System and method for evaluating real-time transverse movement error of warp knitting machine

Abstract

The invention discloses a system and method for evaluating the real-time transverse movement error of a warp knitting machine, and belongs to the technical field of warp knitting equipment. The method for evaluating the real-time transverse movement error of the warp knitting machine comprises the following steps that S100, vibration data of a guide bar is collected and sent; step S200, receiving and storing the collected vibration data; s300, analyzing the stored vibration data of the guide bar, extracting feature information of the vibration of the guide bar, and calculating a transverse movement error of the guide bar by using the feature information of the vibration of the guide bar; and S400, evaluating the transverse movement error, and generating a warp knitting machine operation state report. According to the method, the transverse movement error of the warp knitting machine can be evaluated in real time, the running state report of the warp knitting machine is generated, the problems of machine running faults, quality defects of processed fabrics and the like caused by the transverse movement error in the weaving production process are reduced, and the running stability and reliability of the warp knitting machine are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of warp knitting equipment, and in particular relates to a real-time lateral error evaluation system and an evaluation method for a warp knitting machine. Background Art

[0002] As a highly efficient knitting equipment, warp knitting machine is widely used in the production of various types of fabrics. Due to its advantages of fast operation speed, high production efficiency and good stability, it can produce a large number of knitted fabrics in a short time. The warp knitting machine is equipped with a comb bar transverse movement mechanism. The function of the comb bar transverse movement mechanism is to enable the comb bar to move laterally according to the organization requirements of the knitted fabric during the loop forming process to ensure the correctness and uniformity of the fabric organization. The accuracy of the comb bar transverse movement directly affects the performance, quality and appearance of the knitted fabric.

[0003] Although warp knitting machines have high production efficiency and good stability, when the warp knitting machines run at high speed, the interaction between various mechanical parts will produce complex vibrations, especially vibrations related to the lateral movement mechanism of the comb bar. The vibration will cause the comb bar to have lateral movement errors. The lateral movement errors will affect the lateral movement accuracy of the comb bar, resulting in instability of the fabric structure, which will ultimately affect the appearance, quality and performance of the fabric, and will also reduce the production efficiency of the warp knitting machine.

[0004] Therefore, how to effectively monitor and control the lateral error caused by the vibration of the warp knitting machine, evaluate the cause of the lateral error, and even use the lateral error to compensate or eliminate the operation of the warp knitting machine is a technical problem that needs to be solved at present. Summary of the invention

[0005] The present invention provides a real-time lateral error evaluation system and method for a warp knitting machine, aiming to partially or completely solve the existing technical problems. The present invention can evaluate the lateral error of a warp knitting machine in real time and generate a warp knitting machine operation status report. To achieve the above purpose, the present invention adopts the following technical solutions:

[0006] A first aspect. A real-time lateral shift error evaluation system for a warp knitting machine, comprising: an acquisition module, a storage module, a feature analysis and calculation module, and an evaluation module; the acquisition module acquires vibration data of a comb bar and sends it to the storage module; the storage module receives the vibration data from the acquisition module for storage; the feature analysis and calculation module analyzes the vibration data of the stored comb bar to extract feature information of the comb bar vibration, and uses the feature information of the comb bar vibration to calculate the lateral shift error of the comb bar; the evaluation module evaluates the lateral shift error and generates a warp knitting machine operation status report.

[0007] Optionally, the acquisition module includes an acceleration sensor and a data transmission unit, the acceleration sensor is connected to the data transmission unit, the acceleration sensor collects time domain acceleration data of the comb bar vibration and sends it to the storage module, the feature analysis and calculation module includes a filter, a Fourier transform processing unit and an integrator, the filter filters the time domain acceleration data of the comb bar vibration stored in the storage module to obtain the filtered time domain acceleration data of the comb bar vibration, the Fourier transform processing unit performs Fourier transform on the filtered time domain acceleration data of the comb bar vibration to extract frequency domain feature information of the comb bar vibration; the frequency domain feature information of the comb bar vibration in the low frequency band is selected from the frequency domain feature information of the comb bar vibration, the integrator performs inverse Fourier transform on the frequency domain feature information of the comb bar vibration in the low frequency band to obtain the time domain vibration signal of the processed comb bar; according to the time domain vibration signal of the processed comb bar and the time domain ideal vibration signal of the comb bar, the lateral displacement error of the comb bar is calculated.

[0008] Alternatively, the mathematical expression for the inverse Fourier transform is:

[0009]

[0010] Wherein, yd is the time domain vibration signal of the comb after processing, y(f) is the frequency domain characteristic information of the comb vibration in the low frequency band, f is the frequency, f≤1000Hz, and t is the time;

[0011] The calculation formula of the lateral error e is:

[0012]

[0013] Among them, yd(t) is the value of the time domain vibration signal of the comb after processing at the tth moment, norm(yd(t)) is the normalized value of the time domain vibration signal of the comb after processing at the tth moment, yd max is the maximum value of the time domain vibration signal of the comb after processing, yd min is the minimum value of the time domain vibration signal of the comb after processing;

[0014] y(t) is the value of the ideal vibration signal in the time domain of the comb at the tth moment, norm(y(t)) is the normalized value of the ideal vibration signal in the time domain of the comb at the tth moment, y max is the maximum value of the ideal vibration signal of the comb in the time domain, y min is the minimum value of the ideal vibration signal in the time domain of the comb, and N is the total number of sampling points of the vibration signal in the time domain of the comb after processing.

