Early copper sticking warning device for copper rod continuous casting crystallization wheel and related equipment

Abstract

This application relates to the field of copper rod continuous casting technology, and particularly to an early warning device and related equipment for early copper adhesion on the crystallizing wheel in copper rod continuous casting. The device includes: a monitoring module comprising a temperature sensor, a position sensor, and an acoustic emission sensor; an injection module; and an industrial controller configured to: acquire a first temperature response sequence; calculate a thermal heterogeneity index based on the first temperature response sequence; obtain injection processing parameters based on the thermal heterogeneity index; acquire a second temperature response sequence and a real-time rotation phase angle; obtain an efficiency decay index based on the second temperature response sequence; mark micro-areas with efficiency decay indices exceeding a preset threshold as high-risk micro-areas for copper adhesion, and acquire corresponding stress wave signals; obtain a low-frequency envelope signal based on the stress wave signals; and output an early warning signal when copper adhesion is confirmed to have occurred. Therefore, this application can improve the problem of low accuracy in early warning of copper adhesion caused by the difficulty in distinguishing between abnormal copper adhesion and ordinary process fluctuations.

Description

Technical Field

[0001] This application belongs to the field of copper rod continuous casting technology, and particularly relates to an early warning device for early copper adhesion to the crystallizing wheel in copper rod continuous casting and related equipment. Background Technology

[0002] The casting wheel in copper rod continuous casting is a rotating wheel with annular grooves. After molten copper is poured into the grooves, it is sealed by a steel strip covering the outside to form a casting cavity. The molten copper solidifies by forced cooling with internal water. The casting wheel is usually made of high-purity copper or copper alloy to ensure thermal conductivity, and spiral heat-conducting grooves are often opened on both sides of the wheel to enhance heat dissipation.

[0003] In existing technologies, molten copper is typically poured into the grooves of a rotating crystallizing wheel at a single point or locally. The area near the pouring point is subjected to continuous high-temperature impact, while the temperature in areas farther away from the pouring point is relatively low. This results in a naturally large temperature gradient along the circumference of the wheel. Simultaneously, the cooling water is supplied through fixed mechanical channels, which cannot adaptively match the real-time changing heat dissipation demands across the wheel surface. This leads to localized overheating in high-heat-load areas due to vapor film hindering heat transfer, while low-load areas may experience overcooling. This means that the temperature field itself constantly exhibits numerous normal non-uniform fluctuations. Existing technologies for monitoring the crystallizing wheel typically use methods such as setting fixed thresholds or monitoring average temperatures, failing to distinguish which temperature rises are specific hotspots caused by early signs of copper adhesion, such as interface contamination or microscopic deformation. Due to the lack of multi-dimensional specific identification of fault mechanisms, existing technologies either misjudge process fluctuations as copper adhesion, leading to false alarms, or fail to detect abnormal signals in the early stages of copper adhesion due to averaging, ultimately resulting in low warning accuracy. Therefore, existing technologies suffer from the problem of being unable to distinguish between copper adhesion anomalies and ordinary process fluctuations leading to low accuracy in copper adhesion warnings. Summary of the Invention

[0004] This application provides an early warning device and related equipment for early copper adhesion on the crystallizing wheel of copper rod continuous casting, which can improve the problem of low accuracy of early warning due to difficulty in distinguishing between abnormal copper adhesion and ordinary process fluctuations.

[0005] In a first aspect, embodiments of this application provide an early warning device for early copper adhesion on the crystallizing wheel in continuous copper rod casting, comprising: The monitoring module includes a temperature sensor, a position sensor, and an acoustic emission sensor; A spray module for injecting cooling medium into the crystallizing wheel; The industrial controller is configured as follows: Obtain the first temperature response sequence for each micro-region monitored by the temperature sensor; wherein, a micro-region refers to the working circumference of the crystallizing wheel being divided into arc segments that match the spray resolution; Based on each of the first temperature response sequences, calculate the corresponding thermal heterogeneity index for each microregion; The spraying parameters are obtained based on the thermal heterogeneity index corresponding to each micro-region; During the operating cycle after the injection module performs the injection operation according to the injection processing parameters, the second temperature response sequence of each micro-region monitored by the temperature sensor and the real-time rotation phase angle of the crystallizing wheel monitored by the position sensor are obtained. The corresponding performance degradation index is obtained based on the second temperature response sequence of each micro-region; When the performance degradation index of any micro-region exceeds a preset threshold, the micro-region is marked as a high-risk micro-region for copper adhesion. Acquire the stress wave signal of the high-risk micro-region of copper adhesion monitored by the acoustic emission sensor; The low-frequency envelope signal is obtained based on the stress wave signal; If copper adhesion is determined to occur based on the low-frequency envelope signal and the real-time rotating phase angle, an early warning signal is output.

[0006] The technical solutions described in this application embodiment have at least the following technical effects: The early warning device for copper sticking in the crystallizing wheel of continuous casting provided in this application includes: a monitoring module, including a temperature sensor, a position sensor, and an acoustic emission sensor; a spraying module for spraying cooling medium onto the crystallizing wheel; and an industrial controller configured to: acquire a first temperature response sequence for each micro-region monitored by the temperature sensor; calculate a corresponding thermal heterogeneity index for each micro-region based on each first temperature response sequence; obtain spraying processing parameters based on the thermal heterogeneity index corresponding to each micro-region; during the operating cycle after the spraying module is controlled to perform spraying operation according to the spraying processing parameters, acquire a second temperature response sequence for each micro-region monitored by the temperature sensor, and the real-time rotational phase angle of the crystallizing wheel monitored by the position sensor; obtain a corresponding performance decay index based on the second temperature response sequence of each micro-region; mark the micro-region as a high-risk micro-region for copper sticking when the performance decay index of any micro-region exceeds a preset threshold; acquire the stress wave signal of the high-risk micro-region for copper sticking monitored by the acoustic emission sensor; obtain a low-frequency envelope signal based on the stress wave signal; and output a warning signal when copper sticking is determined to have occurred based on the low-frequency envelope signal and the real-time rotational phase angle. Therefore, in the early copper adhesion warning device for the continuous casting crystallizing wheel of the copper rod provided in this application embodiment, the thermal heterogeneity index is used to quantify the non-uniformity of the thermal field, which is beneficial for accurately identifying specific hot spots caused by local interface deterioration. Extracting the low-frequency envelope signal and combining it with phase angle confirmation ensures that copper adhesion is only confirmed when thermal and acoustic anomalies occur simultaneously at the same physical location, thus reducing resource waste and preventing false alarms.

