Chemical fiber spinning equipment cooperative control method based on multi-band wireless communication

Abstract

The invention provides a chemical fiber spinning equipment cooperative control method based on multi-band wireless communication, and relates to the technical field of textile machinery control, and the method comprises the steps: firstly, determining the operation parameters of chemical fiber spinning equipment, including spinning speed, temperature, pressure and wind speed, so as to set the initial working state of the equipment; secondly, establishing a communication link between the devices through a multi-band wireless communication network, and ensuring synchronous data transmission between the devices; then, dynamically adjusting operation parameters according to the real-time working state of the equipment, and optimizing the cooperative work of the equipment; furthermore, computing equipment cooperative control parameters, including working efficiency and response time delay, and further adjusting the control parameters through an optimization algorithm; and finally, transmitting the adjusted control signal to each device through a wireless communication module to realize synchronous adjustment of the devices. Through the multi-band communication technology, the cooperative efficiency among equipment is improved, the spinning quality is optimized, the production efficiency is improved, and remarkable technical advantages are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of textile machinery control, and in particular to a coordinated control method of chemical fiber spinning equipment based on multi-band wireless communication. Background Art

[0002] With the continuous development of industrial automation and intelligent manufacturing, the chemical fiber spinning industry is gradually moving towards digitalization and intelligence. As a key link in textile production, the optimization and coordinated control of the working state of chemical fiber spinning equipment directly affects production efficiency and spinning quality. Most traditional chemical fiber spinning equipment uses single-band wireless communication technology for data transmission, but due to environmental factors, electromagnetic interference, equipment density and other factors, the single-band communication method is prone to insufficient communication bandwidth, signal transmission delays or data loss when the number of equipment is large. In this case, the collaborative work between equipment is difficult to accurately control, and it is difficult to achieve real-time monitoring and adjustment, which affects the overall efficiency of the production line and the quality of spinning products.

[0003] In order to solve the above problems, some existing technologies attempt to optimize the performance of spinning equipment through multi-band communication and equipment collaborative control. However, most existing multi-band wireless communication systems only focus on the transmission quality of communication signals, lacking real-time perception and dynamic adjustment of the equipment's operating status. Therefore, the collaborative control between devices still faces problems such as inconsistent operating parameters, long equipment response delays, and unbalanced loads, resulting in low spinning production efficiency, unstable product quality, and failure to fully tap the potential of the equipment.

[0004] In addition, the existing technology lacks effective algorithm support in the process of equipment collaborative control, especially in real-time adjustment and optimization of equipment operating parameters. It often cannot dynamically adjust operating parameters according to the real-time status of the equipment, resulting in energy waste and reduced production efficiency. The existing technology has not fully considered the mutual influence and real-time collaboration between devices. Therefore, there is a lack of a control method that can comprehensively optimize multiple devices, multiple frequency bands, and multiple transmission conditions. Summary of the invention

[0005] In order to solve the technical problems of unstable signal transmission, inaccurate collaborative control between devices, long equipment response delay, unbalanced load and lack of dynamic adjustment and optimization mechanism caused by single-band wireless communication in the prior art, the present invention provides a collaborative control method for chemical fiber spinning equipment based on multi-band wireless communication.

[0006] The technical solution provided by the present invention is as follows:

[0007] The present invention provides a method for collaboratively controlling chemical fiber spinning equipment based on multi-band wireless communication, comprising:

[0008] S1. Determine the operating parameters of the chemical fiber spinning equipment, wherein the operating parameters include spinning speed, temperature, pressure and wind speed, so as to set the initial working state of the equipment;

[0009] S2. Establishing a communication link between devices through a multi-band wireless communication network, including at least two spinning devices and their respective control modules, and transmitting data through wireless signals to ensure synchronous transmission of information between modules of each device;

[0010] S3. According to the real-time working status of the spinning equipment, the operating parameters are dynamically adjusted to achieve coordinated work among the equipment and optimize the spinning quality;