[0015] Optionally, the evaluation module includes an error evaluation unit and a report generation unit. The error evaluation unit evaluates whether the lateral shift error is within a preset value range. If so, the report generation unit generates a signal that the operation status of the warp knitting machine is normal. If not, the report generation unit generates a signal that the operation status of the warp knitting machine is abnormal and needs to be inspected and processed.

[0016] In a second aspect, a real-time lateral error evaluation method for a warp knitting machine is provided, using any one of the real-time lateral error evaluation systems for a warp knitting machine described in the first aspect, comprising:

[0017] Step S100: collecting and sending vibration data of the comb;

[0018] Step S200: receiving and storing the collected vibration data;

[0019] Step S300: Analyze the stored vibration data of the comb bar to extract characteristic information of the comb bar vibration, and use the characteristic information of the comb bar vibration to calculate the lateral displacement error of the comb bar;

[0020] Step S400: Evaluate the lateral shift error and generate a warp knitting machine operation status report.

[0021] Optionally, step S100 includes:

[0022] Using an acceleration sensor to collect the time-domain acceleration data of the comb bar vibration, and sending the collected time-domain acceleration data of the comb bar vibration;

[0023] Step S300 includes:

[0024] Step S301: filtering the stored comb bar vibration time domain acceleration data to obtain filtered comb bar vibration time domain acceleration data;

[0025] Step S302: The filtered comb vibration time domain acceleration data is subjected to Fourier transform to extract frequency domain characteristic information of the comb vibration. The formula of Fourier transform is:

[0026]

[0027] Among them, x(t) is the time domain acceleration signal of the comb vibration after filtering, f is the frequency, t is the time, and x(f) is the frequency domain characteristic information of the comb vibration.

[0028] Step S303: Select the frequency domain characteristic information of the comb bar vibration in the low frequency band from the frequency domain characteristic information of the comb bar vibration, perform inverse Fourier transform on the frequency domain characteristic information of the comb bar vibration in the low frequency band to obtain the time domain vibration signal of the processed comb bar; calculate the lateral shift error of the comb bar based on the time domain vibration signal of the processed comb bar and the ideal time domain vibration signal of the comb bar.

[0029] Optionally, in step S303, the mathematical expression of the inverse Fourier transform is:

[0030]

[0031] Wherein, yd is the time domain vibration signal of the comb after processing, y(f) is the frequency domain characteristic information of the comb vibration in the low frequency band, f is the frequency, f≤1000Hz, and t is the time;

[0032] The calculation formula of the lateral error e is:

[0033]

[0034] Among them, yd(t) is the value of the time domain vibration signal of the comb after processing at the tth moment, norm(yd(t)) is the normalized value of the time domain vibration signal of the comb after processing at the tth moment, yd max is the maximum value of the time domain vibration signal of the comb after processing, yd min is the minimum value of the time domain vibration signal of the comb after processing;

[0035] y(t) is the value of the ideal vibration signal in the time domain of the comb at the tth moment, norm(y(t)) is the normalized value of the ideal vibration signal in the time domain of the comb at the tth moment, y max is the maximum value of the ideal vibration signal of the comb in the time domain, y min is the minimum value of the ideal vibration signal in the time domain of the comb, and N is the total number of sampling points of the vibration signal in the time domain of the comb after processing.

[0036] Optionally, step S400 includes: evaluating whether the lateral shift error is within a preset value range; if so, the report generating unit generates that the operation status of the warp knitting machine is normal; if not, the report generating unit generates that the operation status of the warp knitting machine is abnormal and needs to be checked and processed.

[0037] In a third aspect, the present invention application provides a real-time lateral shift error processing device for a warp knitting machine, comprising a memory and a processor that are communicatively connected, wherein the memory is used to store a computer program, and the processor is used to read the computer program and execute the real-time lateral shift error evaluation method for a warp knitting machine as described in any one of the second aspects.

[0038] In a fourth aspect, the present invention application provides a computer-readable storage medium having instructions stored thereon. When the instructions are executed on a computer, the real-time lateral error evaluation method for a warp knitting machine as described in any one of the second aspects is executed.

[0039] (1) In the present invention application, firstly, under the premise of not affecting the production progress, the real-time lateral error evaluation system of the warp knitting machine can perform real-time evaluation on the lateral error of the warp knitting machine and generate a warp knitting machine operation status report, which provides a solid technical foundation for the intelligent and automated production of the warp knitting machine; in addition, the warp knitting machine operation status report generated by the real-time lateral error evaluation system of the warp knitting machine may include the lateral error evaluation result, the trend of the comb vibration data change, etc., which can timely discover the potential abnormality of the warp knitting machine, and also help to reduce the fabric quality defects and rework problems caused by the lateral error in the weaving production process, thereby improving the stability and reliability of the warp knitting machine operation, and also improving the appearance, quality and performance of the fabric.

[0040] (2) In the present invention application, first, the comb bar vibration data is collected and sent, and the frequency domain characteristic information of the comb bar vibration is analyzed and extracted, and is associated with the lateral shift error. The extraction of the comb bar vibration characteristics can not only accurately reflect the working status of the comb bar, but also help identify the potential vibration source and error source of the warp knitting machine, providing a scientific basis for the management of vibration interference in the production process; in addition, the real-time evaluation of the lateral shift error generates a warp knitting machine operation status report, so that the operator can understand whether the warp knitting machine has any abnormalities in the first time, avoiding fabric quality problems caused by the lateral shift error not being discovered in time. Through effective error evaluation, the system can provide real-time feedback on the operating status of the warp knitting machine, and can timely discover and adjust factors affecting production efficiency and fabric quality, thereby optimizing the design and manufacturing process of the warp knitting machine; in addition, without the need for human intervention, through efficient data collection, vibration analysis, error calculation and report generation, the production efficiency, product quality and intelligence and automation level of the warp knitting machine are greatly improved, providing an important technical reference for the precise control and continuous improvement of the warp knitting machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments are briefly introduced below. 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.