[0007] In one possible implementation of the first aspect, the step of calculating the corresponding thermal heterogeneity index for each microregion based on each of the first temperature response sequences is configured as follows: Extract the sequence of sampled values ​​during the preheating cycle of the crystallizing wheel from each of the first temperature response sequences; Based on the final value of each sampled value sequence and the preset target temperature value, the corresponding static deviation component is obtained; Based on the difference between the maximum and minimum values ​​of the sampled value sequence during the preheating period, the corresponding dynamic fluctuation component is obtained; The weighted sum of each static deviation component and each dynamic fluctuation component is used as the thermal heterogeneity index of the corresponding micro-region.

[0008] In one possible implementation of the first aspect, the step of obtaining the jetting parameters based on the thermal heterogeneity index corresponding to each micro-region is configured as follows: Each thermal heterogeneity index is compared with a preset range to determine the corresponding correction coefficient; The product of the standard pulse injection number and each of the aforementioned correction coefficients is taken as the injection pulse number for each micro-region; The injection processing parameters are obtained based on the number of each injection pulse.

[0009] In one possible implementation of the first aspect, obtaining the low-frequency envelope signal based on the stress wave signal is configured as follows: The stress wave signal is converted into an electrical signal; The electrical signal is subjected to bandpass filtering to extract the signal components of the electrical signal within a preset characteristic frequency band; The signal components within the preset characteristic frequency band are subjected to envelope detection processing to obtain the low-frequency envelope signal.

[0010] In one possible implementation of the first aspect, before outputting the warning signal in the event of copper adhesion determined based on the low-frequency envelope signal and the real-time rotating phase angle, the following configuration is made: The determination of whether the first condition is met is based on the low-frequency envelope signal and the real-time rotating phase angle; wherein, the first condition is used to reflect whether the impact amplitude of a certain micro-region at the current phase exceeds the background noise baseline of its normal operation; The determination of whether the second condition is met is based on the total energy of the low-frequency envelope signal; wherein, the second condition is used to reflect whether the total energy of the stress wave of one rotation of the crystallizing wheel exceeds the historical average level; The waveform characteristics of the low-frequency envelope signal are used to determine whether the third condition is met; wherein, the third condition is used to reflect whether the waveform of a single impact event has the extremely short pulse and extremely steep rising edge characteristic of adhesion tearing; The spatial distribution of the impact event in phase based on the low-frequency envelope signal determines whether the fourth condition is met; wherein, the fourth condition is used to reflect whether the high-energy impact is concentrated in multiple consecutive adjacent micro-regions; If the first condition, the second condition, the third condition, and the fourth condition are met, it is determined that copper adhesion has occurred.

[0011] In one possible implementation of the first aspect, the step of determining whether the first condition is satisfied based on the low-frequency envelope signal and the real-time rotating phase angle is configured as follows: The corresponding dynamic threshold is determined based on the real-time rotating phase angle; wherein, the dynamic threshold is calculated based on the background noise baseline updated in real time during the period when no copper sticking occurs within the corresponding phase interval; When the amplitude of the low-frequency envelope signal exceeds the dynamic threshold, the first condition is determined to be satisfied.

[0012] In one possible implementation of the first aspect, the determination of whether the second condition is satisfied based on the total energy of the low-frequency envelope signal is configured as follows: Accumulate the total energy of the low-frequency envelope signal within the current rotation cycle; If the total energy of the current rotation cycle exceeds the average total energy of the previous multiple rotation cycles, and the excess reaches a sharp increase threshold, then the second condition is determined to be satisfied.

[0013] In one possible implementation of the first aspect, the determination of whether the third condition is satisfied based on the waveform characteristics of the low-frequency envelope signal is configured as follows: Extract waveform features of a single impact event from the low-frequency envelope signal; wherein the waveform features include pulse duration and / or rising edge slope; If the waveform feature is determined to be within the preset waveform feature range, then the third condition is determined to be satisfied.

[0014] In one possible implementation of the first aspect, the determination of whether the fourth condition is satisfied based on the spatial distribution of the impact event in phase of the low-frequency envelope signal is configured as follows: After one rotation cycle ends, the energy of all impact events that satisfy the first condition during that rotation cycle is accumulated according to the phase interval in which they occurred, and an array is constructed. If in the array, there exist multiple consecutive adjacent phase intervals whose corresponding energy values ​​all exceed the energy threshold, and the sum of the energy of the multiple adjacent phase intervals accounts for more than a preset proportion of the total energy of the rotation cycle, then the fourth condition is determined to be satisfied.

[0015] Secondly, embodiments of this application provide an early warning method for early copper adhesion to the crystallizing wheel in copper rod continuous casting, applied to copper rod continuous casting equipment. The copper rod continuous casting equipment includes an industrial controller, a monitoring module, and a spraying module for spraying cooling medium onto the crystallizing wheel. The monitoring module includes a temperature sensor, a position sensor, and an acoustic emission sensor. The method includes: Obtain the first temperature response sequence for each micro-region monitored by the temperature sensor; wherein, a micro-region refers to the working circumference of the crystallizing wheel being divided into arc segments that match the spray resolution; Based on each of the first temperature response sequences, calculate the corresponding thermal heterogeneity index for each microregion; The spraying parameters are obtained based on the thermal heterogeneity index corresponding to each micro-region; During the operating cycle after the injection module performs the injection operation according to the injection processing parameters, the second temperature response sequence of each micro-region monitored by the temperature sensor and the real-time rotation phase angle of the crystallizing wheel monitored by the position sensor are obtained. The corresponding performance degradation index is obtained based on the second temperature response sequence of each micro-region; When the performance degradation index of any micro-region exceeds a preset threshold, the micro-region is marked as a high-risk micro-region for copper adhesion. Acquire the stress wave signal of the high-risk micro-region of copper adhesion monitored by the acoustic emission sensor; The low-frequency envelope signal is obtained based on the stress wave signal; If copper adhesion is determined to occur based on the low-frequency envelope signal and the real-time rotating phase angle, an early warning signal is output.

[0016] Thirdly, embodiments of this application provide a copper rod continuous casting equipment, including the early copper adhesion warning device for the crystallizing wheel of the copper rod continuous casting described in the first aspect.

