A method and system for online fault monitoring of cable braiding machines

Abstract

The present invention relates to the technical field of electrical digital data processing, and specifically to an online fault monitoring method and system for a cable braiding machine, the method comprising: obtaining a vibration monitoring signal and a tension monitoring signal of the cable braiding machine when it is working; analyzing the fluctuation of the vibration monitoring signal caused by gear wear at different gear speeds to obtain the degree of abnormal gear vibration of the cable braiding machine; analyzing the time synchronization of the vibration monitoring signal and the tension monitoring signal to obtain the overlap of the mutation position, and analyzing the consistency of the amplitude change of the vibration monitoring signal and the tension monitoring signal to obtain the correlation of the amplitude change; determining the gear failure rate of the cable braiding machine based on the abnormal gear vibration degree, the overlap of the mutation position and the correlation of the amplitude change, and determining the fault inspection and repair strategy of the cable braiding machine based on the gear failure rate. In the present invention, the electrical digital data of the cable braiding machine when it is working is processed, and the fault is monitored online in real time and accurately.

Description

Technical Field

[0001] The invention relates to the technical field of electrical digital data processing, and in particular to an online fault monitoring method and system for a cable braiding machine. Background Art

[0002] With the continuous development of industrial automation technology, cable braiding machines are increasingly used in the wire and cable industry. Cable braiding machines are a type of mechanical equipment specifically used to manufacture wires and cables. They are mainly used to braid the shielding layer of cables. In the production process of wires and cables, the braiding machine forms a tight mesh structure by winding multiple fine metal wires (such as copper wire, aluminum wire or tinned copper wire, etc.) around the core conductor or inner insulation material of the cable at a certain braiding angle and density.

[0003] During long-term continuous operation, braiding machines are susceptible to various factors and malfunctions, leading to production interruptions and reduced product quality. In cable braiding machinery, gears are not only the key to power transmission, but also the core component for precise control of the entire braiding process. Once the gears of the cable braiding machine are slightly worn, it may have a subtle effect on the rhythm and density of the braiding. However, given the large number of gear components on the equipment and the relatively small degree of wear, the interference signal generated is also relatively weak. In addition, the monitoring sensor is susceptible to interference from external environmental factors when performing monitoring tasks, which further increases the difficulty of monitoring. If the gear components cannot be monitored in real time and accurately, it will be impossible to grasp the status of the equipment in real time, and it will be impossible to quickly diagnose and deal with potential faults, which will in turn make it impossible to ensure the stable operation of the braiding machine and reduce production efficiency.

[0004] Therefore, how to conduct real-time and accurate online monitoring of cable braiding machine faults is a problem that needs to be solved urgently. Summary of the invention

[0005] In order to solve the technical problem of how to perform real-time and accurate online monitoring of cable braiding machine faults, the purpose of the present invention is to provide a method and system for online monitoring of cable braiding machine faults. The technical solution adopted is as follows:

[0006] The embodiment of the present application provides a method for online fault monitoring of a cable braiding machine, the method comprising:

[0007] Obtain vibration monitoring signals and tension monitoring signals of the cable braiding machine when it is working;

[0008] For the vibration monitoring signal, at different gear speeds, the fluctuation of the vibration monitoring signal caused by gear wear is analyzed to obtain the abnormal degree of gear vibration of the cable braiding machine;

[0009] Analyze the time synchronization of the vibration monitoring signal and the tension monitoring signal to obtain the mutation position coincidence, and analyze the amplitude change consistency of the vibration monitoring signal and the tension monitoring signal to obtain the amplitude change correlation;

[0010] Based on the abnormal degree of gear vibration, the overlap of the mutation position and the correlation of the amplitude change, the gear failure rate of the cable braiding machine is determined, and the fault inspection and repair strategy of the cable braiding machine is determined based on the gear failure rate.

[0011] In some embodiments, the step of obtaining a vibration monitoring signal and a tension monitoring signal of the cable braiding machine during operation includes:

[0012] Obtaining a vibration monitoring signal of the cable braiding machine when it is working by means of a vibration sensor pre-installed on the surface of the gear box housing of the cable braiding machine;

[0013] A tension monitoring signal of the cable braiding machine when working is obtained through a tension sensor pre-installed at the cable braiding inlet of the cable braiding machine.

[0014] In some embodiments, the vibration monitoring signal is analyzed for fluctuations caused by gear wear at different gear speeds to obtain the degree of gear vibration abnormality of the cable braiding machine, including:

[0015] According to the gear speed, dividing the vibration monitoring signal into a plurality of vibration monitoring sub-signals;

[0016] The amplitude fluctuations corresponding to the inherent modal function components in the multiple vibration monitoring sub-signals are analyzed to obtain the abnormal degree of gear vibration of the cable braiding machine.

[0017] In some embodiments, the analyzing the amplitude fluctuations corresponding to the intrinsic modal function components in the plurality of vibration monitoring sub-signals to obtain the abnormal degree of gear vibration of the cable braiding machine includes:

[0018] Extracting the abnormal vibration degree of the first gear corresponding to the high-frequency natural mode function component from the plurality of vibration monitoring sub-signals;

[0019] For the plurality of vibration monitoring sub-signals, extracting the abnormal vibration degree of the second gear corresponding to the low-frequency natural mode function component;

[0020] The first gear vibration abnormality degree and the second gear vibration abnormality degree are combined to obtain the gear vibration abnormality degree of the cable braiding machine.

[0021] In some embodiments, extracting the first gear vibration abnormality degree corresponding to the high-frequency natural mode function component from the plurality of vibration monitoring sub-signals includes:

[0022] According to the plurality of vibration monitoring sub-signals, acquiring the number of the high-frequency intrinsic modal function components and the entropy corresponding to the high-frequency intrinsic modal function components in each of the vibration monitoring sub-signals;

[0023] Determining a change trend of entropy with the gear speed according to the entropy corresponding to the high-frequency natural mode function component in each of the vibration monitoring sub-signals;

[0024] According to the variation trend of the entropy with the gear speed and the number of the high-frequency natural modal function components, the degree of abnormal vibration of the first gear corresponding to the high-frequency natural modal function component is determined.

[0025] In some embodiments, extracting the second gear vibration abnormality degree corresponding to the low-frequency natural modal function component from the plurality of vibration monitoring sub-signals includes:

[0026] According to the plurality of vibration monitoring sub-signals, acquiring the number of the low-frequency natural modal function components and the energy corresponding to the low-frequency natural modal function components in each of the vibration monitoring sub-signals;

[0027] Determining, according to the energy corresponding to the low-frequency natural mode function component in each of the vibration monitoring sub-signals, a variation trend of the energy with the gear speed;

[0028] According to the changing trend of the entropy with the gear speed, the changing trend of the energy with the gear speed, and the number of the low-frequency natural modal function components, the abnormal degree of the second gear vibration corresponding to the low-frequency natural modal function component is determined.

[0029] In some embodiments, the analyzing the time synchronization of the vibration monitoring signal and the tension monitoring signal to obtain the mutation position coincidence degree includes:

[0030] According to a preset time, the vibration monitoring signal is divided into a plurality of first sliding windows, and the tension monitoring signal is divided into a plurality of second sliding windows;

[0031] For each of the first sliding windows, determining the impact point of the vibration monitoring signal by a kurtosis peak value;

[0032] For each of the second sliding windows, determining a change point corresponding to the maximum change rate in the tension monitoring signal through differential monitoring;

[0033] The time synchronization between the impact point and the change point is analyzed to obtain the overlap of the mutation position.

[0034] In some embodiments, the analyzing the consistency of the amplitude changes of the vibration monitoring signal and the tension monitoring signal to obtain the amplitude change correlation includes:

[0035] Acquire the first amplitude of each of the first sliding windows corresponding to the vibration monitoring signal at the different gear speeds, and the second amplitude of each of the second sliding windows corresponding to the tension monitoring signal at the different gear speeds;

[0036] A consistency analysis is performed on changes in the first amplitude and the second amplitude to obtain correlation of the amplitude changes.

[0037] In some embodiments, determining a fault repair strategy of the cable braiding machine based on the gear failure rate includes:

[0038] comparing the gear failure rate with a preset gear failure rate threshold;

[0039] When the gear failure rate is greater than or equal to the preset gear failure rate threshold, the gears of the cable braiding machine are subjected to wear inspection and repair.

