A monitoring control method and system for an automated production line

Abstract

The present application relates to the technical field of production line monitoring control, and in particular to a kind of monitoring control method and system of automated production line.The technical scheme of the present application transmits pulsed laser through the monitoring optical cable of battery production line, and receives the scattering signal fed back;Time-frequency analysis, space-time array analysis and frequency domain space array analysis are carried out on the scattering signal to obtain multi-dimensional vibration information of each operating equipment of battery production line;Since the multi-dimensional vibration information includes the vibration main frequency of operating equipment and the vibration source position and energy spectrum density of the corresponding load-bearing area, the actual operating state of each operating equipment in executing the current production task can be determined based on the multi-dimensional vibration information of each operating equipment and the progress information of the corresponding production task;According to the actual operating state of each operating equipment, the interlocking operation control of production rhythm is carried out on the battery production line.The technical scheme improves the stability of battery production line production control and the consistency of battery product quality.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of production line monitoring control, and in particular to a monitoring control method and system for an automated production line. BACKGROUND

[0002] Lithium-ion batteries, as a new type of energy storage device, are widely used in new energy vehicles, portable electronic devices, energy storage systems and other fields. With the rapid growth of downstream market demand, lithium battery production lines are developing towards high speed, high precision and full automation. The manufacturing process of lithium batteries usually includes electrode sheet manufacturing, cell assembly and formation and capacity grading, etc. The process equipment is intensive, the operation rhythm is fast, and the product consistency and yield are extremely high.

[0003] During the operation of the lithium battery production line, various high-precision equipment are connected by conveying lines for material transfer in key processes such as rolling, slitting, laminating, winding, liquid injection and packaging. Due to the high-speed motion and structural vibration between devices, quality problems such as electrode sheet deviation, material curling and laminating alignment error are easily caused, and even safety risks such as cell damage and line stop are caused. Therefore, it is of great significance to ensure the stable operation of the production line and improve the product quality by implementing state perception and real-time monitoring of each section of the production line, especially the comprehensive perception and analysis of the running vibration state of the key equipment.

[0004] At present, the common device state monitoring method is mainly based on single sensor means such as accelerometer, strain gauge, camera or current detection. This kind of method is mostly point layout, and the monitoring coverage is limited, which leads to insufficient accuracy of abnormal identification and cannot meet the needs of global perception and predictive maintenance of lithium battery intelligent manufacturing. SUMMARY

[0005] In order to solve the technical problem that the running device state on the automated battery production line cannot be perceived in real time, causing the battery production rhythm to be disorderly. The purpose of the present application is to provide a monitoring control method and system for an automated production line, which improves the stability of battery production line production control and the consistency of battery product quality. The technical solution adopted is as follows:

[0006] In the first aspect, the present application provides a monitoring control method for an automated production line, which comprises:

[0007] The monitoring cable emits pulsed laser to the battery production line, and receives the feedback scattering signal, wherein the monitoring cable is an entire optical cable embedded along the load-bearing area of each running device of the battery production line in the length direction;

[0008] The scattered signals are analyzed in time-frequency, time-space array and frequency domain space array to obtain multi-dimensional vibration information of each running equipment in the battery production line, wherein the multi-dimensional vibration information includes vibration main frequency of the running equipment and vibration source position and energy spectrum density of the corresponding bearing area;

[0009] The multi-dimensional vibration information of each running equipment and the progress information of the corresponding production task are input into a preset monitoring classification model to determine the actual running state of each running equipment in executing the current production task;

[0010] According to the actual running state of each running equipment, the production cycle interlocking operation control of the battery production line is performed.

[0011] In an optional embodiment, before the monitoring optical cable emits pulsed laser and receives the feedback scattered signals, the method further comprises:

[0012] According to the laying length of the monitoring optical cable in the bearing area of each running equipment in the battery production line, the pulse width of the pulsed laser is configured to make the spatial resolution of each running equipment meet the preset interval;

[0013] According to the one-way laying length of the monitoring optical cable, the pulse interval time of the pulsed laser is configured to make the backward Rayleigh scattering of the pulsed laser not aliasing in time domain;

[0014] According to the area length and interval distance of all bearing areas, the relative delay length and sampling point interval distance of the pulsed laser are configured to reduce the sampling blind area of all bearing areas.

[0015] In an optional embodiment, the monitoring optical cable emits pulsed laser and receives the feedback scattered signals, comprising:

[0016] Obtaining the node timing diagram of each running equipment in executing the current production task;

[0017] Analyzing the path interference segment represented in all node timing diagrams to determine the effective emission period and effective receiving period of the pulsed laser;

[0018] Emitting the pulsed laser in the effective emission period and receiving the scattered signals in the effective receiving period.

[0019] In an optional embodiment, analyzing the path interference segment represented in all node timing diagrams to determine the effective emission period and effective receiving period of the pulsed laser, comprising:

[0020] The end station of the monitoring optical cable close to the battery production line is configured as the incident end of the pulsed laser;

[0021] The node timing diagram of the terminal station is taken as a reference, and the running timing diagrams of other running devices are time-axis aligned;

[0022] The node timing diagram after time-axis alignment is subjected to abnormal segment elimination, and the remaining time segment intersection is marked as an effective transmission period, and the period in which the pulsed laser is delayed to propagate in the effective transmission period is marked as an effective receiving period.

