud platform management module sends an upgrade notice only to the upgrade modules of these 10 sewing machines (with equipment IDs from S001 to S010) through specific control instructions. After receiving the notice, since the upgrade mode is selective upgrade and the target equipment ID includes their respective equipment IDs, the upgrade modules of these 10 sewing machines select the corresponding upgrade processes from the firmware version according to their respective equipment IDs (S001 - S010) to complete the upgrade. For example, for the sewing machine with equipment ID S005, its upgrade module will update the electronic control system according to the special upgrade process corresponding to S005 to obtain the new sewing pattern function.

[0051] Situation 3: Separate upgrade of faulty equipment

[0052] During the previous upgrade process, it was found that the upgrade of the sewing machine with equipment ID S078 failed. The cloud platform management module determines that the upgrade mode is separate upgrade of the faulty equipment.

[0053] The cloud platform management module sends an upgrade notice to this sewing machine again. After receiving the notice, since the upgrade mode is separate upgrade of the faulty equipment and the target equipment ID includes S078, the corresponding upgrade process is selected from the firmware version according to the equipment ID S078, and the upgrade is attempted again to ensure that the electronic control system of this sewing machine can be successfully updated to the latest version and the problem of the previous failed upgrade can be fixed.

[0054] It is not difficult to find that in the embodiments of the present application, according to the upgrade notice, upgrade mode, and target equipment ID, the upgrade module can accurately select the corresponding control system to perform the upgrade operation. Whether it is batch upgrade, selective upgrade, or separate upgrade of faulty equipment, the upgrade module can accurately find its corresponding upgrade process based on this information, thus ensuring the smooth upgrade of the electronic control system of each sewing machine and meeting the different upgrade requirements of the enterprise.

[0055] The third embodiment

[0056] The third embodiment of the present application relates to an upgrade management system for the electronic control system of a sewing machine. The third embodiment is an improvement based on the first embodiment. Specifically, in this embodiment, the cloud platform management module may further include an intelligent scheduling module.

[0057] Specifically, the intelligent scheduling module is used to adjust the upgrade frequency of the upgrade module according to the number of the electronic control systems.

[0058] Optionally, in some embodiments, the intelligent scheduling module specifically includes a first data acquisition unit, a second data acquisition unit, and a scheduling unit;

[0059] The first data acquisition unit is used to acquire the load condition of the cloud platform;

[0060] The second data acquisition unit is used to acquire the network bandwidth usage;

[0061] The scheduling unit is used to dynamically adjust the upgrade frequency of the upgrade module according to the number of the electric control systems, the load condition of the cloud platform, and the network bandwidth usage.

[0062] The following takes the scenario where a garment manufacturing enterprise has 100 sewing machines as an example to illustrate the working modes of the units of the intelligent scheduling module and how to dynamically adjust the upgrade frequency.

[0063] The first data acquisition unit can monitor the load condition of the cloud platform in real time. The monitoring metrics can include but are not limited to CPU usage rate, memory occupancy rate, etc. For example, at a certain moment, the first data acquisition unit monitors that the CPU usage rate of the cloud platform is 60% and the memory occupancy rate is 55%, which indicates that the cloud platform is in a certain load state but still has a certain processing capacity.

[0064] The second data acquisition unit is responsible for acquiring the network bandwidth usage in real time. Assume that the current total network bandwidth is 100 Mbps, and the second data acquisition unit monitors that the current network bandwidth usage is 40 Mbps, that is, the network bandwidth usage rate is 40%, indicating that there is still a lot of idle bandwidth available for use in the network.