[0040] The embodiment of the present application also provides an online fault monitoring system for a cable braiding machine, the system comprising:

[0041] A signal acquisition module, used to acquire vibration monitoring signals and tension monitoring signals of the cable braiding machine when it is working;

[0042] A first analysis module is used to analyze the fluctuation of the vibration monitoring signal caused by gear wear at different gear speeds to obtain the abnormal degree of gear vibration of the cable braiding machine;

[0043] The second analysis module is used to analyze the time synchronization of the vibration monitoring signal and the tension monitoring signal to obtain the overlap of the mutation position, and to analyze the consistency of the amplitude change of the vibration monitoring signal and the tension monitoring signal to obtain the correlation of the amplitude change;

[0044] The gear failure rate determination module is used to determine the gear failure rate of the cable braiding machine based on the abnormal degree of gear vibration, the overlap of the mutation position and the correlation of the amplitude change, and determine the fault inspection and repair strategy of the cable braiding machine based on the gear failure rate.

[0045] The present invention has the following beneficial effects:

[0046] First, the vibration monitoring signal and the tension monitoring signal of the cable braiding machine are obtained when the cable braiding machine is working; then, for the vibration monitoring signal, at different gear speeds, the fluctuation of the vibration monitoring signal caused by gear wear is analyzed to obtain the abnormality of the gear vibration of the cable braiding machine; then, the time synchronization of the vibration monitoring signal and the tension monitoring signal is analyzed to obtain the overlap of the mutation position, and the consistency of the amplitude change of the vibration monitoring signal and the tension monitoring signal is analyzed to obtain the correlation of the amplitude change; finally, based on the abnormality of the gear vibration, the overlap of the mutation position and the correlation of the amplitude change, the gear failure rate of the cable braiding machine is determined, and the fault inspection and repair strategy of the cable braiding machine is determined based on the gear failure rate. In this application, the vibration signal is one of the important indicators of the health status of mechanical equipment, especially for key transmission components such as gears. Gear wear will cause changes in vibration characteristics, especially at different speeds, the vibration frequency and amplitude will be different. By analyzing the fluctuations caused by gear wear in the vibration signal, early signs of minor wear can be captured; the tension control of the cable braiding machine directly affects the braiding quality, and the tension change is often closely related to the state of the mechanical components. Gear wear may cause tension fluctuations, which in turn affects the braiding density and rhythm. By monitoring the tension signal, the working state of the gear can be indirectly reflected; by analyzing the time synchronization and amplitude change consistency of the vibration and tension signals, the existence of the fault can be further verified. If the two signals have a sudden change at the same time point and the amplitude change trend is consistent, this strongly suggests that the gear may have a fault. This multi-signal fusion method improves the accuracy of fault diagnosis and avoids the possibility of misjudgment of a single signal. By collecting and monitoring the signal of the cable braiding machine, the potential fault problems of the cable braiding machine can be discovered in real time and accurately, avoiding the interference and influence of other faults caused by long-term gear problems on the cable braiding machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions 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 paying creative work.

[0048] Figure 1 A schematic diagram of an implementation environment of an online fault monitoring method for a cable braiding machine provided by an embodiment of the present invention;

[0049] Figure 2 A schematic flow chart of a method for online fault monitoring of a cable braiding machine provided by an embodiment of the present invention;

[0050] Figure 3 A schematic diagram of a decomposition of a vibration monitoring signal provided by an embodiment of the present invention;

[0051] Figure 4 A schematic structural diagram of an online fault monitoring system for a cable braiding machine provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of an online fault monitoring method and system for a cable braiding machine proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0053] It should be noted that the terms "first", "second", etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0054] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0055] The specific scheme of the online fault monitoring method and system for a cable braiding machine provided by the present invention is described in detail below with reference to the accompanying drawings.

[0056] See also Figure 1 , Figure 1 A schematic diagram of an implementation environment of an online fault monitoring method for a cable braiding machine provided by an embodiment of the present invention. Figure 1As shown, the implementation environment includes an online fault monitoring terminal 101 and a signal acquisition terminal 102. The online fault monitoring terminal 101 may be a terminal device configured with an online fault monitoring system for a cable braiding machine, including but not limited to a laptop computer, a tablet computer, a handheld computer, a PAD (tablet computer), a desktop computer, etc. with local computing capabilities; the online fault monitoring system for a cable braiding machine may be implemented in the form of a target client, and the target client may be a client supporting online fault monitoring for a cable braiding machine, such as a video client, an instant messaging client, a browser client, etc.; the online fault monitoring terminal 101 may, but is not limited to, communicate with the signal acquisition terminal 102 through a network, and the network may include but is not limited to: a wired network, a wireless network, wherein the wired network includes: a local area network, a metropolitan area network, and a wide area network, and the wireless network includes: Bluetooth, WIFI (Wireless Fidelity, a technology that allows electronic devices to connect to a wireless local area network) and other networks that implement wireless communication. The online fault monitoring terminal 101 may, but is not limited to, include a human-computer interaction screen, a processor, and a memory. The human-computer interaction screen may, but is not limited to, be used to display the gear failure rate of the cable braiding machine. The above processor may be used, but is not limited to, to respond to human-computer interaction operations, execute corresponding operations, or generate corresponding instructions.

[0057] As an optional method, the signal acquisition terminal 102 is arranged at the cable braiding machine, and when the cable braiding machine is working, the vibration monitoring signal and the tension monitoring signal can be collected through the signal acquisition terminal 102. The signal acquisition terminal 102 may include, for example: a vibration sensor, a sensor for measuring the vibration characteristics of an object, which may include an accelerometer, a velocity sensor, a displacement sensor, etc.; a tension sensor, a sensor for measuring the tension (pulling force) of an object, which may include a strain gauge tension sensor, an optical fiber tension sensor, a magnetostrictive tension sensor, etc.

[0058] As an optional manner, the above-mentioned fault online monitoring terminal 101 can also be a server, which can be a single server, a server cluster composed of multiple servers, or a cloud server. The above is only an example, and this embodiment does not make any limitation to this.

[0059] As an optional manner, the following steps of the online fault monitoring method for a cable braiding machine may be performed on the online fault monitoring terminal 101:

[0060] Obtain vibration monitoring signals and tension monitoring signals of the cable braiding machine when it is working;

[0061] For the vibration monitoring signal, at different gear speeds, the fluctuation of the vibration monitoring signal caused by gear wear is analyzed to obtain the abnormal degree of gear vibration of the cable braiding machine;

[0062] Analyze the time synchronization of the vibration monitoring signal and the tension monitoring signal to obtain the mutation position coincidence, and analyze the amplitude change consistency of the vibration monitoring signal and the tension monitoring signal to obtain the amplitude change correlation;

[0063] Based on the abnormal degree of gear vibration, the overlap of the mutation position and the correlation of the amplitude change, the gear failure rate of the cable braiding machine is determined, and the fault inspection and repair strategy of the cable braiding machine is determined based on the gear failure rate.

[0064] In the above method, the vibration signal is one of the important indicators of the health status of mechanical equipment, especially for key transmission components such as gears. Gear wear will cause changes in vibration characteristics, especially at different speeds, the vibration frequency and amplitude will be different. By analyzing the fluctuations caused by gear wear in the vibration signal, early signs of minor wear can be captured; the tension control of the cable braiding machine directly affects the braiding quality, and the tension change is often closely related to the state of the mechanical components. Gear wear may cause tension fluctuations, which in turn affects the braiding density and rhythm. By monitoring the tension signal, the working state of the gear can be indirectly reflected; by analyzing the time synchronization and amplitude change consistency of the vibration and tension signals, the existence of the fault can be further verified. If the two signals have a sudden change at the same time point and the amplitude change trend is consistent, it strongly suggests that the gear may have a fault. This multi-signal fusion method improves the accuracy of fault diagnosis and avoids the possibility of misjudgment of a single signal. By collecting and monitoring the signal of the cable braiding machine, the potential fault problems of the cable braiding machine can be discovered in real time and accurately, thereby reducing the decline in cable production yield due to gear failure, and avoiding the interference and impact of other faults caused by long-term gear problems on the cable braiding machine.

[0065] As an optional example, this embodiment does not limit the execution subject of the above-mentioned online fault monitoring method for cable braiding machines. The above-mentioned online fault monitoring method for cable braiding machines can be executed on the online fault monitoring terminal 101. For example, when the online fault monitoring terminal 101 is a desktop computer, some or all steps of the above-mentioned online fault monitoring method for cable braiding machines can be executed on the desktop computer.

[0066] The above section introduces the contents of an exemplary implementation environment for applying the technical solution of the present application. Next, the present application will continue to introduce the online fault monitoring method for a cable braiding machine.

[0067] In order to solve the problem of real-time and accurate online monitoring of cable braiding machine faults in the prior art, the embodiments of the present application respectively propose an online fault monitoring method for a cable braiding machine and an online fault monitoring system for a cable braiding machine. These embodiments will be described in detail below.

[0068] See also Figure 2 , Figure 2 A schematic diagram of a flow chart of a method for online fault monitoring of a cable braiding machine provided by an embodiment of the present invention, which can be applied to Figure 1 It should be understood that the method can also be applied to other exemplary implementation environments and be specifically executed by devices in other implementation environments, and this embodiment does not limit the implementation environment to which the method is applicable.

