Packaging machine cutter operation state detection method, device, equipment and storage medium

Abstract

The application discloses a kind of packaging machine cutter operating state detection method, device, equipment and storage medium.The target packaging machine applied to the wrapping workshop, by when detecting that the target packaging machine is in operating state, the vibration signal data of cutter to be handled of target packaging machine is acquired;First cutter vibration signal data is filtered based on first filtering processing mode, and first filtered vibration signal data is obtained, second cutter vibration signal data is filtered based on second filtering processing mode, and second filtered vibration signal data is obtained;First filtered vibration signal data and second filtered vibration signal data are respectively subjected to spectrum analysis, and first vibration characteristic parameter and second vibration characteristic parameter are obtained;Based on first vibration characteristic parameter and second vibration characteristic parameter, the target cutter detection result of target packaging machine is determined.The cutter state detection of packaging machine is realized without contact, and the efficiency and accuracy of cutter state detection are improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, apparatus, equipment, and storage medium for detecting the operating status of a packaging machine cutter. Background Technology

[0002] The packaging machine cutter is a core cutting component in the cigarette pack workshop, mainly used for cutting the outer film and label paper of cigarette packs. The operational stability of the packaging machine cutter affects the appearance quality of the cigarette packs and production efficiency.

[0003] Currently, the inspection of cutting blades on packaging machines in cigarette packing workshops mainly relies on manual periodic inspections or machine shutdown for disassembly and inspection. However, in practical applications, the cutting blade speed is usually high, making it difficult to accurately determine whether there are problems with the blade edge and blade shaft through manual observation. In other words, there are problems with low inspection efficiency and inaccurate inspection. On the other hand, the method of stopping the machine for disassembly and inspection not only fails to determine whether there are problems with the cutting blade during the operation of the packaging machine, but also affects the normal production process of cigarette packs. Summary of the Invention

[0004] This invention provides a method, device, equipment, and storage medium for detecting the operating status of a packaging machine cutter, enabling non-contact detection of the cutting status of the packaging machine and improving the efficiency and accuracy of cutting status detection.

[0005] According to one aspect of the present invention, a method for detecting the operating status of a packaging machine cutter is provided, applied to a target packaging machine in a roll packaging workshop, the method comprising: When the target packaging machine is detected to be in operation, the unprocessed cutter vibration signal data of the target packaging machine is acquired; wherein, the unprocessed cutter vibration signal data includes at least: a first cutter vibration signal data corresponding to the root of the cutter blade of the target packaging machine, and a second cutter vibration signal data corresponding to the rotation surface of the cutter shaft of the target packaging machine; The first cutter vibration signal data is filtered using a first filtering method to obtain first filtered vibration signal data, and the second cutter vibration signal data is filtered using a second filtering method to obtain second filtered vibration signal data; wherein, the first filtering method includes at least: notch filtering and smoothing filtering, and the second filtering method includes at least: low-pass filtering, phase correction, and moving average filtering. Spectral analysis is performed on the first filtered vibration signal data and the second filtered vibration signal data respectively to obtain the first vibration characteristic parameter corresponding to the first filtered vibration signal data and the second vibration characteristic parameter corresponding to the second filtered data; Based on the first vibration characteristic parameter and the second vibration characteristic parameter, the target cutter detection result of the target packaging machine is determined.

[0006] According to another aspect of the present invention, a device for detecting the operating status of a packaging machine cutter is provided, which is applied to a target packaging machine in a roll packaging workshop. The device includes: The data acquisition module is used to acquire the unprocessed cutter vibration signal data of the target packaging machine when the target packaging machine is detected to be in operation; wherein the unprocessed cutter vibration signal data includes at least: a first cutter vibration signal data corresponding to the root of the cutter blade of the target packaging machine and a second cutter vibration signal data corresponding to the rotation surface of the cutter shaft of the target packaging machine; The data filtering module is used to filter the first cutter vibration signal data based on a first filtering method to obtain first filtered vibration signal data, and to filter the second cutter vibration signal data based on a second filtering method to obtain second filtered vibration signal data; wherein, the first filtering method includes at least: notch filtering and smoothing filtering, and the second filtering method includes at least: low-pass filtering, phase correction, and moving average filtering. The data spectrum analysis module is used to perform spectrum analysis on the first filtered vibration signal data and the second filtered vibration signal data respectively, to obtain the first vibration characteristic parameter corresponding to the first filtered vibration signal data and the second vibration characteristic parameter corresponding to the second filtered data; The cutter detection result determination module is used to determine the target cutter detection result of the target packaging machine based on the first vibration characteristic parameter and the second vibration characteristic parameter.

[0007] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the packaging machine cutter operating status detection method according to any embodiment of the present invention.

[0008] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the packaging machine cutter operating status detection method according to any embodiment of the present invention.

[0009] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the packaging machine cutter operating status detection method as described in any embodiment of the present invention.

[0010] The technical solution of this invention achieves non-contact acquisition of vibration signal data from the cutter of the target packaging machine by acquiring the vibration signal of the cutter when the target packaging machine is detected to be in operation. The first cutter vibration signal data is filtered according to a first filtering method to obtain first filtered vibration signal data, and the second cutter vibration signal data is filtered according to a second filtering method to obtain second filtered vibration signal data, ensuring the reliability and accuracy of the data. The first and second filtered vibration signal data are processed by frequency domain transformation and spectral analysis using a Fast Fourier Transform algorithm associated with the cutter vibration, respectively, to obtain a first vibration characteristic parameter corresponding to the first filtered vibration signal data and a second vibration characteristic parameter corresponding to the second filtered data. Based on the above, normal rotational vibration, material impact vibration, and resonance anomalies can be effectively distinguished, reducing the fault misjudgment rate and improving the accuracy of vibration signal analysis. The target cutter detection result of the target packaging machine is determined based on the first and second vibration characteristic parameters. This invention solves the problems of low detection efficiency and inaccuracy caused by manual periodic inspection or machine shutdown for disassembly and inspection in the prior art. It realizes non-contact detection of the cutting status of the packaging machine, improves the efficiency and accuracy of cutting status detection, and ensures the normal production process of tobacco.

[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart of a method for detecting the operating status of a packaging machine cutter, provided in an embodiment of the present invention; Figure 2 This is an example diagram of the packaging machine cutter operating status detection system provided in an embodiment of the present invention; Figure 3This is a flowchart of a method for detecting the operating status of a packaging machine cutter, provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of a packaging machine cutter operating status detection device provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of an electronic device that implements the packaging machine cutter operation status detection method according to an embodiment of the present invention. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0015] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0016] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0017] Example 1 Figure 1 This is a flowchart of a method for detecting the operating status of a packaging machine cutter according to Embodiment 1 of the present invention. This embodiment is applicable to detecting the operating status of cutters in target packaging machines in cigarette workshops. The method can be executed by a packaging machine cutter operating status detection device, which can be implemented in hardware and / or software. This device can be configured in electronic devices such as mobile phones, computers, or servers. Figure 1 As shown, the method includes: S110. When the target packaging machine is detected to be in operation, acquire the vibration signal data of the cutter of the target packaging machine to be processed.

[0018] The target packaging machine can be a high-speed packaging machine in a cigarette manufacturing plant. Optionally, the cutter of the target packaging machine can be used to cut and shape the outer film of cigarette packs, label paper, etc. The cutter vibration signal data to be processed includes at least: first cutter vibration signal data corresponding to the root of the cutter blade of the target packaging machine, and second cutter vibration signal data corresponding to the rotation surface of the cutter shaft of the target packaging machine. The root of the cutter blade can be the structural part of the target packaging machine where the cutter blade connects to the cutter holder and provides support. The first cutter vibration signal data can be the vibration signal data of the root of the cutter blade collected during the operation of the target packaging machine. The rotation surface of the cutter shaft can be understood as the spatial curved surface swept by the end of the cutter blade during the rotation of the cutter shaft (i.e., the rotating shaft on which the cutter is mounted). Correspondingly, the second cutter vibration signal data can be the vibration signal data of the cutter shaft collected during the operation of the target packaging machine.

[0019] In this embodiment of the invention, the first cutter vibration signal data includes at least: first vibration velocity data and vibration displacement amplitude data at the root of the blade.

[0020] The first vibration velocity data can be understood as data related to the vibration velocity of the cutter root collected within a preset acquisition time during the operation of the target packaging machine. Optionally, the first vibration velocity data may include: peak value of the cutter vibration velocity, effective value of the cutter vibration velocity, and peak value factor of the cutter vibration velocity. The vibration displacement amplitude of the cutter root (integral accuracy ≤ ±0.1μm) can be used to characterize the physical quantity of the maximum distance the cutter root deviates from its preset equilibrium position during vibration.

[0021] The second cutter vibration signal data includes at least: second vibration velocity data. The second vibration velocity data can be data related to the cutter shaft vibration velocity collected within a preset acquisition time period during the operation of the target packaging machine. Optionally, the second vibration velocity data may include at least: the effective value of the radial vibration velocity of the cutter shaft, the peak value of the radial vibration velocity of the cutter shaft, the effective value of the axial vibration velocity of the cutter shaft, the peak value of the axial vibration velocity of the cutter shaft, the phase difference of the radial vibration velocity of the cutter shaft, and the phase difference of the axial vibration velocity of the cutter shaft. It should be noted that the above-mentioned acquisition of the cutter vibration signal data to be processed is done without pausing the target packaging machine and without contacting the cutter of the target packaging machine.