[0023] In an optional embodiment, the scattered signals are subjected to time-frequency analysis, time-space array analysis, and frequency-domain space array analysis to obtain multi-dimensional vibration information of each running device of the battery production line, including:

[0024] The scattered signals are subjected to time-frequency analysis to obtain the vibration main frequency, vibration frequency band, and vibration change curve of the corresponding running device, wherein the vibration change curve is a curve of the vibration frequency of the running device changing with the monitoring time;

[0025] The scattered signals are subjected to time-space array analysis to obtain the vibration source position of the corresponding running device in the belonging load-bearing area, wherein the load-bearing area of each running device is configured with multiple vibration sampling points;

[0026] The scattered signals are subjected to space array analysis to obtain the energy spectrum density and vibration distribution atlas of the corresponding running device in the belonging load-bearing area;

[0027] The vibration main frequency, vibration frequency band, vibration change curve, vibration source position, energy spectrum density, and vibration distribution atlas are determined as the multi-dimensional vibration information of the corresponding running device.

[0028] In an optional embodiment, the scattered signals are subjected to time-space array analysis to obtain the vibration source position of the corresponding running device in the belonging load-bearing area, including:

[0029] According to the sampling time of the scattered signals of the sampling points covered by the running device, a time-space observation matrix of the corresponding running device is constructed;

[0030] Adjacent time-space observation matrices of the same running device are subjected to time delay estimation and time alignment processing to determine whether the belonging load-bearing area of the corresponding running device forms a wave front diffusion feature of a delay superposition beam;

[0031] When it is determined that the belonging load-bearing area of the corresponding running device forms a wave front diffusion feature of a delay superposition beam, the sampling point with the maximum superposition energy is determined as the vibration source position.

[0032] In an optional embodiment, the scattered signals are subjected to space array analysis to obtain the energy spectrum density and vibration distribution atlas of the corresponding running device in the belonging load-bearing area, including:

[0033] According to the preset environment coupled vibration model, the scattering signal of each vibration region of the running equipment is processed to obtain the vibration observation value of the corresponding running equipment at all vibration sampling points in the vibration region;

[0034] The vibration observation value of each vibration sampling point is subjected to frequency spectrum transformation to obtain the vibration energy of the corresponding vibration sampling point of the running equipment in the vibration region;

[0035] The sum of all vibration energies of the running equipment in the vibration region is determined as the energy spectrum density, and the two-dimensional mapping result of all vibration energies in the vibration region is determined as the vibration distribution atlas.

[0036] In an optional embodiment, according to the preset environment coupled vibration model, the scattering signal of each vibration region of the running equipment is processed to obtain the vibration observation value of the corresponding running equipment at all vibration sampling points in the vibration region, comprising:

[0037] According to the formula , the vibration observation value of the vibration sampling point at the time is obtained, wherein, is a discrete time output matrix, is a discrete time direct feed matrix, is the phase change amount of the scattering signal of the vibration sampling point at the time , is the external excitation vector of the vibration sampling point at the time , is the observation output noise of the vibration sampling point at the time .

[0038] In an optional embodiment, according to the actual running state of each running equipment, the interlocking running control of the production rhythm of the battery production line is performed, comprising:

[0039] According to the actual running state of each running equipment, the abnormal state level of the abnormal running equipment is determined;

[0040] According to the abnormal state level and the preset running adjustment curve, the running rhythm of the adjacent running equipment of the abnormal running equipment is adjusted, wherein the running adjustment curve is a curve corresponding to the change of the equipment running rhythm with the running time under the abnormal state level.

[0041] In a second aspect, the embodiments of the present application also provide a monitoring control system of an automatic production line, comprising:

[0042] A monitoring terminal is configured to emit pulsed laser light to a monitoring optical cable of the battery production line and receive feedback scattered signals, wherein the monitoring optical cable is an entire optical cable embedded in a bearing area along a length direction of each operating device of the battery production line.

[0043] A data processing terminal is connected to the monitoring terminal, and is configured to perform time-frequency analysis, time-space array analysis and frequency-domain space array analysis on the scattered signals to obtain multi-dimensional vibration information of each operating device of the battery production line, wherein the multi-dimensional vibration information includes a vibration main frequency of the operating device, a vibration source position and an energy spectrum density of the bearing area to which the operating device belongs, and the multi-dimensional vibration information of each operating device and progress information of a corresponding production task are input into a preset monitoring classification model to determine an actual operating state of each operating device in executing a current production task.

[0044] A control terminal is connected to the data processing terminal, and is configured to perform interlocking operation control on a production rhythm of the battery production line according to the actual operating state of each operating device.

[0045] The present application has the following advantages:

[0046] The technical scheme of the present application emits pulsed laser light to a monitoring optical cable of the battery production line and receives feedback scattered signals, performs time-frequency analysis, time-space array analysis and frequency-domain space array analysis on the scattered signals to obtain multi-dimensional vibration information of each operating device of the battery production line, determines an actual operating state of each operating device in executing a current production task based on the multi-dimensional vibration information of each operating device and progress information of a corresponding production task, and performs interlocking operation control on a production rhythm of the battery production line according to the actual operating state of each operating device. The technical scheme can realize overall perception of the battery production line in an automatic operation process, realize interlocking operation control of the production rhythm, make the production rhythm of the battery production line more orderly, and thus improve the stability of production control of the battery production line and the consistency of the quality of battery products. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, and the advantages thereof, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort based on these drawings.

