Method, device and equipment for evaluating turn-to-turn short circuit fault of No.7 wheel electromagnetic heating coil

Abstract

The invention discloses a No.7 wheel electromagnetic heating coil turn-to-turn short circuit fault assessment method, device and equipment. The method comprises the steps of calculating at least one fault measurement index value according to a power supply input voltage and a loop current of a target electromagnetic heating coil; when it is determined that the target electromagnetic heating coil has a fault risk according to the fault measurement index value, inputting the power supply input voltage and the loop current into a pre-constructed sliding mode observer for iterative calculation to obtain to-be-estimated parameters; calculating a fault inductance estimated value according to the to-be-estimated parameter, and obtaining a short circuit proportion of the target electromagnetic heating coil according to a pre-constructed quantitative mapping relation between the fault inductance and the short circuit proportion; and performing grading judgment on the short circuit proportion and the fault inductance estimation value based on a preset fault grading rule to obtain a fault evaluation result of the target electromagnetic heating coil. According to the technical scheme of the invention, quantitative evaluation of the turn-to-turn short circuit fault of the electromagnetic heating coil can be realized, and the accuracy and efficiency of fault evaluation are improved.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, and in particular to a method, apparatus and equipment for assessing inter-turn short-circuit faults in the electromagnetic heating coil of wheel No. 7. Background Technology

[0002] In the cigarette packaging production process, the No. 7 roller is a core component for heat sealing of cigarette packs, and its performance directly determines the packaging sealing quality and production efficiency. The electromagnetic heating coil equipped with this component generates a high-frequency alternating magnetic field through a series resonant circuit based on inductance and capacitance, causing the packaging material to heat up and solidify rapidly, achieving reliable heat sealing. However, the No. 7 roller needs to meet continuous, high-speed production cycles, causing its electromagnetic heating coil to operate under harsh conditions of high frequency, high current, and high temperature for extended periods. Under these conditions, the insulation layer of the coil winding is highly susceptible to accelerated aging and cracking due to thermal fatigue and electrical stress, leading to inter-turn short circuit faults. Since inter-turn short circuit faults are extremely dangerous, timely detection of inter-turn short circuit faults is crucial.

[0003] In existing technologies, inter-turn short-circuit faults are generally identified through periodic manual inspections or by directly tripping the circuit breaker via overcurrent protection. However, periodic manual inspections suffer from long intervals, high subjectivity, and high costs. They are extremely insensitive to early, minor inter-turn short-circuit characteristics, failing to provide early warnings or real-time monitoring. Furthermore, traditional current and voltage amplitude detection methods are highly susceptible to interference in high-frequency electromagnetic fields and complex industrial electromagnetic noise, resulting in low signal-to-noise ratios and a high risk of false or missed alarms, compromising reliability. Overcurrent protection measures only trip when the short-circuit current reaches a dangerous threshold, representing reactive protection and failing to differentiate the severity of the fault. They cannot provide early warnings or quantitative status assessments after a fault occurs, making it impossible for maintenance personnel to scientifically judge the fault's development trend and formulate preventative maintenance strategies.

[0004] Therefore, how to conduct real-time online monitoring of coil inter-turn short circuit faults, accurately identify early minor short circuits, and quantitatively grade and assess the severity of faults to provide solid technical support for predictive health management and intelligent maintenance of tobacco packaging equipment is an urgent problem to be solved. Summary of the Invention

[0005] This invention provides a method, apparatus, and equipment for assessing inter-turn short-circuit faults in the electromagnetic heating coil of wheel No. 7, which can solve the problems of existing technologies such as reliance on manual inspection, inability to monitor in real time, difficulty in early fault identification, lack of quantitative assessment standards, and weak anti-interference ability.

[0006] According to one aspect of the present invention, a method for assessing inter-turn short-circuit faults in the electromagnetic heating coil of a No. 7 wheel is provided, comprising:

[0007] The power input voltage and loop current of the target electromagnetic heating coil are collected in real time according to the preset collection frequency. Based on the collected power input voltage and loop current, at least one fault measurement index value matching the target electromagnetic heating coil is calculated.