[0022] Specifically, before collecting and processing the vibration signal data of the cutting blade of the target packaging machine, a corresponding vibration signal acquisition device can be deployed for the target packaging machine. When the target packaging machine is detected to be in operation, the vibration signal acquisition device is controlled to collect data on the vibration signals of the cutting blade and the cutting shaft of the target packaging machine in a non-contact manner at a preset acquisition frequency within a preset acquisition time, obtaining the first cutting blade vibration signal data and the second cutting blade vibration signal data. The first cutting blade vibration signal data and the second cutting blade vibration signal data are used as the cutting blade vibration signal data to be processed.

[0023] For example, see Figure 2 The above processing can be achieved through a packaging machine cutter operation status detection system. This system includes at least: a vibration acquisition module 1, a signal conditioning module 2, a data processing module 3, an early warning module 4, and a power supply module 5. The vibration acquisition module 1 is electrically connected to the signal conditioning module 2, the signal conditioning module 2 is electrically connected to the data processing module 3, and the data processing module 3 is electrically connected to the early warning module 4. The power supply module 5 is electrically connected to the vibration acquisition module 1, the signal conditioning module 2, the data processing module 3, and the early warning module 4. This power supply module includes a 220V to 12V AC transformer, a bridge rectifier circuit, and a voltage regulator chip. It converts 220V industrial AC power into a stable 12V DC voltage, and then converts it to 5V via a preset voltage conversion chip to power the various modules of the system.

[0024] Taking a laser Doppler vibrometer as an example, the vibration signal acquisition device is a laser Doppler vibrometer. The first laser Doppler vibrometer of the vibration acquisition module 1 is used to acquire the vibration signal of the root of the cutting blade of the high-speed packaging machine in the roll packaging workshop to obtain the first cutting blade vibration signal data. The second laser Doppler vibrometer of the vibration acquisition module 1 is used to acquire the vibration signal of the rotating surface of the cutting shaft of the high-speed packaging machine to obtain the second cutting blade vibration signal data.

[0025] S120. The first cutter vibration signal data is filtered based on the first filtering method to obtain the first filtered vibration signal data, and the second cutter vibration signal data is filtered based on the second filtering method to obtain the second filtered vibration signal data.

[0026] The first filtering process includes at least two methods: notch filtering and smoothing filtering. Notch filtering selectively suppresses specific frequency components in the first cutter vibration signal data, eliminating noise interference at specific frequencies. Smoothing filtering suppresses high-frequency components in the first cutter vibration signal while retaining low-frequency information, thereby reducing random noise or detail fluctuations in the first cutter vibration signal data.

[0027] The second filtering method includes at least: low-pass filtering, phase correction, and moving average filtering. Low-pass filtering is used to suppress high-frequency signals in the second cutter vibration signal data. Phase correction is used to eliminate or compensate for phase deviations generated during transmission of the second cutter vibration signal data. Moving average filtering is used to perform an arithmetic average on the second cutter vibration signal data according to a preset sliding window to determine the filtered data.

[0028] Specifically, the first cutting tool vibration signal data is subjected to notch filtering and smoothing filtering sequentially using the first filtering method to obtain the first filtered vibration signal data corresponding to the first cutting tool vibration signal data. Correspondingly, the second cutting tool vibration signal data is subjected to low-pass filtering, phase correction, and moving average filtering sequentially using the second filtering method to obtain the second filtered vibration signal data corresponding to the second cutting tool vibration signal data.

[0029] For example, in conjunction with the above example, the above processing can be performed by signal conditioning module 2 to filter the first cutter vibration signal data and the second cutter vibration signal data. The signal conditioning module includes at least: a differential noise reduction circuit, a programmable gain amplifier, and a high-speed analog-to-digital converter (A / D converter) connected in sequence. The common-mode rejection ratio of the differential noise reduction circuit is not less than 140dB, and the gain of the programmable gain amplifier is adjustable from 1 to 2000 times. By performing notch filtering and smoothing filtering on the first cutter vibration signal data through the above signal conditioning module, the processed digital signal data, i.e., the first filtered vibration signal data, is obtained. Correspondingly, by performing low-pass filtering, phase correction processing, and moving average filtering on the second cutter vibration signal data through the above signal conditioning module, the second filtered vibration signal data is obtained.

[0030] S130. Perform spectrum analysis on the first filtered vibration signal data and the second filtered vibration signal data respectively to obtain the first vibration characteristic parameter corresponding to the first filtered vibration signal data and the second vibration characteristic parameter corresponding to the second filtered data.

[0031] The first vibration characteristic parameter can be the cutting edge vibration characteristic parameter obtained by performing spectral analysis on the first filtered vibration signal data. The first vibration characteristic parameter includes at least: time-domain characteristic parameters and frequency-domain characteristic parameters corresponding to the first filtered vibration signal. Optionally, the first vibration characteristic parameter may include: cutting edge resonance frequency offset data, effective value of cutting edge vibration velocity, vibration waveform kurtosis information, peak fluctuation information of cutting edge vibration velocity, high-frequency amplitude information of cutting edge vibration, peak factor of cutting edge vibration velocity, low-frequency amplitude of cutting edge vibration, pulse amplitude of cutting edge vibration signal, vibration consistency coefficient of variation, amplitude of cutting edge resonance frequency range, vibration consistency information during the cutting cycle, and displacement amplitude of cutting edge vibration signal.

[0032] Accordingly, the second vibration characteristic parameter can be the vibration characteristic parameter obtained by performing spectral analysis on the second filtered vibration signal data. The second vibration characteristic parameter includes at least: time-domain characteristic parameters and frequency-domain characteristic parameters corresponding to the second filtered vibration signal. Optionally, the second vibration characteristic parameter may include: the fundamental frequency amplitude of the tool shaft rotation, the fluctuation information of the fundamental frequency amplitude of the tool shaft rotation, the ratio of the radial fundamental frequency amplitude to the axial fundamental frequency amplitude of the tool shaft, the bearing characteristic frequency amplitude, the effective value of the axial vibration velocity of the tool shaft, the ratio of the bearing characteristic frequency amplitude to the fundamental frequency amplitude, the amplitude of twice the fundamental frequency of the tool shaft rotation, radial and axial vibration related data, the amplitude of three times the fundamental frequency of the tool shaft rotation, the rate of change of the fundamental frequency amplitude of the tool shaft rotation with the rotational speed, the amplitude of the radial vibration displacement of the tool shaft, and the phase difference of the fundamental frequency of the tool shaft rotation at different rotational speeds.

[0033] Specifically, the first filtered vibration signal data is processed by a Fast Fourier Transform algorithm associated with the cutter vibration, and the converted first filtered vibration signal data is subjected to spectral analysis to extract frequency domain characteristic parameters such as the first vibration frequency data corresponding to the root of the cutter blade and the vibration consistency variation coefficient. The first vibration frequency data can be data related to the vibration frequency of the cutter blade root collected within a preset acquisition time during the operation of the target packaging machine. Optionally, the first vibration frequency data may include: vibration frequency spectrum information (e.g., 20Hz to 45kHz), resonant frequency, and vibration frequency amplitude variation information. Optionally, the relative dispersion of the vibration signal can be quantified by calculating the ratio (CV) of the standard deviation to the mean of the blade root vibration displacement or blade root vibration amplitude data; the obtained quantized value is the vibration consistency variation coefficient (optionally, the vibration consistency variation coefficient ≤ 5%).

[0034] Determine the time-domain characteristic parameters corresponding to the first filtered vibration signal data. Use the time-domain and frequency-domain characteristic parameters corresponding to the first filtered vibration signal data as the first vibration characteristic parameters.

[0035] Accordingly, the second filtered vibration signal data is processed by Fast Fourier Transform (FFT), and the converted second filtered vibration signal data is subjected to spectral analysis to obtain the frequency domain characteristic parameters corresponding to the second filtered vibration signal data. Optionally, the frequency domain characteristic parameters corresponding to the second filtered vibration signal data may include at least: the second rotational fundamental frequency data, the bearing characteristic frequency amplitude, and relevant data of the cutter shaft vibration and the cutting tool vibration. Among them, the second rotational fundamental frequency data is related to the rotational speed of the cutting tool shaft. Optionally, the second rotational fundamental frequency data may include at least: the cutting tool shaft rotational fundamental frequency, the cutting tool shaft harmonic amplitude (e.g., 2x or 3x), rotational stability information, etc. The bearing characteristic frequency amplitude can be used to characterize the vibration intensity of the bearings (inner ring, outer ring, rolling elements) of the cutting tool shaft at a preset fault characteristic frequency.

[0036] Determine the time-domain characteristic parameters corresponding to the second filtered vibration signal data. Use the time-domain and frequency-domain characteristic parameters corresponding to the second filtered vibration signal data as the second vibration characteristic parameters.

[0037] For example, in conjunction with the above example, the spectrum analysis described above can be implemented through a data processing module. The data processing module integrates a microprocessor, which employs a chip with high-performance floating-point computing capabilities, enabling rapid Fast Fourier Transform (FFT) spectrum analysis. The microprocessor deploys a resonant frequency analysis algorithm adapted to the cutting blade of a high-speed packaging machine, used to perform signal transformation on the first and second filtered vibration signal data using Fast Fourier Transform (FFT) to convert the time-domain signal data into frequency-domain signal data. It also performs feature extraction processing on the transformed first and second filtered vibration signal data respectively, obtaining frequency-domain feature parameters corresponding to the first and second filtered vibration signal data. Finally, it determines the time-domain feature parameters corresponding to the first and second filtered vibration signal data.

