Spindle speed and twist control system of yarn covering machine

Abstract

The invention relates to the technical field of textile machinery, and discloses a covering yarn machine spindle speed and twist control system which comprises a data acquisition module, a global control module, an individual diagnosis module, a power execution module and a man-machine interaction module. The actual average speed of the whole machine is calculated by collecting the speed of each spindle in real time, and PID closed-loop control is carried out on the actual average speed and a set value, so that the systematic speed deviation of the whole machine is accurately corrected. Meanwhile, the individual diagnosis module calculates spindle difference signals of the speeds of the spindles and the average speed of the whole machine in parallel, time domain and frequency domain analysis is carried out on the signals, and hidden faults such as steady-state deviation, periodic fluctuation and transient impact existing in a single spindle are accurately recognized. And finally, the system carries out visual early warning through a human-computer interaction interface and provides a predictive maintenance instruction. According to the method, high-precision control of the twist and high consistency of products are achieved, an effective predictive maintenance mechanism is established, and the production quality and the intelligent level are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of textile machinery, in particular to a twist control system for a covered yarn machine. BACKGROUND

[0002] The covered yarn machine is a key equipment in the textile industry. Its core function is to evenly wrap the outer fiber (such as nylon, polyester) on the core yarn (such as spandex) through the high-speed rotating spindle, forming elastic yarn. In this process, the twist of the yarn, i.e. the number of twists per unit length, is a key process parameter that determines the physical properties of the final product such as elasticity, hand feeling, strength and appearance. Therefore, accurate control and consistency of the twist are crucial to ensure product quality and meet the requirements of downstream weaving processes.

[0003] However, the existing covered yarn machine has inherent technical limitations in spindle speed and twist control. The commonly used control method is to use a frequency converter to drive the main motor, and then distribute power to hundreds of spindles through the whole machine transmission system such as the dragon belt. This method is based on the premise that the speed of all spindles can accurately follow the speed change of the main motor. However, in actual production, due to factors such as uneven and slipping of the dragon belt tension, differences in bearing wear and lubrication state of each spindle, and individual dynamic imbalance of the spindle core and spindle disc, this premise is often difficult to establish. This directly leads to two levels of problems: first, the actual average speed of all spindles in the whole machine deviates from the theoretical process set value calculated by the frequency of the frequency converter, causing systematic batch deviation of product twist; second, the actual speed of each spindle is different, which destroys the quality consistency of the yarn produced by a single machine.

[0004] In addition, in terms of equipment operation state monitoring and fault diagnosis, the existing technology also shows significant shortcomings. The traditional equipment maintenance mode usually relies on periodic inspection by operators or post-fault troubleshooting after the occurrence of explicit faults such as yarn breakage and yarn winding. This method is not only inefficient and lagging in response, but also highly dependent on human experience, making it difficult to accurately locate faults. More importantly, it cannot effectively identify implicit faults in the embryonic state, such as minor vibrations caused by initial bearing wear or periodic speed fluctuations caused by slight imbalance of the spindle disc. These implicit faults have been continuously affecting the yarn quality of individual spindles before evolving into explicit faults. This passive maintenance strategy often leads to unplanned downtime of the equipment and a large number of defective products, significantly increasing operating and maintenance costs and production losses, and cannot meet the needs of modern textile industry for predictive maintenance and intelligent production management. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a covered yarn machine spindle speed and twist control system, which solves the problem that the stability and consistency of the speed of each spindle of the existing covered yarn machine are difficult to maintain due to factors such as power grid fluctuation and equipment mechanical difference during operation, thereby causing uneven yarn twist.

[0006] To achieve the above object, the present application provides a covered yarn machine spindle speed and twist control system, comprising:

[0007] A data acquisition module, which comprises a speed measurement sensor arranged on each spindle of the covered yarn machine, is used to acquire the instantaneous angular velocity of each spindle at a preset sampling frequency and output the acquired instantaneous angular velocity data.

[0008] A global control module, the input end of which is connected with the output end of the data acquisition module. The global control module is used to receive the instantaneous angular velocity data of all spindles and perform the following operations:

[0009] Calculate the arithmetic mean of the instantaneous angular velocities of all spindles to obtain the average speed of the whole machine;

[0010] Compare the average speed of the whole machine with a preset spindle speed reference value to obtain a global speed error;

[0011] Generate a global control signal through a preset control algorithm according to the global speed error.