[0065] Furthermore, the scheduling unit can comprehensively consider the number of the electric control systems, the load condition of the cloud platform, and the network bandwidth usage to dynamically adjust the upgrade frequency. The following gives examples in different cases:

[0066] The number of electric control systems is small, the load of the cloud platform is low, and the network bandwidth is sufficient: Assume that the enterprise has newly added 20 sewing machines, and at this time, a total of 20 electric control systems need to be upgraded. The first data acquisition unit monitors that the CPU usage rate of the cloud platform is 20% and the memory occupancy rate is 15%; the second data acquisition unit monitors that the network bandwidth usage rate is 10%. Since the number of electric control systems is small, the load of the cloud platform is low and the network bandwidth is sufficient, the scheduling unit will increase the upgrade frequency. For example, the upgrade frequency is adjusted to upgrade 15 devices per hour to accelerate the upgrade process.

[0067] The number of electronic control systems is moderate, the cloud platform load is medium, and the network bandwidth is relatively tight: The enterprise has purchased another 80 sewing machines, and now there are 100 electronic control systems to be upgraded. At a certain moment, the first data acquisition unit monitors that the CPU usage rate of the cloud platform is 70%, and the memory occupancy rate is 65%; the second data acquisition unit monitors that the network bandwidth usage rate is 75%. At this time, although the cloud platform still has a certain processing capacity, the network bandwidth is relatively tight, and the scheduling unit will appropriately reduce the upgrade frequency. For example, the upgrade frequency is adjusted to upgrade 5 devices per hour to avoid excessive pressure on the network and the cloud platform.

[0068] The number of electronic control systems is large, the cloud platform load is high, and the network bandwidth is insufficient: The enterprise expands on a large scale, and the number of sewing machines reaches 300, that is, 300 sets of electronic control systems need to be upgraded. The first data acquisition unit monitors that the CPU usage rate of the cloud platform reaches 90%, and the memory occupancy rate is 95%; the second data acquisition unit monitors that the network bandwidth usage rate is 90%. In this case, the cloud platform load is extremely high and the network bandwidth is seriously insufficient. The scheduling unit will greatly reduce the upgrade frequency and adjust the upgrade frequency to upgrade 1 device per hour to ensure the stable operation of the system and avoid failures during the upgrade process.

[0069] Optionally, in some embodiments, corresponding to different numbers of the electronic control systems, different first usage thresholds based on the cloud platform load and second usage thresholds based on the network bandwidth are set; both the first usage threshold and the second usage threshold are negatively correlated with the number of the electronic control systems;

[0070] The scheduling unit is specifically configured to adjust the upgrade frequency of the upgrade module when the cloud platform load condition reaches the first usage threshold or the network bandwidth usage condition reaches the second usage threshold.

[0071] Exemplarily, different cloud platform loads and network bandwidth usage thresholds are set according to different numbers of electronic control systems. For example, when the number of electronic control systems is small (such as less than 50), due to the overall small pressure, the CPU usage rate threshold can be increased to 90% and the network bandwidth usage rate threshold can be increased to 80% before reducing the upgrade frequency; while when the number of electronic control systems is large (such as more than 200), to avoid system overload, the CPU usage rate threshold is reduced to 70% and the network bandwidth usage rate threshold is reduced to 60% to start reducing the upgrade frequency.

[0072] Exemplarily, the intelligent scheduling module can dynamically adjust these thresholds according to the real-time number of electronic control systems. A functional relationship can be established to linearly or non-linearly reduce the resource thresholds as the number of electronic control systems increases. For example, using a simple linear function, when the number of electronic control systems increases by 50 each time, the CPU usage rate threshold is reduced by 5%.

[0073] Specifically, in some examples, assume that the factory has 50 sewing machines (the number of electronic control systems N1 = 50). Based on the factory's past experience and system performance tests, the first usage threshold based on the cloud platform load for this number of electronic control systems is set to 85% CPU usage rate (T1_1), and the second usage threshold based on network bandwidth is set to 75% network bandwidth usage rate (T2_1).

[0074] The first data acquisition unit continuously monitors the cloud platform load. For example, the current CPU usage rate of the cloud platform is 70%, which has not reached the first usage threshold of 85%. The second data acquisition unit monitors the network bandwidth usage. The current network bandwidth usage rate is 60%, which has not reached the second usage threshold of 75%. At this time, the scheduling unit can keep the upgrade module working at the normal frequency. Assume the normal frequency is to upgrade 10 devices per hour.