[0038] It should be noted that, to improve the accuracy of subsequent fault diagnosis, the operating status parameters of the target packaging machine's blade can be collected. The time-domain characteristic parameters, frequency-domain characteristic parameters, and operating status parameters corresponding to the first filtered vibration signal data can be used as the first vibration characteristic parameters. Similarly, the operating status parameters of the target packaging machine's cutter shaft can be collected, and the time-domain characteristic parameters, frequency-domain characteristic parameters, and operating status parameters corresponding to the second filtered vibration signal data can be used as the second vibration characteristic parameters. Based on the above, fault detection can be performed using data from three dimensions: time domain, frequency domain, and operating status, thus improving the accuracy of fault detection.

[0039] It should also be noted that the data processing module can communicate with the encrypted storage unit to associate and store the first and second vibration characteristic parameters obtained by the data processing module, as well as information such as the production shift, cigarette pack specifications, and collection time corresponding to the target packaging machine, into the encrypted storage unit. The encrypted storage unit has a storage capacity of no less than 16GB and supports interface with the Manufacturing Execution System (MES) and quality traceability system in the cigarette pack workshop via Ethernet. This facilitates subsequent tracing of the cutting blade status during the cutting of a specific batch of cigarette packs, providing a basis for quality problem analysis.

[0040] S140. Based on the first vibration characteristic parameter and the second vibration characteristic parameter, determine the target cutter detection result of the target packaging machine.

[0041] The target cutter detection results may include: the fault detection results of the cutter blade of the target packaging machine and the fault detection results of the cutter shaft of the target packaging machine.

[0042] Specifically, based on the first vibration characteristic parameter and the first preset parameter threshold corresponding to the first vibration characteristic parameter, fault detection processing is performed on the cutting edge of the target packaging machine to obtain the fault detection result corresponding to the cutting edge. Correspondingly, based on the second vibration characteristic parameter and the second preset parameter threshold corresponding to the second vibration characteristic parameter, fault detection is performed on the cutting shaft of the target packaging machine to obtain the fault detection result corresponding to the cutting shaft. Based on the fault detection results corresponding to the cutting edge and the cutting shaft, the target cutting result of the target packaging machine is obtained.

[0043] In this embodiment of the invention, the method for determining the target cutter detection result based on the first vibration characteristic parameter and the second vibration characteristic parameter may be as follows: based on the first vibration characteristic parameter and a first preset parameter threshold corresponding to at least one preset blade fault type, determine at least one target blade fault type and blade fault cause information corresponding to each target blade fault type; based on the second vibration characteristic parameter and a second preset parameter threshold corresponding to at least one preset blade shaft fault type, determine at least one target blade shaft fault type and blade shaft fault cause information corresponding to each target blade shaft fault type; and determine the target cutter detection result based on at least one target blade fault type, blade fault cause information corresponding to each target blade fault type, at least one target blade shaft fault type, and blade shaft fault cause information corresponding to each target blade shaft fault type.

[0044] The at least one preset cutting edge fault type may include one or more of the following: cutting edge fatigue fault type, cutting edge wear fault type, cutting edge installation fault type, and cutting edge abnormality fault type. It should be noted that the first vibration characteristic parameter corresponding to different preset cutting edge fault types is different. That is, the parameter information corresponding to the preset cutting edge fault type in the first vibration characteristic parameter is compared with a first preset parameter threshold. The first preset parameter threshold can be a pre-set standard value for the parameter information corresponding to the preset cutting edge fault type. The target cutting edge fault type can be a cutting edge fault type determined from at least one preset cutting edge fault type. It should also be noted that there can be one or more target cutting edge fault types. The cutting edge fault cause information can be the fault cause determined by analysis based on the first vibration characteristic parameter corresponding to the target cutting edge fault type.

[0045] At least one preset toolshaft fault type may include: shaft imbalance fault type, bearing wear fault type, coupling misalignment fault type, and toolshaft deformation fault type. It should be noted that the second vibration characteristic parameter corresponding to different preset toolshaft fault types is different. That is, the second vibration characteristic parameter is compared with the parameter information corresponding to the preset toolshaft fault type and the second preset parameter threshold. The second preset parameter threshold can be a pre-set standard value for the parameter information corresponding to the preset toolshaft fault type. The target toolshaft fault type can be a toolshaft fault type determined from at least one preset toolshaft fault type. It should also be noted that there can be one or more target toolshaft fault types. The toolshaft fault cause information can be the fault cause determined by analysis based on the second vibration characteristic parameter corresponding to the target toolshaft fault type.

[0046] Specifically, for the first vibration characteristic parameter, if the blade resonance frequency offset data in the first vibration characteristic parameter is greater than a preset blade shaft resonance frequency offset threshold, and / or the effective value of the blade vibration velocity in the first vibration characteristic parameter is greater than a threshold for the effective value of the blade vibration velocity, and / or the vibration waveform kurtosis information in the first vibration characteristic parameter is greater than a preset waveform kurtosis threshold, then the target blade fault type is determined to be a blade fatigue fault type. The causes of blade fatigue faults are analyzed based on the blade resonance frequency offset data, the effective value of the blade vibration velocity, and the vibration waveform kurtosis information, thus obtaining the blade fault cause information. And / or, If the peak fluctuation information of the blade vibration velocity in the first vibration characteristic parameter is greater than a preset peak fluctuation threshold, and / or the high-frequency amplitude information of the blade vibration in the first vibration characteristic parameter is greater than a preset high-frequency amplitude threshold, and / or the peak factor of the blade vibration velocity in the first vibration characteristic parameter is greater than a preset peak factor threshold, then the target blade fault type is determined to be a blade wear fault type. Based on the peak fluctuation information of the blade vibration velocity, the high-frequency amplitude information of the blade vibration, and the peak factor of the blade vibration velocity, the causes of blade wear faults are analyzed to obtain the blade fault cause information for the blade wear fault type. And / or, If the low-frequency amplitude of the blade vibration in the first vibration characteristic parameter is greater than a preset low-frequency amplitude threshold, and / or the pulse amplitude of the blade vibration signal in the first vibration characteristic parameter is greater than a preset pulse amplitude threshold, and / or the coefficient of variation of vibration consistency in the first vibration characteristic parameter is greater than a preset coefficient of variation threshold, then the target blade fault type is determined to be a blade installation fault type. The causes of the blade installation fault are analyzed based on the low-frequency amplitude of the blade vibration, the pulse amplitude of the blade vibration signal, and the coefficient of variation of vibration consistency, yielding blade fault cause information corresponding to the blade installation fault type. And / or, If the amplitude of the blade resonant frequency range in the first vibration characteristic parameter is greater than a preset resonance frequency range amplitude threshold, and / or the vibration consistency information of the cutting cycle in the first vibration characteristic parameter is greater than a preset vibration consistency information threshold, and / or the displacement amplitude of the blade vibration signal in the first vibration characteristic parameter is greater than a preset vibration signal displacement amplitude threshold, the target blade fault type is determined to be a blade cutting parameter abnormality fault type. Based on the blade resonant frequency range amplitude, the vibration consistency information of the cutting cycle, and the displacement amplitude of the blade vibration signal, the causes of the abnormal cutting parameters are analyzed to obtain blade fault cause information corresponding to the blade cutting parameter abnormality fault type.

[0047] For the second vibration characteristic parameter, if the fundamental frequency amplitude of the tool shaft rotation in the second vibration characteristic parameter is greater than a preset threshold value, and / or the fluctuation information of the fundamental frequency amplitude of the tool shaft rotation in the second vibration characteristic parameter is greater than a preset threshold value, and / or the ratio of the radial fundamental frequency amplitude to the axial fundamental frequency amplitude of the tool shaft in the second vibration characteristic parameter is greater than a preset first value, then the target tool shaft fault type is determined to be a shaft imbalance fault type. And / or, If the bearing characteristic frequency amplitude in the second vibration characteristic parameter is greater than the preset characteristic frequency amplitude threshold, and / or the effective value of the tool shaft axial vibration velocity in the second vibration characteristic parameter is greater than the preset axial vibration velocity threshold, and / or the ratio of the bearing characteristic frequency amplitude to the fundamental frequency amplitude is greater than the preset second value, then the target tool shaft fault type is determined to be a bearing wear fault type. And / or If the amplitude of the cutter shaft's 2x rotational fundamental frequency in the second vibration characteristic parameter is greater than a preset threshold of 2x rotational fundamental frequency amplitude, and / or the radial and axial vibration correlation data in the second vibration characteristic parameter is greater than a preset correlation threshold, and / or the amplitude of the cutter shaft's 3x rotational fundamental frequency in the second vibration characteristic parameter is greater than a preset threshold of 3x rotational fundamental frequency amplitude, then the target cutter shaft fault type is determined to be a coupling misalignment fault type. And / or, If the rate of change of the fundamental frequency amplitude of the tool shaft rotation with the rotation speed in the second vibration characteristic parameter is greater than the preset amplitude change rate threshold, and / or the radial vibration displacement amplitude of the tool shaft in the second vibration characteristic parameter is greater than the preset vibration displacement amplitude threshold, and / or the phase difference of the fundamental frequency of the tool shaft rotation at different rotation speeds in the second vibration characteristic parameter is greater than the corresponding preset fundamental frequency phase difference threshold, then the target tool shaft fault type is determined to be the tool shaft deformation fault type.