[0042] Figure 1 It is a schematic diagram of the composition of the real-time lateral error evaluation system for warp knitting machines applied for by the present invention;

[0043] Figure 2 A schematic diagram of the working principle of the acquisition module applied for in the present invention;

[0044] Figure 3 A schematic flow chart of a real-time lateral error evaluation method for a warp knitting machine according to the present invention;

[0045] Figure 4 A schematic diagram of the frequency domain characteristic information of the comb bar vibration (i.e., the frequency domain signal of the comb bar vibration) of the present invention;

[0046] Figure 5 A schematic diagram of the lateral error analysis results of the present invention.

[0047] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments; based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0049] In the description of the present invention, it should be understood that the terms "upper", "lower", "front", "back", "left", "right", "top", "bottom", "inside", "outside" and the like indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as a limitation on the present invention. In order to make the purpose, technical solution and advantages of the present invention clearer, the implementation methods of the present invention will be further described in detail below in conjunction with the drawings.

[0050] Real-time slewing error evaluation system for warp knitting machines

[0051] like Figures 1 to 3 As shown, in the first aspect, a real-time lateral shift error evaluation system for a warp knitting machine includes: an acquisition module, a storage module, a feature analysis and calculation module, and an evaluation module; the acquisition module acquires the vibration data of the comb bar and sends it to the storage module; the storage module receives the vibration data from the acquisition module for storage; the feature analysis and calculation module analyzes the vibration data of the stored comb bar to extract the feature information of the comb bar vibration, and uses the feature information of the comb bar vibration to calculate the lateral shift error of the comb bar; the evaluation module evaluates the lateral shift error and generates a warp knitting machine operation status report.

[0052] It should be understood that the real-time lateral displacement error evaluation system of the warp knitting machine collects the vibration data of the comb bar in real time through the acquisition module 100, and transmits it to the storage module 200 for storage and analysis. In this way, it can be ensured that during the high-speed operation of the warp knitting machine, any vibration factors that may affect the lateral displacement accuracy of the comb bar can be monitored and recorded in a timely manner, providing an accurate data basis for subsequent error evaluation and compensation. The feature analysis and calculation module 300 can analyze the vibration data of the comb bar, and extract vibration feature information such as acceleration from the vibration data of the comb bar, and can use the vibration feature information to calculate the lateral displacement error of the comb bar. The evaluation module 400 evaluates the lateral displacement error and generates a warp knitting machine operation status report.

[0053] Therefore, in the real-time lateral shift error evaluation system for warp knitting machines applied for in the present invention, firstly, under the premise of not affecting the production progress, the real-time lateral shift error evaluation system for warp knitting machines can perform real-time evaluation of the lateral shift error of the warp knitting machines, and generate an operation status report of the warp knitting machines, which provides a solid technical foundation for the intelligent and automated production of warp knitting machines; in addition, the operation status report of the warp knitting machines generated by the real-time lateral shift error evaluation system for warp knitting machines may include lateral shift error evaluation results, change trends of comb bar vibration data, etc., which can timely discover potential abnormalities of the warp knitting machines, and also help to reduce technical problems such as quality defects and rework of the processed fabrics caused by lateral shift errors in the weaving production process, thereby improving the stability and reliability of the warp knitting machine operation, and improving the appearance, quality and performance of the fabrics.

[0054] Optionally, the acquisition module includes an acceleration sensor and a data transmission unit. The acceleration sensor is connected to the data transmission unit. The acceleration sensor acquires time domain acceleration data of comb bar vibration and sends it to the storage module. The feature analysis and calculation module includes a filter, a Fourier transform processing unit and an integrator. The filter filters the time domain acceleration data of comb bar vibration stored in the storage module to obtain filtered time domain acceleration data of comb bar vibration. The Fourier transform processing unit performs Fourier transform on the filtered time domain acceleration data of comb bar vibration to extract frequency domain feature information of comb bar vibration. The frequency domain feature information of comb bar vibration in a low frequency band is selected from the frequency domain feature information of comb bar vibration. The integrator performs inverse Fourier transform on the frequency domain feature information of comb bar vibration in a low frequency band to obtain the time domain vibration signal of the processed comb bar. The lateral displacement error of the comb bar is calculated according to the time domain vibration signal of the processed comb bar and the ideal time domain vibration signal of the comb bar.

[0055] In some embodiments, the acquisition module includes an acceleration sensor 101 and a data transmission unit 102. The acceleration sensor is installed on the comb SZ. The comb SZ can be a transverse comb. The warp knitting machine servo driver DR can drive the comb SZ to move. The acceleration sensor 101 is connected to the data transmission unit 102. The acceleration sensor 101 collects vibration data of the comb SZ (in the field of signal processing, the corresponding data can be called the vibration signal of the comb) and can be transmitted to the storage module 200 through the data transmission unit 102. The storage module 200 stores the vibration data of the comb SZ for subsequent analysis.

