Target control method for parameter optimization of electromagnetic induction system

Abstract

The invention discloses a target control method for parameter optimization of an electromagnetic induction system, and particularly relates to the technical field of parameter optimization of the electromagnetic induction system, and the method comprises the steps: inputting a first frequency signal and a second frequency signal to an electromagnetic induction heating coil at the same time, carrying out the stepped adjustment of a phase difference within a preset frequency difference range according to a preset step length, calculating an instantaneous power curve, and measuring a time interval between adjacent instantaneous power troughs to obtain a power fluctuation period; when the deviation between the power fluctuation period and the target period exceeds a preset range, adjusting the phase difference to enable the deviation to enter the preset range, and constructing the valley depth of the instantaneous power curve and the corresponding equivalent resistance into evaluation indexes based on a preset weight; heating control parameters are dynamically corrected under cooperative judgment of power fluctuation and equivalent resistance response, energy dissipation caused by the conductive film is sensed and compensated in real time, and therefore it is guaranteed that the temperature rise process and the stripping process of the bonding surface of the adhesive layer are kept consistent.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic induction system parameter optimization technology, and more specifically, to a target control method for electromagnetic induction system parameter optimization. Background Technology

[0002] During the process of high-frequency electromagnetic induction stripping of special deck thick coating, when the interfacial adhesive layer is heated to the pyrolysis temperature, it will release aerosols containing conductive components. These aerosols will quickly deposit on the steel shell surface to form a transient conductive film.

[0003] The presence of this conductive film alters the energy transfer path of electromagnetic induction, causing significant energy dissipation in the eddy currents within the film layer. This weakens the deep penetration of electromagnetic energy into the adhesive layer interface, thereby reducing the temperature rise rate of the interface and prolonging the time to reach the preset dissolution temperature.

[0004] Existing heating control systems typically use the surface temperature reaching a set value as the sole criterion for the peeling process. They lack direct perception of the actual heating conditions of the bonding surface and cannot identify and compensate for this effect in the early stages of conductive film formation and energy loss. This leads to a deviation between the optimized heating parameters and the actual physical state of the peeling process, limiting peeling efficiency and control accuracy. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a target control method for optimizing electromagnetic induction system parameters. By dynamically correcting heating control parameters under the cooperative determination of power fluctuations and equivalent resistance response, the method can sense and compensate for energy dissipation caused by the conductive film in real time, thereby ensuring that the temperature rise process of the adhesive bonding surface is consistent with the peeling process.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a target control method for optimizing parameters of an electromagnetic induction system, comprising:

[0007] S1: Simultaneously input a first frequency signal and a second frequency signal into the electromagnetic induction heating coil, adjust the phase difference stepwise within a preset frequency difference range according to a preset step size, calculate the instantaneous power curve, measure the time interval between adjacent instantaneous power troughs, and obtain the power fluctuation period.

[0008] S2: When the deviation between the power fluctuation period and the target period exceeds the preset range, the phase difference is adjusted to bring the deviation into the preset range, and the trough depth of the instantaneous power curve and the corresponding equivalent resistance are constructed as evaluation indicators based on the preset weight.

[0009] S3: The evaluation indexes are adjusted stepwise according to the preset step size for the frequency difference and phase difference, the upper limit of the evaluation indexes within the preset range is identified, and the optimized first frequency, second frequency and corresponding power fluctuation period are output.

[0010] S4: Align the optimized power fluctuation period with the corresponding equivalent resistance fluctuation period on the time axis to identify the low power range and output the low power time range.

[0011] S5: At the beginning of the power trough time interval, based on the ratio of the effective power during the original power trough to the target effective power, calculate the compensated drive current amplitude according to the relationship that the power is proportional to the square of the drive current amplitude.

[0012] S6: Collect the voltage and current when maintaining the output of the drive current amplitude during the power trough, and combine them with the equivalent resistance curve to calculate the local temperature rise data according to the product relationship between absorbed power, material specific heat capacity and mass.

[0013] S7: Compare the local temperature rise data with the preset peeling temperature threshold and output a peeling condition met signal.

[0014] In a preferred embodiment, in S1, while keeping the frequency difference between the first frequency signal and the second frequency signal less than a preset interval and the phase fixed, the phase difference between the first frequency signal and the second frequency signal is adjusted in a stepwise manner according to a preset step size to form a phase difference adjustment sequence.

[0015] The voltage and current corresponding to each phase difference in the phase difference adjustment sequence of the electromagnetic induction heating coil are collected, and the voltage and current corresponding to each phase difference are multiplied to obtain the instantaneous power curve;

[0016] Identify all adjacent power troughs in the instantaneous power curve, measure the time interval between adjacent power troughs, and determine the measured time interval as the power fluctuation period.

[0017] In a preferred embodiment, in S2, the deviation between the power fluctuation period and the target period is calculated, and it is determined whether the deviation exceeds a preset range.

[0018] When the deviation exceeds the preset range, the phase difference between the first frequency signal and the second frequency signal is adjusted stepwise according to the preset step size so that the deviation comes within the preset range.