[0048] After determining at least one target toolshaft fault type, the causes of the toolshaft fault are analyzed based on the second vibration characteristic parameters corresponding to each target toolshaft fault type, and toolshaft fault cause information corresponding to each target toolshaft fault type is obtained.

[0049] The target cutting tool detection result includes at least one target cutting edge fault type, the cutting edge fault cause information corresponding to each target cutting edge fault type, at least one target cutting axis fault type, and the cutting axis fault cause information corresponding to each target cutting axis fault type.

[0050] For example, in conjunction with the above example, after determining the corresponding first vibration characteristic parameter and second vibration characteristic parameter, the data processing module compares the first vibration characteristic parameter with a first preset parameter threshold corresponding to at least one preset blade fault type to determine at least one target blade fault type and the corresponding blade fault cause information. That is, If the blade resonant frequency offset Δf is greater than ±2%, and / or the effective value of the blade vibration velocity is greater than 0.12 m / s, and / or the kurtosis of the vibration waveform is greater than 1.5, then the target packaging machine is determined to have blade fatigue failure. Based on the blade resonant frequency offset, the effective value of the blade vibration velocity, and the vibration waveform kurtosis, the possible causes of blade fatigue failure are: microcracks in the blade, leading to decreased stiffness and resonant frequency drift; uneven cutting force amplifies vibration, enhancing impact characteristics. And / or, If the peak fluctuation of the blade vibration velocity is greater than 12%, and / or the high-frequency (30 to 45 kHz) amplitude of the blade vibration is greater than 0.06 m / s, and / or the peak factor of the blade vibration velocity is greater than 3.8, then the target packaging machine is determined to have a blade wear fault. Based on the peak fluctuation of the blade vibration velocity, the high-frequency amplitude of the blade vibration, and the peak factor of the blade vibration velocity, the possible causes of the blade wear fault are: dulling of the blade, increased cutting impact, increased high-frequency vibration components; irregular cutting edge leading to aggravated cutting force fluctuations. And / or, If the low-frequency (20 to 50 Hz) amplitude of the blade vibration is greater than 0.04 m / s, and / or the time-domain waveform exhibits periodic impact pulses, and the blade vibration signal pulse amplitude is greater than 0.3, and / or the vibration consistency coefficient of variation is greater than 8%, then the target packaging machine is determined to have a loose blade installation. Based on the low-frequency amplitude of the blade vibration, the blade vibration signal pulse amplitude, and the vibration consistency coefficient of variation, the possible causes of loose blade installation are: loose fastening bolts or aging gaskets, resulting in gap impacts during cutting; and uneven vibration transmission due to loose mounting surfaces. And / or, If the amplitude of the blade resonance frequency range (±1%) is greater than 0.08 m / s, and / or the coefficient of variation corresponding to the vibration consistency of the cutting cycle is greater than 6%, and / or the displacement amplitude of the blade vibration signal is greater than 2 μm, it is determined that the target packaging machine has an abnormal blade cutting parameter fault. Based on the amplitude of the blade resonance frequency range, the vibration consistency information of the cutting cycle, and the displacement amplitude of the blade vibration signal, the cause of the abnormal cutting parameters may be poor matching between the cutting speed, feed rate, and the cutter's natural frequency, causing resonance; or uneven material hardness leading to fluctuations in cutting load.

[0051] Accordingly, the second vibration characteristic parameter is compared with a second preset parameter threshold corresponding to at least one preset toolshaft fault type to determine at least one target toolshaft fault type and the corresponding toolshaft fault cause information. That is, If the fundamental frequency amplitude of the cutter shaft rotation is greater than 0.07 m / s, and / or the fluctuation of the fundamental frequency amplitude of the cutter shaft rotation corresponding to three consecutive data acquisitions is greater than 8%, and / or the ratio of the radial fundamental frequency amplitude of the cutter shaft to the axial fundamental frequency amplitude of the cutter shaft is greater than 1.5, then the target packaging machine is determined to have a shaft imbalance fault. Correspondingly, the cause of the cutter shaft fault may be: decreased dynamic balance accuracy of the cutter shaft (exceeding G2.5 grade), radial vibration caused by rotational centrifugal force; uneven mass distribution of the cutter disc exacerbating the imbalance. And / or, If the bearing characteristic frequency amplitude is greater than 0.05 m / s, and / or the effective value of the cutter shaft axial vibration velocity is greater than 0.04 m / s, and / or the ratio of the bearing characteristic frequency amplitude to the fundamental frequency amplitude is greater than 0.6, the target packaging machine is determined to have a bearing wear fault. Correspondingly, the cause of the cutter shaft fault may be wear of the bearing balls or raceways, or poor lubrication, resulting in periodic vibration; increased bearing clearance leading to intensified axial movement. And / or, If the amplitude of the cutter shaft's second-times-rotational-fundamental frequency is greater than 0.03 m / s, and / or the radial and axial vibration correlation data is greater than 0.7, and / or the amplitude of the cutter shaft's third-times-rotational-fundamental-frequency frequency is greater than 0.02 m / s, it is determined that the coupling of the cutter shaft of the target packaging machine is misaligned. Correspondingly, the possible causes of the cutter shaft failure are: coupling coaxiality deviation (exceeding 0.02 mm), generating alternating loads during rotation, exciting double-frequency vibrations; aging of the coupling elastomer leading to decreased alignment accuracy. And / or, If the rate of change of the fundamental frequency amplitude of the cutter shaft rotation with respect to rotational speed is greater than 0.005 m / s·(r / min) -1 If the radial vibration displacement amplitude of the cutter shaft is greater than 1.5 μm, and / or the phase difference of the fundamental frequency of the cutter shaft rotation at different speeds in the second vibration characteristic parameter is greater than 15°, then the cutter shaft of the target packaging machine is determined to be deformed. Correspondingly, the cause of the cutter shaft failure may be: thermal deformation due to long-term high-speed operation of the cutter shaft, or permanent deformation caused by impact loads; uneven shaft support stiffness exacerbating the deformation effect.

[0052] It should be noted that the first and second preset parameter thresholds can be baseline data determined based on five sets of continuously collected stable operating data after the target packaging machine's first run or after replacing the cutter or bearing. To better suit practical applications, a first preset parameter range (first preset parameter threshold ± 3 standard deviations) and a second preset parameter range (second preset parameter threshold ± 3 standard deviations) corresponding to the second preset parameter threshold can be set to dynamically calibrate the corresponding feature parameters.

[0053] Optionally, embodiments of the present invention further include: determining and processing a blade warning message based on at least one target blade fault type, blade fault cause information corresponding to each target blade fault type, a first vibration characteristic parameter, and a first preset parameter threshold corresponding to each target blade fault type; and determining and processing a tool shaft warning message based on at least one target tool shaft fault type, tool shaft fault cause information corresponding to each target tool shaft fault type, a second vibration characteristic parameter, and a second preset parameter threshold corresponding to the target tool shaft fault type.

[0054] The blade warning message can be used to alert relevant personnel to adjust the blade of the target packaging machine. The cutter shaft warning message can also be used to alert relevant personnel to adjust the cutter shaft of the target packaging machine.

[0055] Specifically, after determining the target blade fault type and the corresponding cause information, the blade warning level information is determined based on the first vibration characteristic parameter and the corresponding first preset parameter threshold. Then, based on the blade warning level information, the target blade fault type, and the corresponding cause information, a blade warning prompt is generated, and a warning is issued accordingly. This prompts the implementation of corresponding handling measures to adjust or maintain the target packaging machine.

[0056] Accordingly, after determining the target cutter shaft fault type and the corresponding cause information, the cutter shaft warning level information is determined based on the second vibration characteristic parameter and the corresponding second preset parameter threshold. Then, based on the cutter shaft warning level information, the target cutter shaft fault type, and the corresponding cause information, a cutter shaft warning message is generated, and a warning is issued accordingly. This prompts the implementation of corresponding adjustment or maintenance measures for the target packaging machine.

[0057] It should also be noted that adjustments or maintenance can be performed on the target packaging machine during material change intervals to avoid affecting the normal tobacco production process. Additionally, the oil-proof, dust-proof, and light-transmitting cover of the laser acquisition end should be cleaned at the end of each shift to ensure acquisition accuracy.

[0058] Optionally, the blade warning level information can be determined based on the first vibration characteristic parameter and the corresponding first preset parameter threshold. For example, when the first vibration characteristic parameter reaches 80% of the first preset parameter threshold, the blade warning level information is determined to be the first blade warning level. Correspondingly, the blade warning prompt information may include: prompting close monitoring to shorten the acquisition interval between two adjacent acquisitions of the cutter vibration signal data to be processed. For example, acquiring the cutter vibration signal data to be processed every 10 minutes. If the first vibration characteristic parameter determined by two adjacent data acquisitions is consistent with the first preset parameter threshold, the blade warning level information is determined to be the second blade warning level. Correspondingly, the blade warning prompt information may include: controlling the target packaging machine to stop operation and perform inspection. When the first vibration characteristic parameter reaches 120% of the first preset parameter threshold, the blade warning level information is determined to be the third blade warning level. Correspondingly, the blade warning prompt information may include: immediately controlling the target packaging machine to stop operation and performing equipment maintenance.