[0056] In some embodiments, the acceleration sensor may be a multi-axial vibration acceleration sensor, which collects the vibration data of the comb bar and may be selected according to the motion characteristics of the warp knitting machine. Generally speaking, the axial sensitivity of the multi-axial vibration acceleration sensor is required to be greater than 100mV / g, and the response frequency range is higher than 0.5-5000Hz. The vibration acceleration in the lateral direction of the comb bar can be obtained by using the multi-axial vibration acceleration sensor. The acceleration sensor collects the time domain acceleration data of the comb bar vibration (in the field of signal processing, the corresponding time domain acceleration signal of the comb bar vibration can be called), which is the vibration data of the comb bar SZ collected above.

[0057] In some embodiments, the acceleration sensor collects the time domain acceleration data of the comb bar vibration, which may also mean that the acceleration sensor collects the time domain acceleration signal of the comb bar vibration, and the filter may filter out the required comb bar vibration time domain acceleration data according to the following formula:

[0058]

[0059] Where, ω is the angular frequency of the comb vibration time domain acceleration data, ω c is the cutoff frequency of the filter setting and j is a complex number.

[0060] In some embodiments, at high frequencies ω ≥ ω c When H(jω)≈1, the time domain acceleration signal of the comb vibration can pass through the filter; at high frequency ω<ω c When the comb bar vibration time domain acceleration signal is cut off and filtered by the filter, it cannot pass through the filter. Generally speaking, the normal lateral movement operation signal of the comb bar can be excluded from the lateral movement error after being filtered by the filter cut off.

[0061] In some embodiments, the Fourier transform processing unit may perform Fourier transform on the time domain acceleration signal of the filtered comb vibration to extract frequency domain characteristic information of the comb vibration (in the field of signal processing, the corresponding frequency domain signal of the comb vibration may be referred to), and the Fourier transform formula is:

[0062]

[0063] Among them, x(t) is the time domain acceleration signal of the comb vibration after filtering, f is the frequency, t is the time, and x(f) is the frequency domain characteristic information of the comb vibration.

[0064] Therefore, through Fourier transform, we can analyze the amplitude and phase information of the vibration signal of the comb bar at different frequency components, which is helpful to identify the relevant frequency information of the warp knitting machine operation state. For example, the frequency domain feature information of the comb bar vibration can be further extracted and analyzed, for example, the main frequency of the comb bar vibration, the abnormal frequency components of the comb bar vibration, etc. can be identified.

[0065] In some embodiments, the frequency domain characteristic information of the comb bar vibration in the low frequency band is selected from the frequency domain characteristic information x(f) of the comb bar vibration, and an integrator performs an inverse Fourier transform on the frequency domain characteristic information of the comb bar vibration in the low frequency band to obtain a time domain vibration signal of the processed comb bar; based on the time domain vibration signal of the processed comb bar and the time domain ideal vibration signal of the comb bar, the lateral shift error of the comb bar is calculated.

[0066] It should be understood that, according to the frequency domain characteristic information of the comb bar vibration, the spectrum data (for example, spectrum diagram) of the comb bar vibration can be obtained accordingly. According to the working characteristic analysis of the lateral displacement of the comb bar of the warp knitting machine, the frequency domain characteristic information of the comb bar vibration in the low frequency band can be selected. Exemplarily, the frequency range of the low frequency band is: 0-1000Hz. The frequency domain characteristic information of the comb bar vibration in the low frequency band can be inversely transformed to obtain the time domain vibration signal of the processed comb bar (that is, the frequency domain characteristic information of the comb bar vibration of 0-1000Hz can be inversely transformed to obtain the time domain vibration signal of the processed comb bar). The mathematical expression of the inverse Fourier transform is:

[0067]

[0068] Among them, yd is the time domain vibration signal of the comb after processing, y(f) is the frequency domain characteristic information of the comb vibration in the low frequency band, f is the frequency, f≤1000Hz, and t is the time.

[0069] It should be understood that the lateral shift error of the comb bar can be calculated by comparing the difference between the time domain vibration signal yd of the comb bar after processing and the time domain ideal vibration signal y of the comb bar. The lateral shift error can be expressed using different indicators. The calculation formula of the lateral shift error e is:

[0070]

[0071] Among them, yd(t) is the value of the time domain vibration signal of the comb after processing at the tth moment, norm(yd(t)) is the normalized value of the time domain vibration signal of the comb after processing at the tth moment, ydmax is the maximum value of the time domain vibration signal of the comb after processing, yd min is the minimum value of the time domain vibration signal of the comb after processing;

[0072] y(t) is the value of the ideal vibration signal in the time domain of the comb at the tth moment, norm(y(t)) is the normalized value of the ideal vibration signal in the time domain of the comb at the tth moment, y max is the maximum value of the ideal vibration signal of the comb in the time domain, y min is the minimum value of the ideal vibration signal in the time domain of the comb, and N is the total number of sampling points of the vibration signal in the time domain of the comb after processing.

[0073] Therefore, in the present invention application, through the inverse Fourier transform and the calculation of the lateral displacement error, the vibration of the comb bar can be more comprehensively understood, providing an important reference basis for the normal operation and maintenance of the equipment, and the calculated lateral displacement error of the comb bar can be used to evaluate the operating status and performance of the warp knitting machine, as well as to monitor the vibration of the comb bar, and help to timely discover potential problems and make adjustments and optimizations. It should be noted that the lateral displacement error may involve information such as the actual displacement and vibration amplitude of the comb bar, and the specific calculation details may vary depending on the system design and requirements. The inverse Fourier transform process can be achieved through relevant mathematical tools and algorithms, and the specific implementation details may need to be adjusted and optimized accordingly according to the system requirements and the tools used.