[0012] An individual diagnosis module, the input end of which is connected with the output end of the data acquisition module and the global control module. The individual diagnosis module is used to receive the instantaneous angular velocity of each spindle and the average speed of the whole machine and perform the following operations:

[0013] Extract the difference between the instantaneous angular velocity of each spindle and the average speed of the whole machine to obtain a spindle difference signal of the spindle;

[0014] Analyze and process the spindle difference signal to diagnose the running state of the spindle.

[0015] A power execution module, the control input end of which is connected with the output end of the global control module. The power execution module is used to receive the global control signal and adjust the power output of the covered yarn machine accordingly. The power execution module can comprise a frequency converter and a three-phase asynchronous motor.

[0016] A man-machine interaction and decision support module, which is connected with the global control module and the individual diagnosis module. The module is used to:

[0017] An interface is provided for a user to input process parameters and thresholds required for diagnosis; the process parameters include target twist and delivery speed, and the global control module calculates spindle speed reference value based on the two parameters;

[0018] The running state of each spindle output by the individual diagnosis module is received, and a visual state indication is made for each spindle;

[0019] Based on the running state, predictive maintenance instructions are generated and displayed.

[0020] In one embodiment, the individual diagnosis module analyzes and processes the spindle difference signal in the following manner: within a preset time window, the spindle difference signal sequence is subjected to Fourier transform to generate a spindle difference characteristic spectrum of the spindle. Subsequently, based on the spindle difference characteristic spectrum and / or the original spindle difference signal, the running state is diagnosed.

[0021] The specific diagnosis logic includes one or more of the following:

[0022] Steady-state deviation diagnosis: it is determined whether the DC component amplitude of the spindle difference characteristic spectrum at a frequency of zero satisfies a preset condition. For example, it is determined whether the following relationship is satisfied:

[0023] |S i (f0)|>θ ss ;

[0024] Where |S i (f0)| is the DC component amplitude of the spindle difference characteristic spectrum of the i-th spindle at a frequency of zero, and θ ss is a preset steady-state deviation threshold.

[0025] Periodic deviation diagnosis: it is determined whether there is an energy peak in the non-zero frequency band of the spindle difference characteristic spectrum, and whether the amplitude of the energy peak satisfies a preset condition. For example, it is determined whether there is a frequency f p > 0, and the amplitude thereof satisfies the following relationship:

[0026] |S i (f p )|>θ p ;

[0027] Where |S i (f p )| is the amplitude of the spindle difference characteristic spectrum of the i-th spindle at the frequency f p of the energy peak, and θ p is a preset periodic deviation amplitude threshold. If the condition is satisfied, it is determined that the spindle has periodic deviation.

[0028] Transient impact diagnosis: determining whether the absolute value of the change rate of the spindle difference signal in the time domain satisfies a preset condition. For example, by determining whether the following relationship is satisfied at discrete sampling time k:

[0029]

[0030] where Δω i (k) is the spindle difference signal value of the ith spindle at time k, Δt is the sampling time interval, θ t is the preset transient impact change rate threshold. If the condition is satisfied, it is determined that the spindle has a transient impact.

[0031] In one embodiment, the visualization state indication performed by the human-computer interaction and decision support module includes: marking the spindle diagnosed as having a steady-state deviation or a periodic deviation as an attention state; and marking the spindle diagnosed as having a transient impact as an alarm state.

[0032] The second aspect of the application provides a method for controlling the spindle speed and twist of a covering machine, the method comprising the following steps:

[0033] The instantaneous angular velocity of each spindle is collected in real time by a speed sensor arranged on each spindle.

[0034] The arithmetic mean of all collected instantaneous angular velocities is calculated to obtain the overall average speed.

[0035] The overall average speed is compared with a preset spindle speed reference value to generate a global speed error, and a global closed-loop feedback control is performed based on the error to adjust the output of the power execution module driving the covering machine.

[0036] The difference between the instantaneous angular velocity of each spindle and the overall average speed is extracted to obtain the spindle difference signal of the spindle.

[0037] The spindle difference signal of each spindle is analyzed to diagnose the running state of the spindle.

[0038] According to the diagnosed running state, a visual warning or predictive maintenance guidance is performed on the human-computer interaction interface.

[0039] The application provides a covering machine spindle speed and twist control system. The system has the following advantages:

[0040] 1、The present application sets up global control module to compensate the common drift caused by power grid fluctuation and other factors based on the average speed of the whole machine; at the same time, the individual diagnosis module isolates and analyzes the independent running characteristics of each spindle by extracting spindle difference signal. This separate control avoids the interference of the abnormal state of individual spindle on the whole machine control system, thereby improving the stability and accuracy of system control, which is beneficial to ensure the high uniformity of the final yarn twist.