[0019] Extract the power trough depth and the equivalent resistance at the corresponding moment from the instantaneous power curve within the preset range, and combine them according to preset weights to construct evaluation indicators.

[0020] In a preferred embodiment, S2 further includes defining an evaluation index J. kBased on the logarithmic function ln(·) and the exponential function exp(·), the depth D of the power trough of the instantaneous power curve in the k-th iteration is calculated. k and the corresponding equivalent resistance R k We will perform weighted fusion to construct the evaluation index J. k ;

[0021] Formula 1:

[0022]

[0023] Formula 2:

[0024]

[0025] Formula 3:

[0026]

[0027] Formula 4:

[0028] E period (φ)=|T p (φ)-T target |

[0029] Formula 5:

[0030]

[0031] Formula Six:

[0032] B k =mean{P k (t)∣t∈W k}

[0033] Formula 7:

[0034]

[0035] Formula 8:

[0036]

[0037] Formula Nine:

[0038]

[0039] Where e k T represents the relative deviation of the period in the k-th iteration; p,k T represents the power fluctuation period measured from the instantaneous power curve during the k-th iteration; target Indicates the period of target power fluctuation;

[0040] Where ε T The preset threshold representing the periodic deviation; β gateRepresents the gating smoothing coefficient; logistic(·) represents the logistic function; η k This represents the periodicity gate factor for the k-th iteration;

[0041] Where φ k δφ represents the phase difference in the k-th iteration. probe Indicates φ k The amount of disturbance applied with a preset step size; E period (·) denotes the periodic error function; sgn(x) denotes the sign function; α φ Indicates the step size for phase difference adjustment; φ min This represents the lower limit of the preset phase difference range; φ max Indicates the upper limit of the preset phase difference range; Represents the interval projection operator;

[0042] Where T p (φ) represents the power fluctuation period measured when the phase difference is φ; E period (φ) represents the absolute error between the measured power fluctuation period and the target power fluctuation period when the phase difference is φ;

[0043] Where P k (t) The instantaneous power curve of the k-th iteration, which varies with time t; W k t represents a power fluctuation period time window corresponding to the k-th iteration; argmin represents the value of the independent variable when the objective function reaches the lower limit of the preset interval; v,k Indicates W k Internal P k The power trough of (t);

[0044] Where mean(·) represents the arithmetic mean symbol; B k Indicates W k Local power baseline within;

[0045] Where P k (t v,k ) represents the instantaneous power value at the moment of power trough; ε P The lower limit threshold represents the instantaneous power; max(·) represents the upper limit operator; D k This represents the depth of the power trough in the instantaneous power curve during the k-th iteration;

[0046] Where R eq,k (t v,k ) represents the equivalent resistance curve for the k-th iteration; R base Indicates the equivalent resistance reference baseline; ε R R represents the lower threshold of the equivalent resistance. k D represents k The corresponding equivalent resistance;

[0047] Where w D D represents k Weighting coefficients; w R R represents k The weighting coefficients; exp(·) represents the exponential function; ln(·) represents the logarithmic function; λ fuse This represents the blending sharpness coefficient.

[0048] In a preferred embodiment, in S3, the frequency difference and phase difference of the evaluation index are adjusted stepwise according to a preset step size to form a frequency difference sequence and a phase difference sequence.

[0049] Traverse all combinations of frequency difference sequences and phase difference sequences within the preset range, extract the corresponding evaluation index values ​​in sequence, identify the termination boundary point of the increasing interval of the evaluation index value, and determine the evaluation index value corresponding to the termination boundary point as the upper limit value of the evaluation index.

[0050] The first and second frequencies generated during the step adjustment process corresponding to the upper limit values ​​of the evaluation indicators are extracted and determined as the optimized first and second frequencies.

[0051] Based on the optimized first and second frequencies, corresponding power fluctuation curves are generated, and the optimized power fluctuation period is identified in the power fluctuation curves.

[0052] In a preferred embodiment, in S4, based on the optimized power fluctuation period, the voltage to current ratio sequence at the corresponding moment is extracted to obtain the corresponding equivalent resistance fluctuation period.

[0053] The optimized power fluctuation period and the corresponding equivalent resistance fluctuation period are mapped to a unified time axis, and a reference time alignment operation is performed.

[0054] On the aligned unified timeline, each power fluctuation period interval is traversed one by one to extract the power value change sequence within the interval.

[0055] In the aligned unified time axis, identify the continuous time intervals where the power fluctuation period and the equivalent resistance fluctuation period are both at the power trough depth, and determine them as the power trough time intervals.

[0056] In a preferred embodiment, in S5, the original effective power value is obtained based on the product of voltage and current during the power trough time interval.

[0057] The target effective power value preset for the special deck thickness coating requirement is invoked to construct the power ratio between the original effective power value and the target effective power value;

[0058] Based on the relationship that the heating power of the heating coil is proportional to the square of the driving current amplitude, the square root operation is performed on the power ratio to obtain the correction factor of the current amplitude. The original driving current amplitude is multiplied by the correction factor to obtain the compensated driving current amplitude.