[0011] S4. Calculate device collaborative control parameters according to the operation data of the device, including device work efficiency parameters, device work efficiency, and device response delay parameters, device response delay;

[0012] S5. Adjusting device collaborative control parameters through an optimization algorithm to optimize the working status of different devices. The optimization algorithm takes into account the interaction between devices, and specifically includes a bandwidth adjustment algorithm based on multi-band signal strength and a device load balancing algorithm;

[0013] S6. Finally, the adjusted control signal is transmitted to each device through the wireless communication module to achieve synchronous adjustment of the devices.

[0014] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0015] (1) In the present invention, the problem of unstable communication between devices caused by signal interference and insufficient bandwidth in traditional technologies is solved through multi-band wireless communication technology, and real-time and efficient data transmission and information synchronization between different chemical fiber spinning equipment are realized, thereby improving the collaborative working efficiency of the equipment and reducing the response delay between the equipment;

[0016] (2) In the present invention, by dynamically adjusting the working parameters of the spinning equipment (such as spinning speed, temperature, pressure, etc.), the present invention realizes the coordinated control between the equipment, so that each equipment operates in the best working state, thereby ensuring the uniformity and stability of the spinning process, significantly improving the quality and consistency of the product, and reducing the generation of defective products;

[0017] (3) In the present invention, the collaborative control parameters of the equipment are adjusted by optimizing the algorithm, and the working state of the equipment is dynamically adjusted based on factors such as multi-band signal strength and equipment load balance, thereby reducing energy waste and equipment idle time, improving overall production efficiency, and achieving more efficient use of energy and resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 A schematic flow chart of a method for collaboratively controlling chemical fiber spinning equipment based on multi-band wireless communication provided by an embodiment of the present invention;

[0020] Figure 2 A schematic flow chart of a bandwidth adjustment algorithm based on multi-band signal strength of a coordinated control method for chemical fiber spinning equipment based on multi-band wireless communication provided by an embodiment of the present invention;

[0021] Figure 3 A schematic flow chart of a load balancing mechanism in a scheduling algorithm of a collaborative control method for chemical fiber spinning equipment based on multi-band wireless communication provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0022] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0023] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0024] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0025] In the embodiments of the present invention, sometimes a subscript such as W1 may be mistakenly written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are consistent.

[0026] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0027] Reference Manual Attached Figure 1, showing a flow chart of a method for collaborative control of chemical fiber spinning equipment based on multi-band wireless communication provided by an embodiment of the present invention.

[0028] The embodiment of the present invention provides a method for collaborative control of chemical fiber spinning equipment based on multi-band wireless communication, and the processing flow may include the following steps:

[0029] S1. Determine the operating parameters of the chemical fiber spinning equipment, the operating parameters including spinning speed, temperature, pressure and wind speed, so as to set the initial working state of the equipment.

[0030] It should be noted that in the chemical fiber spinning process, the operating parameters of the equipment directly affect the spinning quality and the stability of the equipment. By setting basic parameters such as spinning speed, temperature, pressure and wind speed, a standardized initial working state can be provided for the equipment. These parameters determine the processing effect of the material and the quality of the fiber. Reasonable initial settings help improve production efficiency and reduce possible deviations or failures in the spinning process.

[0031] S2. Establish a communication link between devices through a multi-band wireless communication network, including at least two spinning devices and their respective control modules, and transmit data through wireless signals to ensure synchronous transmission of information between modules of each device.

[0032] It should be noted that by establishing a multi-band wireless communication network, data can be exchanged between devices in real time to ensure information synchronization of equipment modules during the spinning process. This wireless communication method is flexible and efficient, and can avoid the line complexity and susceptibility to interference problems that occur in traditional wired communications. Ensuring the synchronization of data transmission is the basis for achieving equipment collaboration and real-time adjustment, and can effectively improve the coordination between spinning equipment.

