State acquisition device and system of sewing equipment

Abstract

The embodiment of the invention relates to the technical field of industrial automation, and discloses a state acquisition device and system of sewing equipment. The device comprises a power socket, a current sensor, a control processing unit and a Bluetooth unit, the power socket is used for being connected with sewing equipment; the power sockets and the sewing devices are bound in a one-to-one correspondence mode. The current sensor is used for collecting current data of the sewing equipment in the operation process after the power socket is powered on. The control processing unit is used for determining state information of the sewing equipment according to the current data and the binding relation; and the Bluetooth unit is used for sending the state information to a management platform. The technical problems that a general sewing equipment state collecting device in the related technology is complex in installation and construction process, high in requirement for the technical ability of operation and maintenance personnel and high in maintenance cost can be at least solved.

Description

Technical Field

[0001] This application relates to the field of industrial automation technology, and particularly to a state acquisition device and system for sewing equipment. Background Art

[0002] Automation in the sewing industry is the direction of industry upgrading gradually formed under the promotion of various factors such as technological development, market competition, and policy influence in the whole industry. With the development of the clothing industry, in order to reduce manufacturing costs and improve production efficiency, the automation upgrade of sewing equipment is an inevitable trend. Among them, the communication interfaces of sewing equipment produced by different manufacturers are different. Therefore, developing a general state acquisition device for sewing equipment has become an important way to solve this problem.

[0003] In the related art, a general state acquisition device for sewing equipment needs to be compatible with sewing equipment of different models. However, the inventor found that there are at least the following technical problems in the related art:

[0004] Since the spindle encoder interfaces of sewing equipment produced by different manufacturers, or even different models of sewing equipment produced by the same manufacturer, are generally different. Therefore, when installing the state acquisition device, the maintenance personnel need to first measure the model of the electric control interface of the sewing equipment to be acquired under the corresponding model, and then customize the transfer wire according to the measurement result before connecting it to the state acquisition device. Because a separate transfer wire needs to be customized for each model, the installation and construction process is relatively complex, the technical ability requirements for maintenance personnel are relatively high, and the maintenance cost is relatively high. Summary of the Invention

[0005] An object of this application is to provide a state acquisition device and system for sewing equipment, at least to solve the technical problems that the installation and construction process of the general state acquisition device for sewing equipment in the related art is relatively complex, the technical ability requirements for maintenance personnel are relatively high, and the maintenance cost is relatively high.

[0006] To achieve the above object, some embodiments of this application provide the following aspects:

[0007] In a first aspect, some embodiments of this application further provide a state acquisition device for sewing equipment, the device includes: a power socket, a current sensor, a control processing unit, and a Bluetooth unit; the power socket is used to connect to the sewing equipment; there is a one-to-one binding relationship between the power socket and the sewing equipment; the current sensor is used to collect the current data of the sewing equipment during operation after the power socket is powered on. The control processing unit is used to determine the state information of the sewing equipment according to the current data and the binding relationship; the Bluetooth unit is used to send the state information to the management platform.

[0008] In a second aspect, some embodiments of the present application further provide a state acquisition system for a sewing device, characterized in that the system includes the device as described above and at least one sewing device.

[0009] Compared with the related art, in the solution provided by the embodiments of the present application, a general sewing device state acquisition device is provided. The device includes: a power socket, a current sensor, a control processing unit, and a Bluetooth unit; the power socket is used to connect to the sewing device; there is a one-to-one binding relationship between the power socket and the sewing device, and through this binding relationship, it can be ensured that the current data collected by the current sensor can be accurately matched to each specific device; the current sensor is used to collect the current data of the sewing device during operation after the power socket is powered on; the control processing unit is used to determine the state information of the sewing device according to the current data and the binding relationship, so as to realize the refined monitoring of the sewing operation state; the Bluetooth unit is used to send the state information to the management platform. Since there is no need to separately customize an adapter cable for each model, and there is no need for complex wiring, the installation and construction process is relatively simple, the technical ability requirements for operation and maintenance personnel are relatively low, and the maintenance cost is relatively low. Moreover, it is easy to form a network, and the network scalability is good, and it can timely transmit the state information to the management platform, so that relevant personnel can quickly understand the operation situation of the sewing device. In some scenarios that require quick response, such as when the device suddenly fails, relevant personnel do not need to be on-site, and they can discover the failure of the user's sewing device on the management platform, saving the labor and time costs of maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] One or more embodiments are exemplarily illustrated by the pictures in the corresponding drawings. These exemplary illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, unless otherwise stated, and the drawings in the figures do not constitute a proportional limitation.

[0011] Figure 1 FIG. is an exemplary schematic diagram of a state acquisition device provided according to some embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0012] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0013] First Embodiment

[0014] The first embodiment of this application relates to a state acquisition device for a sewing device. As Figure 1 shown, the device may include: a power socket 11, a current sensor 12, a control processing unit 13, and a Bluetooth unit 14.