[0048] Figure 1 A flowchart of a monitoring control method of an automatic production line provided by an embodiment of the present application;

[0049] Figure 2A schematic diagram of a battery production line arrangement provided by an embodiment of the present application;

[0050] Figure 3 A schematic diagram of a coherent detection Φ-OTDR system provided by an embodiment of the present application;

[0051] Figure 4 A schematic diagram of a principle of implementing frequency domain spatial array analysis on scattered signals provided by an embodiment of the present application;

[0052] Figure 5 A schematic diagram of a spatial distribution of frequency domain energy provided by an embodiment of the present application;

[0053] Figure 6 A schematic diagram of a spatial distribution of time domain energy provided by an embodiment of the present application;

[0054] Figure 7 A schematic diagram of a monitoring control system of an automatic production line provided by an embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to further illustrate the technical means and effects taken by the present application to achieve the predetermined purposes, the following describes in detail the specific implementation, structure, features and effects of a monitoring control method and system of an automatic production line according to the present application in combination with the accompanying drawings and preferred embodiments. In the following description, different “one embodiment” or “another embodiment” do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0057] Current automatic production lines such as lithium batteries usually use independent sensors (such as accelerometers, displacement sensors, current sensors) to monitor the running state of a running device. This kind of monitoring method has limited spatial coverage, and each running device forms an information island. After an abnormality occurs in a running device, due to the lag of beat adjustment control, it is easy to cause production rhythm disorder, resulting in insufficient quality stability of battery product production. The following specifically describes the specific scheme of a monitoring control method and system of an automatic production line provided by the present application in combination with the accompanying drawings.

[0058] Please refer to Figure 1 , Figure 1A flow chart of a monitoring control method of an automatic production line is provided for an embodiment of the present application. The monitoring control method can be applied to the operation of a general controller of an automatic production line. The general controller can be an industrial computer or other types of control devices or terminals, which can run the method and are not specifically limited herein. The control method comprises:

[0059] S11, transmitting pulse laser to the monitoring optical cable of the battery production line and receiving the feedback scattering signals, wherein the monitoring optical cable is an entire optical cable embedded in the bearing area along the length direction of each running device of the battery production line.

[0060] Specifically, please refer to Figure 2 , Figure 2 A schematic diagram of the layout of the battery production line is provided. The running devices of the battery production line include a mixer, a coating machine, a rolling machine, a slitting machine, a laminating machine (or a winding machine), a welding machine, a packaging machine and a detection device arranged in the order of production. The mixer is used for slurry preparation of raw materials such as active material, conductive agent and binder, which is the starting process of the whole line; the coating machine is used for uniformly coating the positive and negative electrode slurries on the surface of the metal foil, with strict control of thickness and uniformity; the rolling machine compacts the electrode sheet after coating by mechanical method to improve its volume energy density; the slitting machine is used for cutting the whole roll of electrode sheet into single pieces according to the design specifications; the laminating machine stacks or winds the positive and negative electrode sheets and the separator in a certain order to form the battery cell; the welding machine is used for welding at the tab, lead-out end and other positions; the packaging machine is used for electrolyte injection, shell packaging and vacuum treatment of the battery cell to complete the preparation of the battery; the detection device is used for function tests such as internal resistance test, charge and discharge aging of the prepared battery. In the whole battery production line, each running device is an independent running unit, but must be highly linked in production rhythm to ensure the safety of the production process and the quality of the battery. High-precision and non-interference monitoring of the running state of these running devices is the key to ensuring the continuity of the whole battery production line and the consistency control of the product.

[0061] A phase-sensitive optical cable can be selected as the monitoring optical cable to monitor the running state of the battery production line. The monitoring optical cable is buried along the ground of the battery production line and located below the device base. A U-shaped groove can be opened in the bearing area of each running device, the monitoring optical cable is laid in the U-shaped groove, and the monitoring optical cable is fixed by pouring cement. The monitoring optical cable needs to cover the bearing structure area of each running device, i.e. the area most easily coupled by vibration. The bearing area includes device feet, chassis steel beams, anchor bolt connections and other structure sites. The bearing area and the optical cable position of each running device can be numbered one by one to mark the mapping relationship between each vibration sampling point and the physical position, providing an analysis basis for subsequent signal interpretation and device attribution analysis.

[0062] Please refer to Figure 3 , Figure 3A structure diagram of a coherent detection Φ-OTDR (Phase-Sensitive Optical Time-Domain Reflectometry) system is shown, which specifically comprises a narrow linewidth fiber laser, a first coupler, an acousto-optic modulator, an erbium-doped fiber amplifier, a filter, an optical circulator, a monitoring optical cable, a second coupler, a balanced photodetector, a data acquisition card and a processing terminal. The narrow linewidth fiber laser emits laser light, which is output to a sensing arm and a reference arm through the first coupler. The laser signal of the sensing arm is modulated by the acousto-optic modulator and then output as pulsed laser light, which is output to the monitoring optical cable through the erbium-doped fiber amplifier and the filter. When the running equipment of the battery production line vibrates, the vibration is transmitted to the monitoring optical cable to form a scattering signal, which is scattered back to the second coupler through the optical circulator. The scattering signal and the laser signal of the reference arm are transmitted to the balanced photodetector through the second coupler, and the balanced photodetector outputs an electrical signal to the data acquisition card. The data acquisition card converts the electrical signal into a digital signal and outputs it to the processing terminal. The processing terminal determines the actual running state of each running equipment after processing.

[0063] When monitoring the battery production line, there are many running equipment involved and the length of the monitoring optical cable is relatively long. If the monitoring parameters are not reasonable, the backscattering of multiple pulsed laser lights may overlap on the time axis, and the real spatial response of the backscattering may not be restored. Based on this, in a specific embodiment, the control method further comprises parameter configuration of the Φ-OTDR system.