[0074] Optionally, the storage module includes a historical information storage unit and a basic feature storage unit, the historical information storage unit stores the time domain acceleration data of the comb vibration of the warp knitting machine; the basic feature storage unit includes a basic frequency storage subunit and a frequency domain feature data storage subunit, the basic frequency storage subunit stores the basic frequency information of the comb vibration of the warp knitting machine under normal operating conditions, the basic frequency information of the comb vibration includes at least one of the main frequency component, the main harmonic frequency, and the vibration mode; the frequency domain feature data storage subunit stores the frequency domain feature information of the comb vibration data of the warp knitting machine, the frequency domain feature information includes at least one of the comb vibration spectrum diagram and amplitude-frequency response of the warp knitting machine under normal operating conditions.

[0075] In some embodiments, the historical information storage unit stores the time domain acceleration data of the comb bar vibration of the warp knitting machine. The time domain acceleration data of the comb bar vibration can be waveform data. These waveform data contain the information of the comb bar vibration signal in the time domain. These waveform data can also be converted into the information of the comb bar vibration signal in the frequency domain. By storing the waveform data, the complete information of the original vibration signal can be retained, which can be used to establish a historical record library of the vibration signal, help users analyze the evolution trend of the vibration signal, compare the vibration characteristics of different time periods, etc., and can also provide a basis for the subsequent extraction and analysis of frequency information.

[0076] In some embodiments, the basic frequency storage subunit stores and records the basic frequency information of the comb bar vibration under normal operating conditions of the warp knitting machine. The basic frequency information of the comb bar vibration includes at least one of the main frequency component, the main harmonic frequency, and the vibration mode. By recording these basic frequency information of the comb bar vibration, a comb bar vibration characteristic benchmark under normal operating conditions can be established, which can be used for analysis of subsequent comb bar vibration data.

[0077] In some embodiments, a frequency domain feature data storage subunit stores frequency domain feature information of the warp knitting machine comb vibration data, and the frequency domain feature information includes at least one of a spectrum diagram and an amplitude-frequency response of the comb vibration of the warp knitting machine under normal operating conditions. The spectrum diagram of the comb vibration signal is obtained by performing a fast Fourier transform (FFT) on the comb vibration signal or noise signal in the operation of the warp knitting machine. The amplitude-frequency response refers to the response amplitude of the warp knitting machine to input signals of different frequencies, which can be used to describe the dynamic characteristics of the warp knitting machine. By performing an amplitude-frequency response analysis on the dynamic response of the warp knitting machine, the behavior characteristics of the machine at a specific frequency can be understood, and then the working performance of the machine can be evaluated. For example, an increase in the amplitude-frequency response within a certain frequency range may indicate a resonance phenomenon of the machine in this frequency band, thereby providing a reference for the optimization of the warp knitting machine equipment. By recording the frequency domain feature information data of the warp knitting machine under normal operating conditions, the frequency domain characteristics of the vibration signal can be more comprehensively described, providing a reference basis for subsequent comparison, extraction and analysis.

[0078] Optionally, the evaluation module includes an error evaluation unit and a report generation unit. The error evaluation unit evaluates whether the lateral shift error is within a preset value range. If so, the report generation unit generates a signal that the operation status of the warp knitting machine is normal. If not, the report generation unit generates a signal that the operation status of the warp knitting machine is abnormal and needs to be inspected and processed.

[0079] In some embodiments, after completing the integral operation of the signal to obtain the lateral shift error, the error evaluation unit may include a quantized error index, compare the current lateral shift error with the historical lateral shift error data or the preset value range, and determine whether the current lateral shift error is within the preset value range. If so, it means that the warp knitting machine is operating normally, and if not, it means that the warp knitting machine is operating abnormally and needs to be checked and processed. For example, if the lateral shift error is particularly prominent in a certain frequency band, further filtering or adjustment may be required for the frequency band.

[0080] In some embodiments, based on the evaluation result of the error evaluation unit, the report generation unit can generate a report that the warp knitting machine is in a normal operating state. If not, the report generation unit generates a report that the warp knitting machine is in an abnormal operating state and needs to be checked and processed. The report generation unit can also generate specific suggestions and preventive measures for the operation of the warp knitting machine to prevent the transverse error from exceeding the preset value range.

[0081] In the present application, the evaluation module improves the intelligence and automation level of the warp knitting machine through the cooperation of the error evaluation unit and the report generation unit. The automated evaluation and reporting functions effectively reduce the workload of manual inspection of the warp knitting machine, improve the operating efficiency and reliability of the warp knitting machine, and can effectively avoid fabric quality problems or damage to the warp knitting machine caused by long-term error accumulation, thereby improving fabric production efficiency and fabric quality.

[0082] Real-time slewing error evaluation method for warp knitting machines

[0083] like Figure 4 As shown, in the second aspect, a real-time lateral error evaluation method for a warp knitting machine comprises:

[0084] Step S100: collecting and sending vibration data of the comb;

[0085] Step S200: receiving and storing the collected vibration data;

[0086] Step S300: Analyze the stored vibration data of the comb bar to extract characteristic information of the comb bar vibration, and use the characteristic information of the comb bar vibration to calculate the lateral displacement error of the comb bar;

[0087] Step S400: Evaluate the lateral shift error and generate a warp knitting machine operation status report.

[0088] It should be noted that a real-time lateral shift error assessment method for a warp knitting machine applied for by the present invention may adopt or not adopt any of the real-time lateral shift error assessment systems for a warp knitting machine in the first aspect mentioned above. When adopting any of the real-time lateral shift error assessment systems for a warp knitting machine in the first aspect, it accordingly also includes: all the technical problems, technical solutions and technical effects recorded in any of the real-time lateral shift error assessment systems for a warp knitting machine in the first aspect, which will not be repeated in the present application.