[0015] Among them, the power socket 11 is used to connect to the sewing device; there is a one-to-one binding relationship between the power socket 11 and the sewing device;

[0016] Among them, the current sensor 12 is used to collect the current data of the sewing device during operation after the power socket 11 is powered on.

[0017] Among them, the control processing unit 13 is used to determine the state information of the sewing device according to the current data and the binding relationship;

[0018] Among them, the Bluetooth unit 14 is used to send the state information to the management platform.

[0019] Exemplarily, the power socket 11 may be, but is not limited to, a 220V power socket 11. The power socket 11 can supply power to the sewing device that needs to collect the state, ensuring the normal operation of the sewing device.

[0020] Among them, the sewing device can be identified by a unique QR code or barcode and registered on the management platform. For example, when the sewing device is connected to the power output port of the power socket 11, the power socket 11 can establish a connection with a preset APP on the mobile phone through the Bluetooth unit 14. At this time, use the APP to scan the QR code or barcode on the sewing device, and the APP will send the label value of the identified QR code or barcode to the power socket 11. The power socket 11 then reports the information carrying the QR code or barcode information to the management platform through the Bluetooth unit 14, and then obtains the characteristic values corresponding to the model of the sewing device. Exemplarily, the characteristic values may include, but are not limited to: standby power, power at typical rotational speed, power of thread trimming and presser foot lifting actions, etc., which are not specifically limited here.

[0021] Exemplarily, the current sensor 12 can provide data support for energy consumption analysis, etc. by collecting the current data of the sewing device during operation.

[0022] Exemplarily, the control processing unit 13 may be, but is not limited to, a CPU; the CPU can determine the state information of the sewing device according to the current data and the binding relationship, so as to overall coordinate the orderly operation of each part in the state acquisition device.

[0023] Exemplarily, the Bluetooth unit 14 can be, but is not limited to, a low-power Bluetooth unit 14, i.e., a BLE unit. The Bluetooth unit 14 is mainly used to implement the wireless communication function to ensure that the device can smoothly perform data interaction with external devices.

[0024] Exemplarily, the status information can include, but is not limited to, the power-on state, power-off state, start state, stop state of the sewing device, as well as the start time, stop time, rotation speed, etc.

[0025] For ease of understanding, the following uses an example to elaborate on each of the above steps in detail. In this example, assume that there are 100 sewing devices in a garment production workshop:

[0026] Specifically, each sewing device has a dedicated power socket 11 for power supply. For example, the sewing device numbered S001 is correspondingly connected to the power socket 11 marked "Socket S001" under its workbench. During the installation and commissioning phase, relevant personnel can associate the unique identifier of the sewing device (such as the device serial number, QR code, or barcode information) with the corresponding power socket 11 number through the management platform, thereby establishing a one-to-one binding relationship. It can be understood that in a large garment production workshop, there may be hundreds of sewing devices running simultaneously. Through the binding relationship, the management platform can clearly distinguish the status information of each sewing device and avoid data confusion.

[0027] Furthermore, when the power switch of the sewing device numbered S001 is turned on, "Socket S001" is powered on to supply power to the corresponding sewing device. The current sensor 12 starts to work. Considering that the current will change significantly when the sewing device is in different working states, such as starting, normal operation, abnormal jamming, etc. For example, the current will increase significantly at the moment of starting the sewing device, be relatively stable during normal operation, and increase abnormally when a mechanical failure such as thread jamming occurs. By using the current sensor 12 to collect the current data of the sewing device during operation in real time, the control processing unit 13 can accurately judge the current state of the device based on these real-time current data in combination with the binding relationship, realizing the refined monitoring of the device operation state. Assume that the sewing device is running at a constant speed during normal sewing, and the current sensor 12 detects that the current data at this time is 2.5 amperes and transmits this current data to the control processing unit 13 in the form of a digital signal.

[0028] Further, the control processing unit 13 receives the 2.5-ampere current data from the current sensor 12, and simultaneously calls the established binding relationship between the "socket S001" and the sewing equipment numbered S001. Through analysis using a preset algorithm and the device feature database, the status information of the sewing equipment is determined. For example, it is known that the current range of this model of sewing equipment during normal uniform operation is 2 - 3 amperes. From this, it is determined that the sewing equipment numbered S001 is currently in a normal operating state. In addition, the control processing unit 13 can further determine whether the sewing equipment is in a starting, stopping, accelerating, decelerating, etc. state by combining the change situation of the current data, and calculate information such as the start time and stop time. Suppose through calculation, it is determined that the start time of this sewing equipment this time is 3 seconds after the power switch is turned on.

[0029] Further, after the control processing unit 13 determines the status information of the sewing equipment numbered S001 (such as normal operation, start time is 3 seconds), it transmits this status information to the Bluetooth unit 14. The Bluetooth unit 14 sends the status information to the gateway in the workshop. The gateway then forwards the status information to the enterprise's management platform. On the management platform, relevant personnel can see the detailed information that the sewing equipment numbered S001 is currently in a normal operating state and the start time this time is 3 seconds, so as to conduct real-time monitoring and management of the operation of the sewing equipment in the entire workshop.