[0064] In the Φ-OTDR system, the pulse width of the pulsed laser light determines the expansion of the scattering signal echo in the time domain, which further affects the spatial resolution of the system. Therefore, the pulse width of the pulsed laser light needs to be configured according to the layout length of the monitoring optical cable in the load-bearing area of each running equipment of the battery production line, so that the spatial resolution of each running equipment for monitoring meets the preset interval. The pulse width is related to the spatial sampling resolution of the monitoring optical cable along its length direction. By configuring an appropriate pulse width, it can be ensured that each running equipment's load-bearing area contains multiple vibration sampling points, so that the positioning accuracy of the vibration source meets the monitoring requirements. It can be understood that the layout length of the optical cable in each load-bearing area matches the pulse width, which can enable the monitoring to analyze the vibration source of the running equipment with a preset spatial accuracy, avoiding spatial ambiguity.

[0065] The pulse interval time of the pulsed laser light is configured according to the one-way layout length of the monitoring optical cable, so that the backscattering of the pulsed laser light does not overlap in the time domain. A reasonable pulse interval time can make the analysis of the backscattering more accurate, ensuring that the backscattering signal of the previous pulse is returned completely before the next pulse is emitted; avoiding the overlap of multiple pulse signals on the time axis, causing misjudgment or energy analysis distortion.

[0066] Based on the length and spacing of all load-bearing areas, the relative delay lengths of pulsed laser interleaving and the sampling point spacing are configured to minimize sampling blind spots in all load-bearing areas. By staggering the time domain intervals, all spatial segments on the optical fiber are covered by at least one laser beam. Simultaneously, the sampling point spacing is adjusted to achieve a balanced signal sampling density across all areas.

[0067] Specifically, the first frequency To the Chief The monitoring optical cable injection pulse width is (unit: ns) is the same intensity detection laser pulse, and the second frequency of the data acquisition card sampling is According to the basic principle of the extrapolation coherent detection Φ-OTDR system, the observation data matrix can be obtained:

[0068]

[0069]

[0070] in, The scattering response results in the time dimension and space dimension can be characterized Sampling time, The vibration energy at each sampling position. is the time dimension, is the spatial dimension; is the speed of light propagation in the optical fiber, , is the speed of light in vacuum, is the refractive index of the optical fiber; is the detector responsivity; is the detection intensity of the pulsed laser; is the optical fiber attenuation coefficient; The optical frequency shift introduced for the acousto-optic modulator; is the phase deviation caused by the reference light, which can be derived based on the laser signal of the reference arm; is the differential distance of laser transmission; is the length value, used to identify the location of the vibration sampling point on the monitoring optical cable; 、 They are Fiber scattering points in the length range The amplitude and phase modulation mean of the time interval.

[0071] In order to avoid the aliasing of multiple pulse backscattered Rayleigh signals, there is In order to ensure that the vibration at any point within the monitoring range can be captured by more than one sampling point, and to avoid the formation of monitoring blind spots in space, there is ,Right now:

[0072]

[0073] As can be seen from the above formula, based on reasonable parameter configuration, the backscattering signal changes of each running device at different time and space positions during the operation of the battery production line can be recorded. Further combining the differential structure or phase change relationship between adjacent space positions defined by the formula, the vibration frequency characteristics, energy spectrum density, wave front propagation trend and source position of each running device in its bearing area can be extracted, which constitute the key input of the monitoring classification model.

[0074] For example, step S11 includes sub-steps S11-1 to S11-3, which are specifically described as follows:

[0075] S11-1, obtain the node time sequence diagram of each running device when performing the current production task. The mixer on the battery production line can be configured as a stirring tank structure, and the rotating speed is rapidly increased at the initial stage of starting, and the mechanical vibration is significant. There is strong mechanical vibration at the initial stage of stirring; as the stirring time is prolonged, the vibration gradually eases, and the subsequent tends to be stable, based on the different states of the mixer performing the stirring task, the node time sequence diagram can be obtained. Taking the coating machine as an example, the new pole piece head enters the line, the traction causes vibration, there is vibration sampling interference at the moment of contact of the scraper, and the vibration gradually stabilizes as the coating proceeds, based on the vibration change characteristics of the coating machine implementing the coating process, the corresponding node time sequence diagram can be drafted. Through the vibration change characteristics of each running device in performing the corresponding production task, the corresponding node time sequence diagram can be obtained.

[0076] S11-2, analyze the path interference segment represented in all node time sequence diagrams to determine the effective emission period and effective receiving period of the pulse laser. The path interference segment is based on the time period of interference in the vibration collection of each running device during operation, which can be marked based on the interference intensity, and the path interference segment is excluded when collecting the scattering signal. For example, at the initial stage of the mixer implementing stirring, the stirring paddle, main shaft, tank support structure, etc. produce large vibration, stress rebound and energy coupling in the process of motor starting and high-speed rotation of the slurry, which will cause a large number of irregular phase disturbances of the monitoring optical cable, interfere with normal equipment state sampling, and since there is large vibration, the collection of the scattering signal is disturbed, and the 10s time period of stirring starting can be defined as the path interference segment. Based on the analysis of all path interference segments, the effective emission period and effective receiving period of the pulse laser can be obtained.

[0077] For example, sub-step S11-2 includes:

[0078] Firstly, the end station of the monitoring optical cable close to the battery production line is configured as the incident end of the pulse laser. The pulse laser enters the monitoring optical cable from the end station, which can minimize the vibration interference of the upstream running equipment. The pulse laser first passes through the end station and then propagates to the upstream running equipment. When analyzing, only the path interference caused by the downstream running equipment needs to be considered. Therefore, the battery production line can be monitored more comprehensively, and the subsequent analysis logic is clearer.