[0075] Furthermore, assume that the factory expands its business and adds 100 sewing machines. At this time, there are a total of 150 sewing machines (the number of electronic control systems N2 = 150). Due to the increase in the number of electronic control systems, in order to ensure the stable operation of the cloud platform and the network, the first usage threshold and the second usage threshold are correspondingly reduced. The first usage threshold based on the cloud platform load is reset to 70% CPU usage rate (T1_2), and the second usage threshold based on network bandwidth is reset to 60% network bandwidth usage rate (T2_2). The threshold has a negative correlation with the number of electronic control systems. During the upgrade process, the first data acquisition unit monitors that the CPU usage rate of the cloud platform gradually rises to 72%, reaching the newly set first usage threshold of 70%. At this time, the scheduling unit starts the adjustment mechanism and reduces the upgrade frequency of the upgrade module, such as adjusting it to upgrade 5 devices per hour, to relieve the load pressure on the cloud platform and ensure the stable progress of the upgrade process.

[0076] Furthermore, assume that the factory further expands its scale and the number of sewing machines expands to 300 (the number of electronic control systems N3 = 300). Then the threshold is adjusted again. The first usage threshold based on the cloud platform load is set to 60% CPU usage rate (T1_3), and the second usage threshold based on network bandwidth is set to 50% network bandwidth usage rate (T2_3). The second data acquisition unit monitors that the network bandwidth usage rate reaches 52%, touching the second usage threshold of 50%. Therefore, the scheduling unit adjusts the upgrade frequency. For example, the upgrade frequency is reduced to upgrade 2 devices per hour to prevent the network from being congested due to a large amount of upgrade data transmission and ensure the normal operation of the entire upgrade management system.

[0077] It should be noted that this embodiment can also be an improvement based on the second embodiment.

[0078] It is not difficult to find that in the embodiments of the present application, through the collaborative work of the first data acquisition unit, the second data acquisition unit, and the scheduling unit, the intelligent scheduling module can dynamically adjust the upgrade frequency of the upgrade module according to different actual situations, ensuring that the upgrade process of the electronic control system of the sewing machine is both efficient and stable.

[0079] Fourth Embodiment

[0080] The fourth embodiment of the present application relates to an upgrade management system for the electronic control system of a sewing machine. The fourth embodiment is an improvement based on the third embodiment. Specifically, the improvement lies in that: in this embodiment, the scheduling unit specifically includes a calculation unit and a first adjustment unit.

[0081] Specifically, the load condition of the cloud platform is characterized by the CPU usage rate of the cloud platform, and the network bandwidth usage condition is characterized by the network bandwidth usage rate;

[0082] The scheduling unit specifically includes a calculation unit and a first adjustment unit:

[0083] The calculation unit is used to determine the resource pressure coefficient according to the number of electronic control systems, the CPU usage rate of the cloud platform, and the network bandwidth usage rate;

[0084] The first adjustment unit is used to dynamically adjust the upgrade frequency of the upgrade module according to the resource pressure coefficient.

[0085] Furthermore, in some embodiments, the calculation unit is specifically used to determine the resource pressure coefficient through the following formula:

[0086] The resource pressure coefficient = (the number of electronic control systems / the maximum bearable number) × a + (CPU usage rate / 100) × b + (network bandwidth usage rate / 100) × c;

[0087] Where a, b, and c are weight coefficients, and a + b + c = 1.

[0088] For example, the resource pressure coefficient = (the number of electronic control systems / the maximum bearable number) × 0.4 + (CPU usage rate / 100) × 0.3 + (network bandwidth usage rate / 100) × 0.3. Among them, the maximum bearable number is the maximum number of electronic control system upgrades that the cloud platform and the network can support during stable operation.