[0030] In some examples, managers can remotely and real-time master the status of each sewing equipment through the management platform, without having to check each sewing equipment on-site in the workshop, which facilitates cross-regional management. For example, the production manager of the enterprise can, through a computer or mobile phone terminal in the office, understand the operation of the sewing equipment distributed in workshops on different floors and make management decisions in a timely manner. Moreover, the rich status information provides data support for the enterprise's production management. The enterprise can conduct data analysis and mining, and integrated analysis based on these data. By analyzing data such as the operation duration and failure frequency of different sewing equipment, the enterprise can optimize the production process, reasonably arrange the equipment maintenance plan, discover potential problems in advance, improve the overall utilization rate of the sewing equipment, and reduce production costs.

[0031] Moreover, since the current data and status information of the sewing equipment can be obtained in real time, when the current of the sewing equipment shows abnormal fluctuations and deviates from the normal range, the control processing unit 13 can quickly determine that the sewing equipment may malfunction. For example, when the current of the sewing equipment is 3A during normal operation and suddenly rises to 5A, a warning can be issued in a timely manner to prompt relevant personnel that there may be problems with the equipment. Compared with traditional manual inspections, the time to detect faults is greatly shortened. Moreover, by virtue of the binding relationship between the power socket 11 and the sewing equipment, once an abnormal state is detected, the specific equipment with problems can be quickly determined, and the maintenance personnel can directly go to the equipment for maintenance, reducing the time to troubleshoot the faulty equipment, improving the maintenance efficiency, and ensuring the continuity of production.

[0032] It should be noted that through the above device, multiple key data of the sewing equipment can be collected, such as the power-on and power-off time, running time, stop time, and the energy consumption data of the sewing machine.

[0033] It is not difficult to find that compared with the related art, in the solution provided by the embodiment of the present application, a general sewing equipment status acquisition device is provided. The device includes: a power socket, a current sensor, a control processing unit, and a Bluetooth unit; the power socket is used to connect the sewing equipment; there is a one-to-one binding relationship between the power socket and the sewing equipment, and through this binding relationship, it can be ensured that the current data collected by the current sensor can be accurately matched to each specific device; the current sensor is used to collect the current data of the sewing equipment during operation after the power socket is powered on; the control processing unit is used to determine the status information of the sewing equipment according to the current data and the binding relationship, so as to realize the refined monitoring of the sewing operation status; the Bluetooth unit is used to send the status information to the management platform. Since there is no need to customize a separate adapter cable for each model, and there is no need for complex wiring, the installation and construction process is relatively simple, the technical ability requirements for operation and maintenance personnel are relatively low, and the maintenance cost is relatively low. Moreover, it is easy to form a network, and the network scalability is good, and the status information can be transmitted to the management platform in a timely manner, enabling relevant personnel to quickly understand the operation of the sewing equipment. In some scenarios that require quick response, such as when the equipment suddenly fails, relevant personnel do not need to be on site, and they can find the faults of the user's sewing equipment on the management platform, saving the labor and time costs of maintenance.

[0034] Second Embodiment

[0035] The second embodiment of the present application relates to a sewing equipment status acquisition device. The second embodiment is an improvement based on the first embodiment. The specific improvement lies in that: in the first embodiment of the present application, the device includes: a power socket, a current sensor, a control processing unit, and a Bluetooth unit; while in the second embodiment of the present application, the device may further include a relay 21, asFigure 1 as shown

[0036] Specifically, the relay 21 is used to control the power on / off of the sewing device. For example, it can control the closing and opening of the output of a 220V power socket, thereby accurately managing the power on / off of the sewing device.

[0037] It is not difficult to find that in the embodiments of the present application, by setting the relay, the functions of remotely controlling the power on and power off of the sewing device by the management platform and the dedicated mobile APP can be realized.

[0038] Third Embodiment

[0039] The third embodiment of the present application relates to a state acquisition device for a sewing device. The third embodiment is an improvement based on the second embodiment. The specific improvement lies in: in the second embodiment of the present application, the device includes: a power socket, a current sensor, a control processing unit, a Bluetooth unit, and a relay; while in the third embodiment of the present application, the device may further include an RFID card reading unit, as Figure 1 as shown

[0040] Specifically, the sewing device is equipped with an RFID tag card;

[0041] The RFID card reading unit 31 is used to establish the binding relationship between the power socket and the sewing device by identifying the RFID tag card equipped on the sewing device.

[0042] Exemplarily, since each sewing device has a unique RFID tag card, when the sewing device is connected to the power socket, the RFID card reading unit 31 can identify the RFID tag card equipped on the sewing device to identify the load, that is, the specific "identity information" of the sewing device, and upload the specific "identity information" of the sewing device to the management platform. Then, the management platform analyzes the model corresponding to the sewing device according to the "identity information" corresponding to the RFID tag card, and further obtains the characteristic value corresponding to the model. This makes it convenient to perform data matching on the sewing device, thus facilitating management.