[0033] S3. According to the real-time working status of the spinning equipment, the operating parameters are dynamically adjusted to achieve coordinated work among the equipment and optimize the spinning quality.

[0034] It should be noted that the working state of the spinning equipment will be affected by many factors, such as raw material changes, environmental fluctuations, etc., so it is necessary to make dynamic adjustments based on real-time monitoring data. By adjusting the equipment operating parameters in real time, it is possible to ensure the coordination between different equipment and avoid fluctuations in spinning quality caused by inconsistencies between equipment. Dynamic adjustment helps to optimize key indicators such as fiber uniformity and strength, and ultimately improve product quality.

[0035] S4. Calculate the equipment collaborative control parameters according to the equipment operation data, including the equipment work efficiency parameters equipment work efficiency and the equipment response delay parameters equipment response delay.

[0036] It should be noted that in order to ensure coordination and efficient operation between different devices, key parameters such as equipment efficiency and response delay need to be regularly evaluated and calculated. The equipment efficiency determines the production speed of the spinning process, while the response delay affects the speed at which the equipment responds to the adjustment signal. By calculating these control parameters, accurate data support can be provided for subsequent optimization algorithms, laying the foundation for coordinated control between devices.

[0037] S5. The equipment collaborative control parameters are adjusted through the optimization algorithm to optimize the working status between different equipment. The optimization algorithm takes into account the interaction between equipment, including a bandwidth adjustment algorithm based on multi-band signal strength and an equipment load balancing algorithm.

[0038] It should be noted that the interaction between devices is an important factor in collaborative control. When multiple devices work together, factors such as signal strength, bandwidth allocation and load balancing will directly affect the collaborative efficiency of the devices. The optimization algorithm can not only reduce the uneven load between devices by intelligently adjusting these parameters, but also optimize the allocation of signal resources and improve the overall production efficiency and quality of the spinning process. In particular, the bandwidth adjustment algorithm and load balancing algorithm can effectively reduce the working instability caused by equipment overload or signal interference.

[0039] S6. Finally, the adjusted control signal is transmitted to each device through the wireless communication module to achieve synchronous adjustment of the devices.

[0040] It should be noted that after the optimization and adjustment of the equipment parameters are completed, the adjusted control signal needs to be transmitted to each device through the wireless communication module. Through the transmission of wireless signals, real-time synchronous adjustment of each device can be achieved to ensure that each device operates efficiently according to the optimized parameters. This synchronous adjustment not only ensures the synergy between devices, but also avoids the impact of the deviation of a single device on the overall production process, thereby improving the stability of the spinning process and product consistency.

[0041] It should be further explained that the equipment working efficiency is defined as the ratio of the spinning output per unit time to the equipment power consumption, and the equipment response delay is the time difference from receiving the adjustment signal to the start of the equipment action.

[0042] In a possible implementation, the calculation formula for equipment working efficiency is:

[0043]

[0044] Among them, η is the equipment working efficiency, P output is the spinning output of the equipment, in kg, P input is the power consumption of the device, in W, t operatingis the operating time of the equipment, in seconds, α is the adjustment coefficient, t adjust is the adjustment time, the unit is s, t total is the total working time of the equipment, in seconds. The above formula improves the responsiveness of the equipment to the spinning efficiency during the adjustment process by taking the delay time factor during the equipment adjustment process into consideration.

[0045] It should be noted that this formula is intended to measure the production efficiency of the equipment, that is, the energy efficiency performance of the equipment per unit time. Specifically, it quantifies the energy utilization of the equipment during operation by comparing the ratio between the output output of the equipment and the input power consumption. When considering the operation of the equipment, the impact of the equipment adjustment time on production efficiency is very important. During the adjustment process, the equipment requires a certain amount of time to optimize the parameters, which usually leads to reduced efficiency. Therefore, an adjustment coefficient α is added to the formula to compensate for the impact of this adjustment.