[0059] Optionally, the tool axis warning level information can be determined based on the second vibration characteristic parameter and the corresponding second preset parameter threshold. For example, when the second vibration characteristic parameter reaches 80% of the second preset parameter threshold, the tool axis warning level information is determined to be the first tool axis warning level. If the second vibration characteristic parameter determined by two consecutive data acquisitions is consistent with the second preset parameter threshold, the tool axis warning level information is determined to be the second tool axis warning level. When the second vibration characteristic parameter reaches 120% of the second preset parameter threshold, the tool axis warning level information is determined to be the third tool axis warning level.

[0060] For example, referring to the examples above, see [link to previous section]. Figure 2 The early warning module includes a graded explosion-proof audible and visual alarm and an industrial Ethernet unit, which can simultaneously send abnormal data and early warning information to the central control system of the packaging workshop, the main control system of the high-speed packaging machine, the computer monitoring terminal and mobile terminal. In case of serious abnormality, it can trigger the packaging machine to slow down.

[0061] When issuing warnings based on early warning information, the corresponding audible and visual warning method can be determined according to the warning level. For example, for the first blade warning level or the first cutter shaft warning level, a green flashing light and a low-frequency warning sound can be used. For the second blade warning level or the second cutter shaft warning level, a yellow flashing light and an intermittent buzzer can be used. For the third blade warning level or the third cutter shaft warning level, the target packaging machine can be slowed down by 50%. Through graded warnings, the downtime of the target packaging machine's cutter can be reduced, and the running time of the target packaging machine can be increased, ensuring the output of cigarette packs produced.

[0062] It should also be noted that, in order to improve the accuracy of operational status detection, the laser Doppler vibration meter (vibration signal acquisition device) can be calibrated every quarter to focus on measurement accuracy, frequency response characteristics and anti-interference ability; the first preset parameter threshold and the second preset parameter threshold can also be adjusted every six months in combination with information such as the operating years and maintenance records of the target packaging machine to adapt to the characteristics of the target packaging machine gradually aging over time.

[0063] The technical solution of this embodiment achieves non-contact acquisition of vibration signal data from the cutter of the target packaging machine by acquiring the vibration signal of the cutter when the target packaging machine is detected to be in operation. The first cutter vibration signal data is filtered according to a first filtering method to obtain first filtered vibration signal data, and the second cutter vibration signal data is filtered according to a second filtering method to obtain second filtered vibration signal data, ensuring the reliability and accuracy of the data. The first and second filtered vibration signal data are processed by frequency domain transformation and spectral analysis using a Fast Fourier Transform algorithm associated with the cutter vibration, respectively, to obtain a first vibration characteristic parameter corresponding to the first filtered vibration signal data and a second vibration characteristic parameter corresponding to the second filtered data. Based on the above, normal rotational vibration, material impact vibration, and resonance anomalies can be effectively distinguished, reducing the fault misjudgment rate and improving the accuracy of vibration signal analysis. The target cutter detection result of the target packaging machine is determined based on the first and second vibration characteristic parameters. This invention solves the problems of low detection efficiency and inaccuracy caused by manual periodic inspection or machine shutdown for disassembly and inspection in the prior art. It realizes non-contact detection of the cutting status of the packaging machine, improves the efficiency and accuracy of cutting status detection, and ensures the normal production process of tobacco.

[0064] Example 2 Figure 3 This is a flowchart of a method for detecting the operating status of a packaging machine cutter according to Embodiment 2 of the present invention. This embodiment is a preferred embodiment of the above embodiments. For specific implementation details, please refer to the technical solution of this embodiment. Technical terms that are the same as or corresponding to those in the above embodiments will not be repeated here. Figure 3 As shown, the method includes: S210. When it is detected that at least one first vibration signal acquisition device deployed at the first preset position of the target packaging machine meets the first relative position condition with the root of the cutter blade, the first cutter vibration signal data corresponding to the root of the cutter blade within a preset time period is acquired.

[0065] The first preset position can be a pre-defined location for deploying the first vibration signal acquisition device. Optionally, the first preset position can be the side of the cutter head of the target packaging machine. Accordingly, the first vibration signal acquisition device can be deployed on the side of the cutter head using a three-dimensional adjustable bracket. The first vibration signal acquisition device can be used to collect vibration signal data of the first cutter corresponding to the root of the cutter blade. Optionally, the first vibration signal acquisition device can be a laser Doppler vibrometer.

[0066] The first relative position condition is as follows: the laser emitting end of the first vibration signal acquisition device is directly opposite the first force-bearing area at the root of the cutter blade, and the first relative angle between the laser emitting end and the measured area at the root of the cutter blade is less than a preset angle threshold. The laser emitting end is used to send a laser beam to the root of the cutter blade. This can be understood as the first vibration signal acquisition device sending a laser beam to the root of the cutter blade and determining the first cutter vibration signal data based on the received reflected signal corresponding to the laser beam.

[0067] The first stress-bearing area can be the non-cutting stress area at the root of the cutter blade. The measured area can be a pre-set measured surface or measured position at the root of the cutter blade. The first relative angle can be the angle between the laser emitted by the laser emitter and the measured area at the root of the cutter blade. It should also be noted that, to improve the stability of signal data acquisition, the first relative angle can be made as small as possible. The preset angle threshold can be a pre-set standard angle value corresponding to the first relative angle. For example, the preset angle threshold can be 10 degrees.

[0068] The preset duration, or preset acquisition duration, can be understood as the length of time corresponding to the acquisition of the first cutter vibration signal data. Optionally, for the acquisition of the first cutter vibration signal data, a single continuous acquisition can be ≥15s (covering ≥50 cutting cycles), with one set of data acquired every 20 minutes, for a continuous acquisition of 4 hours. That is, the cutter vibration signal data acquired in these four hours will be used as the first cutter vibration signal data. It should also be noted that for each acquisition, it can be triggered synchronously with the cutting trigger signal after the target packaging machine is detected to be running stably (speed fluctuation ≤±1%), and the cutter vibration signal data corresponding to each cut can be recorded.

[0069] Specifically, for at least one first vibration signal acquisition device deployed at a first preset position on the target packaging machine, when the laser emitting end of each first vibration signal acquisition device is directly facing the first force-bearing area at the root of the cutter blade, and the first relative angle between the laser emitting end and the measured area at the root of the cutter blade is less than a preset angle threshold, it is determined that the first vibration signal acquisition device and the root of the cutter blade meet the first relative position condition. Within a preset time period, the first vibration signal acquisition device sends a laser beam to the measured area at the root of the cutter blade of the target packaging machine, and based on the reflected signal corresponding to the laser beam, the first cutter vibration signal data corresponding to the root of the cutter blade is determined.

[0070] For example, referring to the examples above, see [link to previous section]. Figure 2 The vibration acquisition module is used for non-contact acquisition of cutter vibration signal data from a high-speed packaging machine (corresponding to the target packaging machine mentioned above). The vibration acquisition module includes at least two laser Doppler vibrometers.

[0071] Among them, for the laser Doppler vibrator that collects the vibration signal data of the first cutter, the laser Doppler vibrator is fixed to the side of the cutter disc by a three-dimensional adjustable bracket (the distance between the laser emitting end and the root of the blade is 30-50mm, avoiding the cutting area). The laser emitting end is facing the non-cutting force area at the root of the blade, and the angle between it and the measured surface is ≤10° (reducing the angle improves the signal stability).

[0072] This laser Doppler vibration meter uses a 633nm laser wavelength (He-Ne laser, balancing penetration and reflectivity) and a preset measurement range (±1.5m / s, adaptable to the minute vibration range of precision cutting tools, improving measurement resolution), preset frequency band (20Hz to 45kHz, eliminating low-frequency invalid interference, focusing on the cutting impact and resonance frequency band of the cutting tool), and preset sampling rate (≥250kHz, improving the ability to capture high-frequency vibration details, meeting the requirements of instantaneous impact monitoring in precision cutting). It sends a laser beam to the root of the cutting edge of the target packaging machine and receives the reflected signal corresponding to the laser beam. The first cutting tool vibration signal data is determined based on the reflected signal.

[0073] It should be noted that, to improve the accuracy of the collected first cutter vibration signal data, a high-precision focusing lens (focal length 150-200mm) can be installed at another preset position on the target packaging machine to reduce the laser spot size to ≤0.08mm (precisely locating the tiny area at the root of the blade). An ultra-thin, high-reflectivity target (thickness ≤0.1mm, to avoid affecting cutting balance and vibration characteristics) should be attached to the root of the blade. A sealed, oil-proof, dust-proof, and transparent cover should be added to the monitoring end of the laser Doppler vibration meter to prevent lubricating oil mist and packaging dust from affecting laser transmission. The three-dimensional adjustable bracket uses a double-layer shock-absorbing structure (rubber shock-absorbing pads + spring damping) to attenuate the transmission of vibrations from the equipment itself. The three-dimensional adjustable bracket has an adjustment range of 0-360°, adaptable to the installation space of cutters on different models of high-speed packaging machines. The bracket is fixed to the packaging machine frame with high-strength bolts to ensure the laser emitter remains stable and without displacement during data acquisition. A purging device (low-pressure dry air, flow rate 5-8L / min) should also be added to prevent dust adhesion.