[0043] It should be noted that this embodiment can also be an improvement based on the first embodiment.

[0044] It is not difficult to find that in the embodiments of the present application, by equipping the sewing device with an RFID tag card, the specific "identity information" of the sewing device can be identified by identifying the RFID tag card equipped on the sewing device, and then the binding relationship between the sewing device and the power socket is established.

[0045] Fourth Embodiment

[0046] The fourth embodiment of this application relates to a state acquisition device for a sewing device. The fourth embodiment is an improvement based on the third embodiment. The specific improvement lies in that in the fourth embodiment of this application, the Bluetooth unit is specifically configured to, after the power socket is powered on, broadcast information via Bluetooth, automatically search for a target gateway according to the signal strength, and form a network with the target gateway to join the Bluetooth MESH network of the target gateway, so as to send the state information to the management platform through the Bluetooth MESH network.

[0047] That is to say, in some examples, the Bluetooth unit, as a wireless terminal, can jointly form a Bluetooth MESH network with the target gateway to achieve two-way communication and ensure smooth data interaction.

[0048] Optionally, in some embodiments, the Bluetooth unit can also act as a relay node of the Bluetooth MESH network to forward the state information of the sewing devices on other power sockets, expanding the network coverage and data transmission capabilities.

[0049] Optionally, in some embodiments, the Bluetooth unit can also be used to listen for and respond to the instruction information of the management platform.

[0050] Optionally, in some embodiments, the Bluetooth unit can also be connected to the APP of a preset terminal device (such as a mobile phone, a tablet computer, etc.). In this way, the Bluetooth unit can establish a connection and communication with, for example, a mobile phone APP, so as to facilitate relevant personnel to carry out various installation, maintenance, and configuration operations through the APP, providing a convenient management method.

[0051] The following provides an application example of a state acquisition device for a sewing device.

[0052] Specifically, when the power socket is powered on, the Bluetooth unit broadcasts information via Bluetooth, automatically searches for the target gateway with the strongest surrounding signal (the gateway has built-in BLE+wlan functions), and forms a network with it to join the Bluetooth MESH network of the target gateway. After that, the Bluetooth unit can regularly send the state information of the sewing device to the management platform through the target gateway. At the same time, the Bluetooth unit can always listen for and respond to the instruction information sent by the management platform and the APP.

[0053] During operation, the RFID tag card can be attached to the power socket terminal of the sewing device, and then the power cord of the sewing device can be plugged into the 220V output port of the power socket. At this time, the RFID card reading unit identifies the RFID tag card, thereby establishing a binding relationship between the sewing device and the power socket (the RFID tag card is bound to the sewing device one by one, and the sewing device can be registered in the management platform in advance through a dedicated APP). In this way, the Bluetooth unit can report the data carrying the RFID tag card information to the management platform and obtain the characteristic values of the model of the sewing device from the management platform at the same time. Moreover, the power-on and power-off control of the sewing device can be realized by controlling the opening and closing of the relay.

[0054] Further, after the sewing device is powered on and starts to run, the current sensor can collect the current data of the sewing device in real time. Then, the collected current data is compared with the previously obtained characteristic values, and the status information is calculated. Finally, the status information can be reported to the management platform regularly through the Bluetooth unit so that the management personnel can grasp the running situation of the sewing device in real time.

[0055] It should be noted that this embodiment can also be an improvement based on the first embodiment and / or the second embodiment.

[0056] It is not difficult to find that in the embodiment of the present application, after the power socket is powered on, the Bluetooth unit can automatically broadcast information through Bluetooth, quickly lock the target gateway according to the signal strength and complete networking. For example, in a large clothing production park, there may be multiple workshops, and each workshop has many sewing devices and corresponding status collection devices. By adopting the automatic search mechanism provided in this embodiment, there is no need for manual configuration of connection information, which can greatly save the time cost of equipment deployment and debugging. Compared with the traditional method that requires manual setting of network connection parameters, the work efficiency can be significantly improved, especially suitable for scenarios of large-scale equipment deployment.

[0057] The fifth embodiment

[0058] The fifth embodiment of the present application relates to a status collection device for a sewing device. The fifth embodiment is an improvement based on the first embodiment. The specific improvement lies in that in the fifth embodiment of the present application, the control processing unit is specifically used to obtain the characteristic values corresponding to the model of the sewing device from the management platform according to the binding relationship; compare the current data with the characteristic values to determine the status information of the sewing device.

[0059] Specifically, before the sewing equipment status acquisition device starts running, technicians can preset a series of characteristic values according to the model, specifications of the sewing equipment, and various parameters during normal operation. The characteristic values may include, but are not limited to: typical values such as the power, current, and rotational speed of the sewing equipment in different working modes (such as standby, sewing, thread cutting, presser foot lifting, etc.). For example, in the normal sewing state of a certain model of sewing equipment, the typical power value is 500W, the corresponding current data is 2A, and the rotational speed is 1000 revolutions per minute. These values can be set as the characteristic values in this working state.