[0079] Secondly, the node timing diagram of the end station is taken as the reference, and the running timing diagrams of other running equipment are time-axis aligned. Since each running equipment performs different tasks, the corresponding running tempo may not be consistent. In order to build a common reference time axis for the whole line, the cycle of one running equipment must be taken as the reference. The end station is at the front end of the sampling path, and all interferences are behind it, so it can be used as a stable reference. Time-axis alignment can normalize the running tempo (including the interference section) of all running equipment to a unified cycle coordinate system.

[0080] Thirdly, the node timing diagram after time-axis alignment is used to remove abnormal sections, and the intersection of the remaining time sections is marked as the effective transmission period. The period during which the pulse laser is delayed in the effective transmission period is marked as the effective reception period. All aligned node timing diagrams are superimposed. If there is any running equipment on the path in the interference section at a certain time, this time is determined to be an untransmissible period. The overlapping period in which all running equipment on the path is in a non-intense disturbance state is the effective transmission period. In the effective transmission period, the Φ-OTDR system can transmit pulse laser. In the effective reception period, the scattered signal can be received to ensure that the received scattered signal can be accurately analyzed subsequently. In addition, the determination of the effective reception period also considers the laser propagation and echo delay time to derive the effective reception time window.

[0081] S11-3, transmit pulse laser in the effective transmission period and receive scattered signal in the effective reception period. Since the scattered signal is an important basis for subsequent signal analysis, the pulse laser is transmitted in the effective transmission period to avoid the interference of the scattered laser caused by the start-up period of high-vibration equipment such as the mixer and the roller press. This can significantly improve the signal-to-noise ratio and structural recognition of the sampling data, avoid the influence of path interference on vibration source feature extraction, and ensure the accuracy of running equipment state determination.

[0082] At this point, the scattered signal of the battery production line has been accurately obtained, and the signal analysis is performed in step S12.

[0083] S12, performing time-frequency analysis, time-space array analysis and frequency domain space array analysis on the scattering signal to obtain multi-dimensional vibration information of each operating equipment of the battery production line, wherein the multi-dimensional vibration information comprises a vibration main frequency of the operating equipment and a vibration source position and energy spectrum density of the bearing area to which the operating equipment belongs.

[0084] Specifically, by performing time-frequency analysis on the scattering signal, the variation characteristics of the vibration of the corresponding operating equipment in time-frequency domain can be determined, and the vibration main frequency can be obtained by performing statistics. The time-frequency analysis can be implemented by using short-time Fourier transform and wavelet packet decomposition based on the time sequence of the vibration sampling points of each bearing area, the number of occurrences of each frequency point is obtained, the maximum number of occurrences is defined as the main frequency point, and the vibration main frequency of each operating equipment can be obtained by counting the distribution of the main frequency points. Based on the phase propagation or signal delay between adjacent sampling points in space, the vibration source position of the bearing area is determined by time delay estimation method, that is, the position point with the minimum delay and the maximum energy, which indicates that the position is the vibration source position of the bearing area. The energy spectrum density of the corresponding operating equipment can be obtained by frequency domain space array analysis, and the energy accumulation characteristics of the operating equipment in the bearing area can be obtained.

[0085] For example, step S12 comprises sub-steps S12-1 to S12-3, which are described in detail as follows:

[0086] S12-1, performing time-frequency analysis on the scattering signal to obtain the vibration main frequency, vibration frequency band and vibration variation curve of the corresponding operating equipment, wherein the vibration variation curve is a curve of the vibration frequency of the operating equipment changing with the monitoring time. After receiving the scattering signal, filtering processing can be performed first, and then the time-frequency spectrum of each vibration sampling point is calculated, which is a curve spectrum of the vibration frequency changing with the sampling time. The frequency with the highest energy at each time point of the time-frequency spectrum is extracted as the vibration main frequency; the vibration frequency band is obtained based on the fluctuation of the vibration main frequency; and the vibration variation curve is obtained based on the curve of the vibration main frequency of each vibration sampling point changing with time, which can reflect the frequency drift, jump and other characteristics of the equipment during startup, load change or failure precursor.

[0087] S12-2, performing time-space array analysis on the scattering signal to obtain the vibration source position of the corresponding operating equipment in the bearing area, wherein the bearing area of each operating equipment is configured with multiple vibration sampling points. There are multiple vibration sampling points in the bearing area of each operating equipment, and the specific position of the vibration source on the equipment base or the key support structure can be located by array signal processing, or the time-space array analysis can be implemented based on the data processing model, and the vibration source position can be analyzed, which is not limited here.

[0088] Specifically, the time-space array analysis on the scattering signal comprises:

[0089] The first step is to construct the spatiotemporal observation matrix of the corresponding running equipment according to the sampling time of the scattered signal of the sampling points covered by the running equipment. The calculation logic of Sampling time, The vibration energy at each sampling position is then used to derive the spatiotemporal measurement matrix for each operating device. Each element in the spatiotemporal measurement matrix can be either the vibration energy or the phase change of the pulsed laser. Each element in the spatiotemporal measurement matrix can be used to characterize the backscattered intensity of the pulsed laser at the corresponding vibration sampling point, or the phase offset of the vibration sampling point relative to the reference light after coherent (or differential interferometry) demodulation.