[0017] It is understood that the beneficial effects of the second and third aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of the industrial controller in an early warning device for early copper adhesion to the crystallizing wheel in continuous copper casting of copper rods provided in an embodiment of this application; Figure 2This is a flowchart of the execution steps S200 and S300 of the industrial controller in the early copper adhesion warning device for the crystallizing wheel of copper rod continuous casting provided in an embodiment of this application; Figure 3 This is a flowchart of the execution steps S800 and S900 of the industrial controller in the early copper adhesion warning device for the crystallizing wheel of copper rod continuous casting provided in an embodiment of this application; Figure 4 This is a schematic diagram of the early warning device for copper sticking to the crystallizing wheel in continuous casting of copper rods provided in this application embodiment; Figure 5 This is a schematic diagram of the structure of the copper rod continuous casting equipment provided in the embodiments of this application. Detailed Implementation

[0020] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0021] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0022] In related technologies, molten copper is typically poured into the grooves of a rotating crystallizing wheel at a single point or locally. The area near the pouring point is continuously subjected to high-temperature impact, while the temperature in areas farther away from the pouring point is relatively low. This results in a naturally large temperature gradient along the circumference of the wheel. Simultaneously, the cooling water is supplied by a fixed mechanical flow channel, which cannot adaptively match the real-time changing heat dissipation demands across the wheel surface. This leads to localized overheating in high-heat-load areas due to vapor film hindering heat transfer, while low-load areas may experience overcooling. This means that the temperature field itself constantly exhibits numerous normal non-uniform fluctuations. Existing technologies for monitoring the crystallizing wheel typically use methods such as setting fixed thresholds or monitoring average temperatures, which cannot distinguish which temperature rises are caused by specific hotspots due to early signs of copper adhesion, such as interface contamination or microscopic deformation. Due to the lack of multi-dimensional specific identification of fault mechanisms, existing technologies either misjudge process fluctuations as copper adhesion, leading to false alarms, or fail to detect in the early stages of copper adhesion because abnormal signals are masked by averaging, ultimately resulting in low warning accuracy. Therefore, existing technologies suffer from the problem of being unable to distinguish between copper adhesion anomalies and ordinary process fluctuations leading to low accuracy in copper adhesion warnings.

[0023] To address the aforementioned problems, this application provides an early warning device and related equipment for early copper adhesion on the crystallizing wheel in continuous copper rod casting. The early warning device includes: a monitoring module comprising a temperature sensor, a position sensor, and an acoustic emission sensor; a spraying module for spraying cooling medium onto the crystallizing wheel; and an industrial controller configured to: acquire a first temperature response sequence for each micro-region monitored by the temperature sensor; calculate a corresponding thermal heterogeneity index for each micro-region based on each first temperature response sequence; obtain spraying processing parameters based on the thermal heterogeneity index corresponding to each micro-region; during the operating cycle after the spraying module executes the spraying operation according to the spraying processing parameters, acquire a second temperature response sequence for each micro-region monitored by the temperature sensor, and the real-time rotational phase angle of the crystallizing wheel monitored by the position sensor; obtain a corresponding performance degradation index based on the second temperature response sequence of each micro-region; mark the micro-region as a high-risk micro-region for copper adhesion when the performance degradation index of any micro-region exceeds a preset threshold; acquire the stress wave signal of the high-risk micro-region for copper adhesion monitored by the acoustic emission sensor; obtain a low-frequency envelope signal based on the stress wave signal; and output an early warning signal when copper adhesion is determined to have occurred based on the low-frequency envelope signal and the real-time rotational phase angle. Therefore, in the early copper adhesion warning device for the continuous casting crystallizing wheel of the copper rod provided in this application embodiment, the thermal heterogeneity index is used to quantify the non-uniformity of the thermal field, which is beneficial for accurately identifying specific hot spots caused by local interface deterioration. Extracting the low-frequency envelope signal and combining it with phase angle confirmation ensures that copper adhesion is only confirmed when thermal and acoustic anomalies occur simultaneously at the same physical location, thus reducing resource waste and preventing false alarms.

[0024] The early warning device for copper sticking to the crystallizing wheel in continuous casting of copper rods provided in this application embodiment can be applied to continuous casting equipment of copper rods. This application embodiment does not impose any restrictions on the specific type of continuous casting equipment of copper rods.

[0025] For example, copper rod continuous casting equipment includes an early warning device for early copper adhesion to the crystallizing wheel, a crystallizing wheel, a melting furnace, and a holding furnace. The melting furnace and holding furnace are connected via a flow channel or siphon-type pouring pipe, with the melt outlet of the melting furnace higher than the inlet of the holding furnace. A pouring nozzle is installed at the bottom or side of the holding furnace, with its lower edge close to the groove of the crystallizing wheel. As the crystallizing wheel rotates, the groove is continuously filled with molten copper as it passes under the pouring nozzle. The early warning device for early copper adhesion to the crystallizing wheel includes a monitoring module (including a temperature sensor, a position sensor, and an acoustic emission sensor), a spraying module for injecting cooling medium into the crystallizing wheel, and an industrial controller. The spraying module includes multiple nozzles, solenoid valves, a pressure regulator, and a circulating water pump. The circulating water pump provides power, which is then connected to a pressure regulator to stabilize the pressure on the main pipeline. The main pipeline branches into multiple parallel branches, each with a corresponding solenoid valve and nozzle connected in series. The nozzles are arranged in sections along the circumference of the crystallizing wheel, with each nozzle corresponding to a micro-region. The temperature sensor can be a line-scan infrared pyrometer or an infrared thermal imager, fixed to the side or top of the crystallizing wheel. The position sensor (rotary encoder) can be an incremental encoder (with Z-phase zero-position pulse) or an absolute encoder, mounted on the drive shaft of the crystallizing wheel via a coupling or gear engagement, rotating coaxially with the crystallizing wheel. The acoustic emission sensor can be a broadband piezoelectric acoustic emission sensor, fixed to the crystallizing wheel bearing housing or shaft end, close to the wheel body. The industrial controller communicates with the monitoring module and the injection module. The industrial controller can be an industrial computer, programmable logic controller, embedded control system, distributed control system, etc., but is not limited to these.

[0026] To better understand the early copper adhesion warning device for the crystallizing wheel in continuous copper casting provided in this application, the steps executed by the industrial controller of the early copper adhesion warning device for the crystallizing wheel in continuous copper casting provided in this application will be described below by way of example.

[0027] Figure 1 A schematic flowchart of the industrial controller for the early copper adhesion warning device for the crystallizing wheel in continuous copper casting provided in this application embodiment is shown. The process steps executed by the industrial controller include: S100 acquires the first temperature response sequence for each micro-region monitored by the temperature sensor. Here, a micro-region refers to the working circumference of the crystallizing wheel being divided into arc segments that match the spray resolution.