[0059] In a preferred embodiment, in S6, the voltage and current are synchronously acquired when the drive current amplitude is maintained during the power trough time interval, and the instantaneous power curve and the corresponding equivalent resistance curve are calculated.

[0060] Divide the instantaneous power value at each moment in the instantaneous power curve by the equivalent resistance value at the corresponding moment in the equivalent resistance curve to obtain the absorbed power sequence.

[0061] The cumulative energy is obtained by performing an accumulation operation on the product of the power value at each time point in the absorbed power sequence and the time difference between adjacent time points;

[0062] The local temperature rise data is output by dividing the accumulated energy by the product of the material's specific heat capacity and mass.

[0063] In a preferred embodiment, in S7, the local temperature rise data at the adhesive bonding surface is compared with the preset peeling temperature threshold required for a special deck thickness coating. When the temperature rise data is greater than or equal to the preset peeling temperature threshold, a peeling condition satisfaction signal is output; otherwise, the temperature rise data calculation step is returned until the temperature rise data reaches the preset peeling temperature threshold.

[0064] The technical effects and advantages of this invention are as follows:

[0065] 1. This solution constructs a joint judgment mechanism of power trough time interval and equivalent resistance curve, which can identify energy transfer anomalies in the early stage of conductive film formation and correct heating control parameters in real time, thereby avoiding the lag in temperature rise of the bonding surface caused by energy dissipation and solving the problem that existing methods cannot perceive the real heating state when peeling off thick coatings for special decks.

[0066] 2. By extracting key parameters through the coordinated alignment of power fluctuation period and equivalent resistance fluctuation period, a mapping relationship between interface energy input and interface response was established, enabling the control criterion of the heating process to shift from surface temperature to interface temperature rise, thus achieving accurate perception of the real physical state.

[0067] 3. By integrating the absorbed power sequence and combining it with the material's specific heat capacity and mass to calculate the local temperature rise, an energy accumulation characterization of the bonding surface is formed, avoiding the bias caused by single monitoring of surface temperature and improving the scientificity and reliability of the peeling process determination.

[0068] 4. By combining the power trough depth with the corresponding equivalent resistance according to weights to construct evaluation indicators, it is possible to comprehensively evaluate energy loss and stripping effect, and achieve dual optimization of energy utilization and process efficiency in the process of stripping thick coatings on special decks. Attached Figure Description

[0069] Figure 1 This is a flowchart outlining the method steps of the present invention;

[0070] Figure 2 This is a flowchart of the power fluctuation period identification process of the present invention;

[0071] Figure 3 This is a flowchart illustrating the frequency of evaluation index construction and optimization for this invention.

[0072] Figure 4 This is a flowchart of the power trough time interval identification and drive current compensation of the present invention;

[0073] Figure 5 This is a flowchart of the local temperature rise judgment and stripping signal output of the present invention. Detailed Implementation

[0074] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0075] Refer to the instruction manual appendix Figure 1-5 An embodiment of the present invention provides a target control method for optimizing parameters of an electromagnetic induction system, comprising:

[0076] S1: Simultaneously input a first frequency signal and a second frequency signal into the electromagnetic induction heating coil. The frequency difference between the first frequency signal and the second frequency signal is less than a preset interval, and the phase of the two signals is kept fixed. Within the preset frequency difference range, the phase difference between the two signals is adjusted stepwise according to a preset step size. The voltage and current are collected and the instantaneous power curve is calculated. The time interval between adjacent instantaneous power troughs is measured to obtain the power fluctuation period.

[0077] S2: When the deviation between the power fluctuation period and the target period exceeds the preset range, adjust the phase difference until the deviation enters the preset range, and construct the trough depth of the instantaneous power curve and the corresponding equivalent resistance as evaluation indicators based on the preset weight.

[0078] S3: The evaluation indexes are adjusted stepwise according to the preset step size for the frequency difference and phase difference, the upper limit of the evaluation indexes within the preset range is identified, and the optimized first frequency, second frequency, phase difference and corresponding power fluctuation period are output.

[0079] S4: Align the optimized power fluctuation period with the corresponding equivalent resistance fluctuation period on the time axis, identify the time interval where the power is low, and output the power trough time interval.

[0080] S5: At the beginning of the power trough time interval, based on the ratio of the effective power during the original power trough to the target effective power required to peel off the special deck thick coating, the compensated driving current amplitude is calculated according to the relationship that the heating power of the heating coil is proportional to the square of the driving current amplitude, and the driving current amplitude is maintained throughout the entire power trough time interval, so that the heating energy reaching the adhesive bonding surface after penetrating the conductive film reaches the expected energy value required to peel off the special deck thick coating.

[0081] S6: Synchronously collect voltage and current when maintaining the output of drive current amplitude during power trough, calculate instantaneous power curve, and combine with equivalent resistance curve to convert local temperature rise data at the adhesive layer bonding surface according to the product relationship between absorbed power and material specific heat capacity and mass.