[0090] The second step is to estimate and align the delays of adjacent spatiotemporal observation matrices for the same operating device to determine whether the load-bearing area of ​​the corresponding operating device forms a wavefront diffusion characteristic of a delayed superposition beam. Wavefront diffusion (also known as vibration wavefront spread) refers to the phenomenon in which a vibration event in a distributed fiber optic sensing system no longer appears as an ideal, sharp wavefront passing through a single point. Instead, as the wave propagates through the fiber or structure, it gradually broadens and blurs in space and time, spreading outward due to multiple factors such as refraction, scattering, coupling, and dielectric dispersion. To reveal the true spatial delay of the vibration wavefront, it is necessary to estimate and uniformly align the signals of adjacent channels in the spatiotemporal observation matrix. This involves selecting one vibration sampling point as a reference channel, calculating the cross-correlation function between each adjacent channel and the reference channel, or employing phase-shift cross-correlation methods, and estimating the relative delay from the peak positions of their cross-correlation. Based on the estimated delays, the time series of each channel is shifted along the time axis and fine-tuned using interpolation filtering to achieve temporal alignment of the same excitation wavefront across all channels. After alignment is completed, any row in the entire matrix corresponds to the response of the same wavefront at each spatial sampling point, thereby providing a basic data structure with consistent timing and spatial synchronization for the subsequent delayed-addition beamforming processing, enabling vibration source positioning and spatial energy focusing to achieve maximum accuracy under the same excitation event.

[0091] The third step is to determine the wavefront diffusion characteristics of the delayed superposition beam formed in the load-bearing area of ​​the corresponding operating equipment. The sampling point with the maximum superposition energy is identified as the vibration source location. It can be understood that at the same excitation moment, the moments when different spatial points receive the wave peaks are no longer concentrated in a straight line, but instead exhibit a fan-shaped or curved distribution. As the propagation distance and coupling environment change, the waveform amplitude gradually decays and the wave packet width increases. The vibration sampling point with the maximum superposition energy is determined to be the vibration source location.

[0092] Take the mixer as an example, when the mixer starts, the first shock wave generated by the stirring paddle forms a sharp strain disturbance on the monitoring optical cable at first, but after reflection of the rack structure, elastic coupling of the foot and acoustic scattering, the original shock wave packet is stretched to tens of milliseconds in width within a certain range, and multiple echoes are superimposed in a larger range, resulting in a fan-shaped spatial and temporal distribution of the wave front in backscattering. The position of the vibration source is determined based on the wave front diffusion phenomenon.

[0093] S12-3, spatial array analysis is performed on the scattered signals to obtain the energy spectrum density and vibration distribution map of the corresponding operating equipment in the bearing area. The energy spectrum density of each vibration sampling point in the bearing area of each operating equipment can be calculated, and the energy of each sampling point can be accumulated as the total energy spectrum density of the bearing area of the equipment. Based on the position of each vibration sampling point at the center of the frequency band, a spatial thermal map is drawn, with the horizontal coordinate being the position and the vertical coordinate being the frequency or energy value, forming a two-dimensional vibration distribution map.

[0094] Specifically, the spatial array analysis of the scattered signals comprises:

[0095] First, the scattered signals of each operating equipment in the vibration area are processed according to the pre-set environmental coupling vibration model to obtain the vibration observation values of each operating equipment in the vibration area. As can be seen from the above formula, the Φ-OTDR system can monitor the vibration signals of each point in the length range with a spatial resolution of The actual resolution is ) and a frequency range of The actual resolution is ) to realize vibration signal monitoring in the frequency range; wherein is the lowest observable frequency affected by system noise. Since the light transmission in the optical fiber is exponentially attenuated with distance, the amplitude of the observed signal will also be exponentially attenuated with distance. The phase reflects the dynamic strain scalar of the vibration at each point of the optical fiber in the axial direction of the optical fiber, which is quite different from the three-component vector signal measured by the traditional three-axis direction acceleration sensor. And the pre-embedded way of the monitoring optical cable will produce different vibration coupling forms with the environment.

[0096] Please refer to Figure 4 , Figure 4 for the principle diagram of the frequency domain spatial array analysis of the scattered signals. The monitoring optical cable with different laying modes receives a unique excitation containing environmental noise, forming an optical fiber-environment coupling vibration system. The state at the previous moment and the current moment with noise excitation together affect the noise observation signal obtained by the Φ-OTDR system. It can be assumed that the optical fiber-environment coupling vibration system at the vibration sampling point has degrees of freedom.

[0097] There is a relationship wherein, denotes a time discrete quantity, denotes a space discrete quantity; is a discrete time state variable, is a discrete time state matrix, is a discrete time external excitation vector, is a discrete time input matrix, is a system input noise, is a response of the Φ-OTDR system, is a time difference of adjacent adopted periods.

[0098] According to the formula , the vibration observation value of the vibration sampling point at the time is obtained, wherein, is a discrete time output matrix, is a discrete time direct feed matrix, is a phase change quantity represented by the scattering signal of the vibration sampling point at the time , is an external excitation vector of the vibration sampling point at the time , is an observation output noise of the vibration sampling point at the time .

[0099] Secondly, the frequency spectrum of the vibration observation value sequence of each vibration sampling point is transformed to obtain the vibration energy of the vibration sampling point corresponding to the vibration region of the running equipment. Further, please refer to Figure 4 , the environmental coupling vibration model is processed based on the input noise, system parameters, excitation and vibration state to obtain the actual vibration state , the vibration observation value is obtained in combination with the discrete time direct feed matrix, the discrete time output matrix and the observation noise, and the actual observation value is obtained based on the observation model and the sensing parameter. There is a specific relationship as follows , based on the formula, the vibration energy of the vibration sampling point , , is the number of related vibration sampling points, may be 2-3 vibration sampling points near the vibration sampling point .

[0100] Further, the scope of the discrete time state matrix and the discrete time input matrix may be limited, and there is a relationship as follows: ; ; , , are the mass matrix, the damping matrix and the stiffness matrix, respectively.