[0046] By calculating the amount of fiber that can be produced per unit of power consumed The energy efficiency of the equipment can be effectively evaluated. Improving working efficiency means that the equipment can produce more fibers while consuming the same power.

[0047] The delay of the equipment in the adjustment process will affect the overall production efficiency. The effect of adjustment time is added by adjusting the coefficient α and the ratio It can reflect the efficiency loss of the equipment when adjusting its status. By optimizing the adjustment process, the negative impact of adjustment time on production efficiency can be reduced.

[0048] Among them, the adjustment coefficient α is used to consider the impact of the delay time in the equipment adjustment process on the equipment working efficiency. It reflects the impact of time waste in the equipment adjustment process on efficiency and can be obtained by the following method:

[0049]

[0050] Among them, T adjust The time required for the device to adjust is usually determined by the device's control response time, mechanical adjustment speed, and device feedback time. total It is the total working time of the equipment, that is, the time from the start of the equipment to the completion of the entire cycle.

[0051] The specific steps are as follows: Through the actual test equipment adjustment time, record the time T required for equipment adjustment under normal working conditions. adjust , under different workloads, by running the device for a long time, record the total working time T of the device total, the adjustment coefficient α is calculated based on the data through the above formula, so as to quantify the impact of equipment adjustment time on work efficiency. The larger α is, the more time is wasted in the equipment adjustment process, and the greater the loss of work efficiency is. Therefore, the equipment needs to minimize the adjustment time. By optimizing the adjustment strategy and reducing the α value, the overall work efficiency of the equipment can be improved.

[0052] In a possible implementation, the calculation formula for the device response delay is:

[0053]

[0054] Where Δt is the device response delay, T response is the device response time, in seconds, T load is the equipment load time, in seconds, T comm is the communication delay, in seconds, β is the signal attenuation factor, S signal is the device signal strength in dBm, d is the distance between devices in meters. The above formula takes into account the factors of device load, communication delay, and signal attenuation, making the calculation of response delay more accurate.

[0055] It should be noted that response delay is a key indicator to measure the speed at which a device responds to a control signal. In a system with collaborative control of multiple devices, a lower response delay helps improve the coordination between devices and the synchronization of the entire production line. This formula can more accurately describe the time delay of a device responding to a control signal by comprehensively considering multiple factors such as device load, communication delay, and signal attenuation. The first term in the formula reflects the change in the device's response time under the influence of load and communication delay; the second term takes into account the effects of signal transmission quality, signal strength, and attenuation factor on the response delay.

[0056] The response time of a device under load is affected by production tasks and workload, while communication delay is the inevitable delay in information transmission between devices. By taking these two factors into consideration, the response delay of the device in the actual working environment can be more realistically reflected.

[0057] The attenuation of the signal is directly related to the distance between the devices. The farther the distance between the devices, the more obvious the signal attenuation, resulting in increased response delay. Introducing the signal attenuation factor β and signal strength S signal factors, the communication quality of the system can be optimized, thereby reducing the response delay.

[0058] The above formula helps to accurately predict the delay of the device responding to the control signal and provides a theoretical basis for optimizing the coordinated operation of the device. By optimizing signal transmission and adjusting the distance between devices, the response delay can be effectively reduced and the real-time performance of the coordinated operation of the devices can be improved.

[0059] Among them, the signal attenuation factor β is used to describe the signal strength loss caused by environmental factors (such as device spacing, obstacles, air humidity, etc.) during signal propagation. It can be obtained through theoretical modeling and actual testing.

[0060]

[0061] Among them, S tx Indicates the signal strength of the sending end, in dBm, S rx It indicates the signal strength at the receiving end in dBm. d is the distance between devices in meters. ln(d) is the logarithm of the distance between devices and is used to indicate the attenuation of the signal as the distance changes.