[0041] 2、The individual diagnosis module of the present application generates spindle difference characteristic spectrum by Fourier transform of the spindle difference signal, and can identify the progressive failure caused by mechanical resistance, component imbalance and other reasons according to the steady-state deviation or periodic deviation characteristics in the spectrum. So that the maintenance personnel can obtain clear fault positioning information before the equipment has significant performance degradation or shutdown failure, and carry out targeted maintenance.

[0042] 3、The individual diagnosis module of the present application can detect transient impact in real time, which can immediately warn the sudden events caused by winding, yarn breakage or bearing jamming, so as to gain time for intervention, which helps to prevent equipment damage or a large amount of waste. At the same time, the visual state indication provided by the man-machine interaction and decision support module can intuitively present the health status of all spindles of the whole machine, which provides clear and quantitative decision basis for production managers. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 The system architecture of the present application is shown in the figure;

[0044] Figure 2 The internal function block diagram of the global control module of the present application is shown in the figure;

[0045] Figure 3 The schematic diagram of the power execution module of the present application is shown in the figure;

[0046] Figure 4 The interface schematic diagram of the man-machine interaction and decision support module of the present application is shown in the figure;

[0047] Figure 5 The method flow chart of the present application is shown in the figure.

[0048] Among them, 10, data acquisition module; 20, global control module; 30, individual diagnosis module; 40, power execution module; 50, man-machine interaction and decision support module. DETAILED DESCRIPTION

[0049] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of the present application.

[0050] Embodiment:

[0051] Please refer to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of the present application. Figure 1 The present application provides a kind of covering silk machine spindle speed, twist control system, comprising:

[0052] Data acquisition module 10, for real-time acquisition of the instantaneous angular velocity of each spindle of covering silk machine;

[0053] Data acquisition module 10 is configured to non-contact, high-frequency measurement of the running speed of each spindle on the covering silk machine.In specific implementation, data acquisition module includes multiple speed measurement units corresponding to each spindle.

[0054] Each speed measurement unit includes a speed sensor and a feature body rotating synchronously with the spindle.In the present embodiment, the speed sensor can be a Hall effect sensor, which is fixedly installed on the stationary frame of the covering silk machine, close to the rotation path of the spindle.The feature body can be one or more permanent magnets, which are embedded or fixed on the rotating part of the spindle, such as the lower part of the spindle or the spindle disc.

[0055] As another alternative embodiment, the speed sensor can also be an optical encoder.At this time, a code disc coaxially installed with the spindle replaces the feature body, and the code disc is engraved with uniformly distributed light transmission or light reflection grids.A fixed photoelectric sensor generates a pulse signal by detecting the passing of the grids.Alternatively, an eddy current sensor or a capacitive sensor can be used to detect the pre-set groove or protrusion on the rotating part of the spindle to achieve speed measurement.

[0056] When the spindle rotates, the feature body fixed thereto makes a circular motion.Each time the feature body passes through the effective sensing area of the speed sensor, the output level of the speed sensor will jump once, thereby generating a pulse signal.Therefore, in a rotation period, the speed sensor will output one or more pulses (depending on the number of feature bodies).The frequency of the pulse signal sequence is directly proportional to the instantaneous angular velocity of the spindle.

[0057] The data acquisition module 10 also includes a signal processing circuit for processing the raw pulse signals outputted by the speed sensors and calculating the instantaneous angular velocity values. The signal processing circuit can be a high-speed counter input port of a programmable logic controller (PLC). The high-speed counter takes a fixed, short time period Δt as a sampling window and counts the number of pulses P i outputted by each speed sensor. At the end of each sampling period Δt, the signal processing circuit calculates the instantaneous angular velocity ω i (t) of the i-th spindle within the time window according to the count value P mag and the number of features N i on the spindle. The calculation relationship is as follows:

[0058]

[0059] wherein the unit of ω i (t) is (radians / second), P i is the number of pulses collected within the time Δt, N mag is the number of features (permanent magnets) installed on the spindle, and the unit of Δt is (seconds).

[0060] The value of the sampling period Δt determines the detection ability of the system to the speed fluctuation. In order to capture the high-frequency speed changes caused by mechanical vibration and other factors, the value of Δt is set in a small range, for example, 1 millisecond to 10 milliseconds. This setting ensures that the collected instantaneous angular velocity data can reflect the dynamic details of the spindle operation, providing a data basis for the accurate analysis of the subsequent individual diagnosis module 30.