[0089] In some embodiments, step S100 includes: using an acceleration sensor to collect the time-domain acceleration data of the comb bar vibration, and sending the collected time-domain acceleration data of the comb bar vibration. That is, the above-mentioned collection and sending of the vibration data of the comb bar, illustratively, the acceleration sensor can be a multi-axial vibration acceleration sensor, the multi-axial vibration acceleration sensor collects the time-domain acceleration data of the comb bar vibration, and the multi-axial vibration acceleration sensor can be selected according to the motion characteristics of the warp knitting machine.

[0090] Optionally, step S300 includes:

[0091] Step S301: filtering the stored comb bar vibration time domain acceleration data to obtain filtered comb bar vibration time domain acceleration data;

[0092] Specifically, the stored comb bar vibration time domain acceleration data may be filtered by a filter to obtain filtered comb bar vibration time domain acceleration data. The filter may filter out the required comb bar vibration time domain acceleration data according to the following formula:

[0093]

[0094] Where, ω is the angular frequency of the comb vibration time domain acceleration data, ω c is the cutoff frequency of the filter setting and j is a complex number.

[0095] In some embodiments, at high frequencies ω ≥ ω c When H(jω)≈1, the time domain acceleration signal of the comb vibration can pass through the filter, and at high frequency ω<ω c When the comb bar vibration time domain acceleration signal is cut off and filtered by the filter, it cannot pass through the filter. Generally speaking, the normal lateral movement operation signal of the comb bar can be excluded from the lateral movement error after being filtered by the filter cut off.

[0096] Step S302: The filtered comb vibration time domain acceleration data is subjected to Fourier transform to extract frequency domain characteristic information of the comb vibration. The formula of Fourier transform is:

[0097]

[0098] Where x(t) is the time domain acceleration of the comb vibration after filtering, f is the frequency, and t is the time;

[0099] Therefore, through Fourier transform, we can analyze the amplitude and phase information of the vibration signal of the comb at different frequency components, which helps to identify the relevant frequency information of the operating status of the warp knitting machine.

[0100] Step S303: Select the frequency domain characteristic information of the comb bar vibration in the low frequency band from the frequency domain characteristic information of the comb bar vibration, perform inverse Fourier transform on the frequency domain characteristic information of the comb bar vibration in the low frequency band to obtain the time domain vibration signal of the processed comb bar; calculate the lateral shift error of the comb bar based on the time domain vibration signal of the processed comb bar and the ideal time domain vibration signal of the comb bar.

[0101] In some embodiments, according to the frequency domain characteristic information of the comb bar vibration, the spectrum data (for example, spectrum diagram) of the comb bar vibration can be obtained accordingly. According to the working characteristic analysis of the slewing movement of the comb bar of the warp knitting machine, the frequency domain characteristic information of the comb bar vibration in the low frequency band can be selected. Exemplarily, the frequency range of the low frequency band is: 0-1000Hz, and the frequency domain characteristic information of the comb bar vibration in the low frequency band can be inversely transformed to obtain the time domain vibration signal of the processed comb bar (that is, the frequency domain characteristic information of the comb bar vibration of 0-1000Hz can be inversely transformed to obtain the time domain vibration signal of the processed comb bar). The mathematical expression of the inverse Fourier transform is:

[0102]

[0103] Among them, yd is the time domain vibration signal of the comb after processing, y(f) is the frequency domain characteristic information of the comb vibration in the low frequency band, f is the frequency, f≤1000HZ, and t is the time.

[0104] It should be understood that the lateral shift error of the comb bar can be calculated by comparing the difference between the time domain vibration signal yd of the comb bar after processing and the time domain ideal vibration signal y of the comb bar. The lateral shift error can be expressed using different indicators. The calculation formula of the lateral shift error e is:

[0105]

[0106] Among them, yd(t) is the value of the time domain vibration signal of the comb after processing at the tth moment, norm(yd(t)) is the normalized value of the time domain vibration signal of the comb after processing at the tth moment, yd max is the maximum value of the time domain vibration signal of the comb after processing, yd min is the minimum value of the time domain vibration signal of the comb after processing;

[0107] y(t) is the value of the ideal vibration signal in the time domain of the comb at the tth moment, norm(y(t)) is the normalized value of the ideal vibration signal in the time domain of the comb at the tth moment, y max is the maximum value of the ideal vibration signal of the comb in the time domain, y min is the minimum value of the ideal vibration signal in the time domain of the comb, and N is the total number of sampling points of the vibration signal in the time domain of the comb after processing.

[0108] In the present invention application, firstly, the filtering operation in step S301 can effectively remove high-frequency noise signals by accurately screening out the frequency components related to the lateral displacement error, thereby ensuring the accuracy of the measurement. Through filtering, only those signals whose frequencies are within the normal working range are retained, while the high-frequency noise signals are effectively isolated. In this way, the filtered comb vibration time domain acceleration data is more real and stable, which is helpful for subsequent frequency domain analysis, avoids errors caused by noise, and thus improves the reliability of the measurement results. Through the precise setting of the filter, the problems of misjudgment and error amplification can also be avoided, making the evaluation of the lateral displacement error more accurate. In short, the filtering step effectively filters out irrelevant signals, improves the accuracy of the entire system, and provides high-quality input data for subsequent Fourier transform and error calculation; in addition, the Fourier transform operation in step S302 extracts frequency domain feature information through Fourier transform. Fourier transform can convert time domain signals into frequency domain signals, so that the vibration characteristics of each frequency component can be more intuitively expressed, which can help identify the frequency domain feature information of the comb vibration at different frequencies, and determine which frequency components are related to the lateral shift error, thereby improving the accuracy of the lateral shift error assessment, and thus more accurately assessing the impact of vibration on the lateral shift error; in addition, the lateral shift error calculation operation in step S303 converts the frequency domain information back into time domain information through an inverse Fourier transform, so as to more intuitively evaluate the actual lateral shift error of the comb and then accurately evaluate the size of the lateral shift error, and provide a data basis for the subsequent real-time evaluation of the lateral shift error.