[0089] Furthermore, the maximum bearing number is set to 500, and the upgrade frequency can be adjusted according to the calculated resource pressure coefficient. For example, when the resource pressure coefficient is less than 0.3, increase the upgrade frequency; when the coefficient is between 0.3 - 0.7, maintain the current upgrade frequency; when the coefficient is greater than 0.7, decrease the upgrade frequency.

[0090] In some examples, it is assumed that: Resource Pressure Coefficient = (Number of Electronic Control Systems / Maximum Load Capacity) × 0.4 + (CPU Usage Rate / 100) × 0.3 + (Network Bandwidth Usage Rate / 100) × 0.3, and the maximum load capacity is set to 500 units. At the same time, the upgrade frequencies corresponding to different resource pressure coefficient ranges are set as follows:

[0091] When the resource pressure coefficient is less than 0.3, the upgrade frequency is 20 units per hour.

[0092] When the resource pressure coefficient is between 0.3 and 0.6, the upgrade frequency is 10 units per hour.

[0093] When the resource pressure coefficient is greater than 0.6, the upgrade frequency is 5 units per hour.

[0094] In some other examples, it is assumed that a garment factory has a total of 50 sewing machines, that is, the number of electronic control systems is 50. At a certain moment, the CPU usage rate of the cloud platform is 20%, and the network bandwidth usage rate is 15%. Then the resource pressure coefficient is calculated as follows:

[0095] Substituting the data into the formula by the calculation unit, the resource pressure coefficient = (50 / 500) × 0.4 + (20 / 100) × 0.3 + (15 / 100) × 0.3 = 0.1 × 0.4 + 0.2 × 0.3 + 0.15 × 0.3 = 0.04 + 0.06 + 0.045 = 0.145.

[0096] Furthermore, the upgrade frequency is adjusted. Since the resource pressure coefficient 0.145 is less than 0.3, the first adjustment unit sets the upgrade frequency to 20 units per hour, so that the electronic control system upgrade of these 50 sewing machines can be completed quickly.

[0097] It should be noted that this embodiment can also be an improvement based on the first embodiment and / or the second embodiment.

[0098] It is not difficult to find that in the embodiments of the present application, the CPU usage rate of the cloud platform is used to characterize the load condition of the cloud platform, the network bandwidth usage rate is used to characterize the network bandwidth usage condition, and the calculation unit of the scheduling unit combines the number of electronic control systems, the CPU usage rate, and the network bandwidth usage rate to determine the resource pressure coefficient, and then the first adjustment unit dynamically adjusts the upgrade frequency of the upgrade module according to this coefficient. On the one hand, it can ensure the stability and reliability of the system. When the load of the cloud platform is too high or the network bandwidth is tight, the upgrade frequency is timely reduced, which can avoid system crashes or upgrade failures caused by excessive resource occupation and ensure a smooth and orderly upgrade process. On the other hand, it can effectively improve resource utilization. When resources are sufficient, the upgrade frequency is increased to speed up the upgrade process, make full use of idle resources, and improve the overall upgrade efficiency. In addition, this dynamic adjustment mechanism can also adapt to the upgrade requirements of electronic control systems of different scales. Whether it is a small number of devices or a large number of devices, it can be flexibly adjusted according to the actual resource status, providing an efficient and intelligent solution for the upgrade management of the sewing machine electronic control system of the enterprise, which can reduce operating costs and improve the production efficiency of the enterprise.

[0099] The Fifth Embodiment

[0100] The fifth embodiment of the present application relates to an upgrade management system for an electronic control system of a sewing machine. The fifth embodiment is a parallel embodiment with the fourth embodiment. In this embodiment, another specific implementation manner of the intelligent scheduling module is provided.

[0101] Specifically, the intelligent scheduling module is specifically configured to divide the number of electronic control systems into different intervals, each interval corresponding to a different dynamic adjustment strategy, and adjust the upgrade frequency of the upgrade module according to the cloud platform load condition and the network bandwidth usage condition according to the strategy of the corresponding interval.