[0074] It should also be noted that the collected first cutter vibration signal data can be stored in the corresponding database in the format of binary raw data (sampling point interval ≤ 4μs) + CSV statistical results, and the data such as collection time, target packaging machine speed, cutting load, and ambient temperature and humidity (accuracy ±0.5℃ / ±5%RH) should be marked.

[0075] S220. When it is detected that at least one second vibration signal acquisition device deployed at the second preset position of the target packaging machine meets the second relative position condition with the blade shaft rotation surface, the second cutting blade vibration signal data corresponding to the blade shaft rotation surface within a preset time period is acquired.

[0076] The second preset position can be a pre-defined location for deploying the second vibration signal acquisition device. Optionally, the second preset position can be the side of the cutter shaft end of the target packaging machine. Accordingly, the second vibration signal acquisition device can be fixed to the side of the cutter shaft end using a three-dimensional adjustable bracket. The second vibration signal acquisition device is used to acquire vibration signal data from the second cutter. Optionally, the second vibration signal acquisition device can be the same as the first vibration signal acquisition device, i.e., it can be a laser Doppler vibrometer.

[0077] The second relative position condition is as follows: the laser emitting end of the second vibration signal acquisition device is directly facing the first region of the blade shaft rotation surface, and the second relative angle between the laser emitting end and the rotational tangent direction of the blade shaft rotation surface is less than a preset angle threshold. The first region can be a pre-set smooth region of the blade shaft rotation surface of the target packaging machine. The rotational tangent direction can be used to characterize the instantaneous direction of a point on the blade shaft rotation surface during the rotation of the blade shaft. The second relative angle can be understood as the angle between the laser beam emitted by the laser emitting end and the rotational tangent direction. The preset duration can be understood as the data acquisition duration for acquiring the second blade vibration signal data. Optionally, for acquiring the second blade vibration signal data, a single continuous acquisition of ≥8s (covering ≥30 rotation cycles) can be performed, with one set of data acquired every 40 minutes, for a total of 4 hours. That is, the blade vibration signal data acquired in these 4 hours is used as the second blade vibration signal data. It should also be noted that for each acquisition, after the target packaging machine is running stably, one set of data can be acquired every one rotation using the blade shaft key phase pulse as the synchronization signal to ensure phase consistency.

[0078] Specifically, for at least one second vibration signal acquisition device deployed at the second preset position of the target packaging machine, when it is detected that the laser emitting end of each second vibration signal acquisition device is facing the first region of the blade shaft rotation surface and the second relative angle between the laser emitting end and the rotation tangent direction of the blade shaft rotation surface is less than a preset angle threshold, it is determined that the second vibration signal acquisition device and the blade shaft rotation surface meet the second relative position condition. Then, within a preset time period, the second cutting blade vibration signal data corresponding to the blade shaft rotation surface is acquired by the second vibration signal acquisition device.

[0079] For example, in conjunction with the above example, for the laser Doppler vibrometer that collects vibration signal data of the second cutter, a three-dimensional adjustable bracket can be used to fix the laser Doppler vibrometer to the side of the cutter spindle end, with the laser emitting end facing the smooth area of ​​the cutter spindle rotation surface, the angle between the laser emitting end and the rotation tangent direction being ≤10°, and the distance from the rotation surface being 50-80mm (optimized distance measurement to ensure signal strength).

[0080] This laser Doppler vibration meter uses a 633nm laser wavelength and a preset measurement range (±0.8m / s, matching the low amplitude characteristics of the precision cutter shaft and avoiding range redundancy), a preset frequency band (15Hz to 18kHz, accurately covering the cutter shaft's fundamental frequency, harmonics, and bearing characteristic frequencies), and a preset sampling rate (≥150kHz, improving the sampling accuracy of minute vibration signals in the shaft system). It sends a laser beam to the rotating surface of the cutter shaft of the target packaging machine and receives the reflected signal corresponding to the laser beam. The vibration signal data of the second cutter is determined based on the reflected signal.

[0081] It should be noted that, to improve the accuracy of the collected second cutter vibration signal data, a high-precision focusing lens (focal length 250-300mm) can be installed at another preset position on the target packaging machine to reduce the laser spot size to ≤0.15mm (improving the accuracy of capturing minute vibrations on the rotating surface); the cutting shaft rotating surface is cleaned with anhydrous ethanol to remove oil and oxide layers, ensuring uniform and stable reflected signals. Additionally, the laser path is protected by a metal sleeve to avoid airflow and material transport paths; a dual-stage filtering heterodyne LDV scheme is used to suppress 50Hz power frequency and harmonic interference; and the three-dimensional adjustable bracket can be fixed to an independent foundation to avoid vibration transmission caused by a rigid connection with the high-speed packaging machine frame.

[0082] It should also be noted that the collected vibration signal data of the second cutter can be stored in the corresponding database in the format of binary raw data (sampling point interval ≤ 6.7μs) + CSV statistical results, and the acquisition time, cutter shaft speed, radial / axial direction, bearing temperature and other information should be marked.

[0083] S230. The first cutter vibration signal data is filtered based on the first filtering method to obtain the first filtered vibration signal data, and the second cutter vibration signal data is filtered based on the second filtering method to obtain the second filtered vibration signal data.

[0084] The first filtering method includes at least notch filtering and smoothing filtering, and the second filtering method includes at least low-pass filtering, phase correction, and moving average filtering.

[0085] Optionally, the method for processing the first cutter vibration signal data according to the first filtering method may be as follows: The first cutter vibration signal data is denoised using a preset differential denoising circuit to obtain denoised vibration signal data; the denoised vibration signal data is then subjected to signal amplitude adjustment to obtain adjusted vibration signal data; the adjusted vibration signal data is then subjected to notch filtering based on a preset notch frequency and preset attenuation information to obtain notch-filtered vibration signal data; and the notch-filtered vibration signal data is then subjected to smoothing filtering, outlier removal, and data normalization in sequence to obtain the first filtered vibration signal data.

[0086] The preset differential noise reduction circuit is used to denoise the first cutter vibration signal data to filter out high-frequency interference signals generated by the motor group and conveying components of the target packaging machine. Accordingly, the first cutter vibration signal data after filtering out high-frequency interference signals is the noise-reduced vibration signal data.

[0087] Signal amplitude adjustment processing can be understood as adjusting the gain of the denoised vibration signal data to bring the signal amplitude within a preset range. Correspondingly, the denoised vibration signal data after signal amplitude adjustment processing is the adjusted vibration signal data. The preset notch frequency and preset attenuation information can be understood as parameters for notch filtering. Optionally, the preset notch frequency can be 50Hz / 100Hz, and the preset attenuation information can be ≥40dB to eliminate power frequency interference in the vibration signal data.

[0088] Specifically, the vibration signal data of the first cutter is denoised using a preset differential noise reduction circuit to obtain denoised vibration signal data. The denoised vibration signal data is then subjected to amplitude adjustment to obtain adjusted vibration signal data. Based on preset notch frequency and preset attenuation information, notch filtering is applied to the adjusted vibration signal data to eliminate power frequency interference, resulting in notch-filtered vibration signal data. Smoothing filtering (e.g., Savitzky-Golay smoothing filter with a window size of 5 points) is then applied to the notch-filtered vibration signal data to eliminate noise while preserving impact characteristics, resulting in smoothed vibration signal data. Outlier removal is performed on the smoothed vibration signal data (e.g., removing data points exceeding 5 standard deviations) to avoid the influence of occasional interference, resulting in removed vibration signal data. Finally, based on the baseline data of the target packaging machine's cutter blade at its rated speed, the removed vibration signal data is normalized to obtain the first filtered vibration signal data.

[0089] Optionally, the method for processing the second cutter vibration signal data according to the second filtering method can be as follows: performing low-pass filtering on the second cutter vibration signal data based on a preset cutoff frequency and a preset attenuation slope to obtain low-pass filtered vibration signal data; performing phase correction on the low-pass filtered vibration signal data to obtain corrected vibration signal data; performing moving average filtering on the corrected vibration signal data based on a preset moving window to obtain average filtered vibration signal data; and removing outliers from the average filtered vibration signal data to obtain second filtered vibration signal data.

[0090] The preset cutoff frequency and preset attenuation slope can be understood as parameters for low-pass filtering. Optionally, the preset cutoff frequency can be 18kHz, which means that components with frequencies below 18kHz in the second cutter vibration signal data are allowed to pass through, while components with frequencies above 18kHz are significantly attenuated. Optionally, the preset attenuation slope ≥60dB / oct means that for every octave (i.e., frequency doubling), the signal amplitude is attenuated by at least 60dB. Phase correction processing is used to eliminate phase deviations in the vibration signal data caused by signal transmission delay. The preset moving window can be a pre-set window size corresponding to the moving average filtering processing. Optionally, the preset moving window size can be 3 points.

[0091] Specifically, the vibration signal data of the second cutter is low-pass filtered according to a preset cutoff frequency and a preset attenuation slope to filter out non-axis vibrations, resulting in low-pass filtered vibration signal data. Phase correction is then performed on the low-pass filtered vibration signal data to eliminate phase deviations caused by signal transmission delay, resulting in corrected vibration signal data. Moving average filtering is then performed on the corrected vibration signal data according to a preset moving window to smooth vibration fluctuations within the rotation cycle, resulting in average filtered vibration signal data. Abnormal data in the average filtered vibration signal data, such as data with excessive speed fluctuations (speed fluctuation > ±1%), is removed to obtain the second filtered vibration signal data.