[0082] S7: Compare the local temperature rise data at the adhesive bonding surface with the preset peeling temperature threshold required for special deck thickness coating. When the temperature rise data is greater than or equal to the preset peeling temperature threshold, output a peeling condition satisfied signal; otherwise, return to the temperature rise data calculation step until the temperature rise data reaches the preset peeling temperature threshold.

[0083] In S1, under the condition that the frequency difference between the first frequency signal and the second frequency signal is less than a preset interval and the phase is fixed, the phase difference between the first frequency signal and the second frequency signal is adjusted stepwise according to a preset step size to form a phase difference adjustment sequence.

[0084] The voltage and current corresponding to each phase difference in the phase difference adjustment sequence of the electromagnetic induction heating coil are collected, and the voltage and current corresponding to each phase difference are multiplied to obtain the instantaneous power curve;

[0085] Identify all adjacent power troughs in the instantaneous power curve, measure the time interval between adjacent power troughs, and determine the measured time interval as the power fluctuation period. The power fluctuation period is used to adjust the timing characteristics of electromagnetic induction heating energy so that the heating energy after penetrating the conductive film can stably act on the adhesive bonding surface to meet the energy requirements for peeling off special thick coatings.

[0086] In S2, the deviation between the power fluctuation period and the target period is calculated, and it is determined whether the deviation exceeds the preset range.

[0087] When the deviation exceeds the preset range, the phase difference between the first frequency signal and the second frequency signal is adjusted stepwise according to the preset step size so that the deviation comes within the preset range.

[0088] Extract the power trough depth and the equivalent resistance at the corresponding moment from the instantaneous power curve within the preset range, combine them according to preset weights, and construct evaluation indicators. The evaluation indicators are used to characterize the adaptability of the power trough to the heating energy transfer effect during the peeling of special deck thick coating.

[0089] It should be noted that in the formula structure involved in this scheme, dimensionless terms can be used as proportional or structural adjustment factors. When combined with quantities with units, they only play a role in numerical scaling and do not introduce new physical dimensions. Therefore, they will not change or confuse the overall unit system. This combination of "dimensionless terms and terms with units" can be understood as a composite structural expression commonly used in mathematical physics modeling. It conforms to the principle of dimensional consistency and has a clear physical interpretation basis.

[0090] Secondly, in the formula structure of this scheme, if multiple variables with different physical units are involved, including but not limited to time, mass or energy variables, their joint appearance is to express the collaborative modeling relationship of multiple physical mechanisms. Each variable can form a unified structure through function mapping, ratio combination or normalization adjustment, with clear units and clear meaning. The overall expression conforms to the principle of dimensional consistency and the conventional formula of engineering modeling.

[0091] In this solution, constants, weights, adjustment factors, threshold parameters, proportional coefficients, etc., are all adjustable control parameters for different application environments. Their values ​​depend on the target equipment configuration, data input characteristics, and performance optimization goals. During the implementation phase, they are set to converge within a reasonable range through model verification, performance constraints, or engineering calibration. Although these parameters do not have a unique preset value, they have clear adjustment logic and calculation paths. They belong to the deterministic setting process in engineering implementation. The purpose of this setting is to ensure that the solution is both universally adaptable and reproducible and operable, without affecting its technical clarity and feasibility.

[0092] S2 also includes defining the evaluation index J. k Based on the logarithmic function ln(·) and the exponential function exp(·), the depth D of the power trough of the instantaneous power curve in the k-th iteration is calculated. k and the corresponding equivalent resistance R k We will perform weighted fusion to construct the evaluation index J. k ;

[0093] Formula 1:

[0094]

[0095] Formula 2:

[0096]

[0097] Formula 3:

[0098]

[0099] Formula 4:

[0100] E period (φ)=|T p (φ)-T target |

[0101] Formula 5:

[0102]

[0103] Formula Six:

[0104] B k =mean{P k (t)∣t∈W k}

[0105] Formula 7:

[0106]

[0107] Formula 8:

[0108]

[0109] Formula Nine:

[0110]

[0111] Where e k T represents the relative deviation of the period in the k-th iteration; p,k T represents the power fluctuation period measured from the instantaneous power curve during the k-th iteration; target Indicates the period of target power fluctuation;

[0112] Furthermore, in e k In the formula, the power fluctuation period T is obtained by measuring the instantaneous power curve of the kth iteration. p,k and the corresponding target power fluctuation period T target Normalization is performed to obtain the periodic relative deviation e of the k-th iteration. k ;

[0113] Where ε T The preset threshold representing the periodic deviation; β gateThe gating smoothing coefficient is used to control the speed and intensity of phase difference adjustment; logistic(·) represents the logic function, which maps real numbers to the (0,1) interval; η k Let η represent the periodic gating factor for the k-th iteration. k Used to suppress or amplify the phase difference update intensity based on the periodic alignment degree;