[0060] Exemplarily, the management platform can send down the characteristic values to the control processing units of each sewing equipment. The control processing unit can store the characteristic values for subsequent status monitoring and judgment of the sewing equipment.

[0061] Optionally, in some embodiments, the control processing unit may further include: a calculation module, a judgment module, and an adaptive adjustment module;

[0062] The calculation module is used to determine the power of the sewing equipment according to the current data;

[0063] The judgment module is used to determine whether the adaptive adjustment condition is met according to the power waveform corresponding to the characteristic value and the actual working power waveform corresponding to the power;

[0064] The adaptive adjustment module is used to adaptively adjust the characteristic value to obtain a target characteristic value when the adaptive adjustment condition is met.

[0065] Exemplarily, the current sensor can continuously and real-time collect the current data during the operation of the sewing equipment. The control processing unit calculates the power of the sewing equipment in real time according to these current data and generates a power waveform. By comparing the real-time generated power waveform with the power waveform corresponding to the preset characteristic value, it is judged whether the actual working power waveform of the equipment is within a reasonable range to determine whether the adaptive adjustment condition is met.

[0066] For example, in the normal sewing mode, the power waveform should be relatively stable and fluctuate within a certain power range. If the actual power waveform shows large fluctuations or deviates from the normal power range for a long time, it can be preliminarily determined that the sewing equipment may be abnormal.

[0067] Furthermore, when it is determined that the sewing equipment is in an abnormal or abnormal working state, the management platform can re-send down the characteristic values that are more in line with the actual situation of the current sewing equipment. These characteristic values can specifically be obtained through data analysis of similar sewing equipment in similar abnormal situations, or be calculated in real time according to the real-time monitoring data of the current sewing equipment.

[0068] In some examples, the control processing unit may correct the characteristic value according to the newly issued target characteristic value and the real-time operation data of the sewing device. For example, the weights of parameters such as power, current, and rotation speed in the original state inference algorithm can be adaptively adjusted, or the threshold for judging the state of the sewing device in the state inference algorithm can be changed, etc., to obtain the target characteristic value, so as to more accurately judge the current real state of the sewing device and timely discover potential faults of the sewing device.

[0069] It should be noted that this embodiment can also be an improvement based on any one or more of the second to fourth embodiments.

[0070] It is not difficult to find that in the embodiments of the present application, considering that during the long-term operation of the sewing device, due to reasons such as wear, changes in environmental factors (such as temperature, humidity, etc.), and the usage habits of different operators, the actual working state of the sewing device may change. When the device discovers that there is a deviation between the actual working power waveform of the sewing device and the power waveform corresponding to the preset characteristic value, the adaptive learning mechanism is started. In this way, it can adapt to the changes in the actual state of the sewing device and improve the accuracy of judging the state of the sewing device.

[0071] Sixth Embodiment

[0072] The sixth embodiment of the present application relates to a state acquisition device for a sewing device. The sixth embodiment is an improvement based on the fifth embodiment. The specific improvement lies in: in the sixth embodiment of the present application, the judgment module includes: a classification module and a matching module.

[0073] The classification module is used to classify the action types of the sewing device into: power-on, standby, and operation according to the startup state of the sewing device;

[0074] The matching module is used to determine whether the adaptive adjustment condition is met according to the characteristic waveform corresponding to the action type.

[0075] Exemplarily, the classification module can obtain signals related to the startup state of the sewing device. For example, when the switch of the power socket of the sewing device is closed, an electrical signal change will occur, and the motor control circuit will also receive a startup instruction, and these signals will be obtained by the classification module.

[0076] Exemplarily, once it is detected that the sewing device changes from a power-off state to a power-on state and the motor starts to show signs of starting (such as the current starts to rise), the action type can be determined as: power-on. For example, at the moment when the power is just turned on, the current sensor detects that the current rapidly rises from 0, and the classification module identifies it as power-on accordingly.

[0077] Exemplarily, when the sewing device is powered on but no actual sewing operation is being performed and the motor is running at a low speed or is nearly stationary (maintaining the minimum power consumption), the current value is low and relatively stable. For example, when the worker completes a section of sewing work and pauses the operation but the sewing device remains powered on, and the current stabilizes at a low level, the classification module can determine that the action type is: standby.

[0078] Exemplarily, when it is detected that the motor is running at a high speed and the execution components such as the sewing needle and the feeding mechanism start to work, and at the same time the current value increases significantly and is in a dynamic change, the classification module can determine that the action type is: running. For example, when the worker steps on the foot pedal, the motor runs at a high speed to drive the sewing needle to shuttle up and down, and the feeding mechanism pushes the fabric to move. At this time, the current shows large and regular fluctuations, and the classification module identifies it as running.