[0061] Finally, the value ω i (t) of the instantaneous angular velocity of each spindle calculated by the data acquisition module 10 is transmitted to the global control module 20 and the individual diagnosis module 30 in real time as the input for their operation and analysis.

[0062] The global control module 20, connected with the data acquisition module, is used to calculate the average speed of the entire machine based on the instantaneous angular velocities of all spindles, and to perform global closed-loop feedback control according to the deviation of the average speed of the entire machine from the preset spindle speed reference value.

[0063] Referring to the attached Figure 2 , the data input end of the global control module 20 receives the instantaneous angular velocity data stream of all spindles from the data acquisition module 10, the parameter input and data display end is connected with the human-computer interaction and decision support module 50, and the control output end is connected with the power execution module 40. In this embodiment, the functions of this module can be realized through the program logic of a programmable logic controller (PLC).

[0064] The global control module 20 can include a reference value calculation unit 21, an average speed calculation unit 22, and a PID control law execution unit 23.

[0065] The reference value calculation unit 21 is configured to calculate the reference value of the spindle speed ω set of the entire machine according to the process parameters obtained from the human-computer interaction and decision support module 50.

[0066] ω set = T set ω set = T set × V yarn ;

[0067] wherein T set is the target twist set, with the unit of (twist / meter); V yarn is the set yarn delivery speed, with the unit of (meter / minute); and ω set calculated is the reference value of the spindle speed, with the unit of (turn / minute). This ω set value is used as the target set value of the entire closed-loop control system.

[0068] The average speed calculation unit 22 is configured to process all the instantaneous angular speeds ω i (k) of the N spindles received from the data acquisition module 10 in each discrete control period k, and calculate the average speed of the entire machine The calculation is to take the arithmetic average of all the instantaneous angular speeds:

[0069]

[0070] wherein ω i (k) is the instantaneous angular speed of the i-th spindle in the k-th control period, and N is the total number of spindles of the covering machine. The average speed of the entire machine calculated will be sent to the PID control law execution unit 23 as a feedback value, and also be transmitted to the individual diagnosis module 30.

[0071] The PID control law execution unit 23 is configured to execute a closed-loop feedback control algorithm. In each control period k, the unit first calculates the global speed error e g (k):

[0072]

[0073] wherein e g (k) is the deviation between the reference value of the spindle speed and the average speed of the entire machine.

[0074] Then, the unit calculates the control quantity u(k) that should be output in the current cycle through the position PID control algorithm based on the current and historical global speed errors. The relationship is:

[0075]

[0076] in:

[0077] K p , K i , K d They are proportional, integral and differential gain coefficients respectively, which are set and stored in the module during the system debugging phase and can also be adjusted through the human-computer interaction and decision support module 50;

[0078] is the cumulative sum of errors from system startup to the current moment;

[0079] e g (k-1) is the global velocity error of the previous control cycle;

[0080] Δt is the sampling time interval of the control system, which is consistent with the sampling period of the data acquisition module 10 .

[0081] The final calculated control quantity u(k) is a digital signal, which is output to the power execution module 40. For example, the signal can be a value corresponding to the target motor frequency. The inverter in the power execution module 40 will adjust its output frequency according to this value, thereby accurately adjusting the speed of the drive motor to offset the impact of the common disturbance on the speed of the whole machine and make the average speed of the whole machine Approaching the spindle speed reference value ω set .

[0082] The individual diagnosis module 30 is connected to the data acquisition module and the global control module, and is used to extract the spindle difference signal of each spindle based on the instantaneous angular velocity of each spindle and the average speed of the entire machine, and analyze the spindle difference signal to diagnose the operating status of each spindle;

[0083] The individual diagnosis module 30 has its data input terminals connected to the data acquisition module 10 and the global control module 20. This module receives the instantaneous angular velocity ω of each spindle. i (k) and the average speed of the whole machine calculated by the global control module 20 The diagnosis result is output to the human-computer interaction and decision support module 50. In this embodiment, the function of this module can be implemented by a dedicated digital signal processor (DSP) or in an extended computing module of the main PLC.

[0084] The core function of the individual diagnosis module 30 is to analyze the spindle error signal. First, the module calculates the spindle error signal Δω i (k) of each spindle i in real time at each control cycle k. This signal is defined as the difference between the instantaneous angular velocity of the spindle and the average velocity of the whole machine:

[0085]

[0086] The physical meaning of this spindle error signal Δω i (k) is that it strips off the common velocity fluctuation component acting on all spindles, thus isolating the individualized velocity fluctuation feature related only to the mechanical state of the i-th spindle itself. This signal sequence is the basis for subsequent diagnostic analysis.