[0069] like Figure 2 As shown, in an exemplary embodiment, the online fault monitoring method for a cable braiding machine includes at least steps S210 to S240, which are described in detail as follows:

[0070] In step S210, a vibration monitoring signal and a tension monitoring signal of the cable braiding machine when it is working are obtained.

[0071] Among them, the vibration monitoring signal refers to the mechanical vibration data collected by the vibration sensor installed on the gearbox housing or other key parts. These data reflect the vibration characteristics of the gears inside the cable braiding machine during operation. The vibration signal is one of the important indicators of the health status of mechanical equipment, especially for key transmission components such as gears. Gear wear will cause changes in vibration characteristics, especially at different speeds, the vibration frequency and amplitude will be different. By analyzing the fluctuations in the vibration signal caused by gear wear, early subtle signs of wear can be captured.

[0072] Among them, the tension monitoring signal refers to the cable tension data collected by the tension sensor installed at the cable braiding entrance or at a position where the tension changes greatly during the braiding process. These data reflect the tension changes of the cable during the braiding process. The tension control of the cable braiding machine directly affects the braiding quality, and the tension change is often closely related to the state of the mechanical parts. For example, gear wear may cause tension fluctuations, which in turn affects the braiding density and rhythm. By monitoring the tension signal, the working state of the gear can be indirectly reflected. Especially when the gear wear causes tension fluctuations, the tension sensor can provide important auxiliary information.

[0073] In step S220, with respect to the vibration monitoring signal, at different gear speeds, fluctuations of the vibration monitoring signal caused by gear wear are analyzed to obtain the degree of abnormal gear vibration of the cable braiding machine.

[0074] Among them, gear speed refers to the number of revolutions a gear makes per unit time, usually expressed in revolutions per minute (RPM). In actual operation of the cable braiding machine, the gear speed may be adjusted according to production needs. The vibration characteristics of gears at different speeds are different. Low-frequency vibrations may occur at low speeds, and high-frequency vibrations may occur at high speeds. By analyzing the vibration signal at different speeds, the characteristics of gear wear can be captured more comprehensively. In particular, when gear wear gradually increases, the changes in its vibration characteristics at different speeds will be more obvious, which will help to detect potential problems early.

[0075] Wherein, when analyzing the fluctuation of the vibration monitoring signal caused by gear wear, the specific fluctuation component caused by gear wear is extracted from the vibration monitoring signal. By comparing the vibration signals under normal state and wear state, the abnormal vibration characteristics related to gear wear are identified. In some embodiments, the vibration signal can be decomposed into multiple IMF (Intrinsic Mode Function) components using techniques such as EMD (Empirical Mode Decomposition), and the high-frequency and low-frequency components are analyzed separately. The high-frequency component usually reflects the impact vibration caused by microscopic defects on the surface of the gear, while the low-frequency component reflects the vibration change of the overall structure; the complexity and irregularity of the high-frequency IMF component can also be evaluated by calculating the entropy value of the high-frequency IMF component, and the change trend of the entropy value can reflect the degree of gear wear; the energy of the low-frequency IMF component can also be calculated to evaluate its intensity change, and the change trend of the energy can reflect the change of the overall structure of the gear.

[0076] In step S230, the time synchronization of the vibration monitoring signal and the tension monitoring signal is analyzed to obtain the mutation position coincidence, and the amplitude change consistency of the vibration monitoring signal and the tension monitoring signal is analyzed to obtain the amplitude change correlation.

[0077] Among them, time synchronization analysis refers to comparing the time series of vibration monitoring signals and tension monitoring signals to determine whether the two have mutations at the same time point. Specifically, the signal is divided into multiple time periods through sliding window technology, and mutation points are found in each time period. The vibration monitoring signal and the tension monitoring signal are divided into multiple sliding windows respectively, and the window size can be selected according to the signal frequency characteristics or historical data. For the vibration monitoring signal, the impact point is determined by kurtosis peak detection; for the tension monitoring signal, the change point corresponding to the maximum change rate is determined by differential monitoring. Analyze the time synchronization of the impact point and the change point, and calculate the overlap between the two. If the two signals have mutations at the same time point and the overlap is high, this strongly suggests that the gear may be faulty.

[0078] Among them, the amplitude change consistency analysis refers to comparing the amplitude change trends of the vibration monitoring signal and the tension monitoring signal to determine whether the changes of the two are consistent. Specifically, the amplitudes of the vibration signal and the tension signal are obtained at different gear speeds, and their change trends are analyzed.

[0079] In step S240, the gear failure rate of the cable braiding machine is determined based on the abnormal degree of gear vibration, the mutation position overlap and the amplitude change correlation, and the fault inspection and repair strategy of the cable braiding machine is determined based on the gear failure rate.

[0080] Among them, the fault inspection and repair strategy refers to the maintenance and repair plan determined based on the gear failure rate. The specific inspection and repair strategy can be adjusted according to the gear failure rate to ensure the stable operation of the equipment and product quality. Based on the abnormal degree of gear vibration, the overlap of mutation positions and the correlation of amplitude changes, the health status of the gear is comprehensively evaluated and the gear failure rate is calculated. A preset gear failure rate threshold is set. When the gear failure rate is greater than or equal to the threshold, a maintenance alarm is triggered to prompt the operator to inspect and repair. The inspection and repair strategy can be automatically recommended according to the gear failure rate, such as regular inspection, gear replacement, etc., to ensure the efficient operation of the production line.

[0081] It can be seen from the above steps S210 to S240 that in the scheme proposed in this embodiment, the vibration signal is one of the important indicators of the health status of mechanical equipment, especially for key transmission components such as gears. Gear wear will cause changes in vibration characteristics, especially at different speeds, the vibration frequency and amplitude will be different. By analyzing the fluctuations caused by gear wear in the vibration signal, early signs of slight wear can be captured; the tension control of the cable braiding machine directly affects the braiding quality, and the tension change is often closely related to the state of the mechanical components. Gear wear may cause tension fluctuations, which in turn affects the braiding density and rhythm. By monitoring the tension signal, the working state of the gear can be indirectly reflected; by analyzing the time synchronization and amplitude change consistency of the vibration and tension signals, the existence of the fault can be further verified. If the two signals suddenly change at the same time point and the amplitude change trend is consistent, this strongly suggests that the gear may have a fault. This multi-signal fusion method improves the accuracy of fault diagnosis and avoids the possibility of misjudgment of a single signal. By collecting and monitoring the signals of the cable braiding machine, the potential fault problems of the cable braiding machine can be discovered in real time and accurately, thereby reducing the decline in cable production yield due to gear failure and avoiding interference and impact on the cable braiding machine caused by other faults caused by long-term gear problems.

[0082] In one embodiment of the present application, the step of obtaining a vibration monitoring signal and a tension monitoring signal of the cable braiding machine during operation includes:

[0083] Obtaining a vibration monitoring signal of the cable braiding machine when it is working by means of a vibration sensor pre-installed on the surface of the gear box housing of the cable braiding machine;

[0084] A tension monitoring signal of the cable braiding machine when working is obtained through a tension sensor pre-installed at the cable braiding inlet of the cable braiding machine.

[0085] Among them, the vibration sensor is a sensor used to measure the vibration characteristics of an object, which can convert mechanical vibration into electrical signals. The vibration sensor is installed on the surface of the gearbox housing of the cable braiding machine to monitor the vibration of the gear in real time during operation. The vibration sensor is usually installed on the surface of the gearbox housing or near the key parts of the gear. The reason for choosing this position is that the gears in the gearbox directly drive other parts of the cable braiding machine, and the vibration of the gears will be transmitted to the gearbox housing, so the vibration signal of the gear can be effectively captured. The main function of the vibration sensor is to monitor the vibration of the gear in real time during operation and capture the tiny vibration changes caused by gear wear. By analyzing the vibration signals at different speeds, signs of gear wear can be detected early to avoid further deterioration of the fault.

[0086] Among them, the tension sensor is a sensor used to measure the tension (pulling force) of an object, which can convert the tension signal into an electrical signal. The tension sensor is usually installed at the entrance of the cable braiding or at a location where the tension changes greatly during the braiding process. The reason for choosing this location is that the cable needs to maintain a certain tension when entering the braiding machine to ensure the quality and density of the braiding. The tension sensor can monitor the tension changes of the cable in real time and detect abnormal conditions in time. The main function of the tension sensor is to monitor the tension changes of the cable in real time during the braiding process to ensure the braiding density and quality. By analyzing the tension signal, the working status of the gear can be indirectly reflected. Especially when the tension fluctuates due to gear wear, the tension sensor can provide important auxiliary information.