[0092] For example, referring to the examples above, see [link to previous section]. Figure 2The signal conditioning module is connected to the vibration acquisition module and is used to perform noise reduction, amplification, and analog-to-digital conversion on the vibration signal data output by the laser Doppler vibrometer. The signal conditioning module includes a differential noise reduction circuit, a programmable gain amplifier, and a high-speed A / D converter. The differential noise reduction circuit is constructed using a preset instrumentation amplifier, achieving a common-mode rejection ratio of 140dB, effectively filtering out high-frequency electromagnetic interference generated by the packaging machine's motor group and conveyor mechanism. The programmable gain amplifier uses a first preset chip, with gain controlled and adjusted by a microprocessor, ranging from 1 to 2000 times, amplifying the weak analog signal output by the laser vibrometer to a suitable range. The A / D converter uses a second preset chip, with a sampling accuracy of 24 bits and a sampling rate up to 100kHz, ensuring accurate conversion of the high-speed cutter's vibration signal and transmission to the data processing module. The signal conditioning module processes the first cutter vibration signal data to obtain the first filtered vibration signal data, and processes the second cutter vibration signal to obtain the second filtered vibration signal data.

[0093] S240. Perform spectrum analysis on the first filtered vibration signal data and the second filtered vibration signal data respectively to obtain the first vibration characteristic parameter corresponding to the first filtered vibration signal data and the second vibration characteristic parameter corresponding to the second filtered data.

[0094] S250. Based on the first vibration characteristic parameter and the second vibration characteristic parameter, determine the target cutter detection result of the target packaging machine.

[0095] The technical solution of this embodiment acquires first cutter vibration signal data corresponding to the cutter blade root within a preset time period when at least one first vibration signal acquisition device deployed at a first preset position on the target packaging machine meets a first relative position condition with the cutter blade root. When at least one second vibration signal acquisition device deployed at a second preset position on the target packaging machine meets a second relative position condition with the cutter shaft rotation surface, it acquires second cutter vibration signal data corresponding to the cutter shaft rotation surface within a preset time period. The vibration signal acquisition device maintains a safe distance of 30-50mm from the target packaging machine cutter, achieving non-contact acquisition of vibration signal data from the target packaging machine cutter, avoiding the problems of "mechanical interference causing cutter damage and easy wear" associated with traditional contact sensors. Furthermore, only the oil-proof, dust-proof, and light-transmitting cover of the vibration signal acquisition device needs cleaning, which not only reduces the equipment failure rate but also lowers equipment maintenance costs, significantly reducing the pressure on workshop operation and maintenance. The vibration signal data of the first cutter is filtered using a first filtering method to obtain first filtered vibration signal data, and the vibration signal data of the second cutter is filtered using a second filtering method to obtain second filtered vibration signal data, ensuring the reliability and accuracy of the data. The first and second filtered vibration signal data are then subjected to frequency domain transformation and spectral analysis using a Fast Fourier Transform algorithm associated with the cutter vibration, yielding first vibration characteristic parameters corresponding to the first filtered vibration signal data and second vibration characteristic parameters corresponding to the second filtered data. Based on this, normal rotational vibration, material impact vibration, and resonance anomalies can be effectively distinguished, reducing the fault misjudgment rate and improving the accuracy of vibration signal analysis. The target cutter detection result of the target packaging machine is determined based on the first and second vibration characteristic parameters. This invention solves the problems of low detection efficiency and inaccuracy caused by manual periodic inspections or machine shutdown for disassembly and testing in the prior art. It realizes the detection of the cutting status of the packaging machine without contact, and solves the problems of "minor defects are difficult to detect with the naked eye" in manual inspections and "traditional contact sensors can only monitor basic vibrations" that lead to untimely fault detection. It achieves accurate capture of minute vibrations, early warning of early faults, accurate location of fault types, and no impact on equipment operation, reducing maintenance costs and downtime losses, and ensuring the quality stability of the produced cigarette packs.

[0096] Example 3 Figure 4 This is a schematic diagram of the structure of a packaging machine cutter operation status detection device provided in Embodiment 3 of the present invention. Figure 4 As shown, a target packaging machine applied in a roll packaging workshop includes: a data acquisition module 310, a data filtering module 320, a data spectrum analysis module 330, and a cutter detection result determination module 340.

[0097] The data acquisition module 310 is used to acquire the unprocessed cutter vibration signal data of the target packaging machine when the target packaging machine is detected to be in operation; wherein the unprocessed cutter vibration signal data includes at least: a first cutter vibration signal data corresponding to the root of the cutter blade of the target packaging machine, and a second cutter vibration signal data corresponding to the rotation surface of the cutter shaft of the target packaging machine; the data filtering module 320 is used to filter the first cutter vibration signal data according to a first filtering method to obtain first filtered vibration signal data, and to filter the second cutter vibration signal data according to a second filtering method to obtain second filtered vibration signal data. According to the data; wherein, the first filtering method includes at least: notch filtering and smoothing filtering, and the second filtering method includes at least: low-pass filtering, phase correction, and moving average filtering; the data spectrum analysis module 330 is used to perform spectrum analysis on the first filtered vibration signal data and the second filtered vibration signal data respectively to obtain a first vibration characteristic parameter corresponding to the first filtered vibration signal data and a second vibration characteristic parameter corresponding to the second filtered data; the cutter detection result determination module 340 is used to determine the target cutter detection result of the target packaging machine based on the first vibration characteristic parameter and the second vibration characteristic parameter.

[0098] The technical solution of this embodiment achieves non-contact acquisition of vibration signal data of the target packaging machine's cutter when the target packaging machine is detected to be in operation. The first cutter vibration signal data is filtered according to a first filtering method to obtain first filtered vibration signal data, and the second cutter vibration signal data is filtered according to a second filtering method to obtain second filtered vibration signal data, ensuring the reliability and accuracy of the data. The first and second filtered vibration signal data are processed by frequency domain transformation and spectral analysis using a Fast Fourier Transform algorithm associated with the cutter vibration, obtaining first vibration characteristic parameters corresponding to the first filtered vibration signal data and second vibration characteristic parameters corresponding to the second filtered data. Based on the above, normal rotational vibration, material impact vibration, and resonance anomalies can be effectively distinguished, reducing the fault misjudgment rate and improving the accuracy of vibration signal analysis. The target cutter detection result of the target packaging machine is determined based on the first and second vibration characteristic parameters. This invention solves the problems of low detection efficiency and inaccuracy caused by manual periodic inspection or machine shutdown for disassembly and inspection in the prior art. It realizes non-contact detection of the cutting status of the packaging machine, improves the efficiency and accuracy of cutting status detection, and ensures the normal production process of tobacco.

[0099] Based on the above embodiments, optionally, the data acquisition module is configured to acquire first cutter vibration signal data corresponding to the cutter blade root within a preset time period when it is detected that at least one first vibration signal acquisition device deployed at a first preset position of the target packaging machine and the cutter blade root meet a first relative position condition; wherein, the first relative position condition is: the laser emitting end of the first vibration signal acquisition device is directly opposite the first force-bearing area of ​​the cutter blade root, and the first relative angle between the laser emitting end and the measured area of ​​the cutter blade root is less than a preset angle threshold; and to acquire second cutter vibration signal data corresponding to the cutter shaft rotation surface within a preset time period when it is detected that at least one second vibration signal acquisition device deployed at a second preset position of the target packaging machine and the cutter shaft rotation surface meet a second relative position condition; wherein, the second relative position condition is: the laser emitting end of the second vibration signal acquisition device is directly opposite the first area of ​​the cutter shaft rotation surface, and the second relative angle between the laser emitting end and the rotation tangent direction of the cutter shaft rotation surface is less than a preset angle threshold.

[0100] Optionally, the first cutter vibration signal data includes at least: first vibration velocity data and vibration displacement amplitude data at the root of the blade; the second cutter vibration signal data includes at least: second vibration velocity data.

[0101] Optionally, the data filtering module includes a first data filtering unit, used to perform noise reduction processing on the first cutter vibration signal data according to a preset differential noise reduction circuit to obtain noise-reduced vibration signal data; to perform signal amplitude adjustment processing on the noise-reduced vibration signal data to obtain adjusted vibration signal data; to perform notch filtering processing on the adjusted vibration signal data according to preset notch frequency and preset attenuation information to obtain notch-filtered vibration signal data; and to perform smoothing filtering processing, outlier removal processing, and data normalization processing on the notch-filtered vibration signal data in sequence to obtain first filtered vibration signal data.

[0102] Optionally, the data filtering module includes a second data filtering unit, used to perform low-pass filtering on the second cutter vibration signal data according to a preset cutoff frequency and a preset attenuation slope to obtain low-pass filtered vibration signal data; perform phase correction on the low-pass filtered vibration signal data to obtain corrected vibration signal data; perform moving average filtering on the corrected vibration signal data according to a preset moving window to obtain average filtered vibration signal data; and remove outliers from the average filtered vibration signal data to obtain second filtered vibration signal data.

[0103] Optionally, the cutting tool detection result determination module is used to determine at least one target cutting tool fault type and cutting tool fault cause information corresponding to each target cutting tool fault type based on the first vibration characteristic parameter and a first preset parameter threshold corresponding to at least one preset cutting tool fault type; determine at least one target cutting tool shaft fault type and cutting tool shaft fault cause information corresponding to each target cutting tool shaft fault type based on the second vibration characteristic parameter and a second preset parameter threshold corresponding to at least one preset cutting tool shaft fault type; and determine the target cutting tool detection result based on at least one target cutting tool fault type, the cutting tool fault cause information corresponding to each target cutting tool fault type, at least one target cutting tool shaft fault type, and the cutting tool shaft fault cause information corresponding to each target cutting tool shaft fault type.