[0087] For frequency domain analysis, the individual diagnosis module 30 is configured to process the spindle error signal to generate a spindle error feature spectrum. The process includes: first, a fixed-length time window containing M consecutive sampling points is intercepted from the real-time spindle error signal stream Δω i (k), forming a data frame. In order to suppress the frequency spectrum leakage caused by signal truncation, a window function such as the Hanning window is applied to the data frame before Fourier transform. Subsequently, the windowed data frame is subjected to fast Fourier transform (FFT) to obtain a frequency domain sequence containing M complex points.

[0088] The spindle error feature spectrum is the amplitude spectrum of the frequency domain sequence. The abscissa of the spectrum is the frequency, and the ordinate is the amplitude |S i (f)| of the corresponding frequency component. This spectrum reveals the fluctuation components of different frequencies in the spindle error signal and their energy distribution.

[0089] Based on the time domain spindle error signal Δω i (k) and the frequency domain spindle error feature spectrum |S i (f)|, the individual diagnosis module 30 performs diagnostic logic to determine the running state of the spindle, including the following diagnostic items:

[0090] Diagnosis of steady-state deviation. This diagnosis aims to identify whether there is a persistent speed deviation in the spindle. The basis for judgment is the amplitude of the direct current component at frequency zero (f0=0) in the spindle error feature spectrum. If the amplitude exceeds a preset threshold, it is considered that there is a steady-state deviation. The specific judgment condition is:

[0091] |S i (f0)|>θ ss ;

[0092] Where |S i(f0)| is the DC component amplitude of the i-th spindle signature at frequency zero, which characterizes the average value of the spindle error signal deviating from zero within an observation time window. ss is a pre-set steady-state deviation threshold. Such a deviation is usually related to persistent factors such as excessive spindle bearing resistance, slippage of the spindle belt, or abnormal tension.

[0093] Diagnosis of periodic deviation. This diagnosis aims to identify regular vibrations caused by mechanical component imbalance or periodic defects. The decision method is to search for peaks in the non-zero frequency band (f > 0) of the spindle signature. If there is an energy peak at a certain frequency f p with an amplitude exceeding a pre-set threshold, it is considered that there is a periodic deviation. The specific decision condition is:

[0094] |S i (|S i (f p )|>θ p ;

[0095] where |S i (f p )| is the energy peak amplitude of the i-th spindle signature at frequency f p , and θ p is a pre-set periodic deviation amplitude threshold. The frequency f p at which the peak is located provides important clues about the source of the fault, for example, a peak consistent with the spindle rotation frequency indicates a dynamic imbalance problem.

[0096] Diagnosis of transient impact. This diagnosis is performed in the time domain and aims to capture sudden and dramatic changes in speed caused by broken threads, tangled threads, or foreign objects stuck, etc. The decision method is to calculate the rate of change of the spindle error signal and determine whether its absolute value exceeds a pre-set threshold. In a discrete system, this rate of change can be approximated by first-order difference. The specific decision condition is:

[0097] |(Δω i (k)-Δω i (k-1)) / Δt|>θ t ;

[0098] where Δω i (k) and Δω i (k-1) are the spindle error signal values of the i-th spindle at the current control period k and the previous control period k-1, respectively;

[0099] Δt is the sampling time interval of the system;

[0100] Δt is a pre-set transient impact rate threshold. Satisfying this condition indicates that the spindle speed has changed dramatically in a very short time.

[0101] The individual diagnosis module 30 packs the result of the above one or more diagnoses, i.e. the running state of each spool (normal, steady-state deviation, periodic deviation, transient impact), into state data, and transmits it to the human-computer interaction and decision support module 50 in real time.

[0102] The power execution module 40, connected to the global control module, is used to receive and execute the instructions of the global closed-loop feedback control, and to provide power for the wrapping machine.

[0103] Referring to the accompanying drawings Figure 3 The power execution module 40 receives the control quantity signal from the global control module 20 at its control input end, and is mechanically connected to the whole machine transmission system 60 of the wrapping machine at its power output end.

[0104] In this embodiment, the power execution module 40 includes a frequency converter 41 and a three-phase asynchronous motor 42. The three-phase asynchronous motor 42 is an execution component that provides power for the whole wrapping machine, and its output shaft is coupled to the whole machine transmission system 60 through a belt or a gear, etc., to drive all the spools to rotate synchronously.