[0114] Furthermore, in η k In the formula, the relative deviation of the period e in the k-th iteration is expressed by the logistic function logistic(·). k Preset threshold ε for deviation from period T The difference divided by the gating smoothing coefficient β gate The obtained real number is projected onto the (0,1) interval and used as the periodic gating factor η for the k-th iteration. k ;

[0115] Where φ k δφ represents the phase difference in the k-th iteration. probe Indicates φ k The perturbation amount with a preset step size, δφ probe Used to evaluate the periodic error function E period (·) directionality; E period (·) denotes the periodic error function; sgn(x) denotes the sign function, taking +1 for x>0, -1 for x<0, and 0 for x=0; α φ Indicates the step size for phase difference adjustment; φ min This represents the lower limit of the preset phase difference range; φ max Indicates the upper limit of the preset phase difference range; This represents the interval projection operator, which is used to map any real number to a preset interval [φ]. min ,φ max ]Inside;

[0116] Furthermore, in φ k+1 In the formula, the interval projection operator is used. The phase difference φ in the k-th iteration k Subtract the periodic gating factor η of the kth iteration k Adjusting the step size α by stepping the phase difference φ The update value obtained by multiplying and combining with the sign function sgn(·) is used to apply boundary constraints, ensuring that the phase after iterative update is always limited to the preset interval [φ]. min ,φ max In the process, the phase difference value φ for the next iteration is obtained. k+1 ;

[0117] Where T p (φ) represents the power fluctuation period measured when the phase difference is φ; Eperiod (φ) represents the absolute error between the measured power fluctuation period and the target power fluctuation period when the phase difference is φ;

[0118] Where P k (t) The instantaneous power curve of the k-th iteration, which varies with time t; W k t represents a power fluctuation period time window corresponding to the k-th iteration; argmin represents the value of the independent variable when the objective function reaches the lower limit of the preset interval; v,k Indicates W k Internal P k The power trough of (t);

[0119] Furthermore, in t v,k In the formula, W is defined by a power fluctuation period time window corresponding to the k-th iteration. k The instantaneous power curve P of the k-th iteration k (t) performs a lower limit calculation, outputting power at its lowest point t. v,k ;

[0120] Where mean(·) represents the arithmetic mean symbol; B k Indicates W k Local power baseline within;

[0121] Furthermore, in B k In the formula, W is defined by a power fluctuation period time window corresponding to the k-th iteration. k The instantaneous power curve P of the k-th iteration within k (t) Perform an arithmetic mean operation to obtain the local baseline B of the power within this window. k ;

[0122] Where P k (t v,k ) represents the instantaneous power value at the moment of power trough; ε P The lower limit threshold represents the instantaneous power; max(·) represents the upper limit operator; D k This represents the depth of the power trough in the instantaneous power curve during the k-th iteration;

[0123] Furthermore, in D k In the formula, W k Internal power local baseline B k The instantaneous power value P at the power trough k (t v,k The difference is calculated, and the lower limit threshold ε of the instantaneous power is selected using the upper limit value operator max(·). P and power local baseline B k The upper limit value is used to obtain the power trough depth D of the instantaneous power curve in the k-th iteration. k ;

[0124] Where R eq,k (t v,k ) represents the equivalent resistance curve for the k-th iteration; R base Indicates the equivalent resistance reference baseline; ε R R represents the lower threshold of the equivalent resistance. k D represents k The corresponding equivalent resistance;

[0125] Furthermore, in R k In the formula, the equivalent resistance curve of the k-th iteration is compared with the equivalent resistance reference baseline R. base With the lower limit threshold of equivalent resistance ε R The upper limit value selected in the middle is used to perform a ratio calculation to obtain the equivalent resistance corresponding to the power trough depth;

[0126] Where w D D represents k The weighting coefficient, w, takes the value of a positive real number and is usually set based on experience. R +w D＝1 ;w R R represents k The weighting coefficient, w, takes the value of a positive real number and is usually set based on experience. R +w D＝1 ; exp(·) represents the exponential function; ln(·) represents the logarithmic function; λ fuse This represents the fusion sharpness coefficient, which is used to control the bias of the fusion result.

[0127] In S3, the frequency difference and phase difference of the evaluation index are adjusted stepwise according to a preset step size to form a frequency difference sequence and a phase difference sequence.

[0128] Traverse all combinations of frequency difference sequences and phase difference sequences within the preset range, extract the corresponding evaluation index values ​​in sequence, identify the termination boundary point of the increasing interval of the evaluation index value, and determine the evaluation index value corresponding to the termination boundary point as the upper limit value of the evaluation index.

[0129] Extract the first and second frequencies generated during the step adjustment process corresponding to the upper limit values ​​of the evaluation indicators, and determine them as the optimized first and second frequencies. Simultaneously output the corresponding phase difference as the optimized phase difference.

[0130] Based on the optimized first and second frequencies, corresponding power fluctuation curves are generated, and the optimized power fluctuation period is identified in the power fluctuation curves. The optimized power fluctuation period is used to guide the timing control of drive current output and heating energy distribution during the peeling of special deck thick coating.