[0008] When determining the risk of failure of the target electromagnetic heating coil based on the values ​​of various fault measurement indicators, the input voltage of each power supply and the current of each loop are input into a pre-built sliding mode observer for iterative calculation to obtain the estimated parameters used to measure the fault inductance value; wherein, the sliding mode observer is designed based on the state equation of the inductor-capacitor series resonant circuit.

[0009] Based on the parameters to be estimated, the estimated value of the fault inductance is calculated, and based on the pre-constructed quantitative mapping relationship between the fault inductance and the short-circuit ratio, the short-circuit ratio of the target electromagnetic heating coil is obtained.

[0010] Based on the preset fault classification rules, the short-circuit ratio and fault inductance estimate of the target electromagnetic heating coil are classified and judged to obtain the fault assessment result of the target electromagnetic heating coil.

[0011] According to another aspect of the present invention, a device for assessing inter-turn short-circuit faults in the electromagnetic heating coil of a No. 7 wheel is provided, comprising:

[0012] The data acquisition module is used to acquire the power input voltage and loop current of the target electromagnetic heating coil in real time according to a preset acquisition frequency, and calculate at least one fault measurement index value that matches the target electromagnetic heating coil based on the acquired multiple power input voltages and multiple loop currents.

[0013] The fault measurement module is used to input the input voltage of each power supply and the current of each loop into a pre-built sliding mode observer for iterative calculation when it is determined that the target electromagnetic heating coil has a fault risk based on the values ​​of each fault measurement index. The sliding mode observer is designed based on the state equation of the inductor-capacitor series resonant circuit.

[0014] The quantitative mapping module is used to calculate the estimated value of the fault inductance based on the parameters to be estimated, and to obtain the short-circuit ratio of the target electromagnetic heating coil based on the pre-constructed quantitative mapping relationship between the fault inductance and the short-circuit ratio.

[0015] The fault assessment module is used to classify and judge the short-circuit ratio and fault inductance estimate of the target electromagnetic heating coil based on preset fault classification rules, and obtain the fault assessment result of the target electromagnetic heating coil.

[0016] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0017] At least one processor; and

[0018] A memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the inter-turn short-circuit fault assessment method for the No. 7 wheel electromagnetic heating coil according to any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement the inter-turn short-circuit fault assessment method for the electromagnetic heating coil of wheel No. 7 as described in any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the inter-turn short-circuit fault assessment method for the electromagnetic heating coil of wheel No. 7 as described in any embodiment of the present invention.

[0022] The technical solution of this invention involves real-time acquisition of the power input voltage and loop current of a target electromagnetic heating coil at a preset acquisition frequency. Based on the acquired power input voltages and loop currents, at least one fault assessment index value matching the target electromagnetic heating coil is calculated. Then, when a fault risk is determined for the target electromagnetic heating coil based on the fault assessment index values, each power input voltage and loop current is input into a pre-constructed sliding mode observer for iterative calculation to obtain parameters to be estimated for measuring the fault inductance value. Further, an estimated fault inductance value is calculated based on the estimated parameters, and the short-circuit ratio of the target electromagnetic heating coil is obtained based on a pre-constructed quantitative mapping relationship between fault inductance and short-circuit ratio. Finally, the short-circuit ratio and estimated fault inductance value of the target electromagnetic heating coil are graded according to preset fault classification rules to obtain the fault assessment result of the target electromagnetic heating coil. By employing magnetically coupled block modeling, sliding mode observer estimation, and graded evaluation processes, the degree of fault can be accurately quantified. This solves the problems of existing technologies, such as reliance on manual inspection, inability to monitor in real time, difficulty in early fault identification, lack of quantitative evaluation standards, and weak anti-interference capabilities. It enables real-time online monitoring of coil turn-to-turn short circuit faults, accurate identification of early minor short circuits, and quantitative grading evaluation of fault severity, thereby improving the accuracy and efficiency of fault assessment and providing solid technical support for predictive health management and intelligent maintenance of tobacco packaging equipment.