[0105] The power input end of the frequency converter 41 is connected to the power grid of the factory, and its three-phase alternating current output end is electrically connected to the stator winding of the three-phase asynchronous motor 42. The control signal input end of the frequency converter 41 is connected to the signal output end of the global control module 20.

[0106] The control quantity u(k) output by the global control module 20 is a digital value. This digital value is first converted into a standard industrial analog signal, such as a 0-10V DC voltage signal or a 4-20mA DC current signal, through the digital-analog conversion (D / A) module of the programmable logic controller (PLC). This analog signal is transmitted to the analog quantity input (AI) port of the frequency converter 41.

[0107] The frequency converter 41 is pre-configured with a set of operating parameters, which define the correspondence between its input analog quantity and output frequency. For example, the parameters are set to a linear correspondence, i.e. when the input signal is 0V, the corresponding output frequency is 0Hz, and when the input signal is 10V, the corresponding output frequency is the preset maximum operating frequency (e.g. 60Hz).

[0108] During operation, the frequency converter 41 monitors the voltage or current value of its analog quantity input port in real time, and calculates the target output frequency according to the preset correspondence. Subsequently, the power semiconductor devices inside the frequency converter 41 rectify and invert the input power frequency alternating current into a three-phase alternating current with adjustable frequency and voltage through pulse width modulation technology, and output it to the three-phase asynchronous motor 42.

[0109] Since the synchronous speed of the three-phase asynchronous motor 42 is directly proportional to the supply frequency, the speed of the motor 42 can be directly controlled by adjusting the output frequency of the frequency converter 41. The change of the motor 42 speed is transmitted to each bobbin through the whole machine transmission system 60, thus achieving the synchronous adjustment of the basic running speed of all bobbins in response to the instructions of the global control module 20, and ultimately making the average speed of the whole machine follows the bobbin speed reference value ω set .

[0110] The man-machine interaction and decision support module 50 is connected with the global control module and the individual diagnosis module, and is used for setting process parameters and diagnosis thresholds, and performing visual state marking and generating predictive maintenance instructions for each bobbin according to the running state diagnosed by the individual diagnosis module.

[0111] Referring to the accompanying Figure 4 , the man-machine interaction and decision support module 50, whose hardware carrier can be an industrial touch screen or an industrial computer display connected to the main control system, runs a graphical user interface software thereon. The module performs bidirectional data communication with the global control module 20 and the individual diagnosis module 30 through industrial Ethernet or RS-485 bus.

[0112] The graphical user interface of the module can be divided into a parameter setting area 51, a state monitoring area 52, and a detailed information and instruction area 53.

[0113] The parameter setting area 51 provides a plurality of text boxes or numerical adjustment controls for user input. The user can input the parameters required by the production process through this area, including the target twist T set and the yarn delivery speed V yarn . After these parameters are input, they will be transmitted by the module 50 to the global control module 20 as the basis for calculating the bobbin speed reference value ω set . In addition, this area also allows the user to set the threshold values for diagnosis, including the steady-state deviation threshold θ ss , the periodic deviation amplitude threshold θ p , and the transient impact change rate threshold θ t . After these threshold parameters are set, they will be transmitted by the module 50 to the individual diagnosis module 30 as the judgment basis of its diagnosis logic.

[0114] The state monitoring area 52 visually displays the real-time running state of all bobbins on the wrapping machine in the form of a matrix or array. Each graphical cell (such as a square or circular icon) in this area corresponds to a physical bobbin in terms of physical location and is identified by its number. The background color of each cell is driven by the running state data of the corresponding bobbin transmitted by the individual diagnosis module 30 in real time. The correspondence between the color and the state is predefined, for example:

[0115] Green: indicates that the spool is in normal operation, and its spool deviation signal has not triggered any diagnostic threshold.

[0116] Yellow: indicates that the spool is in an attention state, and it has been diagnosed with a steady-state deviation or a periodic deviation.

[0117] Red: indicates that the spool is in an alarm state, and it has been diagnosed with a transient impact. In this way, the operator can instantly and globally grasp the health status of each spool.

[0118] The detailed information and instruction area 53 is used to display the detailed diagnostic information and maintenance guidance of a specific spool. When the user selects a cell marked in yellow or red in the state monitoring area 52, this area will be activated and display the following information:

[0119] Spool number: the unique identifier of the selected spool.

[0120] Diagnostic status: a clear text description, such as steady-state deviation, periodic deviation, or transient impact.

[0121] Key diagnostic data: specific quantitative indicators that trigger the alarm or attention state. For example, if it is a steady-state deviation, the current direct current component amplitude |S i (f0)| is displayed; if it is a periodic deviation, the peak frequency f p and its amplitude |S i (f p )| are displayed; if it is a transient impact, the maximum change rate value calculated when the impact occurs is displayed.