[0079] In some examples, the matching module can store a feature value matching algorithm preset for different action types. The feature value matching algorithm can be obtained based on a large amount of sewing device operation data and experiments, and can also call the corresponding feature value template library according to the corresponding action type, and compare it with the actual working power waveform collected in real time.

[0080] Exemplarily, assume that the preset startup feature value matching algorithm requires the current to rise from 0 to a specific value (such as 3A) within 0.5 seconds when starting up, and the rising curve has a certain slope range. When the sewing device starts up, the matching module collects the current waveform data in real time. If it meets the above preset requirements, it can be determined that the waveform is the characteristic waveform of the startup action type. If the waveform does not meet the requirements, such as the current rising too slowly or too quickly, exceeding the preset time and slope range, it means that there may be problems with the startup of the sewing device, such as unstable power supply, motor startup circuit failure, etc., thus realizing the monitoring and diagnosis of the startup process.

[0081] Exemplarily, assume that the current should be stable at a low value (such as 0.3A) during standby, and the fluctuation range is extremely small (such as ±0.05A). The matching module continuously monitors the current waveform when the sewing device is in the standby state. If the actual waveform is within this preset range, it is determined as the standby characteristic waveform. If the waveform shows abnormal fluctuations or deviates from the preset value, such as the current suddenly rising to 0.5A, it may indicate problems such as leakage or internal circuit abnormalities of the sewing device, helping to diagnose the operating conditions of the sewing device in the standby state.

[0082] In some examples, different characteristic values can be preset according to different sewing operations (such as sewing straight lines, curves) and fabric materials (thin, thick). For example, when sewing thin fabric, the average current during normal operation is 1.5 A, with a fluctuation range of ±0.2 A; when sewing thick fabric, the average current is 2.5 A, with a fluctuation range of ±0.3 A. The matching module calls the corresponding characteristic value algorithm according to the working parameters of the current sewing device (such as the selected sewing mode, the detected fabric material). If the current waveform collected in real time conforms to the corresponding preset range, it is determined as the characteristic waveform in this operating state. If the current exceeds the range, such as the current reaching 3 A when sewing thin fabric, it may be due to sewing needle jamming, feeding mechanism failure, etc., which is used to judge whether the sewing device is normal during operation, and realize the monitoring and diagnosis of the operating state.

[0083] It should be noted that this embodiment can also be an improvement based on any one or more of the first to fourth embodiments.

[0084] It is not difficult to find that in the embodiments of the present application, a specific implementation form of the control processing unit is provided, which is beneficial to improving the monitoring and diagnosis efficiency of the sewing device.

[0085] The seventh embodiment

[0086] The seventh embodiment of the present application relates to a state acquisition device for a sewing device. The seventh embodiment is an improvement based on the sixth embodiment. The specific improvement lies in: in the seventh embodiment of the present application, the matching module specifically includes a first calculation module, a second calculation module, and a third calculation module.

[0087] The first calculation module is used to calculate the total operating time of the sewing device according to the startup time and action state time of the sewing device; wherein, the action state time is composed of the single state operating time and the state transformation time;

[0088] The second calculation module is used to calculate the current average value per unit operating cycle based on the current data and the total operating time, as well as the average value of the average value of the normal operating current level per unit operating cycle and the average value of the current variance per unit operating cycle for characterizing the current fluctuation;

[0089] The third calculation module is used to screen the characteristic waveform from the waveforms corresponding to the action states under different action types according to the calculation results of the second calculation module to determine whether the adaptive adjustment condition is met.

[0090] Optionally, in some embodiments, during the operation of the sewing device, current data is continuously collected, and time information such as the start, stop, and state transformation of the sewing device is recorded. According to the collected time information, parameters such as the total operation time, action state time, single-state operation time, and state transformation time are calculated.

[0091] Assume that the device operation state is n, and its total operation time T total is the sum of the power-on time t1 and the action state time t2:

[0092] T total = t1 + t2;

[0093] Among them, the power-on time t1 is the time experienced by the sewing device from startup to entering the workable state.

[0094] The action state time t2 is composed of the single-state operation time T n and the state transformation time T s , that is:

[0095] t2 = T n + T s ;

[0096] The single-state operation time is T n , for example, the time duration when the device is in a single action state such as sewing or thread cutting. The state transformation time T s represents the time taken for the sewing device to switch from one action state to another.

[0097] Furthermore, in some embodiments, each single-state operation time T n is decomposed into unit operation cycles T0.

[0098] Assume that the unit operation cycle is represented by T0. The single-state operation time T n of each action can be decomposed into unit operation cycles T0 according to different startup, stop, and state transformation times. In this way, in analyzing the operation of the sewing device, the complex operation process is ingeniously split into relatively independent and representative unit cycles for calculation.

[0099] Furthermore, in some embodiments, the current mean value of each unit operation cycle T0, as well as the mean value and variance mean value of multiple unit operation cycles, are calculated.

[0100] Assume that represents the current mean value of the unit operation cycle T0, which is used to characterize the result obtained by averaging the current values within a unit operation cycle T0.