[0062] The specific steps are as follows: In the experimental environment, set different device spacings d and measure the signal strength between devices at various distances. Environmental modeling: By considering the influence of environmental factors (such as buildings, air humidity, temperature, etc.), model the signal propagation and obtain the signal attenuation coefficient under different conditions. Calculate the signal attenuation factor: According to the experimental data, the signal attenuation factor β is calculated by the above formula to understand the signal attenuation law between different devices. The size of β reflects the degree of attenuation of the signal during the propagation between devices. Generally, as the distance between devices increases, the attenuation factor β increases. By adjusting the layout of the equipment or increasing the transmission power, the transmission of the signal can be optimized and the impact of signal attenuation can be reduced.

[0063] In one possible implementation, the optimization of equipment working efficiency is based on the following optimization algorithm:

[0064] The bandwidth adjustment algorithm based on multi-band signal strength dynamically adjusts the data transmission bandwidth by detecting the spectrum density of the current signal; the load balancing algorithm based on device response delay analyzes the device response delay data and reasonably allocates tasks to the device to avoid device overload. The core of the algorithm is to analyze the real-time working status of each device, calculate the optimal resource allocation plan, and adjust the control signals of each device in real time to achieve collaborative work.

[0065] In a possible implementation, Figure 2 As shown, the bandwidth adjustment algorithm based on multi-band signal strength includes the following steps:

[0066] S501, obtaining signal strength data of each device, and calculating the signal attenuation rate according to the signal strength difference between the device and the control center;

[0067] S502, adjusting the communication bandwidth according to the signal attenuation rate to ensure the reliability and rate of signal transmission;

[0068] S503. Calculate the working efficiency parameter of each device according to the bandwidth adjustment, and optimize and adjust the working state of the device. The calculation formula of the signal attenuation rate is:

[0069]

[0070] Where γ is the signal attenuation rate in dB / m, S tx is the signal strength at the transmitting end, in dB / m, S rx is the signal strength at the receiving end, in dB / m, d is the distance between devices, in m, κ is the attenuation coefficient, f oper is the operating frequency of the device in Hz, f control To control the frequency, the unit is Hz. The above formula further improves the accuracy of bandwidth adjustment by introducing the attenuation coefficient and frequency adjustment factor.

[0071] It should be noted that the above formula is used to calculate the signal attenuation rate γ during signal transmission between devices. Signal attenuation refers to the degree to which a signal gradually weakens during transmission due to factors such as distance and frequency. The formula calculates the signal attenuation rate by considering the difference in signal strength between the transmitter and receiver, the distance between devices, and the attenuation coefficient. In addition, the formula further refines the estimation of signal attenuation by considering the operating frequency and control frequency of the device, which is the frequency adjustment factor.

[0072] Signal attenuation and distance relationship: ln(d) in the formula reflects the degree of signal attenuation at different distances. Generally, the farther the distance between devices, the more obvious the signal attenuation. Using a logarithmic relationship can more accurately simulate the attenuation process of the signal as the distance increases.

[0073] The operating frequency and control frequency of the device will affect the propagation characteristics of the signal. Signals with higher frequencies attenuate faster in the air, so the frequency factor is introduced. This allows for a better estimate of the signal's decay rate.

[0074] The attenuation coefficient κ reflects the impact of environmental factors on signal attenuation, including the material of the device, terrain, and other environmental conditions. By adjusting this coefficient, it is possible to more flexibly adapt to signal propagation in different environments.

[0075] In one possible implementation, a multi-band wireless communication network transmits data via at least two frequency bands, including a low frequency band (<1 GHz) and a high frequency band (>1 GHz), to meet the communication requirements of different devices and ensure communication quality and speed.

[0076] In a possible implementation, a multi-band wireless communication network automatically selects the best frequency band for data transmission through a scheduling algorithm. The scheduling algorithm includes frequency band selection and load balancing mechanisms to optimize data transmission efficiency.