[0131] In S4, based on the optimized power fluctuation period, the voltage-to-current ratio sequence at the corresponding moment is extracted to obtain the corresponding equivalent resistance fluctuation period.

[0132] The optimized power fluctuation period and the corresponding equivalent resistance fluctuation period are mapped to a unified time axis, and a reference time alignment operation is performed.

[0133] On the aligned unified timeline, each power fluctuation period interval is traversed one by one to extract the power value change sequence within the interval.

[0134] In the aligned unified time axis, identify the continuous time period when the power fluctuation period and the equivalent resistance fluctuation period are both at the power trough depth, and determine this continuous time period as the power trough time interval. The power trough time interval is used to control the adjustment of the driving current amplitude and the distribution of heating energy during the peeling process of special deck thick coating, so as to ensure that the adhesive layer bonding surface can be stably peeled under low power conditions.

[0135] In S5, the original effective power value is obtained based on the product of voltage and current during the power trough time interval;

[0136] The target effective power value preset for the special deck thickness coating requirement is invoked to construct the power ratio between the original effective power value and the target effective power value;

[0137] Based on the relationship that the heating power of the heating coil is proportional to the square of the driving current amplitude, the square root operation is performed on the power ratio to obtain the correction factor of the current amplitude. The original driving current amplitude is multiplied by the correction factor to obtain the compensated driving current amplitude. The compensated driving current amplitude is used to control the heating intensity of the heating coil during the peeling of special thick coatings to ensure that the heating energy reaching the adhesive bonding surface after penetrating the conductive film meets the peeling requirements.

[0138] Define the amplitude of the compensated drive current I 补偿 :

[0139]

[0140] Where P 目标 P represents the target effective power value; 原始 Indicates the original effective power value; I represents the correction factor for the current amplitude. 原始 This indicates the magnitude of the original drive current.

[0141] In S6, the voltage and current are synchronously collected when the drive current amplitude is maintained during the power trough time interval, and the instantaneous power curve and the corresponding equivalent resistance curve are calculated.

[0142] Divide the instantaneous power value at each moment in the instantaneous power curve by the equivalent resistance value at the corresponding moment in the equivalent resistance curve to obtain the absorbed power sequence.

[0143] The cumulative energy is obtained by performing an accumulation operation on the product of the power value at each time point in the absorbed power sequence and the time difference between adjacent time points;

[0144] Divide the accumulated energy by the product of the material's specific heat capacity and mass to output local temperature rise data at the adhesive bonding surface. This local temperature rise data is used to assess whether the adhesive bonding surface has reached the heating state required to peel off the special deck thick coating during the process.

[0145] In S7, the local temperature rise data at the adhesive bonding surface is compared with the preset peeling temperature threshold required for special deck thickness coating. When the temperature rise data is greater than or equal to the preset peeling temperature threshold, a peeling condition satisfaction signal is output; otherwise, the temperature rise data calculation step is returned until the temperature rise data reaches the preset peeling temperature threshold.

[0146] It should be noted that, including but not limited to: This solution aims to solve the problems of low peeling efficiency and surface overheating caused by energy distribution imbalance during the current peeling process of special deck thick coatings. By introducing a drive current amplitude compensation mechanism based on the linkage between power fluctuation and equivalent resistance, the energy absorption and temperature rise at the adhesive layer bonding surface are accurately reflected, and dynamic control of the peeling process is reasonably implemented accordingly.

[0147] While existing heating coils can provide continuous electromagnetic energy when heating and peeling multilayer composite coatings, the energy is concentrated on the surface due to the shielding effect of the conductive film and uneven heat diffusion, making it difficult to accurately act on the adhesive bonding surface. This results in incomplete coating peeling and low efficiency.

[0148] Therefore, based on traditional power and current regulation, this solution constructs an execution process consisting of multiple stages, including power fluctuation cycle identification, power trough interval extraction, amplitude compensation calculation, and temperature rise determination, thereby improving the energy utilization efficiency and determination accuracy of the stripping process.

[0149] The specific implementation steps are divided into six progressively layered stages:

[0150] In the first stage, by acquiring continuous signals of driving current and coil voltage, the instantaneous power and equivalent resistance curves are calculated, and the correspondence between the power fluctuation period and the equivalent resistance fluctuation period is identified in the aligned unified time axis, forming a basic energy fluctuation expression structure.

[0151] In the second stage, the power trough moment is located in the power fluctuation cycle, and the time window when the energy can effectively penetrate the conductive film and be transferred to the adhesive layer bonding surface is determined by combining the equivalent resistance change at the corresponding moment. Then, the continuous trough interval is extracted as the power trough time interval.

[0152] In the third stage, based on the voltage and current signals within the trough time interval, the instantaneous power sequence and the corresponding equivalent resistance sequence are calculated, and the absorbed power sequence is obtained by dividing the instantaneous power value at each moment by the corresponding equivalent resistance value, so as to reflect the effective energy actually obtained by the adhesive bonding surface.