[0101] Thirdly, the summation result of all vibration energy in the vibration region of the running equipment is determined as the energy spectrum density, and the two-dimensional mapping result of all vibration energy in the vibration region of the running equipment is determined as the vibration distribution atlas. The vibration energy of all sampling points is summed to obtain the energy spectrum density of the running equipment, and the vibration energy of each sampling point is constructed into a two-dimensional distribution atlas according to the spatial position, which is used to reflect the response characteristics of the equipment running state in space, and realize the identification and early warning of high energy density concentration area.

[0102] S12-4, the vibration main frequency, the vibration frequency band, the vibration change curve, the vibration source position, the energy spectrum density and the vibration distribution atlas are determined as the multi-dimensional vibration information of the corresponding running equipment. Each type of data in the multi-dimensional vibration information represents the vibration of the corresponding running equipment from different dimensions, and each type of data can be given a corresponding variable name to construct the mapping relationship between each running equipment and various data in the multi-dimensional vibration information, which is convenient for subsequent implementation and processing.

[0103] At this point, the multi-dimensional vibration information of each running equipment has been obtained, and then step S13 is entered.

[0104] S13, the multi-dimensional vibration information of each running equipment and the progress information of the corresponding production task are input into the preset monitoring classification model to determine the actual running state of each running equipment in executing the current production task.

[0105] Specifically, the progress information of each running equipment in the corresponding production task can be determined based on the task execution time of the running equipment. Through the progress information, the vibration state to which the running equipment belongs can be determined. For example, when the mixer is stirring to the middle stage of the task, the corresponding running vibration is mainly caused by the nonlinear torque fluctuation caused by the change of slurry viscosity, local agglomerate beating, unbalanced excitation of stirring paddle, and low-frequency resonance coupling of tank structure. At this stage, the mixer usually enters the middle and late stages of stable stirring stage, the motor speed remains constant, but the internal shear resistance of the slurry becomes the main excitation source, the vibration frequency is relatively concentrated but the energy may be intermittent. The monitoring classification model can determine whether the vibration of each running equipment in the current production task matches the corresponding progress information based on the multi-dimensional vibration information.

[0106] Further, please refer to Figure 5 and Figure 6 , Figure 5 is the spatial distribution of the frequency domain energy obtained from the scattering signal, Figure 6The spatial distribution of the time-domain energy of the scattered signal is obtained. As can be seen from the figure, the battery production line characterizes different vibration energy distributions on different running equipment. Based on the multi-dimensional vibration information of each running equipment and the progress information of the corresponding production task, after comparative analysis, the actual running state of the running equipment can be obtained. The actual running state can be characterized based on different abnormal vibration levels, for example, based on the abnormal vibration characteristics of the mixer, 6 vibration levels are set; for the abnormal vibration characteristics of the coating machine, 4 vibration levels are set, and the actual running state of each running equipment can be determined through the monitoring classification model.

[0107] It can be understood that the monitoring classification model can adopt a multi-layer classifier constructed based on supervised learning, and the input includes characteristic items such as vibration main frequency, vibration frequency band, energy spectrum density, and vibration source position, which is used to output the abnormal level label of each running equipment as the actual running state. Preferably, the monitoring classification model can adopt a random forest model, an LSTM time sequence model, or a lightweight neural network model with attention mechanism to improve the recognition ability of complex vibration patterns and the detection sensitivity of weak abnormalities.

[0108] S14、According to the actual running state of each running equipment, the interlocking running control of the production rhythm of the battery production line is performed.

[0109] Specifically, on the battery production line, by obtaining the real-time running state of each running equipment, such as the abnormal state level of abnormal vibration, the running rhythm and task execution speed of the associated running equipment before and after it are dynamically adjusted, so as to realize the linkage control and flexible response of the whole production line under abnormal conditions, and prevent the whole line from stagnating or the product quality from declining due to local abnormalities. For example, in the case of slight abnormality, the current production rhythm is maintained; in the case of moderate abnormality, the upstream and downstream equipment is run at a reduced speed; in the case of severe abnormality, the site is alarmed, and the alarm mode can be through sound and light alarm, etc.

[0110] Illustratively, step S14 includes sub-steps S14-1 to S14-2, which are specifically described as follows:

[0111] S14-1, determine the abnormal state level of the abnormal running equipment according to the actual running state of each running equipment. The abnormal state level can be determined based on the characteristics of each running equipment, for example, for the running state fluctuation which has greater impact on production quality, more dense abnormal state levels can be set, for example, 8-10 levels; for the running state fluctuation which has less impact on production quality, more sparse abnormal state levels can be set, for example, 3-5 levels.

[0112] S14-2, according to the abnormal state level and the preset operation adjustment curve, the adjacent operation equipment of the abnormal operation equipment is adjusted in operation rhythm, wherein the operation adjustment curve is a curve corresponding to the change of the operation rhythm of the equipment with the operation time under the abnormal state level. Since there is a dependent relationship between the production lines of the equipment, when one equipment is abnormal, the adjacent equipment before and after it needs to be adjusted in rhythm. In order to reduce the production quality problems caused by the fluctuation of the production rhythm, the operation equipment can be adjusted more smoothly in operation rhythm by setting the operation adjustment curve, so as to avoid the problems such as blockage caused by the continuous feeding of the upstream and accumulation caused by the stop of the upstream. It should be noted that the operation adjustment curve can be set based on the technical experience of the technical personnel or based on the calibration experiment, which can make the operation rhythm adjustment of the battery production line more stable.

[0113] Based on the same technical concept as the monitoring control method, the embodiment of the present application also provides a monitoring control system of an automatic production line, please refer to Figure 7 , Figure 7 is a structural schematic diagram of the control system. The control system comprises a monitoring terminal 701, a data processing terminal 702 and a control terminal 703.