[0023] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart of a method for assessing inter-turn short-circuit faults in the electromagnetic heating coil of wheel No. 7 according to Embodiment 1 of the present invention;

[0026] Figure 2 This is a flowchart of a method for assessing inter-turn short-circuit faults in the electromagnetic heating coil of wheel No. 7 according to Embodiment 2 of the present invention;

[0027] Figure 3 This is a schematic diagram of the structure of a No. 7 wheel electromagnetic heating coil provided according to Embodiment 2 of the present invention;

[0028] Figure 4 This is a flowchart of an optional inter-turn short-circuit fault assessment method for the electromagnetic heating coil of wheel No. 7 according to Embodiment 2 of the present invention;

[0029] Figure 5 This is a schematic diagram of the structure of a short-circuit fault assessment device for an electromagnetic heating coil of a No. 7 wheel according to Embodiment 3 of the present invention;

[0030] Figure 6 This is a schematic diagram of the structure of an electronic device that implements the inter-turn short-circuit fault assessment method for the electromagnetic heating coil of wheel number seven according to an embodiment of the present invention. Detailed Implementation

[0031] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first," "second," "target," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] Example 1

[0034] Figure 1 This is a flowchart of a method for assessing inter-turn short-circuit faults in the electromagnetic heating coil of a No. 7 wheel according to Embodiment 1 of the present invention. This embodiment is applicable to situations requiring real-time fault monitoring of the electromagnetic heating coil in a No. 7 wheel. This method can be executed by an inter-turn short-circuit fault assessment device for the No. 7 wheel's electromagnetic heating coil. This device can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0035] S110. Collect the power input voltage and loop current of the target electromagnetic heating coil in real time according to the preset collection frequency, and calculate at least one fault measurement index value that matches the target electromagnetic heating coil based on the multiple power input voltages and multiple loop currents collected.

[0036] The sampling frequency refers to the number of times the sensor collects signal data per second. For example, in this embodiment of the invention, to ensure signal integrity, the preset sampling frequency can be set to 1MHz. The electromagnetic heating coil refers to an induction coil or excitation coil that converts electrical energy into heat energy using the principle of electromagnetic induction. Typically, the electromagnetic heating coil itself does not generate heat; instead, it generates a high-frequency alternating magnetic field, causing the metal object within the magnetic field to heat up internally. The target electromagnetic heating coil refers to the electromagnetic heating coil selected for fault monitoring. For example, in this embodiment of the invention, the target electromagnetic heating coil can be the electromagnetic heating coil equipped for wheel number seven in any cigarette packaging production workshop. The power input voltage refers to the power supply voltage supplied to the entire electromagnetic heating equipment, such as the inverter or mainboard inside the target electromagnetic heating coil. The loop current refers to the high-frequency alternating current flowing through the target electromagnetic heating coil itself. The fault measurement index value refers to the index value used to qualitatively determine the fault condition of the target electromagnetic heating coil.

[0037] S120. When it is determined that the target electromagnetic heating coil has a fault risk based on the values ​​of each fault measurement index, the input voltage of each power supply and the current of each circuit are input to the pre-constructed sliding mode observer for iterative calculation to obtain the estimated parameters used to measure the fault inductance value; wherein, the sliding mode observer is designed based on the state equation of the inductor-capacitor series resonant circuit.

[0038] Inter-turn short circuit refers to a situation where the insulation between adjacent turns of a coil breaks down, causing direct connection. Typically, an inter-turn short circuit can lead to a sharp drop in the local resistance of the coil, forming a short-circuit loop. This generates huge eddy currents and heat at the short-circuit point, instantly melting the copper tubing and causing a change in the overall inductance, thus disrupting the resonance condition. Fault risk refers to the probability of an inter-turn short circuit occurring. A sliding mode observer is an intelligent estimator used to simulate a real system. Typically, by comparing the output of the sliding mode observer with the measurable output of the actual system, such as current or voltage, the internal state of the sliding mode observer is continuously corrected to approximate the real state. The parameter to be estimated refers to an inherent characteristic of the system that is desired in the mathematical model but cannot be directly measured. For example, the inductance value of a healthy system. The fault inductance value refers to the specific change in the parameter to be estimated when a fault occurs in the system, such as an inter-turn short circuit. Typically, the fault inductance value can serve as quantitative evidence of the fault.