[0153] In the fourth stage, the absorbed power sequence is integrated over time to accumulate the energy value, which is then divided by the product of the material's specific heat capacity and mass to convert it into local temperature rise data, which is used to quantify the thermal response level of the adhesive bonding surface during the peeling process.

[0154] In the fifth stage, based on the physical relationship that the heating power of the heating coil is proportional to the square of the driving current amplitude, the current amplitude correction factor is calculated by taking the square root of the ratio of the target power to the current power, and then multiplied by the original driving current amplitude to output the compensated driving current amplitude, ensuring that the adhesive bonding surface can still obtain sufficient energy in the power trough range.

[0155] In the sixth stage, the local temperature rise data is compared with the threshold temperature required for stripping. If the threshold is reached or exceeded, the stripping conditions are confirmed to be met and the stripping operation continues. Otherwise, the process returns to the trough range to re-execute amplitude compensation and energy calculation, thus forming process control.

[0156] In summary, this solution starts with the identification of power fluctuation cycles and gradually introduces mechanisms for extracting low-temperature intervals, converting absorbed power, and determining amplitude and temperature rise. It no longer relies on surface temperature or a single power input as the basis for peeling, but instead uses the actual energy absorption and thermal effect of the adhesive bonding surface as the basis for judgment, which substantially improves the accuracy, energy efficiency and controllability of peeling off thick coatings on special decks.

[0157] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A target control method for optimizing parameters of an electromagnetic induction system, characterized in that, include: S1: Simultaneously input a first frequency signal and a second frequency signal into the electromagnetic induction heating coil, adjust the phase difference stepwise within a preset frequency difference range according to a preset step size, calculate the instantaneous power curve, measure the time interval between adjacent instantaneous power troughs, and obtain the power fluctuation period. S2: When the deviation between the power fluctuation period and the target period exceeds the preset range, the phase difference is adjusted to bring the deviation into the preset range, and the trough depth of the instantaneous power curve and the corresponding equivalent resistance are constructed as evaluation indicators based on the preset weight. S3: The evaluation indexes are adjusted stepwise according to the preset step size for the frequency difference and phase difference, the upper limit of the evaluation indexes within the preset range is identified, and the optimized first frequency, second frequency and corresponding power fluctuation period are output. S4: Align the optimized power fluctuation period with the corresponding equivalent resistance fluctuation period on the time axis to identify the low power range and output the low power time range. S5: At the beginning of the power trough time interval, based on the ratio of the effective power during the original power trough to the target effective power, calculate the compensated drive current amplitude according to the relationship that the power is proportional to the square of the drive current amplitude. S6: Collect the voltage and current when maintaining the output of the drive current amplitude during the power trough, and combine them with the equivalent resistance curve to calculate the local temperature rise data according to the product relationship between absorbed power, material specific heat capacity and mass. S7: Compare the local temperature rise data with the preset peeling temperature threshold and output a peeling condition met signal.

2. The target control method for optimizing parameters of an electromagnetic induction system according to claim 1, characterized in that: In S1, under the condition that the frequency difference between the first frequency signal and the second frequency signal is less than a preset interval and the phase is fixed, the phase difference between the first frequency signal and the second frequency signal is adjusted stepwise according to a preset step size to form a phase difference adjustment sequence. The voltage and current corresponding to each phase difference in the phase difference adjustment sequence of the electromagnetic induction heating coil are collected, and the voltage and current corresponding to each phase difference are multiplied to obtain the instantaneous power curve; Identify all adjacent power troughs in the instantaneous power curve, measure the time interval between adjacent power troughs, and determine the measured time interval as the power fluctuation period.

3. The target control method for optimizing parameters of an electromagnetic induction system according to claim 2, characterized in that: In S2, the deviation between the power fluctuation period and the target period is calculated, and it is determined whether the deviation exceeds the preset range. When the deviation exceeds the preset range, the phase difference between the first frequency signal and the second frequency signal is adjusted stepwise according to the preset step size so that the deviation comes within the preset range. Extract the power trough depth and the equivalent resistance at the corresponding moment from the instantaneous power curve within the preset range, and combine them according to preset weights to construct evaluation indicators.