[0109] Optionally, step S400 includes: evaluating whether the lateral shift error is within a preset value range; if so, the report generating unit generates that the operation status of the warp knitting machine is normal; if not, the report generating unit generates that the operation status of the warp knitting machine is abnormal and needs to be checked and processed.

[0110] In the present invention application, based on the evaluation result of whether the lateral shift error is within the preset value range, the report generation unit can generate a report that the warp knitting machine is in a normal operating state. If not, the report generation unit generates a report that the warp knitting machine is in an abnormal operating state and needs to be checked and processed. The report generation unit can even generate specific suggestions and preventive measures for the operation of the warp knitting machine to prevent the lateral shift error from exceeding the preset value range, and can even eliminate these errors by adjusting the operating parameters of the warp knitting machine or compensation measures, thereby improving the production efficiency and fabric quality of the warp knitting machine.

[0111] Therefore, in the real-time lateral error evaluation method for a warp knitting machine of the present invention, firstly, steps S100 and S200 ensure that the vibration data of the comb bar is accurately recorded through the vibration data collection and storage mechanism of the comb bar, ensure the high quality of the comb bar vibration data used for subsequent analysis, and avoid the error evaluation problem caused by the loss or error of the comb bar vibration data; at the same time, step S300 extracts the vibration characteristic information of the comb bar through the analysis of the comb bar vibration data, and associates it with the lateral error. The extraction of the vibration characteristic of the comb bar can not only accurately reflect the working state of the comb bar, but also help identify potential sources of errors, and provide a scientific basis for the management of vibration interference in the production process; in addition, step S400 analyzes the lateral error. Real-time evaluation generates a warp knitting machine operation status report, allowing the operator to understand whether the warp knitting machine has any abnormalities at the first time, avoiding fabric quality problems caused by the lateral error not being discovered in time. Through effective error evaluation, the system can provide real-time feedback on the operation status of the warp knitting machine, and can promptly discover and adjust factors affecting production efficiency and fabric quality, thereby optimizing the design and manufacturing process of the warp knitting machine; in addition, without the need for human intervention, through efficient data collection, vibration analysis, error calculation and report generation, the production efficiency, product quality and intelligence and automation level of the warp knitting machine are greatly improved, providing an important technical reference for the precise control and continuous improvement of the warp knitting machine.

[0112] Real-time lateral error processing device for warp knitting machine

[0113] In the third aspect, the present invention application provides a real-time lateral shift error processing device for a warp knitting machine, comprising a memory and a processor that are communicatively connected, wherein the memory is used to store a computer program, and the processor is used to read the computer program and execute the steps in the real-time lateral shift error evaluation method for a warp knitting machine as described in any one of the second aspects.

[0114] In some embodiments, a real-time lateral error processing device for a warp knitting machine comprises: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in any one of the methods for evaluating the real-time lateral error of a warp knitting machine described in the second aspect are implemented.

[0115] Computer readable storage medium

[0116] In a fourth aspect, the present invention application provides a computer-readable storage medium having instructions stored thereon. When the instructions are executed on a computer, the steps in the real-time lateral error evaluation method for a warp knitting machine as described in any one of the second aspects are executed.

[0117] Those skilled in the art will understand that the schematic diagram is merely an example of a terminal device and does not constitute a limitation on the terminal device. The terminal device may include more or fewer components than shown in the diagram, or a combination of certain components, or different components. For example, the terminal device may also include input and output devices, network access devices, buses, etc.

[0118] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0119] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the terminal device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0120] Wherein, if the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0121] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0122] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A real-time lateral error evaluation system for a warp knitting machine, characterized in that: include: Acquisition module, storage module, feature analysis and calculation module and evaluation module; the acquisition module collects the vibration data of the comb and sends it to the storage module; A storage module receives the vibration data from the collection module for storage; The characteristic analysis and calculation module analyzes the vibration data of the stored comb bar to extract the characteristic information of the comb bar vibration, and uses the characteristic information of the comb bar vibration to calculate the lateral shift error of the comb bar; the evaluation module evaluates the lateral shift error and generates a warp knitting machine operation status report.

2. A real-time lateral error evaluation system for a warp knitting machine according to claim 1, characterized in that: The acquisition module includes an acceleration sensor and a data transmission unit. The acceleration sensor is connected to the data transmission unit. The acceleration sensor collects time-domain acceleration data of comb bar vibration and sends it to the storage module. The feature analysis and calculation module includes a filter, a Fourier transform processing unit and an integrator. The filter filters the time-domain acceleration data of comb bar vibration stored in the storage module to obtain filtered time-domain acceleration data of comb bar vibration. The Fourier transform processing unit performs Fourier transform on the filtered time-domain acceleration data of comb bar vibration to extract frequency-domain feature information of comb bar vibration; selects frequency-domain feature information of comb bar vibration in a low-frequency band in the frequency-domain feature information of comb bar vibration, and the integrator performs inverse Fourier transform on the frequency-domain feature information of comb bar vibration in a low-frequency band to obtain the time-domain vibration signal of the processed comb bar; and calculates and obtains the lateral displacement error of the comb bar according to the time-domain vibration signal of the processed comb bar and the time-domain ideal vibration signal of the comb bar.