[0102] Exemplarily, when the number of electronic control systems is less than 100, the network bandwidth usage condition can be focused on because the load of the cloud platform is relatively low at this time. If the network bandwidth usage rate exceeds 70%, the upgrade frequency can be reduced.

[0103] Exemplarily, when the number of electronic control systems is between 100 and 200, both the cloud platform load and the network bandwidth are taken into account. If the CPU usage rate exceeds 75% or the network bandwidth usage rate exceeds 65%, the upgrade frequency can be reduced.

[0104] Exemplarily, when the number of electronic control systems exceeds 200, more emphasis is placed on the cloud platform load because a large number of upgrade requests may overload the cloud platform. If the CPU usage rate exceeds 70%, the upgrade frequency can be reduced.

[0105] Optionally, in some embodiments, the load condition of the cloud platform is characterized by the CPU usage rate of the cloud platform, and the network bandwidth usage condition is characterized by the network bandwidth usage rate; the intelligent scheduling module specifically includes an input unit, an acquisition unit, an inference unit, and a second adjustment unit; the input unit is configured to use the number of electronic control systems, the CPU usage rate of the cloud platform, and the network bandwidth usage rate as input variables; the partitioning unit is configured to perform fuzzy processing on the input variables, partition them into different fuzzy sets, and define membership functions for each fuzzy set; the acquisition unit is configured to acquire pre-established fuzzy rules, and the fuzzy rules establish a corresponding relationship between the fuzzy set combination of the input variables and the fuzzy set of the upgrade frequency; the inference unit is configured to perform inference based on the fuzzy processing results of the input variables and the fuzzy rules to determine the fuzzy output of the upgrade frequency; the second adjustment unit is configured to convert the fuzzy output into an upgrade frequency value through a defuzzification method to adjust the upgrade frequency of the upgrade module.

[0106] In some examples, it is assumed that the number of electronic control systems, the CPU usage rate, and the network bandwidth usage rate are partitioned into three fuzzy sets of "low", "medium", and "high", and membership functions are defined for each fuzzy set. At the same time, the upgrade frequency is partitioned into three fuzzy sets of "low", "medium", and "high".

[0107] Regarding the number of electronic control systems: Low: The number range is 0 - 100 units, and the membership function can be defined as a linear function. For example, when the number is 0, the membership degree is 1, and when the number is 100, the membership degree is 0. Medium: The number range is 80 - 200 units, and the membership degree is 1 when the number is 140, and decreases towards both ends. High: The number range is 180 - 300 units, and the membership degree is 1 when the number is 300, and the membership degree is 0 when the number is 180.

[0108] Regarding the CPU usage rate: Low: The usage rate range is 0 - 30%, and the membership degree is 1 when the usage rate is 0, and the membership degree is 0 when the usage rate is 30%. Medium: The usage rate range is 20 - 60%, and the membership degree is 1 when the usage rate is 40, and decreases towards both ends. High: The usage rate range is 50 - 100%, and the membership degree is 1 when the usage rate is 100%, and the membership degree is 0 when the usage rate is 50%.

[0109] Regarding the upgrade frequency: Low: The frequency range is 0 - 5 units / hour, and the membership degree is 1 when the frequency is 0, and the membership degree is 0 when the frequency is 5 units / hour. Medium: The frequency range is 4 - 10 units / hour, and the membership degree is 1 when the frequency is 7 units / hour, and decreases towards both ends. High: The frequency range is 9 - 15 units / hour, and the membership degree is 1 when the frequency is 15 units / hour, and the membership degree is 0 when the frequency is 9 units / hour.

[0110] Further, assume that the pre-established fuzzy rules are as follows: Rule 1: If the number of electronic control systems is high, the CPU utilization rate is high, and the network bandwidth utilization rate is high, then the upgrade frequency is low. Rule 2: If the number of electronic control systems is medium, the CPU utilization rate is medium, and the network bandwidth utilization rate is medium, then the upgrade frequency is medium. Rule 3: If the number of electronic control systems is low, the CPU utilization rate is low, and the network bandwidth utilization rate is low, then the upgrade frequency is high.