[0087] For example, gears are important components of cable braiding machines. Although slight wear on gears will not cause major failures in cable braiding machines, they will have a certain impact on the braiding rhythm and density of the cables actually produced. To this end, it is necessary to install sensors on the cable braiding machine to monitor the data during operation to analyze the gear failures on the current cable braiding machine. When there is slight wear on the gears, the gap between the gear meshing during operation will increase, resulting in unevenness in the power transmission process, which will cause slight vibrations in the cable braiding machine. To this end, a vibration sensor can be used to monitor the vibration monitoring signal of the cable braiding machine during operation, which is installed on the surface of the gear box housing, and then the gear failure is mined from the monitored vibration data. The unstable tension in the power transmission process caused by the wear of the gears will affect the tension control system, causing the tension of the wire to be large and small, resulting in uneven braiding layers on the cable surface. To this end, a tension sensor is installed at the cable braiding entrance of the current cable braiding machine, so that the tension is more directly affected by the transmission system.

[0088] In this embodiment, the vibration sensor is installed on the surface of the gearbox housing, which can directly capture the vibration signal of the gear and avoid attenuation and distortion during signal transmission. This installation method ensures high-precision acquisition of vibration signals and can sensitively capture small vibration changes caused by gear wear. The tension sensor is installed at the cable braiding entrance, which can monitor the tension changes of the cable in real time to ensure the braiding quality and density. By selecting a suitable sensor type (such as a strain gauge tension sensor), high-precision tension measurement can be achieved and tension fluctuations can be detected in time. The selection and installation position of the vibration sensor and the tension sensor are carefully designed to ensure the reliability and stability of signal acquisition. Even in a complex industrial environment with background noise or other interference factors, the signals of gear wear and tension changes can still be accurately captured. By double verification of the time synchronization and amplitude change consistency of the vibration signal and the tension signal, the anti-interference ability is effectively improved and the reliability of the monitoring results is ensured. The installation position of the vibration sensor and the tension sensor is clear, which is convenient for operators to install and maintain. The installation process of the sensor is simple, and there is no need for large-scale transformation of existing equipment, which reduces the installation cost and maintenance difficulty. The selection of the installation position of the sensor also takes into account the safety and stability of the equipment, avoiding the impact on normal production. By combining the data from the vibration sensor and the tension sensor, multi-dimensional data analysis is achieved, avoiding the possibility of misjudgment of a single signal. In particular, by analyzing the time synchronization and the consistency of amplitude changes, the existence of the fault is further verified, improving the accuracy of diagnosis.

[0089] In one embodiment of the present application, the vibration monitoring signal is analyzed for fluctuations caused by gear wear at different gear speeds to obtain the abnormal degree of gear vibration of the cable braiding machine, including:

[0090] According to the gear speed, dividing the vibration monitoring signal into a plurality of vibration monitoring sub-signals;

[0091] The amplitude fluctuations corresponding to the inherent modal function components in the multiple vibration monitoring sub-signals are analyzed to obtain the abnormal degree of gear vibration of the cable braiding machine.

[0092] Among them, the slight wear problem of the cable braiding machine gear has a relatively small impact on the production process. Usually, the slight wear of individual gears caused by the emergency shutdown of the cable braiding machine may cause the cable braiding density to change. Although the slight wear of the gear has little effect in the monitoring process, given that the sizes of many gears on the cable braiding machine are different, the data they feedback are different, and the interference information generated by other components of the cable braiding machine makes the data mining work extremely complicated. In order to more effectively monitor these gear wear faults on the cable braiding machine, it is necessary to combine the vibration monitoring signal and the fluctuation information under the tension monitoring signal collected on the cable braiding machine to obtain the gear wear fault of the cable braiding machine. When discussing the gear wear problem of the cable braiding machine, it was found that the slightly worn gears will cause the cable braiding machine to vibrate slightly during operation. There is a certain correlation between this vibration and the speed of the running gear of the braiding machine. Specifically, when the speed of the cable braiding machine is low, the vibration amplitude caused by the wear of the wheel surface is relatively small. At this time, the monitored vibration monitoring signal is mainly interfered by the running noise of the cable braiding machine. However, as the speed increases, the pressure on the wear area of ​​the wheel gradually increases, and the vibration amplitude caused by wear also increases accordingly. In order to deeply understand the specific impact of gear wear on vibration monitoring signals, the cable braiding machine was tested at different speeds and the corresponding vibration monitoring signal data was collected. By comparing and analyzing the vibration monitoring signals at different speeds, the specific impact of the current gear speed on the vibration monitoring signal can be evaluated.

[0093] For example, the current cable braiding machine speed strategy is set to obtain the current rated speed of the cable braiding machine. . The vibration monitoring signal is monitored at five speed intervals of 80%, 90%, 100%, 110% and 120% of the current rated speed. For the vibration monitoring signal monitored at any single speed, a vibration monitoring signal of five minutes under the stable working environment of the cable braiding machine is selected for extraction. Any segment of the collected vibration monitoring signal is split, and the original signal is decomposed into multiple signals of different frequencies through the EMD signal decomposition algorithm. Figure 3 , Figure 3 A schematic diagram of a decomposition of a vibration monitoring signal provided by an embodiment of the present invention. Figure 3 It can be seen that when the cable braiding machine is in a low-speed operation state, the vibration value caused by wear is small, the signal performance is relatively stable, and the fault-related characteristics are covered by the signal. In this regard, the vibration caused by noise and wear in signal 1 and signal 2 is mainly noise; signal 3-signal 4 shows low-frequency periodic changes. As the speed of the cable braiding machine's running gear continues to increase, the vibration caused by wear continues to increase, mainly in the high-frequency component, and a periodic impact signal appears; there are frequency characteristics caused by wear in the medium and low frequency components, and the amplitude increases with the increase of speed. Therefore, the performance of different speeds under the same IMF component can be extracted, and the amplitude abnormality information of the characteristic fluctuation caused by gear wear under its component can be extracted to obtain the overall gear vibration abnormality.

[0094] Among them, dividing the vibration monitoring signal into multiple vibration monitoring sub-signals according to the gear speed means that according to the different speeds of the cable braiding machine gears, the collected vibration monitoring signal is divided into multiple time segments or frequency segments, and each segment is called a "vibration monitoring sub-signal". The vibration characteristics at different speeds may be different, so it is necessary to analyze the vibration signals at each speed separately to capture the specific fluctuations caused by gear wear. According to the change of gear speed, the vibration monitoring signal is divided into time windows. For example, a fixed time window (such as per second or per minute) can be set, or the window size can be dynamically adjusted according to the change of gear speed. According to the frequency range corresponding to the gear speed, the vibration monitoring signal is divided into frequency segments. For example, at low speed, low-frequency vibration is mainly concerned, and at high speed, high-frequency vibration is concerned. Through spectrum analysis, the signal can be decomposed into different frequency components for subsequent analysis.

[0095] Among them, the intrinsic mode function (IMF) is a series of signal components that meet specific conditions generated during the empirical mode decomposition process. Each IMF represents an oscillation mode in a specific frequency range in the original signal, and usually contains information on different time scales. In any segment of data, the number of maximum and minimum points of the IMF is either equal or differs by one. In addition, the number of zero-crossing points of the IMF should also be the same as the number of extreme points or differ by one. For each point of the IMF, the upper envelope constructed by all the maximum points and the lower envelope constructed by all the minimum points should have an average value close to zero at this point.

[0096] Among them, in the EMD process, the original vibration monitoring signal is decomposed into multiple IMF components. Each IMF component represents an oscillation mode in a specific frequency range in the signal, usually including high-frequency components and low-frequency components. The high-frequency component reflects the impact vibration caused by microscopic defects on the surface of the gear, which is usually related to local wear or cracks on the gear. The amplitude of the high-frequency component fluctuates greatly and increases with the increase in gear wear. The low-frequency component reflects the changes in the overall structure of the gear, which is usually related to the overall deformation or looseness of the gear. The amplitude of the low-frequency component fluctuates less, but its energy change can reflect the overall health of the gear.

[0097] Among them, amplitude fluctuation refers to the change of amplitude in the vibration signal over time or frequency. By analyzing the amplitude fluctuation of the IMF component in the vibration monitoring sub-signal, the degree of gear wear can be evaluated. By calculating the entropy value of the high-frequency IMF component, its complexity and irregularity can be evaluated. The change trend of the entropy value can reflect the degree of gear wear. For example, as the gear wear increases, the entropy value of the high-frequency IMF component may increase, indicating that the vibration signal becomes more complex and irregular. By calculating the energy of the low-frequency IMF component, its intensity change can be evaluated. The change trend of the energy can reflect the change of the overall structure of the gear. For example, as the gear wear increases, the energy of the low-frequency IMF component may increase, indicating that the overall vibration intensity of the gear increases. By detecting the peaks in the IMF components, the mutation points in the vibration signal can be identified. If the peak of a certain IMF component appears frequently or the amplitude increases significantly, it may indicate that the gear has local wear or failure.