4. The target control method for optimizing parameters of an electromagnetic induction system according to claim 3, characterized in that: S2 also includes defining the evaluation index J. k Based on the logarithmic function ln(·) and the exponential function exp(·), the depth D of the power trough of the instantaneous power curve in the k-th iteration is calculated. k and the corresponding equivalent resistance R k We will perform weighted fusion to construct the evaluation index J. k ; Formula 1: Formula 2: Formula 3: Formula 4: E period (φ)=|T p (φ)-T target | Formula 5: Formula Six: B k =mean{P k (t)∣t∈W k } Formula 7: Formula 8: Formula Nine: Where e k T represents the relative deviation of the period in the k-th iteration; p,k T represents the power fluctuation period measured from the instantaneous power curve during the k-th iteration; target Indicates the period of target power fluctuation; Where ε T The preset threshold representing the periodic deviation; β gate Represents the gating smoothing coefficient; logistic(·) represents the logistic function; η k This represents the periodic gating factor for the k-th iteration; Where φ k δφ represents the phase difference in the k-th iteration. probe Indicates φ k The amount of disturbance applied with a preset step size; E period (·) denotes the periodic error function; sgn(x) denotes the sign function; α φ Indicates the step size for phase difference adjustment; φ min This indicates the lower limit of the preset phase difference range; φ max Indicates the upper limit of the preset interval for phase difference; Represents the interval projection operator; Where T p (φ) represents the power fluctuation period measured when the phase difference is φ; E period (φ) represents the absolute error between the measured power fluctuation period and the target power fluctuation period when the phase difference is φ; Where P k (t) The instantaneous power curve of the k-th iteration, which varies with time t; W k argmin represents the power fluctuation period time window corresponding to the k-th iteration; argmin represents the value of the independent variable when the objective function reaches the lower limit of the preset interval; t v,k Indicates W k Internal P k The power trough of (t); Where mean(·) represents the arithmetic mean symbol; B k Indicates W k Local power baseline within; Where P k (t v,k ) represents the instantaneous power value at the moment of power trough; ε P The lower limit threshold represents the instantaneous power; max(·) represents the upper limit operator; D k This represents the depth of the power trough in the instantaneous power curve during the k-th iteration; Where R eq,k (t v,k ) represents the equivalent resistance curve for the k-th iteration; R base Indicates the equivalent resistance reference baseline; ε R R represents the lower threshold of the equivalent resistance. k D represents k The corresponding equivalent resistance; Where w D D represents k Weighting coefficients; w R R represents k The weighting coefficients; exp(·) represents the exponential function; ln(·) represents the logarithmic function; λ fuse This represents the blending sharpness coefficient.

5. The target control method for optimizing parameters of an electromagnetic induction system according to claim 4, characterized in that: In S3, the frequency difference and phase difference of the evaluation index are adjusted stepwise according to a preset step size to form a frequency difference sequence and a phase difference sequence. Traverse all combinations of frequency difference sequences and phase difference sequences within the preset range, extract the corresponding evaluation index values ​​in sequence, identify the termination boundary point of the increasing interval of the evaluation index value, and determine the evaluation index value corresponding to the termination boundary point as the upper limit value of the evaluation index. The first and second frequencies generated during the step adjustment process corresponding to the upper limit values ​​of the evaluation indicators are extracted and determined as the optimized first and second frequencies. Based on the optimized first and second frequencies, corresponding power fluctuation curves are generated, and the optimized power fluctuation period is identified in the power fluctuation curves.

6. The target control method for optimizing parameters of an electromagnetic induction system according to claim 5, characterized in that: In S4, based on the optimized power fluctuation period, the voltage-to-current ratio sequence at the corresponding moment is extracted to obtain the corresponding equivalent resistance fluctuation period. The optimized power fluctuation period and the corresponding equivalent resistance fluctuation period are mapped to a unified time axis, and a reference time alignment operation is performed. On the aligned unified timeline, each power fluctuation period interval is traversed one by one to extract the power value change sequence within the interval. In the aligned unified time axis, identify the continuous time intervals where the power fluctuation period and the equivalent resistance fluctuation period are both at the power trough depth, and determine them as the power trough time intervals.

7. The target control method for optimizing parameters of an electromagnetic induction system according to claim 6, characterized in that: In S5, the original effective power value is obtained based on the product of voltage and current during the power trough time interval; The target effective power value preset for the special deck thickness coating requirement is invoked to construct the power ratio between the original effective power value and the target effective power value; Based on the relationship that the heating power of the heating coil is proportional to the square of the driving current amplitude, the square root operation is performed on the power ratio to obtain the correction factor of the current amplitude. The original driving current amplitude is multiplied by the correction factor to obtain the compensated driving current amplitude.

8. The target control method for optimizing parameters of an electromagnetic induction system according to claim 7, characterized in that: In S6, the voltage and current are synchronously collected when the drive current amplitude is maintained during the power trough time interval, and the instantaneous power curve and the corresponding equivalent resistance curve are calculated. Divide the instantaneous power value at each moment in the instantaneous power curve by the equivalent resistance value at the corresponding moment in the equivalent resistance curve to obtain the absorbed power sequence. The cumulative energy is obtained by performing an accumulation operation on the product of the power value at each time point in the absorbed power sequence and the time difference between adjacent time points; The local temperature rise data is output by dividing the accumulated energy by the product of the material's specific heat capacity and mass.

9. The target control method for optimizing parameters of an electromagnetic induction system according to claim 8, characterized in that: In S7, the local temperature rise data at the adhesive bonding surface is compared with the preset peeling temperature threshold required for special deck thickness coating. When the temperature rise data is greater than or equal to the preset peeling temperature threshold, a peeling condition satisfaction signal is output; otherwise, the temperature rise data calculation step is returned until the temperature rise data reaches the preset peeling temperature threshold.

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