Monitoring control method and system for automatic production line

Abstract

The invention relates to the technical field of production line monitoring control, in particular to a monitoring control method and system for an automatic production line. According to the technical scheme, the pulse laser is transmitted to the monitoring optical cable of the battery production line, and the feedback scattering signal is received; performing time-frequency analysis, space-time array analysis and frequency-domain space array analysis on the scattered signals to obtain multi-dimensional vibration information of each operation device of the battery production line; the multi-dimensional vibration information comprises the vibration main frequency of the operation equipment and the vibration source position and the energy spectrum density of the bearing area to which the operation equipment belongs, so that the actual operation state of each operation equipment during execution of the current production task can be determined based on the multi-dimensional vibration information of each operation equipment and the progress information of the corresponding production task; and performing interlocking operation control on the production takt of the battery production line according to the actual operation state of each operation device. According to the technical scheme, the stability of production control of a battery production line and the consistency of battery product quality are improved.

Description

Technical Field

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

[0002] As a new type of energy storage device, lithium-ion batteries 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 in the direction of high speed, high precision and full automation. The manufacturing process of lithium batteries usually includes multiple key process links such as pole piece manufacturing, battery cell assembly and chemical composition. Its process equipment is intensive, the operation rhythm is fast, and the product consistency and yield rate are extremely high.

[0003] During the operation of the lithium battery production line, in key processes such as rolling, slitting, lamination, winding, injection, and packaging, materials are transferred between various high-precision equipment through conveyor lines. Due to the high-speed movement and structural vibration between the equipment, it is easy to cause quality problems such as pole piece deviation, material curling, lamination alignment error, and even cause safety risks such as battery cell damage and line stoppage. Therefore, implementing status perception and real-time monitoring of each section of the production line, especially comprehensive perception and analysis of the operating vibration status of key equipment, is of great significance to ensure the stable operation of the production line and improve product quality.

[0004] At present, common equipment status monitoring methods are mainly based on single sensor means such as accelerometers, strain gauges, cameras or current detection. These methods are mostly point-based, with limited monitoring coverage, resulting in insufficient accuracy in abnormal identification and unable to meet the needs of lithium battery intelligent manufacturing for global perception and predictive maintenance. Summary of the invention

[0005] In order to solve the technical problem that the status of the running equipment on the automated battery production line cannot be perceived in real time, causing the battery production rhythm to be disrupted. The purpose of the present invention is to provide a monitoring and control method and system for an automated production line, which improves the stability of the battery production line production control and the consistency of the battery product quality. The technical solutions adopted are as follows: In a first aspect, an embodiment of the present invention provides a monitoring and control method for an automated production line, the method comprising: The monitoring optical cable of the battery production line emits a pulsed laser and receives the feedback scattered signal, wherein the monitoring optical cable is a whole optical cable pre-buried in the load-bearing area along the length direction of each running equipment of the battery production line; 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 equipment in the battery production line, where the multi-dimensional vibration information includes the vibration main frequency of the operating equipment and the vibration source position and energy spectrum density of the load-bearing area to which it belongs; Input the multi-dimensional vibration information of each running equipment and the progress information of its corresponding production task into a preset monitoring classification model to determine the actual operating status of each running equipment in executing the current production task; According to the actual operating status of each operating equipment, the production rhythm of the battery production line is interlocked and controlled.

[0006] In an optional embodiment, before emitting a pulsed laser to the monitoring optical cable of the battery production line and receiving the fed-back scattered signal, the method further includes: According to the length of the monitoring optical cable in the load-bearing area of each operating equipment in the battery production line, the pulse width of the pulse laser is configured so that the spatial resolution of monitoring each operating equipment meets the preset range; The pulse interval of the pulse laser is configured according to the one-way length of the monitoring optical cable so that the back Rayleigh scattering of the pulse laser does not cause aliasing in the time domain; According to the area length and spacing distance of all load-bearing areas, the relative delay time of pulse laser to implement pulse interleaving emission and the spacing distance of sampling points are configured to reduce the sampling blind area of all load-bearing areas.

[0007] In an optional embodiment, emitting a pulsed laser to a monitoring optical cable of a battery production line and receiving a feedback scattered signal include: Obtain the node timing diagram of each running device when executing the current production task; Analyze the path interference segments represented in the timing diagrams of all nodes to determine the effective emission period and effective reception period of the pulsed laser; The pulse laser is emitted during the effective emission period, and the scattered signal is received during the effective reception period.

[0008] In an optional embodiment, the path interference segments represented in all node timing diagrams are parsed to determine the effective emission period and the effective reception period of the pulsed laser, including: Configure the end station of the monitoring optical cable close to the battery production line as the incident end of the pulsed laser; Using the node timing diagram of the end station as a reference, align the time axis of the operation timing diagrams of other running equipment; The abnormal segments of the node timing diagram after the time axis alignment are eliminated, and the intersection of the remaining time periods is marked as the effective transmission period, and the period of delayed propagation of the pulse laser in the effective transmission period is marked as the effective reception period.

[0009] In an optional embodiment, the scattered signal is subjected to time-frequency analysis, time-space array analysis, and frequency-domain space array analysis to obtain multi-dimensional vibration information of each operating device in the battery production line, including: Perform time-frequency analysis on the scattered signal to obtain the main vibration frequency, vibration frequency band, and vibration change curve of the corresponding operating device, where the vibration change curve is the curve of the vibration frequency of the operating device changing with the monitoring time; Perform spatio-temporal array analysis on the scattered signal to obtain the vibration source position of the corresponding operating device in its bearing area, where multiple vibration sampling points are configured in the bearing area of each operating device; Perform spatial array analysis on the scattered signal to obtain the energy spectral density and vibration distribution map of the corresponding operating device in its bearing area; Determine the main vibration frequency, vibration frequency band, vibration change curve, vibration source position, energy spectral density, and vibration distribution map as the multi-dimensional vibration information of the corresponding operating device.