[0039] S130. Based on the parameters to be estimated, calculate the estimated value of the fault inductance, and based on the pre-constructed quantitative mapping relationship between the fault inductance and the short-circuit ratio, obtain the short-circuit ratio of the target electromagnetic heating coil.

[0040] The short-circuit percentage can refer to the portion of the coil that experiences a short-circuit fault, such as the number of short-circuited turns, as a proportion of the total number of turns in the coil. The quantitative mapping relationship refers to the correspondence between the short-circuit percentage and observable changes in electrical parameters, such as the estimated fault inductance, which can be precisely described by a mathematical formula. Typically, the quantitative mapping relationship can reveal the inherent pattern between the severity of the fault and its external manifestations.

[0041] S140. Based on the preset fault classification rules, the short-circuit ratio and fault inductance estimation value of the target electromagnetic heating coil are classified and judged to obtain the fault assessment result of the target electromagnetic heating coil.

[0042] Fault classification refers to the process of intuitively categorizing the severity of a fault. For example, fault classification could categorize fault severity into minor short circuits, moderate short circuits, severe short circuits, and extremely severe short circuits. Preset fault classification rules refer to pre-defined rules that define the fault classification process. Fault assessment results refer to the fault classification results obtained after quantitatively assessing the short circuit percentage and estimated fault inductance using the preset fault classification rules.

[0043] The technical solution of this invention involves real-time acquisition of the power input voltage and loop current of a target electromagnetic heating coil at a preset acquisition frequency. Based on the acquired power input voltages and loop currents, at least one fault assessment index value matching the target electromagnetic heating coil is calculated. Then, when a fault risk is determined for the target electromagnetic heating coil based on the fault assessment index values, each power input voltage and loop current is input into a pre-constructed sliding mode observer for iterative calculation to obtain parameters to be estimated for measuring the fault inductance value. Further, an estimated fault inductance value is calculated based on the estimated parameters, and the short-circuit ratio of the target electromagnetic heating coil is obtained based on a pre-constructed quantitative mapping relationship between fault inductance and short-circuit ratio. Finally, the short-circuit ratio and estimated fault inductance value of the target electromagnetic heating coil are graded according to preset fault classification rules to obtain the fault assessment result of the target electromagnetic heating coil. By employing magnetically coupled block modeling, sliding mode observer estimation, and graded evaluation processes, the degree of fault can be accurately quantified. This solves the problems of existing technologies, such as reliance on manual inspection, inability to monitor in real time, difficulty in early fault identification, lack of quantitative evaluation standards, and weak anti-interference capabilities. It enables real-time online monitoring of coil turn-to-turn short circuit faults, accurate identification of early minor short circuits, and quantitative grading evaluation of fault severity, thereby improving the accuracy and efficiency of fault assessment and providing solid technical support for predictive health management and intelligent maintenance of tobacco packaging equipment.

[0044] Example 2

[0045] Figure 2 This is a flowchart of a method for assessing inter-turn short-circuit faults in the electromagnetic heating coil of wheel No. 7, provided in Embodiment 2 of the present invention. This embodiment is a refinement based on the above embodiment. Specifically, it refines the step of "inputting each power supply input voltage and each loop current into a pre-constructed sliding mode observer for iterative calculation to obtain the estimated parameters used to measure the fault inductance value." Specifically, it may include: calculating each power supply input voltage and each loop current using the observer control law and initial estimate value corresponding to the sliding mode observer to obtain an initial current estimate value; comparing the initial current estimate value and the loop current to obtain a corresponding initial sliding surface; and performing a threshold judgment on the initial sliding surface based on a preset sliding surface convergence threshold to obtain a third threshold judgment result; and optimizing the initial estimate value based on the third threshold judgment result to obtain the estimated parameters used to measure the fault inductance value. Figure 2 As shown, the method includes:

[0046] S210. Collect the power input voltage and loop current of the target electromagnetic heating coil in real time according to the preset acquisition frequency.