[0111] Further, assume that there are the following actual data currently:

[0112] The number of electronic control systems is 220 sets.

[0113] The CPU utilization rate is 70%.

[0114] The network bandwidth utilization rate is 80%.

[0115] According to the membership function, calculate the membership degree of each input variable in different fuzzy sets:

[0116] The number of electronic control systems: The membership degree in the "high" fuzzy set is 0.8 (assumed to be calculated through the membership function).

[0117] The CPU utilization rate: The membership degree in the "high" fuzzy set is 0.9.

[0118] The network bandwidth utilization rate: The membership degree in the "high" fuzzy set is 0.95.

[0119] Perform reasoning according to the fuzzy rules. For Rule 1, since the membership degrees of the three input variables in the corresponding "high" fuzzy sets are 0.8, 0.9, and 0.95 respectively, take the minimum value 0.8 as the excitation intensity of this rule for the "low" fuzzy set of the upgrade frequency. Assume that the excitation intensities of Rule 2 and Rule 3 are calculated to be 0.1 and 0.05 respectively (because the current input data has a low matching degree with Rule 2 and Rule 3).

[0120] Convert the fuzzy output into a specific upgrade frequency value through methods such as weighted average. Assume that the central value corresponding to the "low" fuzzy set of the upgrade frequency is 2 sets / hour, the central value corresponding to the "medium" fuzzy set is 7 sets / hour, and the central value corresponding to the "high" fuzzy set is 12 sets / hour. Then the specific upgrade frequency value = (0.8×2 + 0.1×7 + 0.05×12) / (0.8 + 0.1 + 0.05) ≈ 2.7 sets / hour.

[0121] The second adjustment unit operates on the upgrade module according to the calculated upgrade frequency of 2.7 sets / hour, that is, upgrades the electronic control systems of about 2 - 3 sewing machines per hour to ensure the stability and efficiency of the upgrade process under the current cloud platform load and network bandwidth usage conditions.

[0122] Yes. In this embodiment, input variables such as the number of electronic control systems, the CPU usage rate of the cloud platform, and the network bandwidth usage rate are fuzzified through a fuzzy logic algorithm, fuzzy rules are formulated and reasoning is performed. When the network condition is complex, the upgrade frequency can be more flexibly adjusted dynamically according to the fuzzy reasoning result. For example, when the network state is difficult to accurately define but shows a high-load tendency, the fuzzy logic algorithm can timely reduce the upgrade frequency based on the fuzzy rules, effectively cope with the uncertainty of network conditions, and solve the upgrade problems when high network conditions are required and the network is unstable.

[0123] It should be noted that this embodiment can also be an improvement based on any one or more of the first embodiment, the second embodiment, and the fourth embodiment.

[0124] It is not difficult to find that in the embodiment of the present application, the intelligent scheduling module divides the number of electronic control systems into different intervals, and each interval matches different dynamic adjustment strategies. The upgrade frequency of the upgrade module is adjusted according to the corresponding strategy based on the cloud platform load and network bandwidth usage. In this way, efficient allocation of resources is achieved. For the interval with a small number of electronic control systems, the upgrade frequency can be increased to make full use of the idle resources of the cloud platform and the network and speed up the upgrade process; while in the interval with a large number, the upgrade frequency is reasonably reduced to ensure fair distribution of resources among devices and avoid resource waste.

[0125] It is worth mentioning that each module involved in this embodiment is a logical module. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. In addition, in order to highlight the innovative part of the present application, units that are not closely related to solving the technical problems proposed by the present application are not introduced in this embodiment, but this does not mean that there are no other units in this embodiment.