[0028] For example, the outer circumference of the crystallizing wheel can be divided into N micro-regions based on the physical resolution of the injection module (e.g., the minimum effective arc length of the cooling nozzle). For instance, if the circumference of the crystallizing wheel is 3000 mm and the effective arc length of the nozzle is 15 mm, it can be divided into 200 micro-regions, each corresponding to a central angle of 1.8°. A non-contact temperature sensor (such as an infrared thermal imager or a line-scanning pyrometer) is used to synchronously measure each micro-region, and the sampling frequency needs to be high enough (e.g., 50 Hz) to capture dynamic temperature changes. The preheating cycle is defined as the stage from when the crystallizing wheel starts to rotate and cooling water is introduced, but before the copper liquid is poured, which typically lasts for several minutes (e.g., 5 minutes). On each micro-region i, the temperature value from the start time t0 to the end time t_end of the preheating is recorded to form the first temperature response sequence T_i(1), T_i(2), ..., T_i(K), where K is the number of sampling points.

[0029] S200 calculates the corresponding thermal heterogeneity index for each microregion based on each first temperature response sequence.

[0030] For example, the coefficient of variation of each first temperature response sequence can be calculated, that is, the ratio of the standard deviation to the mean of the temperature sequence, to obtain the thermal heterogeneity index corresponding to each microregion.

[0031] S300, the spraying parameters are obtained based on the thermal heterogeneity index corresponding to each micro-region.

[0032] For example, the standard number of pulse jets can be obtained (e.g., 10 jets per revolution per micro-region under ideal thermal uniformity conditions). The number of pulse jets for all micro-regions can be obtained by linear mapping or piecewise mapping based on the thermal heterogeneity index of each micro-region and the standard number of pulse jets, which is the jetting processing parameter.

[0033] S400, during the operating cycle after the injection module performs the injection operation according to the injection processing parameters, acquires the second temperature response sequence of each micro-region monitored by the temperature sensor, and the real-time rotation phase angle of the crystallizing wheel monitored by the position sensor.

[0034] For example, a second temperature response sequence can be acquired in the same manner as S100 during the stable operation phase after differential cooling (e.g., from the 10th to the 15th minute after the start of casting). Each micro-region i generates a new temperature sequence T'_i(1), T'_i(2), ..., T'_i(L), where L is the number of sampling points. Simultaneously, a position sensor (such as an incremental encoder or an absolute encoder) monitors the rotation angle of the crystallizing wheel in real time and outputs a real-time rotation phase angle θ(t), typically ranging from 0 to 360° (or 0 to 2π radians), which corresponds one-to-one with the micro-regions: the phase interval corresponding to micro-region i is [(i-1)×360 / N, i×360 / N).

[0035] S500 obtains the corresponding performance degradation index based on the second temperature response sequence of each micro-region.

[0036] For example, a linear regression can be performed on each microregion i at the end of the second temperature response sequence (e.g., the last 10 sampling points) to obtain the slope of temperature change over time. i (Unit: °C / s). Temperature control deviation integral (IAE) i =∫|T'_i(t)-T target |dt (where T) target (This is the preset target temperature), slope i and IAE i After normalization and weighted summation, the efficiency decay index D is obtained. i =w1 norm(slope i )+w2 norm(IAE i ), where w1 and w2 are preset weights.

[0037] S600: When the performance degradation index of any micro-region exceeds the preset threshold, the micro-region is marked as a high-risk micro-region for copper adhesion.

[0038] For example, a performance degradation index can be compared with a preset threshold. Once the performance degradation index of a micro-region exceeds the preset threshold, it is marked as a high-risk micro-region for copper adhesion.

[0039] The S700 acquires stress wave signals from high-risk micro-regions of copper adhesion monitored by an acoustic emission sensor.

[0040] For example, the industrial controller can read the phase angle θ(t) of the position sensor in real time. When θ(t) enters the phase interval of a high-risk micro-region (e.g., [120°, 240°) of micro-region 2), the industrial controller triggers the acoustic emission data acquisition card to start recording the stress wave signal output by the acoustic emission sensor at a high sampling rate (e.g., 1MHz) until it leaves the interval.

[0041] S800 obtains the low-frequency envelope signal based on the stress wave signal. For example, a bandpass filter (such as a fourth-order Butterworth filter) can be designed based on the characteristic frequency band of the copper bonding stress wave (e.g., 50~200 kHz) to filter the stress wave signal s(t), removing low-frequency mechanical vibrations and high-frequency electrical noise, resulting in a filtered signal s_f(t). Taking the absolute value of s_f(t) yields the unipolar signal |s_f(t)|. Setting a cutoff frequency much lower than the characteristic frequency band (e.g., 5 kHz) and performing a low-pass filter on |s_f(t)| yields a smooth envelope signal e(t). Reducing the sampling rate of e(t) to around 100 kHz results in a low-frequency envelope signal.

[0042] The S900 outputs a warning signal when copper adhesion is determined based on the low-frequency envelope signal and the real-time rotating phase angle.

[0043] For example, a background noise baseline can be established for the phase window of each high-risk micro-region of copper adhesion (this baseline can be the average value of the envelope signal amplitude over several cycles in which copper adhesion has not occurred). The total energy of the envelope signal in the current rotation cycle is calculated and compared with the historical average energy of the previous M cycles. The pulse duration Δt and rise slope S of a single impact event are extracted. If the current envelope signal amplitude is greater than the background noise baseline, the total energy of the envelope signal in the current rotation cycle is greater than the historical average energy, and Δt is within a preset range (e.g., 0.05~0.8 ms) and S is greater than the lower limit (e.g., S>5 V / ms), then copper adhesion is confirmed, and a warning signal is immediately output through an audible and visual alarm, PLC, or host computer interface. Otherwise, monitoring continues.

[0044] In one possible implementation, please refer to Figure 2 S200, based on each first temperature response sequence, calculates the corresponding thermal heterogeneity index for each micro-region, and is configured as follows: S210, extract the sampled value sequence within the preheating cycle of the crystallizing wheel from each first temperature response sequence.

[0045] For example, the industrial controller can record the start point of the preheating cycle by using a timer or detecting when the crystallizing wheel speed and cooling water flow rate are stable; the length of the preheating cycle is generally 2-10 minutes. The complete temperature response sequence of each micro-region i is denoted as T_i(t), where t is the absolute time. All sampling points within the time interval [t_pre_start, t_pre_end] are extracted to form the sampling value sequence S. i =[T_i(t1), T_i(t2), ..., T_i(t m )], where m is the sequence length.

[0046] S220: Based on the final value of each sampled value sequence and the preset target temperature value, the corresponding static deviation component is obtained.

[0047] For example, the sampled value sequence S of micro-region i can be set. i The last value (i.e., the temperature at the end of the preheating cycle) is T_i(end). Then the static deviation component P... s_i =|T_i(end)-T t |. Among them, the preset target temperature T t The optimal operating temperature of the crystallizing wheel is usually set by process experts based on the best operating temperature of the crystallizing wheel (for example, for continuous casting of copper rods, the operating surface temperature of the crystallizing wheel is usually controlled between 150 and 200°C; too high a temperature can easily lead to copper sticking, while too low a temperature can affect the fluidity of the molten copper).