[0098] In this embodiment, by dividing the vibration monitoring signal into multiple sub-signals and analyzing the vibration characteristics of the gears at different speeds, it is avoided that the analysis results at a single speed cover up the abnormal conditions at other speeds. In particular, through the comprehensive analysis of high-frequency and low-frequency IMF components, the characteristics of gear wear can be captured more comprehensively and the accuracy of fault diagnosis can be improved. Through the entropy analysis of high-frequency IMF components and the energy analysis of low-frequency IMF components, tiny gear wear signals can be sensitively captured to achieve early fault warning. Even if the gear wear is relatively light, potential problems can be discovered in time through changes in amplitude fluctuations to prevent the fault from further deteriorating.

[0099] In one embodiment of the present application, the analyzing the amplitude fluctuations corresponding to the intrinsic modal function components in the plurality of vibration monitoring sub-signals to obtain the abnormal vibration degree of the gear of the cable braiding machine includes:

[0100] Extracting the abnormal vibration degree of the first gear corresponding to the high-frequency natural mode function component from the plurality of vibration monitoring sub-signals;

[0101] For the plurality of vibration monitoring sub-signals, extracting the abnormal vibration degree of the second gear corresponding to the low-frequency natural mode function component;

[0102] The first gear vibration abnormality degree and the second gear vibration abnormality degree are combined to obtain the gear vibration abnormality degree of the cable braiding machine.

[0103] In one embodiment of the present application, extracting the first gear vibration abnormality degree corresponding to the high-frequency natural mode function component from the plurality of vibration monitoring sub-signals includes:

[0104] According to the plurality of vibration monitoring sub-signals, acquiring the number of the high-frequency intrinsic modal function components and the entropy corresponding to the high-frequency intrinsic modal function components in each of the vibration monitoring sub-signals;

[0105] Determining a change trend of entropy with the gear speed according to the entropy corresponding to the high-frequency natural mode function component in each of the vibration monitoring sub-signals;

[0106] According to the variation trend of the entropy with the gear speed and the number of the high-frequency natural modal function components, the degree of abnormal vibration of the first gear corresponding to the high-frequency natural modal function component is determined.

[0107] Among them, entropy is an important concept in information theory, which is used to measure the complexity and irregularity of signals. The entropy value reflects the randomness and irregularity of the impact vibration in the high-frequency IMF component. As the gear wear increases, the impact vibration in the high-frequency IMF component will become more complex and irregular, resulting in an increase in the entropy value.

[0108] The entropy variation trend with the gear speed refers to the trend of the entropy value of the high-frequency IMF component with the gear speed. The gear vibration characteristics are different at different speeds, so the entropy variation trend can provide more information about gear wear. Specifically, as gear wear increases, the entropy value of the high-frequency IMF component may increase significantly at certain speeds, while remaining relatively stable at other speeds.

[0109] For example, the high-frequency component signal 1 and signal 2 are screened. When the gear is worn, as the gear speed increases, the external impact force on the gear increases, and the amplitude caused by wear in the component signal continues to increase, gradually showing periodic characteristics in the signal. The entropy corresponding to the high-frequency natural mode function component in the vibration monitoring sub-signal is recorded as , when the entropy is larger, it means the current signal is more disordered. The gear vibration anomaly in the current high-frequency natural mode function component is analyzed by the entropy of the signal at different gear speeds. If the entropy shows a trend of gradually decreasing as the signal increases, the gear vibration anomaly shown by the signal is higher.

[0110] Exemplarily, the abnormal vibration degree of the first gear may be expressed as follows:

[0111]

[0112] Wherein, ZP represents the abnormal vibration degree of the first gear; GA represents the number of high-frequency natural modal function components, which may be the number of signal 1 and signal 2 in this embodiment; MV represents the number of vibration monitoring sub-signals; It represents the entropy corresponding to the high-frequency intrinsic modal function component in the vibration monitoring sub-signal, that is, the entropy of the signal under the ath intrinsic modal function component corresponding to the gear speed v; Indicates gear speed The entropy of the signal under the corresponding a-th natural mode function component, gear speed Greater than the gear speed v; Represents the maximum and minimum normalization function.

[0113] in, The difference between the entropy of the signal of high gear speed under the high-frequency inherent modal function component and the entropy of the adjacent signal of low gear speed is the changing trend of entropy with gear speed. When the changing trend is greater, it means that with the increase of gear speed, the data in its high-frequency inherent modal function component shows a gradually orderly trend. In this regard, the currently collected signal data has a higher gear vibration abnormality under the high-frequency component.

[0114] In this embodiment, by analyzing the entropy value of the high-frequency IMF component, the system can sensitively capture tiny gear wear signals, especially when microscopic defects appear on the gear surface, the change trend of the entropy value can provide important diagnostic information. Compared with the traditional vibration analysis method, entropy value analysis can more accurately reflect the complexity and irregularity of gear wear, thereby improving the accuracy of fault diagnosis. By analyzing the change trend of the entropy value with the gear speed, the system can detect signs of slight wear of the gear at an early stage. Even if the gear wear is light, the system can issue an early warning through the change trend of the entropy value to prevent the fault from further deteriorating. In particular, when the entropy value suddenly changes at certain speeds, it may be a sign of local wear or failure of the gear. The system can take measures in advance to avoid equipment downtime and maintenance costs. By analyzing the change trend of the entropy value, the system effectively improves the anti-interference ability. Even in a complex industrial environment with background noise or other interference factors, the system can still accurately judge the health status of the gear. The change trend of the entropy value can filter out short-term noise interference and focus on long-term wear trends, thereby improving the reliability of the system.

[0115] In one embodiment of the present application, extracting the second gear vibration abnormality degree corresponding to the low-frequency natural modal function component from the plurality of vibration monitoring sub-signals includes:

[0116] According to the plurality of vibration monitoring sub-signals, acquiring the number of the low-frequency natural modal function components and the energy corresponding to the low-frequency natural modal function components in each of the vibration monitoring sub-signals;

[0117] Determining, according to the energy corresponding to the low-frequency natural mode function component in each of the vibration monitoring sub-signals, a variation trend of the energy with the gear speed;

[0118] According to the changing trend of the entropy with the gear speed, the changing trend of the energy with the gear speed, and the number of the low-frequency natural modal function components, the abnormal degree of the second gear vibration corresponding to the low-frequency natural modal function component is determined.

[0119] Among them, energy refers to the integral of the total amplitude square of the low-frequency intrinsic mode function component within a certain time window, which is used to measure the intensity of the low-frequency IMF component. The low-frequency IMF component usually reflects the changes in the overall structure of the gear, such as the overall deformation, looseness, and misalignment of the gear. As the gear wear increases, the energy of the low-frequency IMF component will gradually increase, indicating that the overall vibration intensity of the gear increases.

[0120] The energy variation trend with the gear speed refers to the energy variation trend of the low-frequency IMF component with the gear speed. The vibration characteristics of the gears at different speeds are different, so the energy variation trend can provide more information about gear wear. Specifically, as the gear wear increases, the energy of the low-frequency IMF component may increase significantly at certain speeds, while remaining relatively stable at other speeds.

[0121] For example, for the medium and low frequency component signals, under normal circumstances, they are mainly manifested as low-frequency periodic changes caused by gear rotation, and their frequency is proportional to the rotation speed. When the gear is worn, a relatively high vibration will be generated each time it rotates to the wear area, and the amplitude of its low-frequency signal will increase significantly with the rotation speed. At the same time, due to the unevenness of gear wear, the signal gradually becomes periodically unstable as the rotation speed increases. When the energy in the low-frequency component signal increases with the increase in gear speed and the entropy of the signal shows a downward trend, the current low-frequency signal component shows a high degree of abnormality in the gear vibration.

[0122] Exemplarily, the abnormal vibration degree of the second gear may be expressed as follows:

[0123]

[0124] Wherein, DP represents the abnormal vibration degree of the second gear; DA represents the number of low-frequency natural modal function components, which may be signal 3 or signal 4 in this embodiment; MV represents the number of vibration monitoring sub-signals; It indicates the energy of the ath natural mode function component corresponding to the gear speed v. As the gear speed increases, its energy gradually increases and the stability of its signal gradually decreases, the higher the current vibration abnormality. It represents the energy of the ath natural mode function component corresponding to the gear speed v+1; Represents the maximum and minimum normalization function.

[0125] in, It indicates the changing trend of energy with gear speed. The greater the changing trend, the greater the abnormal vibration of the second gear.

[0126] For example, the abnormal degree of gear vibration of the cable braiding machine can be expressed as:

[0127]

[0128] in, is the abnormal vibration degree of the gear of the cable braiding machine, DP represents the abnormal vibration degree of the second gear, and ZP represents the abnormal vibration degree of the first gear.