[0126] Sixth Embodiment

[0127] The sixth embodiment of the present application relates to an upgrade management method for an electronic control system of a sewing machine. The method is applied to the system described in any one or more of the first embodiment to the fifth embodiment, and the method includes:

[0128] Step S101, manage the firmware version of the electronic control system, and when a new firmware version is received, send an upgrade notice to the electronic control system through the HTTP protocol;

[0129] Step S102, according to the upgrade notice, obtain the firmware version from the cloud platform management module for upgrade operations, and send the upgrade status to the cloud platform management module through the HTTP protocol;

[0130] Step S103, determine the upgrade result according to the upgrade status.

[0131] As Figure 2 The flowchart shown is an exemplary schematic diagram of the process of upgrading the electronic control system through the cloud platform: First, complete the registration of the sewing machine (corresponding to the device in the figure) according to the registered cloud platform module. After completing the registration, relevant personnel can upload the software version file of the sewing machine and view the version files uploaded historically at the same time. Then, manage the firmware version of the electronic control system. Relevant personnel can select the corresponding sewing machine and the correct version. When a new firmware version is received, an upgrade notification is sent to the electronic control system through the HTTP protocol to prepare for the upgrade.

[0132] Further, the server broadcasts an upgrade notification to the sewing machine through the http protocol. According to the upgrade notification, obtain the firmware version from the cloud platform management module for the upgrade operation, and send the upgrade status to the cloud platform management module through the HTTP protocol.

[0133] Further, determine the upgrade result according to the upgrade status. For example, after the sewing machine receives the file and completes the upgrade, it responds through the http protocol whether the upgrade is completed.

[0134] The step division of the above various methods is only for clear description. When implemented, they can be combined into one step or some steps can be split into multiple steps. As long as the same logical relationship is included, it is within the protection scope of this application; adding insignificant modifications to the algorithm or process or introducing insignificant designs, but not changing the core design of its algorithm and process are all within the protection scope of this application.

[0135] It is not difficult to find that this embodiment is a method embodiment corresponding to the first embodiment, and this embodiment can be implemented in cooperation with the first embodiment. The relevant technical details mentioned in the first embodiment are still valid in this embodiment. To avoid repetition, they will not be elaborated here. Correspondingly, the relevant technical details mentioned in this embodiment can also be applied in the first embodiment.

[0136] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of devices, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a portion of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur in a different order than that noted in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system that performs the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0137] The scope of the present application is defined by the appended claims rather than the above description. Therefore, all changes that fall within the meaning and scope of the equivalent elements of the claims are intended to be encompassed by the present application. Any reference signs in the claims should not be construed as limiting the claims concerned. In addition, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. The multiple elements or devices recited in the apparatus claims may also be implemented by one element or device through software or hardware. The terms "first", "second", etc. are used only for distinguishing descriptions and do not represent any particular order, nor can they be construed as indicating or implying relative importance.

[0138] As described above, these are only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present application should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims, and the above embodiments should be regarded as exemplary and non-limiting.

Claims

1. An upgrade management system for an electric control system of a sewing machine, characterized in that The system includes a cloud platform management module and an electric control system; the upgrade module is disposed in the electric control system and establishes a communication connection with the cloud platform management module through the HTTP protocol; The cloud platform management module is used to manage the firmware version of the electric control system. When a new firmware version is received on the cloud platform, an upgrade notice is sent to the upgrade module through the HTTP protocol; The upgrade module is used to obtain the firmware version from the cloud platform for upgrade operations according to the upgrade notice, and send the upgrade status to the cloud platform management module through the HTTP protocol; The cloud platform management module is further used to determine the upgrade result according to the upgrade status.

2. The system according to claim 1, characterized in that, The firmware version includes multiple device IDs; the device ID is used to control the upgrade process of the electric control system of a single sewing machine; The cloud platform management module is specifically used to add the device ID to the newly received firmware version when a new firmware version is received on the cloud platform to obtain a target device ID; The cloud platform management module is further used to determine an upgrade mode; the upgrade mode includes at least one of the following: batch upgrade, selective upgrade, and individual upgrade of faulty devices; The upgrade module is specifically used to select a corresponding control system to perform the upgrade operation according to the upgrade notice, the upgrade mode, and the target device ID.