[0010] In an alternative embodiment, performing spatio-temporal array analysis on the scattered signal to obtain the vibration source position of the corresponding operating device in its bearing area includes: Construct a spatio-temporal observation matrix for the corresponding operating device according to the sampling time of the scattered signal at the sampling points covered by the operating device; Perform time delay estimation and time alignment processing on adjacent spatio-temporal observation matrices of the same operating device to determine whether the wavefront diffusion characteristics of a delayed superposition beam are formed in the bearing area of the corresponding operating device; When it is determined that the wavefront diffusion characteristics of a delayed superposition beam are formed in the bearing area of the corresponding operating device, determine the sampling point with the maximum superposition energy as the vibration source position.

[0011] In an alternative embodiment, performing spatial array analysis on the scattered signal to obtain the energy spectral density and vibration distribution map of the corresponding operating device in its bearing area includes: Process the scattered signal in the vibration area of each operating device according to a preset environmental coupling vibration model to obtain the vibration observation values of all vibration sampling points of the corresponding operating device in its vibration area; Perform spectral transformation on the time-varying sequence of the vibration observation value of each vibration sampling point to obtain the vibration energy of the corresponding vibration sampling point of the operating device in its vibration area; Determine the summation result of all vibration energies of the operating device in its vibration area as the energy spectral density, and determine the two-dimensional mapping result of all vibration energies in its vibration area as the vibration distribution map.

[0012] In an alternative embodiment, processing the scattered signal in the vibration area of each operating device according to a preset environmental coupling vibration model to obtain the vibration observation values of all vibration sampling points of the corresponding operating device in its vibration area includes: According to the formula , obtain the vibration sampling point At the moment The vibration observation value of 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.

[0013] In an optional embodiment, according to the actual operating status of each operating device, the interlocking operation control of the production rhythm of the battery production line is performed, including: Determine the abnormal status level of the abnormally operating equipment according to the actual operating status of each operating equipment; According to the abnormal state level and the preset operation adjustment curve, the operation rhythm of the adjacent operating equipment of the abnormal operating equipment is adjusted, wherein the operation adjustment curve is a curve showing the change of the equipment operation rhythm with the operating time under the corresponding abnormal state level.

[0014] In a second aspect, an embodiment of the present invention further provides a monitoring and control system for an automated production line, the system comprising: The monitoring terminal is used to emit pulsed laser to the monitoring optical cable of the battery production line and receive the feedback scattered signal, wherein the monitoring optical cable is a whole optical cable pre-buried in the load-bearing area along the length direction of each running equipment of the battery production line; The data processing terminal is connected to the monitoring terminal. The data processing terminal is used 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 running equipment of the battery production line, wherein the multi-dimensional vibration information includes the vibration main frequency of the running equipment and the vibration source position and energy spectrum density of the load-bearing area to which it belongs; and input the multi-dimensional vibration information of each running equipment and the progress information of its corresponding production task into a preset monitoring classification model to determine the actual operating status of each running equipment in executing the current production task; The control terminal is connected to the data processing terminal. The control terminal is used to perform interlocking operation control of the production rhythm of the battery production line according to the actual operating status of each operating equipment.

[0015] The present invention has the following beneficial effects: The technical solution of the present invention emits pulsed laser through the monitoring optical cable of the battery production line and receives the reflected scattered signal; performs time-frequency analysis, spatio-temporal array analysis, and frequency-domain spatial array analysis on the scattered signal to obtain multi-dimensional vibration information of each operating device on the battery production line; since the multi-dimensional vibration information includes the main vibration frequency of the operating device, the vibration source position and energy spectral density of the corresponding load-bearing area, the actual operating state of each operating device during the execution of the current production task can be determined based on the multi-dimensional vibration information of each operating device and the progress information of the corresponding production task; according to the actual operating state of each operating device, interlocking operation control of the production rhythm of the battery production line is carried out. This technical solution can achieve overall perception during the automatic operation of the battery production line, realize interlocking operation control of the production rhythm, make the rhythm of the battery production line more orderly, and thus improve the stability of the production control of the battery production line and the consistency of the battery product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 It is a flowchart of a monitoring and control method for an automated production line provided by an embodiment of the present invention; Figure 2 It is a layout schematic diagram of a battery production line provided by an embodiment of the present invention; Figure 3 It is a structural schematic diagram of a coherent detection Φ-OTDR system provided by an embodiment of the present invention; Figure 4 It is a schematic diagram of the principle of performing frequency-domain spatial array analysis on the scattered signal provided by an embodiment of the present invention; Figure 5 It is a schematic diagram of the spatial distribution of frequency-domain energy provided by an embodiment of the present invention; Figure 6 It is a schematic diagram of the spatial distribution of time-domain energy provided by an embodiment of the present invention; Figure 7 It is a structural schematic diagram of a monitoring and control system for an automated production line provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the monitoring and control method and system of an automated production line proposed by the present invention, its specific implementation, structure, features and effects, in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0019] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0020] At present, automated production lines such as lithium batteries usually use independent sensors (such as accelerometers, displacement sensors, and current sensors) to monitor the operating status of a certain operating device. This type of monitoring method has limited spatial coverage, and information islands are formed between the operating devices. When a certain operating device is abnormal, the production rhythm is easily disturbed due to the lag in the beat adjustment control, resulting in insufficient quality stability of battery product production. The following is a specific scheme of a monitoring and control method and system for an automated production line provided by the present invention, which is specifically described in conjunction with the accompanying drawings.