[0129] In this embodiment, by analyzing the energy of the low-frequency IMF component, the system can evaluate the overall health status of the gear, especially when the gear is severely worn, the energy of the low-frequency IMF component will increase significantly. Compared with the traditional vibration analysis method, energy analysis can more accurately reflect the overall vibration intensity of the gear, thereby improving the accuracy of fault diagnosis. By analyzing the trend of energy value changes with gear speed, the system can detect signs of slight wear of the gear at an early stage. Even if the gear wear is light, the system can issue an early warning through the trend of energy value changes to prevent the fault from further deteriorating. In particular, when the energy value changes suddenly at certain speeds, it may be a sign of local wear or failure of the gear. The system can take measures in advance to avoid equipment downtime and maintenance costs. By analyzing the trend of energy value changes, the system effectively improves the anti-interference ability. Even in a complex industrial environment with background noise or other interference factors, the system can still accurately judge the health status of the gear. The trend of energy value changes can filter out short-term noise interference and focus on long-term wear trends, thereby improving the reliability of the system.

[0130] In the above steps, the abnormal degree of gear vibration was successfully identified by analyzing the vibration monitoring signal obtained by monitoring the cable braiding machine at different speeds. Gear wear will not only cause the generation of vibration monitoring signals, but also affect the tension monitoring signal. The fluctuations in the vibration monitoring signal generated by the worn gears during the meshing process usually cause fluctuations in the tension monitoring signal simultaneously. Different degrees of gear wear will cause the amplitude of the vibration monitoring signal to increase, which in turn causes the fluctuation of the amplitude of the tension monitoring signal to increase. In order to analyze the abnormal condition of the gears of the cable braiding machine, it is necessary to observe the consistency of the periodic changes of the vibration monitoring signal and the changes of the tension monitoring signal at different speeds, and to verify whether their corresponding change amplitudes show a linear relationship.

[0131] In one embodiment of the present application, the time synchronization of the vibration monitoring signal and the tension monitoring signal is analyzed to obtain the mutation position coincidence, including:

[0132] According to a preset time, the vibration monitoring signal is divided into a plurality of first sliding windows, and the tension monitoring signal is divided into a plurality of second sliding windows;

[0133] For each of the first sliding windows, determining the impact point of the vibration monitoring signal by a kurtosis peak value;

[0134] For each of the second sliding windows, determining a change point corresponding to the maximum change rate in the tension monitoring signal through differential monitoring;

[0135] The time synchronization between the impact point and the change point is analyzed to obtain the overlap of the mutation position.

[0136] Among them, sliding window is a commonly used signal processing method. By dividing the continuous time domain signal into multiple fixed-length time periods (windows), the signal in each time period can be analyzed independently. According to actual needs, a fixed time interval (such as 1 second, 2 seconds, etc.) is set as the length of the sliding window. The time interval should be short enough to capture instantaneous impacts or changes, but not too short to avoid introducing too much noise.

[0137] Among them, kurtosis is a parameter in statistics, which is used to measure the "sharpness" or "tail thickness" of the signal distribution. In vibration signals, kurtosis can be used to detect instantaneous impact events. The larger the kurtosis value, the more extreme values ​​(i.e., impacts) there are in the signal. By detecting the kurtosis peak, the impact point in the vibration monitoring signal can be determined. In each first sliding window, the kurtosis value of the vibration monitoring signal is calculated, and the maximum value (i.e., peak value) of the kurtosis is found. The moment corresponding to the peak is the impact point. By detecting the kurtosis peak, the system can sensitively capture instantaneous impact events in the vibration monitoring signal, especially in the impact vibration caused by gear wear. The kurtosis peak can provide important diagnostic information. Compared with the traditional amplitude threshold method, kurtosis peak detection can more accurately identify small impact events and avoid misjudgment.

[0138] Among them, differential monitoring refers to calculating the rate of change between adjacent data points by performing point-by-point differential operations on the signal. In the tension monitoring signal, differential monitoring can be used to detect the sudden change point of tension. Specifically, the differential value reflects the rate of change of tension over time. The larger the differential value, the more drastic the tension change. Through differential monitoring, the system can sensitively capture the sudden change points in the tension monitoring signal, especially when the tension fluctuates due to gear wear. Differential monitoring can provide important auxiliary information. Compared with directly analyzing the amplitude of the tension signal, differential monitoring can more accurately identify the changing trend of tension and avoid the influence of background noise.

[0139] Among them, the change point corresponding to the maximum change rate refers to the moment when the change rate in the tension monitoring signal is the largest in each second sliding window. Through differential monitoring, the maximum change rate point in each sliding window can be found, which usually corresponds to the position of the sudden change of tension. The maximum change rate point can reflect the sudden change event in the tension monitoring signal, especially when the tension fluctuates due to gear wear, the maximum change rate point can provide important fault diagnosis information. By analyzing these change points, the system can more accurately judge the working status of the gear and help discover potential faults.

[0140] Among them, time synchronization refers to whether the impact point in the vibration monitoring signal and the change point in the tension monitoring signal occur at the same time or close to the same time. If the two signals have mutations at the same time point and the overlap is high, this strongly suggests that the gear may be faulty. By analyzing the time synchronization of the impact point and the change point, the system can verify the presence of gear wear. If the mutation events of the vibration signal and the tension signal occur at the same time point or close to the same time point, this further proves that the gear may be faulty. This dual verification mechanism improves the accuracy of fault diagnosis and avoids the possibility of misjudgment of a single signal.

[0141] For example, the impact point of the vibration monitoring signal and the change point of the tension monitoring signal are located. To analyze the impact point of the vibration monitoring signal, firstly, the vibration monitoring signal is segmented into sliding windows, with each minute as a single sliding window, and the kurtosis value of the signal in the sliding window is calculated. The peak value of the kurtosis corresponds to the impact point, and the time of obtaining the corresponding impact point is recorded as , where i represents the serial number of the sliding window. For the location of the change point of the tension monitoring signal, a single sliding window is used for calculation every minute. For the i-th sliding window, its signal value is obtained, and the tension monitoring signal is first-order differentiated by differential monitoring. The point with the largest change rate is captured as the change point, and the change time of the corresponding change point is obtained as , where i represents the serial number of the sliding window. Then, the corresponding time position differences of the impact points and change points obtained in each sliding window are analyzed. Since the fluctuations caused by the gear failure of the cable braiding machine will directly affect its vibration monitoring signal and tension monitoring signal, when the corresponding gear is in the meshing process, it will directly cause the tension and vibration monitoring signals to mutate. Therefore, at any time interval, the time corresponding to the impact point and the change point should be the same. The smaller the time difference, the higher the possibility of gear failure. It should be noted that, under normal circumstances, the number of first sliding windows is equal to the number of second sliding windows.

[0142] For example, the degree of overlap of mutation positions may be expressed as:

[0143]

[0144] Among them, SJ represents the overlap of the mutation positions of the vibration monitoring signal and the tension monitoring signal; MI represents the number of sliding windows.

[0145] in, Represents the mutation time of the impact point in the sliding window and the mutation time of the change point The absolute values ​​of the differences are accumulated. The smaller the value is, the higher the overlap of the mutation positions is.

[0146] In this embodiment, by detecting the kurtosis peak of the vibration monitoring signal and differential monitoring of the tension monitoring signal, the system can sensitively capture instantaneous impact and tension fluctuation events. In particular, by analyzing the time synchronization of the impact point and the change point, the system can verify the existence of gear wear and avoid the possibility of misjudgment of a single signal. This double verification mechanism significantly improves the accuracy of fault diagnosis. By analyzing the overlap of the mutation position, the system can detect signs of slight wear of the gear at an early stage. Even if the gear wear is light, the system can issue an early warning through the synchronization of the impact point and the change point to prevent the fault from further deteriorating. In particular, when the overlap of the mutation position is high, it may be a sign of local wear or failure of the gear. The system can take measures in advance to avoid equipment downtime and maintenance costs.

[0147] In one embodiment of the present application, the analysis of the amplitude change consistency of the vibration monitoring signal and the tension monitoring signal to obtain the amplitude change correlation includes:

[0148] Acquire the first amplitude of each of the first sliding windows corresponding to the vibration monitoring signal at the different gear speeds, and the second amplitude of each of the second sliding windows corresponding to the tension monitoring signal at the different gear speeds;

[0149] A consistency analysis is performed on changes in the first amplitude and the second amplitude to obtain correlation of the amplitude changes.

[0150] Among them, the first amplitude refers to the maximum amplitude or average amplitude of the vibration monitoring signal in each first sliding window at different gear speeds. The vibration amplitude reflects the vibration intensity when the gear is running, especially when the gear is worn, the vibration amplitude may change with the change of gear speed. The second amplitude refers to the maximum tension or average tension of the tension monitoring signal in each second sliding window at different gear speeds. The tension amplitude reflects the change in tension of the cable during the braiding process, especially when the tension fluctuates due to gear wear, the tension amplitude will also change.