[0077] In a possible implementation, the calculation formula of the scheduling algorithm is:

[0078]

[0079] Among them, F select is the selected frequency band, S freq1 and S freq2 They are the signal strength of the low frequency band and the high frequency band, in dBm, L freq1 and L freq2 They are the load conditions of the low frequency band and the high frequency band, the unit is %, T comm1 and T comm2 They are the communication delays of low frequency band and high frequency band, in s, T lood1 and T lood2 are the load times of the low frequency band and the high frequency band respectively, in seconds. The above formula automatically selects the optimal frequency band by comprehensively considering signal strength, load and communication delay.

[0080] It should be noted that the above formula is used to automatically select the optimal frequency band for data transmission. By comprehensively considering the signal strength, load and communication delay of each frequency band, the formula can select the frequency band that best suits the current device needs to maximize data transmission efficiency and network performance. The selected frequency band is based on the comprehensive ratio of signal strength to load and delay, and the max operation of the formula selects the optimal frequency band.

[0081] Signal strength directly affects the quality of data transmission. The greater the signal strength, the higher the reliability and rate of transmission. Therefore, the signal strength S is used in the formula freq To measure the potential transmission capacity of each frequency band.

[0082] The load and communication delay of the frequency band determine its transmission efficiency. A frequency band with a high load means that resource usage is close to saturation, while a long communication delay will reduce the data transmission rate. Therefore, by weighting the load and communication delay, you can ensure that the selected frequency band can balance various parameters and avoid selecting a frequency band that is too crowded or has too high a delay.

[0083] By comprehensively considering signal strength, load, and communication delay, the formula can select the optimal frequency band to ensure that devices can transmit data with lower latency and higher efficiency.

[0084] In a possible implementation, Figure 3 As shown, the load balancing mechanism in the scheduling algorithm is carried out through the following steps:

[0085] S901. Obtain the real-time load status of each frequency band;

[0086] S902, calculating a load balancing index according to the load condition and signal strength;

[0087] S903. Dynamically select a suitable frequency band for data transmission according to the load balancing index to ensure load balancing of each device and maximize resource utilization.

[0088] In a possible implementation, the calculation formula of the load balancing index is:

[0089]

[0090] Among them, L balance is the load balancing index, L freqi is the load value of frequency band i, in %, S freq is the signal strength of frequency band i, in dBm, T loodi is the load time of frequency band i, in seconds, T comm is the communication delay of frequency band i, in seconds, and n is the total number of device frequency bands.

[0091] It should be noted that the load balancing index L balance The relationship between the load, signal strength, and communication delay of each frequency band is calculated, which helps the system dynamically select the optimal frequency band for data transmission among multiple frequency bands. By weighting the load, signal strength, and communication delay of the frequency band, the formula can balance the load of each frequency band and ensure the reasonable allocation of network resources.

[0092] The combination of load and signal strength can effectively reflect the load pressure and signal transmission capacity of each frequency band. Highly loaded frequency bands may lead to reduced data transmission efficiency, while frequency bands with higher signal strength have stronger transmission capacity. By combining the two, the formula can take into account the resource usage of each frequency band and its transmission potential.

[0093] Load time and communication delay have an important impact on the transmission efficiency of the frequency band. Long load time may mean that the frequency band is overloaded, while communication delay may cause data transmission bottlenecks. By weighting these two factors, the formula can ensure that the selected frequency band not only has good signal strength, but also completes the data transmission task in a reasonable time.

[0094] By calculating the load balancing index, the system can dynamically select a frequency band with a more balanced load according to real-time conditions to improve the working efficiency of the equipment, reduce the impact of overloaded frequency bands, and ultimately achieve the best data transmission effect.