[0021] See also Figure 1 , Figure 1 This is a flow chart of a monitoring and control method for an automated production line provided by an embodiment of the present invention. The monitoring and control method can be applied to the operation of the master controller of the automated production line. The master controller can be an industrial computer or other types of control equipment or terminals. It only needs to be able to run the method, and no specific restrictions are made here. The control method includes: S11. Emitting pulsed laser to the monitoring optical cable of the battery production line and receiving the feedback scattered signal, wherein the monitoring optical cable is a whole optical cable pre-buried in the load-bearing area along the length direction of each operating equipment of the battery production line.

[0022] For details, please refer to Figure 2 , Figure 2It is a layout schematic diagram of a battery production line. The operating equipment of the battery production line includes a mixer, a coater, a roll press, a slitter, a stacker (or winder), a welder, a packager, and a testing device, which are arranged in the order of production. The mixer is used to prepare slurry from raw materials such as active materials, conductive agents, and binders, and it is the starting process of the whole line; the coater is used to evenly coat the positive and negative electrode slurries on the surface of metal foil, with strict control over thickness and uniformity; the roll press compacts the coated electrode sheets mechanically to improve their volumetric energy density; the slitter is used to cut the whole roll of electrode sheets into single pieces according to the designed specifications; the stacker stacks or winds the positive and negative electrode sheets and the separator in a certain order to form an electric core; the welder is used for welding treatment at positions such as tab ears and lead-out ends; the packager is used for injecting electrolyte, encapsulating the housing, and vacuum treatment of the electric core to complete the preparation of the battery; the testing device is used for functional tests such as internal resistance testing and charge-discharge aging of the prepared battery. In the whole battery production line, each operating device is an independent operating unit, but they must be highly linked in the production rhythm to ensure the safety of the production process and the quality of the battery. High-precision and non-interfering monitoring of the operating status of these operating devices is the key to ensuring the continuity of the whole battery production line and the control of product consistency.

[0023] A phase-sensitive optical fiber cable can be selected as the monitoring optical fiber cable to monitor the operating status of the battery production line. The monitoring optical fiber cable is buried along the ground of the battery production line and is located below the equipment base. U-shaped grooves can be opened in the load-bearing areas of each operating device, and the monitoring optical fiber cable is laid in the U-shaped grooves and fixed by pouring cement. The monitoring optical fiber cable needs to cover the load-bearing structure areas of each operating device, that is, the areas where vibration is most easily coupled. The load-bearing areas include structural sites such as equipment feet, chassis steel beams, and anchor bolt connection points. The load-bearing areas of each operating device and the optical fiber cable position 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 equipment attribution analysis.

[0024] Please refer to Figure 3 , Figure 3It is a schematic structural diagram of a coherent detection Φ-OTDR (Phase Sensitive Optical Time Domain Reflectometry) system, which specifically includes 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 outward, and outputs 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 to output pulsed laser light, and then outputs to the monitoring optical cable through the erbium-doped fiber amplifier and the filter. When there is vibration in the operating equipment of the battery production line, the vibration is conducted to the monitoring optical cable to form a scattered signal, which is backscattered to the second coupler through the optical circulator. The scattered signal and the laser signal of the reference arm reach the balanced photodetector through the second coupler. 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. After the processing terminal performs processing, it determines the actual operating state of each operating equipment.

[0025] When implementing the monitoring of the battery production line, due to the large number of operating equipment involved and the long length of the monitoring optical cable, if the configured monitoring parameters are unreasonable, the backscattering of multiple pulsed laser lights will be aliased on the time axis, and it may be impossible to restore the true spatial response of the backscattering. Based on this, in a specific implementation manner, the control method further includes parameter configuration for the Φ-OTDR system.

[0026] In the Φ-OTDR system, the pulse width of the pulsed laser light determines the expansion of the scattered signal echo in the time domain, which in turn affects the spatial resolution of the system. Therefore, it is necessary to configure the pulse width of the pulsed laser light according to the laying length of the monitoring optical cable in the load-bearing area of each operating equipment in the battery production line, so that the spatial resolution of the monitoring of each operating equipment meets the preset range. There is an association between the pulse width and 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 load-bearing area of the operating equipment contains multiple vibration sampling points, and the positioning accuracy of the vibration source meets the monitoring requirements. It can be understood that the laying length of the optical cable in each load-bearing area matches the pulse width, which can enable the monitoring to resolve the vibration source of the operating equipment with a preset spatial accuracy and avoid spatial ambiguity.

[0027] Configure the pulse interval time of the pulsed laser light according to the one-way laying length of the monitoring optical cable, so that the backscattering of the pulsed laser light does not occur aliasing in the time domain. A reasonable pulse interval time can make the analysis of the backscattering more accurate, ensure that all the backscattering signals of the previous pulse return before the next pulsed laser light is emitted; avoid the overlap of multi-pulse signals on the time axis, resulting in misjudgment or energy analysis distortion.

[0028] According to the regional lengths and interval distances of all load-bearing areas, configure the relative delay duration and sampling point interval distance for the pulsed laser to implement pulsed interleaved emission, so as to reduce the sampling blind areas of all load-bearing areas. By staggering the time domain intervals, all spatial segments on the optical fiber are at least covered by a laser beam once; at the same time, adjust the sampling point interval distance to make the signal sampling distribution density of each area balanced.