3. The system according to claim 1, wherein The cloud platform management module further includes an intelligent scheduling module; The intelligent scheduling module is used to adjust the upgrade frequency of the upgrade module according to the number of electric control systems.

4. The system according to claim 3, characterized in that, The intelligent scheduling module specifically includes a first data acquisition unit, a second data acquisition unit, and a scheduling unit; The first data acquisition unit is used to acquire the load condition of the cloud platform; The second data acquisition unit is used to acquire the network bandwidth usage condition; The scheduling unit is used to dynamically adjust the upgrade frequency of the upgrade module according to the number of electric control systems, the load condition of the cloud platform, and the network bandwidth usage condition.

5. The system according to claim 4, wherein For different numbers of the electric control systems, different first usage thresholds based on the cloud platform load and second usage thresholds based on the network bandwidth are set; both the first usage threshold and the second usage threshold have a negative correlation with the number of electric control systems; The scheduling unit is specifically used to adjust the upgrade frequency of the upgrade module when the load condition of the cloud platform reaches the first usage threshold or the network bandwidth usage condition reaches the second usage threshold.

6. The system according to claim 4, characterized in that, The load condition of the cloud platform is characterized by the CPU usage rate of the cloud platform, and the network bandwidth usage condition is characterized by the network bandwidth usage rate; The scheduling unit specifically includes a calculation unit and a first adjustment unit: The calculation unit is used to determine a resource pressure coefficient according to the number of electric control systems, the CPU usage rate of the cloud platform, and the network bandwidth usage rate; The first adjustment unit is used to dynamically adjust the upgrade frequency of the upgrade module according to the resource pressure coefficient.

7. The system according to claim 6, wherein The calculation unit is specifically used to determine the resource pressure coefficient through the following formula: The resource pressure coefficient = (the number of electronic control systems / the maximum bearable number) × a + (CPU utilization rate / 100) × b + (network bandwidth utilization rate / 100) × c; where a, b, and c are weight coefficients, and a + b + c = 1.

8. The system according to claim 3, wherein The intelligent scheduling module is specifically configured to divide the number of electronic control systems into different intervals, each interval corresponding to a different dynamic adjustment strategy, and adjust the upgrade frequency of the upgrade module according to the cloud platform load condition and network bandwidth usage condition according to the strategy of the corresponding interval.

9. The system according to claim 8, wherein The load condition of the cloud platform is characterized by the CPU utilization rate of the cloud platform, and the network bandwidth usage condition is characterized by the network bandwidth utilization rate; The intelligent scheduling module specifically includes an input unit, an acquisition unit, an inference unit, and a second adjustment unit; The input unit is configured to use the number of electronic control systems, the CPU utilization rate of the cloud platform, and the network bandwidth utilization rate as input variables; The partitioning unit is configured to perform fuzzy processing on the input variables, partition them into different fuzzy sets, and define membership functions for each fuzzy set; The acquisition unit is configured to acquire pre-established fuzzy rules, and the fuzzy rules establish a corresponding relationship between the combination of the fuzzy sets of the input variables and the fuzzy sets of the upgrade frequency; The inference unit is configured to perform inference according to the fuzzy processing result of the input variables and the fuzzy rules to determine the fuzzy output of the upgrade frequency; The second adjustment unit is configured to convert the fuzzy output into an upgrade frequency value through a defuzzification method to adjust the upgrade frequency of the upgrade module.

10. A method for upgrading an electronic control system for a sewing machine, characterized in that, The method is applied to the system according to any one of claims 1-9, and the method includes: Managing the firmware version of the electronic control system, and when a new firmware version is received, sending an upgrade notice to the electronic control system through the HTTP protocol; According to the upgrade notice, obtaining the firmware version from the cloud platform management module for an upgrade operation, and sending the upgrade status to the cloud platform management module through the HTTP protocol; Determining the upgrade result according to the upgrade status.

Images