[0101] Assume that and respectively represent the mean value and the mean variance of the unit operation period T0. is the average value of the current mean values of multiple unit operation periods T0, and is used to reflect the average level of the current during the normal operation of the sewing device; is the average value of the current variances of these unit operation periods T0, and reflects the fluctuation of the current value.

[0102] Furthermore, in some embodiments, by comparing each state characteristic value I state with the mean value of the normal working current and the deviation of this difference from the standard deviation (i.e., the square root of the mean variance ), the characteristic waveform is screened. Among them, the state characteristic value is I state , which is used to represent the value that can represent the current characteristic of the state after being collected by the current sensor and processed by the control processing unit under the specific action state of the sewing device, that is, the current characteristic value of the sewing device under a certain specific state.

[0103] Based on the above assumptions, the formula for determining whether the waveform in a certain state is a characteristic waveform can be:

[0104]

[0105] Among them, calculate the difference between the state characteristic value and the mean value of the normal working current:

[0106] The deviation threshold is k, which is used to define the difference degree between the characteristic waveform and the normal waveform, and can be adjusted according to the actual situation and experience of the device. When , it is considered that the waveform in this state is a characteristic waveform.

[0107] It should be noted that this embodiment can also be an improvement based on any one or more of the first to fifth embodiments.

[0108] It is not difficult to find that in the embodiment of the present application, a specific implementation manner of the matching module is provided. Through the method provided in this embodiment, representative characteristic waveforms can be effectively screened out from a large number of operation waveforms of sewing devices, providing an important basis for subsequent device state analysis, fault diagnosis, etc.

[0109] Eighth Embodiment

[0110] The eighth embodiment of the present application relates to a state acquisition device for a sewing device. The eighth embodiment is an improvement based on the first embodiment, and the specific improvement lies in that: the device further includes: a state prediction module.

[0111] The state prediction module is configured to predict the operating state of the sewing device at the next moment according to the first state data in at least two operating states of the sewing device;

[0112] The first state data includes at least one of the following: first current data in a normal state, second current data in a fault state, and third current data in a dangerous state;

[0113] The operating states include: standby state, operating state, and fault state;

[0114] Optionally, in some embodiments, the state prediction module may specifically include a first determination module and a second determination module:

[0115] The first determination module is configured to determine the proportion of each state in a time period according to the first state data in at least two operating states of the sewing device;

[0116] The second determination module is configured to predict the operating state of the sewing device at the next moment according to the proportion.

[0117] Exemplarily, in the process of the first determination module determining the proportion of each state in a time period, it mainly includes data collection, state duration statistics, and calculation of state proportion.

[0118] Specifically, in a relatively long observation time period T, the first state data in at least two operating states of the sewing device can be collected. At the same time, by monitoring and judging the sewing device, mark the operating state of the sewing device at each moment: standby state S1, operating state S2, and fault state S3, and whether the corresponding current data belongs to the first current data in a normal state, the second current data in a fault state, or the third current data in a dangerous state.

[0119] Further, for each operating state S i (i = 1, 2, 3), its total duration t i within the observation time period T can be statistically calculated. It can be achieved by recording the time points of state transitions. When the state changes from S j to S i , record the switching time t ji ; when the state changes from S i to S k , record the switching time t ik , then the duration of S i in this time period is t ik - t ji . Accumulate the durations of all S i to obtain the duration of S iTotal duration t within the entire time period T i 。

[0120] Furthermore, based on the statistically obtained duration t of each state i , the proportion p of each state S i within the observation time period T can be calculated. The calculation formula can refer to the following: i That is, the sum of the durations of all states is equal to the observation time period T.

[0121] That is, the sum of the durations of all states is equal to the observation time period T.

[0122] Exemplarily, in the process of the second determination module predicting the operating state of the sewing device at the next moment, it mainly includes constructing a state transition probability matrix, optimizing the prediction by combining current data, and making a prediction based on the proportion and transition probability.

[0123] Specifically, a state transition probability matrix P can be constructed based on historical data. The element P of this state transition probability matrix P ij represents the probability that the sewing device transitions from state S i to state S j . The probability P i can be evaluated by counting the number N j of times the state transitions from S ij to state S i in the historical data and dividing it by the total number N i of times state S ij appears, that is:

[0124] P ij =N ij N i ;

[0125] Furthermore, when making a prediction, in addition to considering the state transition probability, the current current data type (first current data, second current data, third current data) at the current moment is also combined to further optimize the prediction. For example, if the current is a fault state and the current is the second current data, the probability of transitioning to the continued fault state may be relatively high; if it is a normal operating state and the current is the first current data, the probability of transitioning to the standby state or the continued operating state will be adjusted according to the state transition matrix and the actual situation.