[0029] Specifically, at the first frequency inject into the monitoring optical cable with a total length of equally intense detection laser pulses with a pulse width of (unit: ns). The second frequency of data acquisition card sampling is . According to the basic principle of the external coherent detection Φ-OTDR system, the observed data matrix can be obtained:

[0030]

[0031] Among them, is the scattering response result in the time dimension and the spatial dimension, which can characterize the vibration energy at the th sampling moment and the th sampling position. is the time dimension, is the spatial dimension; is the propagation speed of light 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; is the optical frequency shift introduced by the acousto-optic modulator; is the phase deviation brought by the reference light and can be obtained based on the laser signal of the reference arm; is the differential distance of laser transmission; is the length value used to identify the position of the vibration sampling point in the monitoring optical cable; , are respectively the amplitude and phase modulation means of the optical fiber scattering points in the length interval at the time interval.

[0032] To avoid the aliasing of multiple pulsed backscattering signals, there is ; to ensure that the vibration at any point within the monitoring range can be captured by more than 1 sampling point and avoid forming a monitoring hole blind area in space, there is , that is:

[0033] As can be seen from the above formula, based on reasonable parameter configuration, it is possible to record the changes in the backward Rayleigh scattering signals of each operating device at different time and space positions during the operation of the battery production line under pulse excitation. Further combining the differential structure or phase change relationship between adjacent spatial positions defined by the formula, multi-dimensional features such as the vibration frequency characteristics, energy spectral density, wavefront propagation trend, and source point position of each operating device within its load-bearing area can be extracted, constituting the key inputs of the monitoring classification model.

[0034] Exemplarily, step S11 includes sub-steps S11-1 to S11-3, which are specifically described as follows: S11-1. Obtain the node timing diagram of each operating device during the execution of the current production task. On the battery production line, the mixer can be configured as a stirring tank structure. At the initial stage of startup, the rotation speed increases rapidly, and mechanical vibration is significant. There is strong mechanical vibration in the initial stage of stirring; as the stirring time extends, the vibration gradually subsides and then tends to be stable. Based on the different states of the mixer during the stirring task, its node timing diagram can be obtained. Taking the coater as an example, when the new pole piece enters the line at the head, it starts to vibrate when pulled. There is vibration sampling interference at the moment when the doctor blade contacts. As the coating progresses, the vibration gradually becomes stable. Based on the vibration change characteristics of the coater during the coating process, the corresponding node timing diagram can be drawn up. Through the vibration change characteristics of each operating device during the execution of the corresponding production task, the corresponding node timing diagram can be obtained.

[0035] S11-2. Analyze the path interference segments characterized in all the node timing diagrams to determine the effective emission period and effective reception period of the pulsed laser. The path interference segment is the time period during which there is interference with vibration acquisition during the operation of each operating device, and it can be marked based on the interference intensity. The path interference segment is excluded when implementing the acquisition of the scattering signal. For example, during the initial stage of stirring of the mixer, the mixing paddle, main shaft, and tank support structure generate large vibrations, stress rebounds, and energy coupling during the startup of the motor and the high-speed rotation of the slurry, which will cause a large number of irregular phase disturbances in the monitoring optical cable and interfere with the normal sampling of the device state. Due to the large vibration, it interferes with the acquisition of the scattering signal. The time period of 10 s after the start of stirring can be defined as the path interference segment. By analyzing all the path interference segments, the effective emission period and effective reception period of the pulsed laser can be obtained.

[0036] Exemplarily, sub-step S11-2 includes: In the first step, configure the end station of the monitoring optical cable close to the battery production line as the incident end of the pulsed laser. The pulsed laser enters the monitoring optical cable from the end station, which can minimize the vibration interference of upstream operating equipment. The pulsed laser will first pass through the end station and then propagate successively to the upstream operating equipment. When analyzing, only the path interference caused by downstream operating equipment needs to be considered, enabling more comprehensive monitoring of the battery production line and a clearer logic for subsequent analysis.

[0037] In the second step, based on the node timing diagram of the end station, align the timing diagrams of other operating equipment along the time axis. Since the tasks performed by each operating equipment are different, the corresponding operating rhythms may not be consistent. To construct a common reference time axis for the entire line, the cycle of one operating equipment must be used as a reference benchmark; the end station, being at the forefront of the sampling path with all interference behind it, can serve as a stable reference; aligning the time axis can normalize the operating rhythms (paths including interference segments) of all operating equipment into a unified cycle coordinate system.

[0038] In the third step, eliminate the abnormal segments from the node timing diagrams with the time axis aligned, mark the intersection of the remaining time periods as the effective emission period, and mark the period of the delayed propagation of the pulsed laser during the effective emission period as the effective reception period. Overlay all the aligned node timing diagrams; in a certain time period, if any operating equipment on the path is in the path interference segment, that moment is determined as a non - emission period. The overlapping period when all operating equipment on all paths is in a non - violently disturbed state is the effective emission period. During the effective emission period, the Φ - OTDR system can emit pulsed laser; during the effective reception period, scattered signals can be received to enable the subsequent accurate analysis of the received scattered signals. In addition, the determination of the effective reception period also needs to combine the laser propagation and echo delay time to derive an effective reception time window.

[0039] S11 - 3. Emit pulsed laser during the effective emission period and receive the scattered signals during the effective reception period. Since the scattered signals are an important basis for subsequent signal analysis, emitting the pulsed laser into the monitoring optical cable during the effective emission period can avoid the pulsed laser passing through high - vibration equipment during the propagation path, such as the start - up periods of mixers and roll presses, which may cause laser scattering and interference superposition, significantly improving the signal - to - noise ratio and structural identifiability of the sampled data, avoiding the influence of path interference on the extraction of vibration source characteristics, and thus ensuring the accuracy of the determination of the operating equipment state.

[0040] At this point, the scattered signals of the battery production line have been accurately obtained, and then proceed to step S12 for signal analysis.

[0041] S12. Perform time-frequency analysis, spatio-temporal array analysis, and frequency-domain spatial array analysis on the scattered signals to obtain multi-dimensional vibration information of each operating device on the battery production line. The multi-dimensional vibration information includes the main vibration frequency of the operating device, the vibration source position, and the energy spectral density of the load-bearing area to which it belongs.