3. A real-time lateral error evaluation system for a warp knitting machine according to claim 2, characterized in that: The mathematical expression of the inverse Fourier transform is: Wherein, yd is the time domain vibration signal of the comb after processing, y(f) is the frequency domain characteristic information of the comb vibration in the low frequency band, f is the frequency, f≤1000Hz, and t is the time; The calculation formula of the lateral error e is: Among them, yd(t) is the value of the time domain vibration signal of the comb after processing at the tth moment, norm(yd(t)) is the normalized value of the time domain vibration signal of the comb after processing at the tth moment, yd max is the maximum value of the time domain vibration signal of the comb after processing, yd min is the minimum value of the time domain vibration signal of the comb after processing; y(t) is the value of the ideal vibration signal in the time domain of the comb at the tth moment, norm(y(t)) is the normalized value of the ideal vibration signal in the time domain of the comb at the tth moment, y max is the maximum value of the ideal vibration signal of the comb in the time domain, y min is the minimum value of the ideal vibration signal in the time domain of the comb, and N is the total number of sampling points of the vibration signal in the time domain of the comb after processing.

4. A real-time lateral error evaluation system for a warp knitting machine according to claim 3, characterized in that: The evaluation module includes an error evaluation unit and a report generation unit. The error evaluation unit evaluates whether the lateral shift error is within a preset value range. If so, the report generation unit generates a signal that the warp knitting machine is operating normally. If not, the report generation unit generates a signal that the warp knitting machine is operating abnormally and needs to be checked and processed.

5. A method for real-time lateral error evaluation of a warp knitting machine, using a real-time lateral error evaluation system for a warp knitting machine according to any one of claims 1 to 4, characterized in that: include: Step S100: collecting and sending vibration data of the comb; Step S200: receiving and storing the collected vibration data; Step S300: Analyze the stored vibration data of the comb bar to extract characteristic information of the comb bar vibration, and use the characteristic information of the comb bar vibration to calculate the lateral displacement error of the comb bar; Step S400: Evaluate the lateral shift error and generate a warp knitting machine operation status report.

6. A method for real-time lateral error evaluation of a warp knitting machine according to claim 5, characterized in that: Step S100 includes: Using an acceleration sensor to collect time-domain acceleration data of comb bar vibration, and sending the collected time-domain acceleration data of comb bar vibration; Step S300 includes: Step S301: filtering the stored comb bar vibration time domain acceleration data to obtain filtered comb bar vibration time domain acceleration data; Step S302: The filtered comb vibration time domain acceleration data is subjected to Fourier transform to extract frequency domain characteristic information of the comb vibration. The formula of Fourier transform is: Among them, x(t) is the time domain acceleration signal of the comb vibration after filtering, f is the frequency, t is the time, and x(f) is the frequency domain characteristic information of the comb vibration; Step S303: Select the frequency domain characteristic information of the comb bar vibration in the low frequency band from the frequency domain characteristic information of the comb bar vibration, perform inverse Fourier transform on the frequency domain characteristic information of the comb bar vibration in the low frequency band to obtain the time domain vibration signal of the processed comb bar; calculate the lateral shift error of the comb bar based on the time domain vibration signal of the processed comb bar and the ideal time domain vibration signal of the comb bar.

7. A method for real-time lateral error evaluation of a warp knitting machine according to claim 6, characterized in that: In step S303, the mathematical expression of the inverse Fourier transform is: Wherein, yd is the time domain vibration signal of the comb after processing, y(f) is the frequency domain characteristic information of the comb vibration in the low frequency band, f is the frequency, f≤1000Hz, and t is the time; The calculation formula of the lateral error e is: Among them, yd(t) is the value of the time domain vibration signal of the comb after processing at the tth moment, norm(yd(t)) is the normalized value of the time domain vibration signal of the comb after processing at the tth moment, yd max is the maximum value of the time domain vibration signal of the comb after processing, yd min is the minimum value of the time domain vibration signal of the comb after processing; y(t) is the value of the ideal vibration signal in the time domain of the comb at the tth moment, norm(y(t)) is the normalized value of the ideal vibration signal in the time domain of the comb at the tth moment, y max is the maximum value of the ideal vibration signal of the comb in the time domain, y min is the minimum value of the ideal vibration signal in the time domain of the comb, and N is the total number of sampling points of the vibration signal in the time domain of the comb after processing.

8. A method for real-time lateral error evaluation of a warp knitting machine according to claim 7, characterized in that: Step S400 includes: evaluating whether the lateral shift error is within a preset value range; if so, the report generating unit generates that the warp knitting machine is operating normally; if not, the report generating unit generates that the warp knitting machine is operating abnormally and needs to be checked and processed.

9. A real-time lateral error processing device for a warp knitting machine, characterized in that: It comprises a memory and a processor which are communicatively connected, wherein the memory is used to store a computer program, and the processor is used to read the computer program and execute the real-time lateral error evaluation method for a warp knitting machine as described in any one of claims 5 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a computer, the method for evaluating the real-time lateral shift error of a warp knitting machine according to any one of claims 5 to 8 is executed.

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