[0122] Predictive maintenance instructions: a preset text instruction directly related to the diagnostic state. The instruction is generated based on an internal rule base. For example: if the diagnostic state is a steady-state deviation, the instruction "Check the bearing lubrication status and spool belt tension of spool [i] for normality" is displayed.

[0123] If the diagnostic state is a periodic deviation, the instruction "Check the spool disc and spool core of spool [i] for imbalance or looseness" is displayed.

[0124] If the diagnostic state is "transient impact", the instruction "Immediately stop and check spool [j] for yarn winding, yarn breakage or mechanical jamming" is displayed.

[0125] In addition, the module is also configured to automatically record all diagnosed abnormal events (including event type, occurrence time, spool number, key diagnostic data) into a log file or database. This function provides historical data support for subsequent long-term performance trend analysis of the equipment, fault root cause tracing, and optimization of maintenance plans.

[0126] Reference to the drawings Figure 5 The present application also provides a method for controlling the speed and twist of a covering machine. The method comprises the following steps:

[0127] S100: Collecting the instantaneous angular velocity of each spindle.

[0128] This step measures the rotational speed of each spindle continuously and non-contactly with a preset sampling frequency through the speed sensor configured on each spindle of the covering machine. The measurement result is converted into a digitized instantaneous angular velocity data sequence ω i (k), where i is the spindle number and k is the discrete sampling time point. The data sequence is transmitted to the subsequent processing unit in real time.

[0129] S200: Calculating the machine average speed.

[0130] In each control cycle k, the system receives the instantaneous angular velocity data ω i (k) of all N spindles from step S100. By performing an arithmetic average operation on the N data, the machine average speed of the current cycle is calculated.

[0131] S300: Performing global closed-loop feedback control.

[0132] This step compares the machine average speed calculated in step S200 as the feedback quantity with a preset spindle speed reference value ω set , to obtain the global speed error Subsequently, according to the error, the control quantity u(k) of the power execution module 40 is calculated through the PID control algorithm. The control quantity drives the power execution module 40 to adjust the output, so that the machine average speed tends to the spindle speed reference value ω set , thereby suppressing common speed fluctuations.

[0133] S400: Extracting the spindle difference signal of each spindle.

[0134] This step is performed in parallel with step S300. In each control cycle k, for each spindle i, the system performs a subtraction operation between its instantaneous angular velocity ω i (k) and the machine average speed calculated in step S200, to obtain the spindle difference signal of the spindle. The signal sequence isolates the running characteristics of the individual spindle.

[0135] S500: Analyzing the spindle difference signal and diagnosing the running state.

[0136] This step processes and analyzes the spindifference signal sequence of each spindle obtained in step S400. The analysis includes time-domain analysis and frequency-domain analysis.

[0137] Frequency-domain analysis: a frame of spindifference signal data within a time window is intercepted, and fast Fourier transform is performed thereon to generate a spindifference characteristic spectrum |S i (f) |. Then, a decision is made according to a preset threshold:

[0138] If |S i (f0) | > θ ss , it is determined that the spindle has a steady-state deviation.

[0139] If there is an energy peak at a non-zero frequency f p , and its amplitude |S i (f p ) | > θ p , it is determined that the spindle has a periodic deviation.

[0140] Time-domain analysis: the real-time change rate of the spindifference signal is calculated, and a decision is made according to a preset threshold:

[0141] If |Δω i (k) - Δω i (k-1) | / Δt > θ c , it is determined that the spindle has a transient impact.

[0142] Wherein, |S i (f0) | is the amplitude of the direct current component, θ ss is the steady-state deviation threshold; |S i (f p ) | is the peak amplitude at frequency f p , θ p is the periodic deviation threshold; Δω i (k) is the spindifference signal value at the current time, Δt is the sampling interval, and θ c is the transient impact threshold.

[0143] S600: visual warning and maintenance guidance are provided.

[0144] This step transmits the diagnosis result (normal, steady-state deviation, periodic deviation, or transient impact) of each spindle generated in step S500 to the human-computer interaction and decision support module 50. According to the diagnosis result, the module updates the visual state indication (for example, by changing the color) of the corresponding spindle on the graphical user interface in real time. When a spindle is marked as abnormal, if the user inquires, the system further displays its detailed diagnosis data and specific predictive maintenance instruction text generated based on the preset rule base.