[0042] Specifically, by performing time-frequency analysis on the scattered signals, the variation characteristics of the vibration of the corresponding operating device in the time-frequency domain can be determined, and the main vibration frequency can be obtained through statistics. Based on the time series of vibration sampling points in each load-bearing area, time-frequency analysis can be implemented using the short-time Fourier transform and wavelet packet decomposition to obtain the occurrence times of each frequency point. The frequency point with the most occurrences is defined as the main frequency point, and the distribution of the main frequency points can be statistically analyzed to obtain the main vibration frequency of each operating device. Based on the phase propagation or signal delay between spatially adjacent sampling points, the time-delay estimation method is used to determine the position point in the load-bearing area with the minimum delay and the maximum energy, indicating that this position is the vibration source position of the load-bearing area to which it belongs. Through frequency-domain spatial array analysis, the energy spectral density of the corresponding operating device can be obtained, and the energy accumulation characteristics of the operating device in the bearing area can be obtained.

[0043] Exemplarily, step S12 includes sub-steps S12-1 to S12-3, which are specifically described as follows: S12-1. Perform time-frequency analysis on the scattered signals to obtain the main vibration frequency, vibration frequency band, and vibration variation curve of the corresponding operating device. The vibration variation curve is a curve of the vibration frequency of the operating device changing with the monitoring time. After receiving the scattered signals, filtering processing can be performed first, and then the time-frequency spectrum of each vibration sampling point can be calculated. The time-frequency spectrum is a curve spectrum of the vibration frequency changing with the sampling time. The frequency with the highest energy at each moment of the time-frequency spectrum is extracted as the main vibration frequency; the vibration frequency band is obtained based on the fluctuation of the main vibration frequency; based on the curve of the main vibration frequency of each vibration sampling point changing with time, the vibration variation curve is obtained. Through the vibration variation curve, characteristics such as frequency drift and jump during device startup, load change, or pre-fault can be reflected.

[0044] S12-2. Perform spatio-temporal array analysis on the scattered signals to obtain the vibration source position of the corresponding operating device in its load-bearing area. Multiple vibration sampling points are configured in the load-bearing area of each operating device. There are multiple vibration sampling points in the load-bearing area of each operating device. The specific position of the excitation source on the device base or key support structure can be located through array signal processing, or spatio-temporal array analysis can be implemented based on a data processing model, as long as the vibration source position can be resolved, and no specific restrictions are imposed here.

[0045] Specifically, performing spatio-temporal array analysis on the scattered signals includes: The first step is to construct a spatio-temporal observation matrix of the corresponding operating device based on the sampling time of the scattered signals of the sampling points covered by the operating device. It can be based on the observation data matrix The calculation logic yields the vibration energy at the th sampling moment and the

[0046] th sampling position, and then obtains the spatio-temporal observation matrix of each operating device. Each element in the spatio-temporal observation matrix can be vibration energy or the phase change amount of the pulsed laser. Through each element in the spatio-temporal observation matrix, the backscattering intensity of the pulsed laser at the corresponding vibration sampling point can be characterized, or the phase shift generated by the vibration sampling point relative to the reference light after coherent (or differential interference) demodulation can be characterized.

[0047] In the second step, perform time delay estimation and time alignment processing on adjacent spatio-temporal observation matrices of the same operating device to determine whether the wavefront diffusion characteristics of the delayed superposition beam are formed in the load-bearing area to which the corresponding operating device belongs. The wavefront diffusion characteristic (or vibration wavefront diffusion) refers to the phenomenon that in a distributed fiber optic sensing system, a single excitation event no longer only presents as an ideal sharp wavefront instantaneously passing through a certain point, but as the wave propagates in the fiber or structure, affected by multiple factors such as refraction, scattering, coupling, and medium dispersion, the wavefront gradually broadens, blurs, and spreads around in space and time. In order to reveal the true delay of the vibration wavefront propagating in space, it is necessary to perform time delay estimation and unified alignment on the signals of adjacent channels in the spatio-temporal observation matrix. Specifically, it includes selecting one of the vibration sampling points as the reference channel, calculating the cross-correlation function between each adjacent channel and the reference channel respectively or using the phase transformation cross-correlation method, and estimating the relative time delay from the position of the cross-correlation peak; translating the time series of each channel along the time axis according to the estimated time delay and fine-tuning it through interpolation filtering, so as to align the same excitation wavefront of all channels in time. After completion of the alignment, any row in the entire matrix corresponds to the response of the same wavefront at each spatial sampling point, thus providing a basic data structure with consistent time series and spatial synchronization for subsequent delayed superposition beam formation processing, enabling the vibration source localization and spatial energy focusing to achieve the maximum accuracy under the same excitation event.

[0048] Taking the start-up of a mixer as an example, when the mixer starts, the primary shock wave generated by the mixing paddle initially forms a sharp strain disturbance on the monitoring optical cable. However, after reflection by the frame structure, elastic coupling of the foundation bolts, and acoustic scattering, the original shock wave packet is stretched to a width of dozens of milliseconds within a certain range, and multiple echoes are superimposed within a larger range, resulting in the wavefront in the backscattering being dispersed into a fan-shaped spatio-temporal distribution. Based on this wavefront diffusion phenomenon, the position of the vibration source is determined.

[0049] S12-3. Perform spatial array analysis on the scattered signals to obtain the energy spectral density and vibration distribution map of the corresponding operating equipment in its bearing area. The energy spectral density can be calculated for each vibration sampling point in the bearing area of each operating equipment, and the energies of each sampling point can be accumulated as the total energy spectral density of the bearing area of this equipment. A spatial heat map is drawn based on the position of each vibration sampling point at the center of the frequency band, with the abscissa being the position and the ordinate being the frequency or energy value, forming a two-dimensional vibration distribution map.