[0095] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0096] (1) In the present invention, the problem of unstable communication between devices caused by signal interference and insufficient bandwidth in traditional technologies is solved through multi-band wireless communication technology, and real-time and efficient data transmission and information synchronization between different chemical fiber spinning equipment are realized, thereby improving the collaborative working efficiency of the equipment and reducing the response delay between the equipment;

[0097] (2) In the present invention, by dynamically adjusting the working parameters of the spinning equipment (such as spinning speed, temperature, pressure, etc.), the present invention realizes the coordinated control between the equipment, so that each equipment operates in the best working state, thereby ensuring the uniformity and stability of the spinning process, significantly improving the quality and consistency of the product, and reducing the generation of defective products;

[0098] (3) In the present invention, the collaborative control parameters of the equipment are adjusted by optimizing the algorithm, and the working state of the equipment is dynamically adjusted based on factors such as multi-band signal strength and equipment load balance, thereby reducing energy waste and equipment idle time, improving overall production efficiency, and achieving more efficient use of energy and resources.

[0099] The above contents are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

[0100] There are a few points to note:

[0101] (1) The drawings of the embodiments of the present invention only relate to the structures related to the embodiments of the present invention, and other structures may refer to the general design.

[0102] (2) For the sake of clarity, in the drawings used to describe the embodiments of the present invention, the thickness of the layers or regions is exaggerated or reduced, that is, these drawings are not drawn according to the actual scale. It is understood that when an element such as a layer, film, region or substrate is referred to as being "on" or "under" another element, the element may be "directly" "on" or "under" the other element or there may be intermediate elements.

[0103] (3) In the absence of conflict, the embodiments of the present invention and the features therein may be combined with each other to obtain new embodiments.

[0104] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for collaborative control of chemical fiber spinning equipment based on multi-band wireless communication, characterized in that: include: S1. Determine the operating parameters of the chemical fiber spinning equipment, wherein the operating parameters include spinning speed, temperature, pressure and wind speed, so as to set the initial working state of the equipment; S2. Establishing a communication link between devices through a multi-band wireless communication network, including at least two spinning devices and their respective control modules, and transmitting data through wireless signals to ensure synchronous transmission of information between modules of each device; S3. According to the real-time working status of the spinning equipment, the operating parameters are dynamically adjusted to achieve coordinated work among the equipment and optimize the spinning quality; S4. Calculate device collaborative control parameters according to the operation data of the device, including device work efficiency parameters, device work efficiency, and device response delay parameters, device response delay; S5. Adjusting device collaborative control parameters through an optimization algorithm to optimize the working status of different devices. The optimization algorithm takes into account the interaction between devices, and specifically includes a bandwidth adjustment algorithm based on multi-band signal strength and a device load balancing algorithm; S6. Finally, the adjusted control signal is transmitted to each device through the wireless communication module to achieve synchronous adjustment of the devices; Among them, the equipment working efficiency is defined as the ratio of spinning output to equipment power consumption per unit time, and the equipment response delay is the time difference from receiving the adjustment signal to the start of equipment action.

2. The method for collaborative control of chemical fiber spinning equipment based on multi-band wireless communication according to claim 1, characterized in that: include: The calculation formula of the equipment working efficiency is: Among them, η is the equipment working efficiency, P output is the spinning output of the equipment, in kg, P inpu is the power consumption of the device, in W, t operating is the operating time of the equipment, in seconds, α is the adjustment coefficient, t adjust is the adjustment time, the unit is s, t total is the total working time of the equipment, in seconds. The above formula improves the responsiveness of the equipment to the spinning efficiency during the adjustment process by taking the delay time factor during the equipment adjustment process into consideration.

3. The method for collaborative control of chemical fiber spinning equipment based on multi-band wireless communication according to claim 1, characterized in that: include: The calculation formula of the device response delay is: Where Δt is the device response delay, T response T is the device response time, in seconds. load is the equipment load time, in seconds, T comm is the communication delay, in seconds, β is the signal attenuation factor, S signal is the device signal strength in dBm, d is the distance between devices in meters. The above formula takes into account the factors of device load, communication delay, and signal attenuation, making the calculation of response delay more accurate.