[0145] While embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary of the principles and application of the present application. Numerous modifications and adaptions can be effected without departing from the spirit and scope of the present application, which is not limited to the exact construction and arrangement described. It is to be understood that all related terms not specifically defined in the specification shall be interpreted in accordance with 37 C.F.R. § 1.822.

Claims

1. A spindle speed and twist control system for a covered yarn machine, characterized in that: include: Data acquisition module, used to collect the instantaneous angular velocity of each spindle of the cladding machine in real time; A global control module, connected to the data acquisition module, is used to calculate the average speed of the entire machine based on the instantaneous angular velocity of all spindles, and perform global closed-loop feedback control according to the deviation of the average speed of the entire machine from a preset spindle speed reference value; an individual diagnosis module connected to the data acquisition module and the global control module, for extracting a spindle difference signal of each spindle based on the instantaneous angular velocity of each spindle and the average speed of the entire machine, and analyzing the spindle difference signal to diagnose the operating status of each spindle; A power execution module, connected to the global control module, for receiving and executing instructions of the global closed-loop feedback control to provide power for the covering yarn machine; The human-computer interaction and decision support module is connected to the global control module and the individual diagnosis module, and is used to set process parameters and diagnosis thresholds, and to visually mark the status of each spindle and generate predictive maintenance instructions based on the operating status diagnosed by the individual diagnosis module.

2. A spindle speed and twist control system for a covering yarn machine according to claim 1, characterized in that: The individual diagnostic module is further configured to: Generate a spindle difference characteristic spectrum of each spindle by performing Fourier transform on the spindle difference signal; The operating status of each spindle is diagnosed based on the spindle difference characteristic spectrum.

3. A spindle speed and twist control system for a covering yarn machine according to claim 2, characterized in that: The diagnosis of the operating status includes: determining whether the spindle has a steady-state deviation or a periodic deviation based on the spindle difference characteristic spectrum, or determining whether there is a transient impact based on the spindle difference signal.

4. A spindle speed and twist control system for a covering yarn machine according to claim 3, characterized in that: The steady-state deviation is determined by checking whether the DC component amplitude of the spindle difference characteristic spectrum at zero frequency satisfies the following conditions: |S i (f0)|>θ ss ; Among them, |S i (f0)| is the DC component amplitude of the spindle difference characteristic spectrum of the i-th spindle at frequency zero, θ ss is the preset steady-state deviation threshold.

5. A spindle speed and twist control system for a covering yarn machine according to claim 3, characterized in that: The determination of the periodic deviation is performed by searching for an energy peak in the non-zero frequency band of the ingot difference characteristic spectrum to determine whether the energy peak exists at a frequency of f p The amplitude at satisfies the following conditions: |S i (f p )|>θ p ; Among them, |S i (f p )| is the spindle difference characteristic spectrum of the i-th spindle at the frequency f of the energy peak p The amplitude at θ p is the preset periodic deviation amplitude threshold.

6. A spindle speed and twist control system for a covering yarn machine according to claim 3, characterized in that: The transient impact is determined by calculating the rate of change of the spindle difference signal in the time domain and judging whether it exceeds a preset transient impact rate of change threshold.

7. The spindle speed and twist control system of a covering yarn machine according to claim 1, characterized in that: The global control module is configured to calculate the spindle speed reference value according to the target twist and the yarn delivery speed.

8. The spindle speed and twist control system of a covering yarn machine according to claim 1, characterized in that: The visual status marking performed by the human-computer interaction and decision support module includes: A spindle diagnosed as having a steady-state deviation or a periodic deviation is marked as a caution state, and a spindle diagnosed as having a transient shock is marked as an alarm state.

9. The spindle speed and twist control system of a covering yarn machine according to claim 1, characterized in that: The power execution module includes a frequency converter and a three-phase asynchronous motor.

10. A method for controlling spindle speed and twist of a covering yarn machine, according to a control system for spindle speed and twist of a covering yarn machine according to any one of claims 1 to 9, characterized in that: The following steps are involved: Real-time acquisition of the instantaneous angular velocity of each spindle of the covering yarn machine; Calculate the average speed of the entire machine from the instantaneous angular velocities of all spindles; Performing global closed-loop feedback control to adjust the power of the covering yarn machine based on the deviation between the average speed of the entire machine and a preset spindle speed reference value; Extracting the difference between the instantaneous angular velocity of each spindle and the average speed of the entire machine as a spindle difference signal of the spindle; The spindle difference signal of each spindle is analyzed to diagnose the operating status of the spindle, and a visual early warning or predictive maintenance guidance is provided based on the operating status.

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