[0114] The monitoring terminal 701 is used to emit pulsed laser to the monitoring optical cable of the battery production line and receive the feedback scattering signal, wherein the monitoring optical cable is an entire optical cable embedded in the load-bearing area along the length direction of each operation equipment of the battery production line.

[0115] The data processing terminal 702 is connected with the monitoring terminal 701, and the data processing terminal 702 is used to perform time-frequency analysis, time-space array analysis and frequency-domain space array analysis on the scattering signal, so as to obtain the multi-dimensional vibration information of each operation equipment of the battery production line, wherein the multi-dimensional vibration information comprises the vibration main frequency of the operation equipment and the vibration source position and energy spectrum density of the belonging load-bearing area; and input the multi-dimensional vibration information of each operation equipment and the progress information of the corresponding production task into a preset monitoring classification model, so as to determine the actual operation state of each operation equipment in executing the current production task.

[0116] The control terminal 703 is connected with the data processing terminal 702, and the control terminal 703 is used to perform interlocking operation control on the production rhythm of the battery production line according to the actual operation state of each operation equipment.

[0117] It should be noted that the above-mentioned embodiment sequence of the present application is only for description, and does not represent the advantages and disadvantages of the embodiment. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0118] The various embodiments described in this specification are presented by way of example, and each embodiment is not inherently more important than any other embodiment.

Claims

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comprises: The method comprises: The method comprises: According to the length and interval distance of all bearing areas, the relative delay duration and sampling point interval distance of the pulse laser are configured to implement pulse staggered emission, so as to reduce the sampling blind area of all bearing areas.

3. The monitoring control method of an automated production line according to claim 1, characterized in that, The path interference section represented in the node timing diagram of all nodes is analyzed to determine the effective emission period and effective receiving period of the pulse laser, including: The end station of the monitoring optical cable close to the battery production line is configured as the incident end of the pulse laser; The node timing diagram of the end station is used as a reference, and the running timing diagram of other running equipment is time-axis aligned; The node timing diagram after time-axis alignment is used to remove abnormal sections, and the intersection of the remaining time periods is marked as the effective emission period, and the period of the pulse laser delayed propagation in the effective emission period is marked as the effective receiving period.

4. The monitoring control method of an automated production line according to claim 1, characterized in that, The scattered signal is analyzed by a space-time array to obtain the vibration source position of the corresponding running equipment in the bearing area, including: According to the sampling time of the sampling point scattered signal covered by the running equipment, a space-time observation matrix of the corresponding running equipment is constructed; The adjacent space-time observation matrices of the same running equipment are time-delay estimated and time-aligned to determine whether the bearing area of the corresponding running equipment forms a wave front diffusion feature of a delay superposition beam; When it is determined that the bearing area of the corresponding running equipment forms a wave front diffusion feature of a delay superposition beam, the sampling point with the maximum superposition energy is determined as the vibration source position.

5. The monitoring control method of an automated production line according to claim 1, characterized in that, The scattered signal is analyzed by a space-time array to obtain the vibration source position of the corresponding running equipment in the bearing area, including: According to the preset environmental coupling vibration model, the scattered signal of the vibration area of each running equipment is processed to obtain the vibration observation value of each vibration sampling point in the vibration area of the corresponding running equipment; The frequency spectrum of the vibration observation value of each vibration sampling point is transformed to obtain the vibration energy of the corresponding vibration sampling point in the vibration area of the running equipment; The sum of all vibration energies of the running equipment in the vibration area is determined as the energy spectrum density, and the two-dimensional mapping result of all vibration energies in the vibration area is determined as the vibration distribution atlas.

6. The monitoring control method of an automated production line according to claim 5, characterized in that, According to the preset environmental coupling vibration model, the scattered signal of the vibration area of each running equipment is processed to obtain the vibration observation value of each vibration sampling point in the vibration area of the corresponding running equipment, including: According to the formula , obtain vibration sampling points At the moment Vibration observation value of , where is the discrete-time output matrix, is the discrete-time direct-feed matrix, Vibration sampling point At the moment The phase change represented by the scattered signal, Vibration sampling point At the moment The external excitation vector, Vibration sampling point At the moment The observed output noise.

7. The monitoring control method of an automated production line according to claim 1, characterized in that, According to the actual running state of each running equipment, the interlocking running control of the production beat of the battery production line is performed, including: The abnormal state level of the abnormal running equipment is determined according to the actual running state of each running equipment; The running beat of the adjacent running equipment of the abnormal running equipment is adjusted according to the abnormal state level and the preset running adjustment curve, wherein the running adjustment curve is a curve of the running beat of the equipment changing with running time under the corresponding abnormal state level.

8. A monitoring control system of an automated production line, characterized by, The system is used to implement the monitoring control method of any one of claims 1-7, and the system includes: A monitoring terminal is configured to emit pulsed laser to a monitoring optical cable and receive feedback scattered signals, wherein the monitoring optical cable is an entire optical cable embedded in a load-bearing area along a length direction of each operating device of a battery production line; A data processing terminal is connected to the monitoring terminal, and is configured to perform time-frequency analysis, time-space array analysis and frequency-domain space array analysis on the scattered signals to obtain multi-dimensional vibration information of each operating device of the battery production line, wherein the multi-dimensional vibration information includes a vibration main frequency of the operating device, a vibration source position and an energy spectrum density of the load-bearing area; and input the multi-dimensional vibration information of each operating device and progress information of a corresponding production task into a preset monitoring classification model to determine an actual operating state of each operating device in executing a current production task; A control terminal is connected to the data processing terminal, and is configured to perform interlocking operation control on a production tempo of the battery production line according to the actual operating state of each operating device.

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