[0050] Specifically, performing spatial array analysis on the scattered signals includes: The first step is to process the scattered signals in the vibration area of each operating equipment according to the preset environmental coupling vibration model to obtain the vibration observation values of all vibration sampling points of the corresponding operating equipment in its vibration area. As can be seen from the above formula, the Φ-OTDR system can achieve vibration signal monitoring of each point on the monitoring optical cable within a length range with a spatial resolution (the actual resolution is ), within the frequency range; where is the lowest observable frequency affected by system noise. Since the light transmitted in the optical fiber decays exponentially with distance, the amplitude of the observed signal also decays exponentially with distance. Its phase reflects the dynamic strain scalar generated by the vibration at each point of the optical fiber in the axial direction of the optical fiber, which is quite different from the triaxial vibration three-component vector signal measured by traditional triaxial acceleration sensors. Moreover, the pre-buried method of the monitoring optical cable will generate different vibration coupling forms with the environment. on the monitoring optical cable within the range of ; among them For the principle schematic diagram of the frequency-domain spatial array analysis of the scattered signals, please refer to

[0051] Please refer to Figure 4 , Figure 4 . Monitoring optical cables with different laying methods receive specific excitations containing environmental noise, forming an optical fiber-environment coupling vibration system. Its state at the previous moment and the current moment's noise-containing excitation together affect the noise-containing observed signals 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.

[0052] There is a relational expression , where Represents a time-discrete quantity, represents 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 the system input noise, is the responsivity of the Φ-OTDR system, is the time difference between adjacent sampling periods.

[0053] According to the formula , the vibration sampling points are obtained At the moment The vibration observation value, where, is a discrete-time output matrix, is a discrete-time direct feed matrix, is the vibration sampling point At the moment The phase change amount characterized by the scattered signal, is the vibration sampling point At the moment The external excitation vector, is the vibration sampling point At the moment The observed output noise.

[0054] Second step, perform a spectral transformation on the time-varying sequence of the vibration observation values of each vibration sampling point to obtain the vibration energy of the operating equipment at the corresponding vibration sampling points in the vibration region. Further, please continue to refer to Figure 4 , the environmental coupling vibration model is processed based on input noise, system parameters, excitation, and vibration state, etc., to obtain the actual vibration state , combine the discrete-time direct feed matrix, discrete-time output matrix, and observation noise to obtain the vibration observation value, and obtain the actual observation value based on the observation model and sensing parameters. There are the following specific relationships , based on this formula, the vibration energy of the vibration sampling point can be calculated , , is the number of relevant vibration sampling points, , which can be 2-3 vibration sampling points near the vibration sampling point .

[0055] Furthermore, the range of the discrete-time state matrix , and the discrete-time input matrix can be limited. There are the following relationships: ; ; , , are the mass matrix, damping matrix and stiffness matrix respectively.

[0056] The third step is to determine the energy spectrum density by summing up all the vibration energies of the running equipment in the vibration area to which it belongs, and to determine the vibration distribution spectrum by the two-dimensional mapping results of all the vibration energies in the vibration area to which it belongs. 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 spectrum according to its spatial position, which is used to reflect the spatial response characteristics of the equipment's operating status and realize the identification and early warning of high energy density concentrated areas.

[0057] S12-4, determine the vibration main frequency, vibration frequency band, vibration change curve, vibration source position, energy spectrum density and vibration distribution map as the multi-dimensional vibration information of the corresponding operating equipment. The various types of data in the multi-dimensional vibration information characterize the vibration conditions of the corresponding operating equipment from different dimensions. Each type of data can be assigned a corresponding variable name to construct a mapping relationship between each operating equipment and various data in the multi-dimensional vibration information, which is convenient for subsequent processing.

[0058] At this point, the multi-dimensional vibration information of each running device has been obtained, and then the process goes to step S13.

[0059] S13, inputting the multi-dimensional vibration information of each running device and the progress information of its corresponding production task into a preset monitoring classification model to determine the actual operating status of each running device in executing the current production task.

[0060] Specifically, the progress information of each operating equipment in the corresponding production task can be determined based on the task execution time of the operating equipment. The vibration state of the operating equipment can be determined through the progress information. For example, when the mixer is stirring to the middle of the task, the corresponding operating vibration mainly comes from the nonlinear torque fluctuation caused by the change of slurry viscosity, the impact of local agglomerates, the unbalanced excitation of the stirring paddle, and the low-frequency resonance coupling of the tank structure. This stage usually enters the middle and late stages of the stable stirring stage. The motor speed remains constant, but the fluctuation of the shear resistance inside the slurry becomes the main excitation source. The vibration frequency is relatively concentrated, but the energy may be intermittently enhanced. The monitoring classification model can determine whether the vibration of each operating equipment in the current production task matches the corresponding progress information based on multi-dimensional vibration information.

[0061] For further information, see Figure 5 and Figure 6 , Figure 5 The spatial distribution of frequency domain energy obtained for the scattered signal, Figure 6The spatial distribution of the time-domain energy obtained from the scattered signals. As can be seen from the figure, the battery production line exhibits different vibration energy distributions on different operating devices. Based on the multi-dimensional vibration information of each operating device and the progress information of the corresponding production tasks, after implementing a comparative analysis, the actual operating state of the operating device can be obtained. The actual operating state can be characterized based on different abnormal vibration levels. For example, based on the abnormal vibration characteristics of the blender, 6 vibration levels are set for it; for the abnormal vibration characteristics of the coater, 4 vibration levels are set for it. The actual operating state of each operating device can be determined through the monitoring classification model.