[0048] S230: Based on the difference between the maximum and minimum values ​​of the sampled value sequence during the preheating period, the corresponding dynamic fluctuation component is obtained.

[0049] For example, for the sampled value sequence S_i of micro-region i, find its maximum value T_i. max and minimum value T_i min The dynamic fluctuation component of this micro-region is defined as P. d_i =T_i max -T_i min It can be used for P d_i Normalization is performed (e.g., by dividing by the maximum fluctuation range of all micro-regions, or by a preset fluctuation range such as 200℃) to prevent the component value from being too large.

[0050] S240 uses the weighted sum of each static deviation component and each dynamic fluctuation component as the thermal heterogeneity index of the corresponding micro-region.

[0051] For example, the thermal heterogeneity index of the corresponding micro-region can be obtained by weighted summation of each static deviation component and each dynamic fluctuation component, such as H. i =α P s_i +β P d_i , where α and β are weighting coefficients, satisfying α+β=1, and α, β∈[0,1]. The weighting coefficients can be determined through field experiments or expert experience.

[0052] Through steps S210 to S240, by defining a preheating period and capturing temperature data within that timeframe, the thermal response of the crystallizing wheel itself is successfully separated from strong thermal interference sources such as subsequent copper molten metal pouring and solidification. This allows the calculated static deviation component and dynamic fluctuation component to purely reflect the abnormal thermal behavior of the crystallizing wheel itself, rather than being masked by the heat release from the copper molten metal. The static deviation component focuses on whether the temperature at the end of preheating reaches the process target, reflecting the long-term thermal balance capability of the micro-region; the dynamic fluctuation component focuses on the temperature oscillation amplitude during preheating, reflecting the stability and anti-interference capability of the micro-region's thermal response. Combining the two can cover a more comprehensive range of fault modes. Subsequent acoustic emission detection is only triggered when the thermal anomaly simultaneously meets both static and dynamic criteria and reaches a certain weight threshold, avoiding malfunctions caused by accidental fluctuations of a single indicator; potential problem micro-regions can be identified and intervened in advance before the copper molten metal contacts the crystallizing wheel, which is beneficial for suppressing copper adhesion before it occurs.

[0053] In one possible implementation, please refer to Figure 2 S300, based on the thermal heterogeneity index corresponding to each micro-region, obtains the jetting treatment parameters and configures them as follows: S310: Compare each thermal heterogeneity index with a preset range to determine the corresponding correction coefficient.

[0054] For example, the thermal heterogeneity index H of each microregion can be... i Transformed into a dimensionless correction coefficient k through piecewise mapping. i Correction factor k i This is used to subsequently adjust the number of jet pulses in this micro-region, thereby achieving differentiated cooling. For example, if H i <H low Then k i =0.8; if H low ≤H i <H mid Then k i =1.0; if H mid ≤H i <H high Then k i =1.3; if H i ≥H high Then k i =1.8. The threshold can be determined based on historical data statistics, for example, H. low =2.0,H mid =4.0,H high =6.0.

[0055] S320 uses the product of the standard pulse injection number and each correction coefficient as the injection pulse number for each micro-region.

[0056] For example, the correction factor can be multiplied by the preset standard number of pulse injections to calculate the number of injection pulses that each micro-area should receive per rotation in actual operation.

[0057] S330 obtains injection processing parameters based on the number of each injection pulse.

[0058] For example, the number of injection pulses in all micro-regions can be arranged into an array, which is the injection processing parameter.

[0059] Through the above steps S310 to S330, the jetting treatment parameters are generated, which helps to improve the uniformity of the thermal field, reduce the number of high-risk micro-areas of copper adhesion that require acoustic emission monitoring, reduce the amount of data acquisition and the complexity of subsequent signal processing, and improve the signal-to-noise ratio of copper adhesion judgment.

[0060] In one possible implementation, please refer to Figure 3 The S800, based on the stress wave signal, obtains a low-frequency envelope signal and is configured as follows: S810 converts stress wave signals into electrical signals.

[0061] For example, the sensed mechanical stress wave can be converted into an analog electrical signal that can be processed by an electronic system using an acoustic emission sensor (typically a piezoelectric sensor).

[0062] S820 performs bandpass filtering on electrical signals to extract signal components within a preset characteristic frequency band.

[0063] For example, the electrical signal can be bandpass filtered to retain only the frequency band components closely related to the copper adhesion characteristics, while filtering out low-frequency environmental noise, so as to obtain the signal components of the electrical signal within a preset characteristic frequency band (such as 50 kHz to 200 kHz).

[0064] S830 performs envelope detection processing on the signal components within a preset characteristic frequency band to obtain a low-frequency envelope signal.

[0065] For example, a low-frequency envelope signal can be obtained by performing envelope detection processing on the signal components within a preset characteristic frequency band through digital envelope detection (Hilbert transform, or rectification and low-pass filtering).

[0066] Through the above steps S810 to S830, the low-frequency envelope signal can intuitively reflect the energy time distribution of the impact event, so that the unique waveform characteristics of copper adhesion can be quantified and thresholded.

[0067] In one possible implementation, please refer to Figure 3 Before outputting a warning signal when copper adhesion is determined to have occurred based on the low-frequency envelope signal and the real-time rotating phase angle, the S900 is configured as follows: S901 determines whether the first condition is met based on the low-frequency envelope signal and the real-time rotating phase angle. The first condition reflects whether the impact amplitude of a certain micro-region at the current phase exceeds the background noise baseline of its normal operation.

[0068] For example, during the initial stage of operation before copper adhesion occurs, for each micro-region i, the low-frequency envelope signal within the corresponding phase range of that micro-region can be collected, and its mean value within that phase window can be calculated. and standard deviation σ. The background noise baseline is: B= +k1 σ, where k1 is typically 3 to 5 (corresponding to 99.7% to 99.997% confidence level). Based on the real-time rotating phase angle, determine the micro-region to which it belongs, and compare whether the current low-frequency envelope value is greater than the background noise baseline of the micro-region at that phase. If the current low-frequency envelope value of n consecutive sampling points (e.g., n=3) is greater than the corresponding background noise baseline, then the first condition is satisfied.

[0069] S902, determine whether the second condition is met based on the total energy of the low-frequency envelope signal. The second condition reflects whether the total energy of the stress wave during one revolution of the crystallizing wheel exceeds the historical average level.