4. The method for collaborative control of chemical fiber spinning equipment based on multi-band wireless communication according to claim 2, characterized in that: include: The optimization of the equipment working efficiency is based on the following optimization algorithm: The bandwidth adjustment algorithm based on multi-band signal strength dynamically adjusts the data transmission bandwidth by detecting the spectrum density of the current signal; the load balancing algorithm based on device response delay analyzes the device response delay data and reasonably allocates tasks to the device to avoid device overload. The core of the algorithm is to analyze the real-time working status of each device, calculate the optimal resource allocation plan, and adjust the control signals of each device in real time to achieve collaborative work.

5. The method for collaborative control of chemical fiber spinning equipment based on multi-band wireless communication according to claim 4, characterized in that: The bandwidth adjustment algorithm based on multi-band signal strength includes the following steps: S501, obtaining signal strength data of each device, and calculating the signal attenuation rate according to the signal strength difference between the device and the control center; S502, adjusting the communication bandwidth according to the signal attenuation rate to ensure the reliability and rate of signal transmission; S503. Calculate the working efficiency parameter of each device according to the bandwidth adjustment, and optimize and adjust the working state of the device. The calculation formula of the signal attenuation rate is: Where γ is the signal attenuation rate in dB / m, S tx is the signal strength at the transmitting end, in dB / m, S rx is the signal strength at the receiving end, in dB / m, d is the distance between devices, in m, K is the attenuation coefficient, f oper is the operating frequency of the device in Hz, f control To control the frequency, the unit is Hz. The above formula further improves the accuracy of bandwidth adjustment by introducing the attenuation coefficient and frequency adjustment factor.

6. The method for collaborative control of chemical fiber spinning equipment based on multi-band wireless communication according to claim 1, characterized in that: include: The multi-band wireless communication network transmits data via at least two frequency bands, including a low frequency band and a high frequency band, to meet the communication requirements of different devices and ensure communication quality and speed.

7. The method for collaborative control of chemical fiber spinning equipment based on multi-band wireless communication according to claim 6, characterized in that: include: The multi-band wireless communication network automatically selects the best frequency band for data transmission through a scheduling algorithm, and the scheduling algorithm includes a frequency band selection and a load balancing mechanism to optimize data transmission efficiency.

8. The method for collaborative control of chemical fiber spinning equipment based on multi-band wireless communication according to claim 7, characterized in that: include: The calculation formula of the scheduling algorithm is: Among them, F select is the selected frequency band, S freq1 and S freq2 They are the signal strength of the low frequency band and the high frequency band, in dBm, L freq1 and L freq2 They are the load conditions of the low frequency band and the high frequency band, in %, T comm1 and T comm2 They are the communication delays of low frequency band and high frequency band, in s, T lood1 and T lood2 are the load times of the low frequency band and the high frequency band respectively, in seconds. The above formula automatically selects the optimal frequency band by comprehensively considering signal strength, load and communication delay.

9. The method for collaborative control of chemical fiber spinning equipment based on multi-band wireless communication according to claim 8, characterized in that: include: The load balancing mechanism in the scheduling algorithm is performed by the following steps: S901, obtaining the real-time load status of each frequency band; S902, calculating a load balancing index according to the load condition and signal strength; S903. Dynamically select a suitable frequency band for data transmission according to the load balancing index to ensure load balancing of each device and maximize resource utilization.

10. The method for collaborative control of chemical fiber spinning equipment based on multi-band wireless communication according to claim 9, characterized in that: include: The calculation formula of the load balancing index is: Among them, L balance is the load balancing index, is the load value of frequency band i, in %, is the signal strength of frequency band i, in dBm, T loodi is the load time of frequency band i, in seconds, T comm is the communication delay of frequency band i, in seconds, and n is the total number of device frequency bands.

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