[0062] It can be understood that the monitoring classification model can adopt a multi-layer classifier constructed based on supervised learning. The inputs include feature items such as the main vibration frequency, vibration frequency band, energy spectral density, and vibration source position, and are used to output the abnormal level label of each operating device as the actual operating state. Preferably, the monitoring classification model can adopt a random forest model, an LSTM time series model, or a lightweight neural network model integrating an attention mechanism to improve the recognition ability of complex vibration patterns and the detection sensitivity to weak abnormalities.

[0063] S14. Perform interlocking operation control of the production rhythm of the battery production line according to the actual operating state of each operating device.

[0064] Specifically, on the battery production line, by obtaining the real-time operating state of each operating device, such as the abnormal state level of abnormal vibration, dynamically adjust the operating rhythm and task execution speed of its front and rear associated operating devices, so as to achieve the linkage control and flexible response of the entire production line in case of abnormalities, and prevent the entire line from stagnating or the product quality from deteriorating due to local abnormalities. For example, when there is a slight abnormality, maintain the current production rhythm; when there is a moderate abnormality, slow down the upstream and downstream devices; when there is a severe abnormality, give an alarm on site, and the alarm method can be through sound and light alarms, etc.

[0065] Exemplarily, step S14 includes sub-steps S14-1 to S14-2, which are specifically described as follows: S14-1. Determine the abnormal state level of the abnormal operating device according to the actual operating state of each operating device. The abnormal state level can be determined based on the characteristics of each operating device. For example, for those with a greater impact on production quality due to fluctuations in the operating state, more intensive abnormal state levels can be set, such as setting 8-10 levels; for those with a smaller impact on production quality due to fluctuations in the operating state, more sparse abnormal state levels can be set, such as setting 3-5 levels.

[0066] S14-2. According to the abnormal state level and the preset operation adjustment curve, the operation rhythm of the adjacent operating equipment of the abnormal operating equipment is adjusted, wherein the operation adjustment curve is a curve showing the change of the equipment operation rhythm with the operating time under the corresponding abnormal state level. Since there is a dependency relationship between the production line processes between the operating equipment, when a device is abnormal, the adjacent equipment before and after it needs to adjust the rhythm. In order to reduce the production quality problems caused by fluctuations in the production rhythm, the operation adjustment curve can be set to make the operating equipment adjust the operation rhythm more smoothly, avoiding problems such as blockage caused by continued upstream feeding and backlog caused by stopping upstream material collection. It should be noted that the operation adjustment curve can be set based on the technical experience of the technicians, or it can be set based on calibration experiments, as long as the operation rhythm of the battery production line can be adjusted more smoothly.

[0067] Based on the same technical concept as the monitoring and control method, the embodiment of the present invention also provides a monitoring and control system for an automated production line, see Figure 7 , Figure 7 Schematic diagram of the control system. The control system includes a monitoring terminal 701, a data processing terminal 702 and a control terminal 703.

[0068] The monitoring terminal 701 is used to emit pulsed laser to the monitoring optical cable of the battery production line and receive the feedback scattered signal, wherein the monitoring optical cable is a whole optical cable pre-buried in the load-bearing area along the length direction of each operating equipment of the battery production line.

[0069] The data processing terminal 702 is connected to the monitoring terminal 701. The data processing terminal 702 is used to perform time-frequency analysis, time-space array analysis and frequency-domain space array analysis on the scattered signal to obtain multi-dimensional vibration information of each operating equipment in the battery production line, wherein the multi-dimensional vibration information includes the vibration main frequency of the operating equipment and the vibration source position and energy spectrum density of the load-bearing area to which it belongs; and the multi-dimensional vibration information of each operating equipment and the progress information of its corresponding production task are input into a preset monitoring classification model to determine the actual operating status of each operating equipment in executing the current production task.

[0070] The control terminal 703 is connected to the data processing terminal 702, and the control terminal 703 is used to perform interlocking operation control of the production rhythm of the battery production line according to the actual operation status of each operating device.

[0071] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0072] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

Claims

1. A monitoring and control method for an automated production line, characterized in that, The method includes: Emitting pulsed laser light to the monitoring optical cable of the battery production line and receiving the feedback scattered signal, wherein the monitoring optical cable is the entire optical cable embedded in the load-bearing area along the length direction of each operating device on the battery production line; Performing time-frequency analysis, spatio-temporal array analysis, and frequency-domain spatial array analysis on the scattered signal to obtain multi-dimensional vibration information of each operating device on the battery production line, wherein the multi-dimensional vibration information includes the main vibration frequency of the operating device, the vibration source position and energy spectral density of the affiliated load-bearing area; Inputting the multi-dimensional vibration information of each operating device and the progress information of its corresponding production task into a preset monitoring classification model to determine the actual operating state of each operating device when executing the current production task; Performing interlocking operation control of the production rhythm on the battery production line according to the actual operating state of each operating device.

2. The monitoring and control method of the automated production line according to claim 1, characterized in that, Before emitting pulsed laser light to the monitoring optical cable of the battery production line and receiving the feedback scattered signal, the method further includes: Configuring the pulse width of the pulsed laser according to the laying length of the monitoring optical cable in the load-bearing area of each operating device on the battery production line, so that the spatial resolution of the monitoring of each operating device meets a preset interval; Configuring the pulse interval time of the pulsed laser according to the one-way laying length of the monitoring optical cable, so that the backward Rayleigh scattering of the pulsed laser does not overlap in the time domain; Configuring the relative delay duration and sampling point interval distance of the pulsed laser for pulse interleaved emission according to the area lengths and interval distances of all load-bearing areas to reduce the sampling blind area of all load-bearing areas.