[0126] Furthermore, assume that the current sewing device is in state S k , and the current current data type is known. A prediction can be made by combining the state transition probability matrix P and the current current data type. Calculate the probability P k of transitioning from the current state S j to each state S kj, and adjust the probability according to the current current data type (for example, assign different weights to the transition probabilities under different current data types based on experience), and then select the state with the highest probability as the prediction result. That is, select the state S with the highest probability after adjustment. m As the predicted state for the next moment.

[0127] It should be noted that this embodiment can also be an improvement based on any one or more of the second to seventh embodiments.

[0128] It is not difficult to find that in the embodiments of the present application, by analyzing the first state data under at least two operating states (such as current data in normal, faulty, and dangerous states), potential problems of the sewing equipment can be detected in advance. For example, by continuously monitoring the first current data in the normal state, if it is found that it gradually deviates from the standard range, it may imply that some components of the equipment start to wear or the performance decreases. Based on this, maintenance can be arranged before the actual occurrence of a fault to avoid sudden shutdown of the equipment and reduce the risk of production interruption.

[0129] The ninth embodiment

[0130] The ninth embodiment of the present application relates to a state acquisition system for a sewing equipment, and the system includes the device described in any one or more of the first to eighth embodiments, and at least one sewing equipment.

[0131] It is not difficult to find that this embodiment is a system 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 are not elaborated here. Correspondingly, the relevant technical details mentioned in this embodiment can also be applied to the first embodiment.

[0132] 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, 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.

[0133] 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, and 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.

[0134] 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 included in 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 term "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.

[0135] 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. A state acquisition device for a sewing device, characterized in that: The device comprises: a power socket, a current sensor, a control processing unit and a Bluetooth unit; The power socket is used to connect the sewing equipment; there is a one-to-one binding relationship between the power socket and the sewing equipment; The current sensor is used to collect current data of the sewing device during operation after the power socket is powered on; The control processing unit is used to determine the status information of the sewing device according to the current data and the binding relationship; The Bluetooth unit is used to send the status information to the management platform.

2. The device according to claim 1, characterized in that The device also includes a relay and / or an RFID card reader unit; The relay is used to control the power on and off of the sewing equipment. The sewing device is equipped with an RFID tag card; the RFID card reading unit is used to establish the binding relationship between the power socket and the sewing device by identifying the RFID tag card equipped by the sewing device.

3. The device according to claim 1, characterized in that The Bluetooth unit is specifically used to broadcast information via Bluetooth after the power socket is powered on, automatically search for the target gateway according to the signal strength, and network with the target gateway to join the Bluetooth MESH network of the target gateway to send the status information to the management platform via the Bluetooth MESH network.

4. The device according to claim 1, characterized in that The control processing unit is specifically used to obtain a characteristic value corresponding to the model of the sewing device from the management platform according to the binding relationship; compare the current data with the characteristic value to determine the status information of the sewing device.

5. The device according to claim 4, characterized in that The control processing unit also includes: a calculation module, a judgment module and an adaptive adjustment module; The calculation module is used to determine the power of the sewing device according to the current data; The judgment module is used to determine whether the adaptive adjustment condition is met according to the power waveform corresponding to the characteristic value and the actual working power waveform corresponding to the power; The adaptive adjustment module is used to adaptively adjust the characteristic value to obtain a target characteristic value when an adaptive adjustment condition is met.

6. The device according to claim 5, characterized in that The judgment module includes: a classification module and a matching module; The classification module is used to classify the action types of the sewing device into: starting, standby and running according to the startup state of the sewing device; The matching module is used to determine whether the adaptive adjustment condition is met according to the characteristic waveform corresponding to the action type.

7. The device according to claim 6, characterized in that The matching module specifically includes a first calculation module, a second calculation module and a third calculation module; The first calculation module is used to calculate the total operation time of the sewing device according to the start-up time and the action state time of the sewing device; wherein the action state time is composed of a single state operation time and a state change time; The second calculation module is used to calculate the current mean value of the unit operation cycle, the average value of the unit operation cycle mean value used to reflect the normal operation current level, and the average value of the unit operation cycle current variance used to characterize the current fluctuation situation based on the current data and the total operation time; The third calculation module is used to screen characteristic waveforms from waveforms corresponding to action states under different action types according to the calculation results of the second calculation module to determine whether the adaptive adjustment condition is met.

8. The device according to any one of claims 1 to 7, characterized in that The device also includes: a state prediction module; The state prediction module is used to predict the operating state of the sewing device at the next moment according to the first state data of at least two operating states of the sewing device; The first state data includes at least one of the following: first current data in a normal state, second current data in a fault state, and third current data in a dangerous state; The operating status includes: a standby status, an operating status and a fault status.

9. The device according to claim 8, characterized in that The state prediction module specifically includes a first determination module and a second determination module: The first determination module is used to determine the proportion of each state in the time period according to the first state data of at least two operating states of the sewing device; The second determination module is used to predict the operating state of the sewing equipment at the next moment according to the proportion.

10. A state acquisition system for sewing equipment, characterized in that: The system comprises the apparatus according to any one of claims 1 to 9, and at least one sewing device.

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