[0151] Among them, consistency analysis refers to evaluating the correlation between the first amplitude of the vibration monitoring signal and the second amplitude of the tension monitoring signal by comparing the change trends of the two. Specifically, if the vibration amplitude and the tension amplitude show similar change trends (such as increasing or decreasing at the same time) in the same time period, they are considered to be consistent; conversely, if the change trends are inconsistent, it may indicate that there is a fault in the gear or other components.

[0152] Exemplarily, the overlap between the mutation positions of the current vibration monitoring signal and the tension monitoring signal is obtained. Since the amplitude changes of the tension monitoring signal and the vibration monitoring signal are consistent, the amplitude at the mutation position of the screened single sliding window is collected, and the correlation of the amplitude changes at different gear speeds is analyzed. When the amplitudes of the vibration monitoring signal and the tension monitoring signal at different gear speeds have a high correlation, it means that the current cable braiding machine is more likely to have a gear failure. The first amplitude of each first sliding window corresponding to the vibration monitoring signal at different gear speeds is obtained, recorded as . Obtain the second amplitude of each second sliding window corresponding to the tension monitoring signal at different gear speeds, recorded as .

[0153] Exemplarily, the amplitude change correlation may be expressed as follows:

[0154]

[0155] Among them, R represents the correlation between the amplitude changes of the vibration monitoring signal and the tension monitoring signal; yes and The sample covariance of They are and The sample standard deviation of .

[0156] Among them, by using the Pearson correlation coefficient, the amplitude size under different gear speed monitoring sliding windows is collected. When the changes in the amplitude size of the corresponding positions are more consistent, the correlation of the amplitude change is closer to 1, and the possibility of gear failure in the current cable braiding machine is higher.

[0157] In this embodiment, by performing consistency analysis on the changes in the first amplitude of the vibration monitoring signal and the second amplitude of the tension monitoring signal, the system can more comprehensively evaluate the impact of gear wear on vibration and tension. In particular, when the changing trends of the vibration amplitude and the tension amplitude are consistent, this strongly suggests that there may be a fault in the gear. Compared with single signal analysis, this double verification mechanism significantly improves the accuracy of fault diagnosis. By analyzing the consistency of amplitude changes, the system can detect signs of slight wear of the gear at an early stage. Even if the gear wear is light, the system can issue an early warning through the changing trends of the vibration amplitude and the tension amplitude to prevent the fault from further deteriorating. In particular, when the changing trends of the two are consistent and there is a sudden change, it may be a sign of local wear or failure of the gear. The system can take measures in advance to avoid equipment downtime and maintenance costs.

[0158] In one embodiment of the present application, the determining of the fault repair strategy of the cable braiding machine based on the gear failure rate includes:

[0159] comparing the gear failure rate with a preset gear failure rate threshold;

[0160] When the gear failure rate is greater than or equal to the preset gear failure rate threshold, the gears of the cable braiding machine are subjected to wear inspection and repair.

[0161] Among them, wear inspection refers to the detailed inspection and maintenance of the gears of the cable braiding machine when the gear failure rate is detected to exceed the preset threshold, so as to determine the specific wear of the gears and take corresponding repair or replacement measures. The goal of wear inspection is to prevent the gear failure from further deteriorating and ensure the normal operation of the equipment and product quality. Visually inspect the surface of the gear for obvious wear, cracks, peeling and other defects. Appearance inspection can help quickly identify whether the gear is seriously damaged. Use precision measuring tools (such as micrometers, vernier calipers, etc.) to measure the key dimensions of the gear (such as tooth thickness, tooth height, tooth pitch, etc.), and compare them with the design standards to evaluate the degree of wear of the gear. By collecting the vibration signal of the gear during operation again, analyze whether its vibration characteristics have returned to normal. If the vibration abnormality still exists, it may be necessary to further check the installation status or lubrication of the gear. Check whether the tension of the cable is stable during the braiding process, especially when the gear wear may cause tension fluctuations, to ensure the normal operation of the tension control system. Check the lubrication of the gear to ensure that the amount and quality of the lubricating oil or grease meet the requirements. Insufficient lubrication or poor lubrication may accelerate the wear of the gear. If the gear is severely worn and its performance cannot be restored by repair, it is necessary to replace it with a new gear. When replacing gears, ensure that the new gear is compatible with the original equipment and follow the correct installation procedures.

[0162] Exemplarily, in the above steps, the vibration monitoring signal is first analyzed in detail. By decomposing the vibration monitoring signal at different gear speeds, the characteristics of the decomposed vibration monitoring signal at different frequencies are extracted, so as to accurately obtain the abnormal degree of gear vibration. In view of the fact that abnormal gear vibration may be caused by a variety of factors, the multi-source data is fused based on the temporal synchronization and amplitude change consistency of the vibration monitoring signal and the tension monitoring signal caused by gear wear. By dividing the monitoring signal into sliding windows and processing the divided sliding windows, the corresponding mutation position overlap and amplitude change correlation are obtained. When the collected data shows that the gear vibration abnormality is high, and the mutation position overlap and the amplitude change correlation are both maintained at a high level, it can be inferred that the current cable braiding machine gear wear failure rate is high.

[0163] Exemplarily, the gear failure rate may be expressed as:

[0164]

[0165] Among them, JG represents the gear failure rate; YJ represents the degree of gear vibration abnormality; R represents the correlation of amplitude changes; SJ represents the overlap of mutation positions.

[0166] Exemplarily, the preset gear failure rate threshold is 0.5. It is considered that the gears of the current cable braiding machine are worn and the gears of the cable braiding machine need to be repaired for wear.

[0167] In this embodiment, by real-time monitoring of the gear failure rate and timely performing wear inspection and maintenance when the failure rate exceeds the preset threshold, the system can effectively prevent the gear failure from further deteriorating and ensure the normal operation of the equipment. Regular wear inspection and maintenance can help extend the service life of the gear, reduce equipment downtime, and improve the reliability of the production line. By early detection of slight wear of the gear and timely maintenance, the system can avoid further expansion of the fault and reduce the need for large-scale maintenance. Compared with emergency repairs after the failure occurs, preventive wear inspection and maintenance are usually less expensive and do not affect the production schedule. In addition, timely replacement of severely worn gears can prevent other components from being damaged by gear failure, further reducing maintenance costs. By comparing the gear failure rate with the preset threshold, the system can flexibly adjust the maintenance plan according to the actual fault situation. For example, when the gear failure rate is close to the threshold, maintenance can be arranged in advance; when the failure rate is low, the maintenance cycle can be appropriately extended. This data-based maintenance strategy can avoid unnecessary frequent maintenance, improve maintenance efficiency, and reduce labor costs. Gear wear may cause tension fluctuations in the cable braiding process, thereby affecting the quality and consistency of the product. By timely repairing the wear, the system can ensure the normal operation of the gears and keep the tension stable during the cable braiding process, thus improving the quality and consistency of the product. Especially for high-precision cable braiding machines, stable tension control is essential.

[0168] Figure 4 A schematic diagram of the structure of an online fault monitoring system for a cable braiding machine provided by an embodiment of the present invention. The system can be applied to Figure 1 The system can also be applied to other exemplary implementation environments and specifically configured in other devices. This embodiment does not limit the implementation environment to which the system is applied.

[0169] like Figure 4 As shown, the exemplary online fault monitoring system for a cable braiding machine includes:

[0170] The signal acquisition module 401 is used to acquire the vibration monitoring signal and the tension monitoring signal of the cable braiding machine when it is working;

[0171] A first analysis module 402 is used to analyze the fluctuation of the vibration monitoring signal caused by gear wear at different gear speeds to obtain the abnormal degree of gear vibration of the cable braiding machine;

[0172] The second analysis module 403 is used to analyze the time synchronization of the vibration monitoring signal and the tension monitoring signal to obtain the mutation position coincidence, and analyze the amplitude change consistency of the vibration monitoring signal and the tension monitoring signal to obtain the amplitude change correlation;

[0173] The gear failure rate determination module 404 is used to determine the gear failure rate of the cable braiding machine based on the abnormal degree of the gear vibration, the overlap of the mutation position and the correlation of the amplitude change, and determine the fault inspection and repair strategy of the cable braiding machine based on the gear failure rate.