3. The monitoring and control method of the automated production line according to claim 1, wherein Emitting pulsed laser light to the monitoring optical cable of the battery production line and receiving the feedback scattered signal includes: Obtaining the node timing diagram of each operating device when executing the current production task; Analyzing the path interference segments represented in all node timing diagrams to determine the effective emission period and effective reception period of the pulsed laser; Emitting the pulsed laser during the effective emission period and receiving the scattered signal during the effective reception period.

4. The monitoring and control method of the automated production line according to claim 3, characterized in that, Analyzing the path interference segments represented in all node timing diagrams to determine the effective emission period and effective reception period of the pulsed laser includes: Configuring the end station of the monitoring optical cable close to the battery production line as the incident end of the pulsed laser; Taking the node timing diagram of the end station as a reference to align the operation timing diagrams of other operating devices along the time axis; Eliminating abnormal segments from the node timing diagrams after time-axis alignment, and marking the intersection of the remaining time periods as the effective emission period, and marking the period of the pulsed laser delayed propagation during the effective emission period as the effective reception period.

5. The monitoring and control method of the automated production line according to claim 1, characterized in that, Performing time-frequency analysis, spatio-temporal array analysis, and frequency-domain spatial array analysis on the scattered signal to obtain multi-dimensional vibration information of each operating device on the battery production line includes: Performing time-frequency analysis on the scattered signal to obtain the main vibration frequency, vibration frequency band, and vibration change curve of the corresponding operating device, wherein the vibration change curve is a curve of the vibration frequency of the operating device changing with the monitoring time; Perform spatio-temporal array analysis on the scattered signal to obtain the vibration source position of the corresponding operating equipment in its bearing area, where multiple vibration sampling points are configured in the bearing area of each operating equipment; Perform spatial array analysis on the scattered signal to obtain the energy spectral density and vibration distribution map of the corresponding operating equipment in its bearing area; Determine the vibration main frequency, the vibration frequency band, the vibration change curve, the vibration source position, the energy spectral density, and the vibration distribution map as the multi-dimensional vibration information of the corresponding operating equipment.

6. The monitoring and control method of the automated production line according to claim 5, characterized in that, The performing spatio-temporal array analysis on the scattered signal to obtain the vibration source position of the corresponding operating equipment in its bearing area includes: Construct a spatio-temporal observation matrix of the corresponding operating equipment according to the sampling time of the scattered signal of the sampling points covered by the operating equipment; Perform time delay estimation and time alignment processing on adjacent spatio-temporal observation matrices of the same operating equipment to determine whether the wavefront diffusion characteristics of a delayed superposition beam are formed in the bearing area of the corresponding operating equipment; When it is determined that the wavefront diffusion characteristics of a delayed superposition beam are formed in the bearing area of the corresponding operating equipment, determine the sampling point with the maximum superposition energy as the vibration source position.

7. The monitoring and control method of the automated production line according to claim 5, wherein The performing spatial array analysis on the scattered signal to obtain the energy spectral density and vibration distribution map of the corresponding operating equipment in its bearing area includes: Process the scattered signal of the vibration area of each operating equipment according to a preset environmental coupling vibration model to obtain the vibration observation values of all vibration sampling points of the corresponding operating equipment in its vibration area; Perform spectral transformation on the time-varying sequence of the vibration observation values of each vibration sampling point to obtain the vibration energy of the corresponding vibration sampling point of the operating equipment in its vibration area; Determine the summation result of all vibration energies of the operating equipment in its vibration area as the energy spectral density, and determine the two-dimensional mapping result of all the vibration energies in the vibration area as the vibration distribution map.

8. The monitoring and control method of the automated production line according to claim 7, wherein The processing the scattered signal of the vibration area of each operating equipment according to a preset environmental coupling vibration model to obtain the vibration observation values of all vibration sampling points of the corresponding operating equipment in its vibration area includes: According to the formula , obtain the vibration sampling points at time of the vibration observation values, where is the discrete-time output matrix, is the discrete-time direct feed matrix, is the phase change amount characterized by the scattered signal of the vibration sampling point at time , is the external excitation vector of the vibration sampling point at time , is the observation output noise of the vibration sampling point at time .

9. The monitoring and control method of the automated production line according to claim 1, characterized in that, The interlocking operation control of the production rhythm of the battery production line according to the actual operating state of each operating equipment includes: Determine the abnormal state level of the abnormal operating equipment according to the actual operating state of each operating equipment; Adjust the operating rhythm of the adjacent operating equipment of the abnormal operating equipment according to the abnormal state level and a preset operating adjustment curve, where the operating adjustment curve is a curve of the operating rhythm of the equipment varying with the operating time under the corresponding abnormal state level.

10. A monitoring and control system for an automated production line, characterized in that, The system includes: A monitoring terminal, which is used to emit pulsed laser to the monitoring optical cable of the battery production line and receive the feedback scattered signal, where the monitoring optical cable is a whole optical cable buried along the bearing area in the length direction of each operating equipment of the battery production line; A data processing terminal, connected to the monitoring terminal, is configured to perform time-frequency analysis, spatio-temporal array analysis, and frequency-domain spatial array analysis on the scattered signals to obtain multi-dimensional vibration information of each operating device on the battery production line. The multi-dimensional vibration information includes the main vibration frequency of the operating device, the vibration source position and energy spectral density of the corresponding load-bearing area; and input the multi-dimensional vibration information of each operating device and the progress information of its corresponding production task into a preset monitoring and classification model to determine the actual operating state of each operating device when performing the current production task. A control terminal, connected to the data processing terminal, is configured to perform interlocking operation control of the production beat of the battery production line according to the actual operating state of each operating device.

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