[0070] For example, the low-frequency envelope signal e(t) can be integrated within the time window T during which the crystallizing wheel completes one revolution (e.g., T = 1 second at a rotation speed of 60 rpm): E total = 2(t)dt. Historical average energy E h The average energy value of the most recent W laps (e.g., W=20 laps) is obtained by using a sliding window to calculate: E h = total (j), if E total >E h +k2 σ h Then the third condition is satisfied, where σ h k2 is the standard deviation of historical energy, and is usually taken as 2 to 3.

[0071] S903 determines whether the third condition is met based on the waveform characteristics of the low-frequency envelope signal. The third condition reflects whether the waveform of a single impact event possesses the extremely short pulse and extremely steep rising edge characteristic of adhesion tearing.

[0072] For example, the rising edge tr (the time required for the envelope to rise from 10% peak value to 90% peak value) and pulse width tw (the time width during which the envelope exceeds 50% peak value) can be determined based on the low-frequency envelope signal. If tr <tr th And tw <tw thThen the third condition is satisfied, where tr th =5μs, tw th =20μs.

[0073] S904, based on the spatial distribution of the phase of the impact event in the low-frequency envelope signal, determines whether the fourth condition is satisfied. The fourth condition reflects whether the high-energy impact is concentrated in multiple consecutive adjacent micro-regions.

[0074] For example, within the current rotation cycle, the high-frequency envelope peak value e is calculated for each micro-region i. peak (i) Determine whether the energy threshold E of the micro-region is exceeded. th (i) (The background noise baseline in S901 can be used), marked as high-energy microregions. Check whether the high-energy microregions form a continuous cluster on the circumference. Let the set of high-energy microregions be H={i1,i2,...,i...} m After sorting them, check the length L of the longest consecutive segment. max If L max ≥L min Then the fourth condition is satisfied, where L min The minimum number of continuous micro-regions (can be 2 or 3).

[0075] S905, under the condition that the first condition, the second condition, the third condition and the fourth condition are met, it is determined that copper adhesion has occurred.

[0076] For example, copper adhesion can be determined to have occurred if the first, second, third, and fourth conditions are met after each rotation cycle. Alternatively, copper adhesion can be confirmed only if the first, second, third, and fourth conditions are met for multiple consecutive rotation cycles (e.g., three consecutive rotations).

[0077] Through steps S901 to S905, each condition describes the essential characteristics of copper adhesion from different and complementary dimensions: the first condition focuses on the local impact amplitude, the second condition focuses on the global energy level, the third condition focuses on the waveform morphology, and the fourth condition focuses on the spatial distribution. Any single interference event (such as accidental steel strip jitter, cooling water droplet impact, or electromagnetic noise) is unlikely to simultaneously satisfy all four conditions, which helps to improve the problem of missed detections in high-noise micro-areas or false alarms in low-noise micro-areas caused by globally fixed thresholds.

[0078] Optionally, please refer to Figure 3 S901, based on the low-frequency envelope signal and the real-time rotating phase angle, determines whether the first condition is met, and is configured as follows: S9011 determines the corresponding dynamic threshold based on the real-time rotating phase angle. The dynamic threshold is calculated based on the background noise baseline, which is updated in real-time during the period when no copper adhesion occurs within the corresponding phase interval.

[0079] For example, during the initial stage of operation before copper adhesion occurs, the low-frequency envelope signal amplitude can be continuously recorded for each phase angle interval (i.e., each micro-region) over multiple rotation cycles (e.g., 100 revolutions). For each micro-region, the average amplitude μ is calculated. j and standard deviation σ j This serves as the background noise baseline for the micro-region. Dynamic threshold Th j It can be μ j +K σ j K is typically taken as 3 to 5 (corresponding to 99.7% to 99.999% confidence level).

[0080] S9012, when the amplitude of the low-frequency envelope signal exceeds the dynamic threshold, the first condition is determined to be met.

[0081] For example, when the crystallizing wheel rotates to micro-region j, the industrial controller reads the low-frequency envelope signal e(t) within the corresponding phase window and extracts its peak amplitude A. j = max(e(t)), if A j >Th j If so, then the first condition is satisfied.

[0082] Through the above steps S9011 to S9012, by independently updating the baseline for each micro-region, each micro-region has a corresponding threshold, which helps the early warning device maintain stable and reliable performance throughout the entire equipment life cycle without the need for manual periodic recalibration.

[0083] Optionally, please refer to Figure 3 S902, based on the total energy of the low-frequency envelope signal, determines whether the second condition is met, and is configured as follows: S9021, the total energy of the low-frequency envelope signal accumulated within the current rotation cycle.

[0084] For example, Q can be obtained by integrating (or discretizing and summing) the square of the low-frequency envelope signal e(t) for one revolution of the crystallizing wheel (period T). curr = 2 Since e(t) has been envelope-detected, its square is proportional to the instantaneous energy of the stress wave.

[0085] S9022, if the total energy of the current rotation cycle exceeds the average total energy of the previous multiple rotation cycles, and the excess reaches the steep increase threshold, then the second condition is determined to be satisfied.

[0086] For example, the total energy of the past M normal operating cycles (e.g., M=20, and none of these cycles have experienced copper sticking) can be recorded, and its average value Q can be calculated.avg When Q curr Q avg When ×R, the second condition is satisfied, where R can be 2.0 to 3.0, indicating that the current energy is more than twice the historical average.

[0087] Through steps S9021 to S9022, if multiple small pulses are generated, the first condition may be difficult to capture, but the second condition can be captured by accumulating the total energy. Using them together improves the coverage of various copper sticking evolution modes. Furthermore, the second condition can also serve a verification function: even if the first condition falsely reports several pulses, as long as the total energy does not increase sharply, the second condition will not be met, and ultimately, it will not be confirmed as copper sticking, thus reducing the false alarm rate.

[0088] Optionally, please refer to Figure 3 S903, based on the waveform characteristics of the low-frequency envelope signal, determines whether the third condition is met, and is configured as follows: S9031, extract waveform features of a single impact event in the low-frequency envelope signal. These waveform features include pulse duration and / or rising edge slope.

[0089] For example, a single impact event can be detected from the low-frequency envelope signal within a phase window that satisfies a first condition: recording begins when the low-frequency envelope signal e(t) exceeds a trigger threshold (e.g., 50% of a dynamic threshold) and ends when e(t) falls below the trigger threshold and remains below it for a period of time (e.g., 50 μs). Waveform features are extracted: pulse duration Δt (the time difference between the moment the rising edge crosses 10% of the peak amplitude and the moment the falling edge crosses 10% of the peak amplitude) and rising edge slope S (peak amplitude divided by the rise time from 10% peak to 90% peak).