[0104] Optionally, the device further includes: an information warning module, configured to determine and handle a blade warning message based on at least one target blade fault type, blade fault cause information corresponding to each target blade fault type, the first vibration characteristic parameter, and a first preset parameter threshold corresponding to each target blade fault type; and to determine and handle a tool shaft warning message based on at least one target tool shaft fault type, tool shaft fault cause information corresponding to each target tool shaft fault type, the second vibration characteristic parameter, and a second preset parameter threshold corresponding to the target tool shaft fault type.

[0105] The packaging machine cutter operating status detection device provided in this embodiment of the invention can execute the packaging machine cutter operating status detection method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0106] Example 4 Figure 5 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0107] like Figure 5As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0108] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0109] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the packaging machine cutter operating status detection method.

[0110] In some embodiments, the packaging machine cutter operating status detection method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the packaging machine cutter operating status detection method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the packaging machine cutter operating status detection method by any other suitable means (e.g., by means of firmware).

[0111] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0112] The computer program for implementing the packaging machine cutter operating status detection method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0113] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 19, or installed from storage unit 18, or installed from ROM 12. When the computer program is executed by processor 11, it performs the functions defined in the methods of the embodiments of the present invention.

[0114] Example 5 Embodiment 5 of the present invention also provides a computer-readable storage medium storing computer instructions for causing a processor to execute a method for detecting the operating status of a packaging machine cutter, applied to a target packaging machine in a roll packaging workshop. The method includes: When the target packaging machine is detected to be in operation, the unprocessed cutter vibration signal data of the target packaging machine is acquired; wherein, the unprocessed cutter vibration signal data includes at least: a first cutter vibration signal data corresponding to the root of the cutter blade of the target packaging machine, and a second cutter vibration signal data corresponding to the rotation surface of the cutter shaft of the target packaging machine; The first cutter vibration signal data is filtered using a first filtering method to obtain first filtered vibration signal data, and the second cutter vibration signal data is filtered using a second filtering method to obtain second filtered vibration signal data; wherein, the first filtering method includes at least: notch filtering and smoothing filtering, and the second filtering method includes at least: low-pass filtering, phase correction, and moving average filtering. Spectral analysis is performed on the first filtered vibration signal data and the second filtered vibration signal data respectively to obtain the first vibration characteristic parameter corresponding to the first filtered vibration signal data and the second vibration characteristic parameter corresponding to the second filtered data; Based on the first vibration characteristic parameter and the second vibration characteristic parameter, the target cutter detection result of the target packaging machine is determined.

[0115] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0116] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0117] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0118] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0119] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0120] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for detecting the operating status of a packaging machine cutter, characterized in that, A target packaging machine applied in a roll packaging workshop, the method comprising: When the target packaging machine is detected to be in operation, the unprocessed cutter vibration signal data of the target packaging machine is acquired; wherein, the unprocessed cutter vibration signal data includes at least: a first cutter vibration signal data corresponding to the root of the cutter blade of the target packaging machine, and a second cutter vibration signal data corresponding to the rotation surface of the cutter shaft of the target packaging machine; The first cutter vibration signal data is filtered using a first filtering method to obtain first filtered vibration signal data, and the second cutter vibration signal data is filtered using a second filtering method to obtain second filtered vibration signal data; wherein, the first filtering method includes at least: notch filtering and smoothing filtering, and the second filtering method includes at least: low-pass filtering, phase correction, and moving average filtering. Spectral analysis is performed on the first filtered vibration signal data and the second filtered vibration signal data respectively to obtain the first vibration characteristic parameter corresponding to the first filtered vibration signal data and the second vibration characteristic parameter corresponding to the second filtered data; Based on the first vibration characteristic parameter and the second vibration characteristic parameter, the target cutter detection result of the target packaging machine is determined.

2. The method according to claim 1, characterized in that, The acquisition of the cutter vibration signal data to be processed from the target packaging machine includes: When at least one first vibration signal acquisition device deployed at a first preset position of the target packaging machine is detected to meet a first relative position condition with the root of the cutter blade, first cutter vibration signal data corresponding to the root of the cutter blade is acquired within a preset time period; wherein, the first relative position condition is: the laser emitting end of the first vibration signal acquisition device is directly opposite the first force-bearing area of ​​the root of the cutter blade, and the first relative angle between the laser emitting end and the measured area of ​​the root of the cutter blade is less than a preset angle threshold; When at least one second vibration signal acquisition device deployed at the second preset position of the target packaging machine is detected to meet the second relative position condition with the blade shaft rotation surface, the second cutter vibration signal data corresponding to the blade shaft rotation surface is acquired within a preset time period; wherein, the second relative position condition is: the laser emitting end of the second vibration signal acquisition device is directly opposite the first region of the blade shaft rotation surface, and the second relative angle between the laser emitting end and the rotation tangent direction of the blade shaft rotation surface is less than a preset angle threshold.

3. The method according to claim 1, characterized in that, The first cutter vibration signal data includes at least: first vibration velocity data and vibration displacement amplitude data at the root of the blade; the second cutter vibration signal data includes at least: second vibration velocity data.

4. The method according to claim 1, characterized in that, The filtering process of the first cutter vibration signal data based on the first filtering method to obtain the first filtered vibration signal data includes: The vibration signal data of the first cutter is denoised according to the preset differential denoising circuit to obtain the denoised vibration signal data. The noise-reduced vibration signal data is subjected to signal amplitude adjustment processing to obtain adjusted vibration signal data; Based on the preset notch frequency and preset attenuation information, the adjusted vibration signal data is subjected to notch filtering to obtain notch-filtered vibration signal data. The vibration signal data after notch filtering is sequentially subjected to smoothing filtering, outlier removal, and data normalization to obtain the first filtered vibration signal data.

5. The method according to claim 1, characterized in that, The filtering process of the second cutter vibration signal data based on the second filtering method to obtain the second filtered vibration signal data includes: The vibration signal data of the second cutter is low-pass filtered according to the preset cutoff frequency and preset attenuation slope to obtain the low-pass filtered vibration signal data. The low-pass filtered vibration signal data is subjected to phase correction processing to obtain corrected vibration signal data; The corrected vibration signal data is subjected to moving average filtering based on a preset moving window to obtain average filtered vibration signal data. Outlier removal is performed on the averaged and filtered vibration signal data to obtain the second filtered vibration signal data.

6. The method according to claim 1, characterized in that, The determination of the target cutter detection result of the target packaging machine based on the first vibration characteristic parameter and the second vibration characteristic parameter includes: Based on the first vibration characteristic parameters and the first preset parameter threshold corresponding to at least one preset blade fault type, at least one target blade fault type and blade fault cause information corresponding to each target blade fault type are determined. Based on the second vibration characteristic parameter and the second preset parameter threshold corresponding to at least one preset tool shaft fault type, at least one target tool shaft fault type and tool shaft fault cause information corresponding to each target tool shaft fault type are determined; The target cutting tool detection result is determined based on at least one target cutting edge fault type, the cutting edge fault cause information corresponding to each target cutting edge fault type, at least one target cutting axis fault type, and the cutting axis fault cause information corresponding to each target cutting axis fault type.

7. The method according to claim 6, characterized in that, The method further includes: Based on at least one of the target blade fault types, the blade fault cause information corresponding to each target blade fault type, the first vibration characteristic parameter, and the first preset parameter threshold corresponding to each target blade fault type, a blade warning message is determined and a warning is processed. Based on at least one target toolshaft fault type, toolshaft fault cause information corresponding to each target toolshaft fault type, the second vibration characteristic parameter, and the second preset parameter threshold corresponding to the target toolshaft fault type, a toolshaft early warning message is determined and an early warning is processed.

8. A device for detecting the operating status of a packaging machine cutter, characterized in that, A target packaging machine used in a roll packaging workshop, the device comprising: The data acquisition module is used to acquire the unprocessed cutter vibration signal data of the target packaging machine when the target packaging machine is detected to be in operation; wherein the unprocessed cutter vibration signal data includes at least: a first cutter vibration signal data corresponding to the root of the cutter blade of the target packaging machine and a second cutter vibration signal data corresponding to the rotation surface of the cutter shaft of the target packaging machine; The data filtering module is used to filter the first cutter vibration signal data based on a first filtering method to obtain first filtered vibration signal data, and to filter the second cutter vibration signal data based on a second filtering method to obtain second filtered vibration signal data; wherein, the first filtering method includes at least: notch filtering and smoothing filtering, and the second filtering method includes at least: low-pass filtering, phase correction, and moving average filtering. The data spectrum analysis module is used to perform spectrum analysis on the first filtered vibration signal data and the second filtered vibration signal data respectively, to obtain the first vibration characteristic parameter corresponding to the first filtered vibration signal data and the second vibration characteristic parameter corresponding to the second filtered data; The cutter detection result determination module is used to determine the target cutter detection result of the target packaging machine based on the first vibration characteristic parameter and the second vibration characteristic parameter.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the packaging machine cutter operating status detection method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the packaging machine cutter operating status detection method according to any one of claims 1-7.

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