[0174] In this exemplary online fault monitoring system for cable braiding machines, vibration signals are one of the important indicators of the health status of mechanical equipment, especially for key transmission components such as gears. Gear wear will cause changes in vibration characteristics, especially at different speeds, the vibration frequency and amplitude will be different. By analyzing the fluctuations caused by gear wear in the vibration signal, early signs of minor wear can be captured; the tension control of the cable braiding machine directly affects the braiding quality, and the tension change is often closely related to the state of the mechanical components. Gear wear may cause tension fluctuations, which in turn affects the braiding density and rhythm. By monitoring the tension signal, the working state of the gear can be indirectly reflected; by analyzing the time synchronization and amplitude change consistency of the vibration and tension signals, the existence of the fault can be further verified. If the two signals have a sudden change at the same time point and the amplitude change trend is consistent, it strongly suggests that the gear may have a fault. This multi-signal fusion method improves the accuracy of fault diagnosis and avoids the possibility of misjudgment of a single signal. By collecting and monitoring the signal of the cable braiding machine, the potential fault problems of the cable braiding machine can be discovered in real time and accurately, thereby reducing the decline in cable production yield due to gear failure, and avoiding the interference and impact of other faults caused by long-term gear problems on the cable braiding machine.

[0175] It should be noted that the online fault monitoring system for cable braiding machines provided in the above embodiment and the online fault monitoring method for cable braiding machines provided in the above embodiment belong to the same concept, wherein the specific manner in which each module and unit performs the operation has been described in detail in the method embodiment and will not be repeated here. In actual applications, the online fault monitoring system for cable braiding machines provided in the above embodiment can distribute the above functions to different functional modules as needed, that is, divide the internal structure of the system into different functional modules to complete all or part of the functions described above, and this is not limited here.

[0176] It should be noted that the sequence of the above embodiments of the present invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0177] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for online fault monitoring of a cable braiding machine, characterized in that: The method comprises: Obtain vibration monitoring signals and tension monitoring signals of the cable braiding machine when it is working; For the vibration monitoring signal, at different gear speeds, the fluctuation of the vibration monitoring signal caused by gear wear is analyzed to obtain the abnormal degree of gear vibration of the cable braiding machine; Analyze the time synchronization of the vibration monitoring signal and the tension monitoring signal to obtain the mutation position coincidence, and analyze the amplitude change consistency of the vibration monitoring signal and the tension monitoring signal to obtain the amplitude change correlation; Determine the gear failure rate of the cable braiding machine based on the abnormal degree of gear vibration, the overlap of the mutation position and the correlation of the amplitude change, and determine the fault inspection and repair strategy of the cable braiding machine based on the gear failure rate; The analysis of the time synchronization of the vibration monitoring signal and the tension monitoring signal to obtain the mutation position coincidence includes: According to a preset time, the vibration monitoring signal is divided into a plurality of first sliding windows, and the tension monitoring signal is divided into a plurality of second sliding windows; For each of the first sliding windows, determining the impact point of the vibration monitoring signal by a kurtosis peak value; For each of the second sliding windows, determining a change point corresponding to the maximum change rate in the tension monitoring signal through differential monitoring; Analyze the time synchronization of the impact point and the change point to obtain the overlap of the mutation position; The analysis of the consistency of the amplitude changes of the vibration monitoring signal and the tension monitoring signal to obtain the amplitude change correlation includes: Acquire the first amplitude of each of the first sliding windows corresponding to the vibration monitoring signal at different gear speeds, and the second amplitude of each of the second sliding windows corresponding to the tension monitoring signal at the different gear speeds; A consistency analysis is performed on changes in the first amplitude and the second amplitude to obtain correlation of the amplitude changes.

2. The method for online fault monitoring of a cable braiding machine according to claim 1, characterized in that: The method of obtaining a vibration monitoring signal and a tension monitoring signal of the cable braiding machine when the cable braiding machine is working includes: Obtaining a vibration monitoring signal of the cable braiding machine when it is working by means of a vibration sensor pre-installed on the surface of the gear box housing of the cable braiding machine; A tension monitoring signal of the cable braiding machine when working is obtained through a tension sensor pre-installed at the cable braiding inlet of the cable braiding machine.

3. The method for online fault monitoring of a cable braiding machine according to claim 1, characterized in that: The method of analyzing the fluctuation of the vibration monitoring signal caused by gear wear at different gear speeds to obtain the abnormal degree of gear vibration of the cable braiding machine includes: According to the gear speed, dividing the vibration monitoring signal into a plurality of vibration monitoring sub-signals; The amplitude fluctuations corresponding to the inherent modal function components in the multiple vibration monitoring sub-signals are analyzed to obtain the abnormal degree of gear vibration of the cable braiding machine.

4. The method for online fault monitoring of a cable braiding machine according to claim 3, characterized in that: The analyzing the amplitude fluctuations corresponding to the intrinsic modal function components in the plurality of vibration monitoring sub-signals to obtain the abnormal vibration degree of the gear of the cable braiding machine includes: Extracting the abnormal vibration degree of the first gear corresponding to the high-frequency natural mode function component from the plurality of vibration monitoring sub-signals; For the plurality of vibration monitoring sub-signals, extracting the abnormal vibration degree of the second gear corresponding to the low-frequency natural mode function component; The first gear vibration abnormality degree and the second gear vibration abnormality degree are combined to obtain the gear vibration abnormality degree of the cable braiding machine.

5. The method for online fault monitoring of a cable braiding machine according to claim 4, characterized in that: The step of extracting the first gear vibration abnormality degree corresponding to the high-frequency natural modal function component from the plurality of vibration monitoring sub-signals includes: According to the plurality of vibration monitoring sub-signals, acquiring the number of the high-frequency intrinsic modal function components and the entropy corresponding to the high-frequency intrinsic modal function components in each of the vibration monitoring sub-signals; Determining a change trend of entropy with the gear speed according to the entropy corresponding to the high-frequency natural mode function component in each of the vibration monitoring sub-signals; According to the variation trend of the entropy with the gear speed and the number of the high-frequency natural modal function components, the degree of abnormal vibration of the first gear corresponding to the high-frequency natural modal function component is determined.

6. The method for online fault monitoring of a cable braiding machine according to claim 5, characterized in that: The step of extracting the abnormal vibration degree of the second gear corresponding to the low-frequency natural modal function component from the plurality of vibration monitoring sub-signals includes: According to the plurality of vibration monitoring sub-signals, acquiring the number of the low-frequency natural modal function components and the energy corresponding to the low-frequency natural modal function components in each of the vibration monitoring sub-signals; Determining a variation trend of the energy with the gear speed according to the energy corresponding to the low-frequency natural mode function component in each of the vibration monitoring sub-signals; According to the changing trend of the entropy with the gear speed, the changing trend of the energy with the gear speed, and the number of the low-frequency natural modal function components, the abnormal degree of the second gear vibration corresponding to the low-frequency natural modal function component is determined.

7. The method for online fault monitoring of a cable braiding machine according to claim 1, characterized in that: The method of determining a fault repair strategy for the cable braiding machine based on the gear failure rate includes: comparing the gear failure rate with a preset gear failure rate threshold; When the gear failure rate is greater than or equal to the preset gear failure rate threshold, the gears of the cable braiding machine are subjected to wear inspection and repair.

8. An online fault monitoring system for a cable braiding machine, characterized in that: The system comprises: A signal acquisition module, used to acquire vibration monitoring signals and tension monitoring signals of the cable braiding machine when it is working; A first analysis module is used to analyze the fluctuation of the vibration monitoring signal caused by gear wear at different gear speeds to obtain the abnormal degree of gear vibration of the cable braiding machine; The second analysis module is used to analyze the time synchronization of the vibration monitoring signal and the tension monitoring signal to obtain the overlap of the mutation position, and to analyze the consistency of the amplitude change of the vibration monitoring signal and the tension monitoring signal to obtain the correlation of the amplitude change; A gear failure rate determination module, used to determine the gear failure rate of the cable braiding machine based on the abnormal degree of gear vibration, the overlap of the mutation position and the correlation of the amplitude change, and determine the fault inspection and repair strategy of the cable braiding machine based on the gear failure rate; The analysis of the time synchronization of the vibration monitoring signal and the tension monitoring signal to obtain the mutation position coincidence includes: According to a preset time, the vibration monitoring signal is divided into a plurality of first sliding windows, and the tension monitoring signal is divided into a plurality of second sliding windows; For each of the first sliding windows, determining the impact point of the vibration monitoring signal by a kurtosis peak value; For each of the second sliding windows, determining a change point corresponding to the maximum change rate in the tension monitoring signal through differential monitoring; Analyze the time synchronization of the impact point and the change point to obtain the overlap of the mutation position; The analysis of the consistency of the amplitude changes of the vibration monitoring signal and the tension monitoring signal to obtain the amplitude change correlation includes: Acquire the first amplitude of each of the first sliding windows corresponding to the vibration monitoring signal at different gear speeds, and the second amplitude of each of the second sliding windows corresponding to the tension monitoring signal at the different gear speeds; A consistency analysis is performed on changes in the first amplitude and the second amplitude to obtain correlation of the amplitude changes.

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