[0090] S9032, if the waveform characteristics are determined to be within the preset waveform characteristic range, then the third condition is satisfied.

[0091] For example, if the waveform characteristics are within a preset waveform characteristic range, that is, if both the preset duration range and the preset slope range are satisfied (determined based on laboratory tests or historical copper bonding waveforms), then the third condition is determined to be satisfied.

[0092] Through the above steps S9031 to S9032, the waveform features are compared with the preset waveform feature range to achieve pattern recognition based on physical mechanism. The false judgment rate is much lower than that of the method that relies solely on amplitude or energy, because even if a certain interference produces a sufficiently large amplitude, its waveform shape does not match the copper adhesion, and the third condition will not be met, thus being excluded.

[0093] Optionally, please refer to Figure 3S904, based on the spatial distribution of the phase of the impact event in the low-frequency envelope signal, determines whether the fourth condition is met, and is configured as follows: S9041, after a rotation cycle ends, the energy of all impact events that satisfy the first condition during the rotation cycle is accumulated according to the phase interval in which they occur, and an array is constructed.

[0094] For example, after one rotation cycle ends, all impact events that satisfy the first condition (i.e., amplitude exceeding the threshold) within that cycle can be traversed, and their energy (which can be approximated as pulse peak or integrated energy) can be accumulated according to the micro-region to which the phase angle of their occurrence belongs, to obtain an array E of length N. zone [1..N], initialized to 0.

[0095] S9042, if in the array, there are multiple consecutive adjacent phase intervals whose corresponding energy values ​​all exceed the energy threshold, and the sum of the energy of multiple adjacent phase intervals accounts for more than a preset proportion of the total energy of the rotation cycle, then the fourth condition is determined to be satisfied.

[0096] For example, the energy of each event can be accumulated into the corresponding micro-region. A preset energy threshold E is used. th For example, take twice the average energy of all microregions or an absolute empirical value. Scan array E zone Find the longest continuous subsequence such that Ei of each micro-region in the sequence zone [j]>E th Let the length of this continuous subsequence be L (i.e., the number of continuous micro-regions), and its total energy be E. sum If simultaneously: L≥L min (Minimum number of consecutive numbers, e.g., L) min =3), and E sum / Q curr ≥P total (where Q) curr P is the total energy of this period. total If a preset percentage threshold is used (e.g., 30%), then the fourth condition is determined to be met.

[0097] Copper adhesion is not an isolated random phenomenon, but a systematic failure caused by interface deterioration (such as localized wear, coating peeling, or uneven cooling) on ​​a continuous arc segment of the crystallizing wheel surface. Therefore, its acoustic emission events exhibit a clustered characteristic in space—multiple adjacent micro-regions simultaneously or successively experience high-energy impacts. Random interference (such as the passage of a single large particle or occasional steel belt vibration) usually occurs in isolation within a single micro-region; even if it occasionally occurs in two micro-regions, it is difficult for multiple micro-regions to experience it simultaneously. Through the steps S9041 to S9042 described above, various non-copper adhesion single-point interferences can be effectively filtered out, which helps reduce the false alarm rate. Furthermore, the fourth condition introduces a spatial distribution dimension, forming a complete multi-dimensional judgment matrix with the first three conditions. If any dimension is not satisfied, it will not be confirmed as copper adhesion.

[0098] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0099] Corresponding to the early copper adhesion warning device for the crystallizing wheel in copper rod continuous casting described in the above embodiments, this application also provides an early copper adhesion warning method for the crystallizing wheel in copper rod continuous casting, applied to copper rod continuous casting equipment. The copper rod continuous casting equipment includes a monitoring module and an injection module. The monitoring module includes a temperature sensor, a position sensor, and an acoustic emission sensor. The method includes: Obtain the first temperature response sequence for each micro-region monitored by the temperature sensor; wherein, a micro-region refers to the working circumference of the crystallizing wheel being divided into arc segments that match the spray resolution; Based on each of the first temperature response sequences, calculate the corresponding thermal heterogeneity index for each microregion; The spraying parameters are obtained based on the thermal heterogeneity index corresponding to each micro-region; During the operating cycle after the injection module performs the injection operation according to the injection processing parameters, the second temperature response sequence of each micro-region monitored by the temperature sensor and the real-time rotation phase angle of the crystallizing wheel monitored by the position sensor are obtained. The corresponding performance degradation index is obtained based on the second temperature response sequence of each micro-region; When the performance degradation index of any micro-region exceeds a preset threshold, the micro-region is marked as a high-risk micro-region for copper adhesion. Acquire the stress wave signal of the high-risk micro-region of copper adhesion monitored by the acoustic emission sensor; The low-frequency envelope signal is obtained based on the stress wave signal; If copper adhesion is determined to occur based on the low-frequency envelope signal and the real-time rotating phase angle, an early warning signal is output.

[0100] This application also provides a copper rod continuous casting device. Figure 5 This is a schematic diagram of the structure of a copper rod continuous casting equipment provided in one embodiment of this application. Figure 5 As shown, the industrial controller in the copper rod continuous casting equipment 5 of this embodiment includes: at least one processor 50 ( Figure 5 Only one is shown in the image), at least one memory 51 ( Figure 5 (Only one is shown in the image) and a computer program 52 stored in the at least one memory 51 and executable on the at least one processor 50. When the processor 50 executes the computer program 52, it causes the copper rod continuous casting equipment 5 to perform the steps in any of the above embodiments of the early copper adhesion warning device for the crystallizing wheel of the copper rod continuous casting, or causes the copper rod continuous casting equipment 5 to perform the functions of each module / unit in the above embodiments of the devices.

[0101] For example, the computer program 52 may be divided into one or more modules / units, which are stored in the memory 51 and executed by the processor 50 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 52 in the copper rod continuous casting equipment 5.

[0102] The industrial controller can be a computing device such as an industrial computer, programmable logic controller, embedded control system, or distributed control system. The copper rod continuous casting equipment may include, but is not limited to, a processor 50 and a memory 51. Those skilled in the art will understand that... Figure 5 This is merely an example of the copper rod continuous casting equipment 5 and does not constitute a limitation on the copper rod continuous casting equipment 5. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0103] The processor 50 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0104] In some embodiments, the memory 51 may be an internal storage unit of the copper rod continuous casting equipment 5, such as a hard disk or memory of the copper rod continuous casting equipment 5. In other embodiments, the memory 51 may be an external storage device of the copper rod continuous casting equipment 5, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the copper rod continuous casting equipment 5. Further, the memory 51 may include both internal storage units and external storage devices of the copper rod continuous casting equipment 5. The memory 51 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 51 can also be used to temporarily store data that has been output or will be output.

[0105] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0106] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0107] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. An early warning device for early copper adhesion on the crystallizing wheel of a copper rod continuous casting, characterized in that, include: The monitoring module includes a temperature sensor, a position sensor, and an acoustic emission sensor; A spray module for injecting cooling medium into the crystallizing wheel; The industrial controller is configured as follows: Obtain the first temperature response sequence for each micro-region monitored by the temperature sensor; wherein, a micro-region refers to the working circumference of the crystallizing wheel being divided into arc segments that match the spray resolution; Based on each of the first temperature response sequences, calculate the corresponding thermal heterogeneity index for each microregion; The spraying parameters are obtained based on the thermal heterogeneity index corresponding to each micro-region; During the operating cycle after the injection module performs the injection operation according to the injection processing parameters, the second temperature response sequence of each micro-region monitored by the temperature sensor and the real-time rotation phase angle of the crystallizing wheel monitored by the position sensor are obtained. The corresponding performance degradation index is obtained based on the second temperature response sequence of each micro-region; When the performance degradation index of any micro-region exceeds a preset threshold, the micro-region is marked as a high-risk micro-region for copper adhesion. Acquire the stress wave signal of the high-risk micro-region of copper adhesion monitored by the acoustic emission sensor; The low-frequency envelope signal is obtained based on the stress wave signal; If copper adhesion is determined to occur based on the low-frequency envelope signal and the real-time rotating phase angle, an early warning signal is output.

2. The early warning device for copper sticking to the crystallizing wheel in continuous copper rod casting as described in claim 1, characterized in that, The step of calculating the corresponding thermal heterogeneity index for each micro-region based on each of the first temperature response sequences is configured as follows: Extract the sequence of sampled values ​​during the preheating cycle of the crystallizing wheel from each of the first temperature response sequences; Based on the final value of each sampled value sequence and the preset target temperature value, the corresponding static deviation component is obtained; Based on the difference between the maximum and minimum values ​​of the sampled value sequence during the preheating period, the corresponding dynamic fluctuation component is obtained; The weighted sum of each static deviation component and each dynamic fluctuation component is used as the thermal heterogeneity index of the corresponding micro-region.

3. The early warning device for copper sticking to the crystallizing wheel in continuous copper rod casting as described in claim 1, characterized in that, The jetting parameters, obtained based on the thermal heterogeneity index corresponding to each micro-region, are configured as follows: Each thermal heterogeneity index is compared with a preset range to determine the corresponding correction coefficient; The product of the standard pulse injection number and each of the aforementioned correction coefficients is taken as the injection pulse number for each micro-region; The injection processing parameters are obtained based on the number of each injection pulse.

4. The early warning device for copper sticking to the crystallizing wheel in continuous copper rod casting as described in claim 1, characterized in that, The low-frequency envelope signal obtained from the stress wave signal is configured as follows: The stress wave signal is converted into an electrical signal; The electrical signal is subjected to bandpass filtering to extract the signal components of the electrical signal within a preset characteristic frequency band; The signal components within the preset characteristic frequency band are subjected to envelope detection processing to obtain the low-frequency envelope signal.

5. The early warning device for copper sticking to the crystallizing wheel in continuous copper rod casting as described in claim 1, characterized in that, Before outputting a warning signal when copper adhesion is determined to have occurred based on the low-frequency envelope signal and the real-time rotating phase angle, the configuration is as follows: The determination of whether the first condition is met is based on the low-frequency envelope signal and the real-time rotating phase angle; wherein, the first condition is used to reflect whether the impact amplitude of a certain micro-region at the current phase exceeds the background noise baseline of its normal operation; The determination of whether the second condition is met is based on the total energy of the low-frequency envelope signal; wherein, the second condition is used to reflect whether the total energy of the stress wave of one rotation of the crystallizing wheel exceeds the historical average level; The waveform characteristics of the low-frequency envelope signal are used to determine whether the third condition is met; wherein, the third condition is used to reflect whether the waveform of a single impact event has the extremely short pulse and extremely steep rising edge characteristic of adhesion tearing; The spatial distribution of the impact event in phase based on the low-frequency envelope signal determines whether the fourth condition is met; wherein, the fourth condition is used to reflect whether the high-energy impact is concentrated in multiple consecutive adjacent micro-regions; If the first condition, the second condition, the third condition, and the fourth condition are met, it is determined that copper adhesion has occurred.

6. The early warning device for copper sticking to the crystallizing wheel in continuous copper rod casting as described in claim 5, characterized in that, The step of determining whether the first condition is met based on the low-frequency envelope signal and the real-time rotating phase angle is configured as follows: The corresponding dynamic threshold is determined based on the real-time rotating phase angle; wherein, the dynamic threshold is calculated based on the background noise baseline updated in real time during the period when no copper sticking occurs within the corresponding phase interval; When the amplitude of the low-frequency envelope signal exceeds the dynamic threshold, the first condition is determined to be satisfied.

7. The early warning device for copper sticking to the crystallizing wheel in continuous copper rod casting as described in claim 5, characterized in that, The determination of whether the total energy of the low-frequency envelope signal satisfies the second condition is configured as follows: Accumulate the total energy of the low-frequency envelope signal within the current rotation cycle; If the total energy of the current rotation cycle exceeds the average total energy of the previous multiple rotation cycles, and the excess reaches a sharp increase threshold, then the second condition is determined to be satisfied.

8. The early warning device for copper sticking to the crystallizing wheel in continuous copper rod casting as described in claim 5, characterized in that, The determination of whether the third condition is satisfied based on the waveform characteristics of the low-frequency envelope signal is configured as follows: Extract waveform features of a single impact event from the low-frequency envelope signal; wherein the waveform features include pulse duration and / or rising edge slope; If the waveform feature is determined to be within the preset waveform feature range, then the third condition is determined to be satisfied.

9. The early warning device for copper sticking to the crystallizing wheel in continuous copper rod casting as described in claim 5, characterized in that, The determination of whether the fourth condition is satisfied based on the spatial distribution of the impact event in phase according to the low-frequency envelope signal is configured as follows: After one rotation cycle ends, the energy of all impact events that satisfy the first condition during that rotation cycle is accumulated according to the phase interval in which they occurred, and an array is constructed. If in the array, there exist multiple consecutive adjacent phase intervals whose corresponding energy values ​​all exceed the energy threshold, and the sum of the energy of the multiple adjacent phase intervals accounts for more than a preset proportion of the total energy of the rotation cycle, then the fourth condition is determined to be satisfied.

10. A copper rod continuous casting equipment, comprising an early warning device for early copper adhesion on the crystallizing wheel of copper rod continuous casting as described in any one of claims 1 to 9.

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