[0047] Specifically, when assessing the inter-turn short-circuit fault of the target electromagnetic heating coil (electromagnetic heating coil of wheel number seven), the voltage sensor corresponding to the target electromagnetic heating coil can be used to collect the power input voltage of the target electromagnetic heating coil in real time at a preset sampling frequency. Similarly, the high-frequency current sensor corresponding to the target electromagnetic heating coil can be used to collect the loop current of the target electromagnetic heating coil in real time at a preset sampling frequency. This provides a solid foundation for subsequent operations.

[0048] S220. Based on preset data processing rules, filter the multiple power input voltages collected to obtain a target power input voltage set, and based on preset data processing rules, filter the multiple loop currents collected to obtain a target loop current set.

[0049] The preset data processing rules refer to pre-defined rules that define the data processing flow. For example, preset data processing rules can be anti-aliasing filtering and digital low-pass filtering. This removes a large amount of high-frequency noise from the acquired signal while retaining the main harmonic components. The target power input voltage refers to the power input voltage after processing by the preset data processing rules. The target power input voltage set refers to the set of all target power input voltages within the preset data window. The target loop current refers to the loop current after processing by the preset data processing rules. The target loop current set refers to the set of all target loop currents within the preset data window. It is worth noting that in this embodiment of the invention, the preset data window can refer to the length of an integer number of fundamental frequency periods. Typically, this can be determined by the fundamental frequency and the preset acquisition frequency. For example, with a preset acquisition frequency of 1MHz and a fundamental frequency of f1=250kHz, the data points corresponding to 4 periods are (1 / f1)×4×1MHz=16 points, meaning the preset data window contains 16 data points.

[0050] S230. Perform a Discrete Fourier Transform on the target power input voltage set to obtain the voltage spectrum corresponding to the target electromagnetic heating coil, and perform a Discrete Fourier Transform on the target circuit current set to obtain the current spectrum corresponding to the target electromagnetic heating coil.

[0051] The Discrete Fourier Transform (DFT) refers to the algorithm that transforms a finite-length, discrete digital signal (time domain signal) into a set of complex coefficients at discrete frequencies (frequency domain signal), thus revealing the frequency composition of the signal. The voltage spectrum refers to the graphical or data representation of the power supply input voltage after converting it from the time domain to the frequency domain. Typically, the voltage spectrum reflects the characteristics of the excitation source, clearly indicating which frequencies of sine waves constitute the power supply input voltage, and the amplitude and phase of each frequency component. The current spectrum refers to the graphical or data representation of the loop current after converting it from the time domain to the frequency domain. Typically, the current spectrum reflects the load's response characteristics to voltage excitation, clearly indicating which frequencies of sine waves constitute the loop current, and the amplitude and phase of each frequency component.

[0052] S240. Obtain the fundamental frequency corresponding to the target electromagnetic heating coil, and perform data indexing calculation on the voltage spectrum and current spectrum based on the fundamental frequency to obtain at least one fault measurement index value that matches the target electromagnetic heating coil; wherein, the fault measurement index value includes the fundamental phase difference or the total harmonic distortion rate of the current.

[0053] The fundamental frequency refers to the frequency of the most dominant and highest-energy sinusoidal component in a periodic alternating current signal. Typically, the fundamental frequency is the preset operating frequency used by an electromagnetic heating system to generate the alternating magnetic field. For example, if a frequency converter drives a motor at 30Hz, the fundamental frequencies of the output voltage and current are both 30Hz. The fundamental phase difference refers to the time-axis offset between the fundamental components of the voltage and current in the same system. For example, the fundamental phase difference can be represented by angles, describing the degree of inconsistency between the two sinusoidal waves of voltage and current. For example, it indicates which is leading and which is lagging, and by how many degrees. Generally, a negative fundamental phase difference indicates that the current leads the voltage; a zero fundamental phase difference indicates that the current and voltage are in phase; and a positive fundamental phase difference indicates that the current lags behind the voltage. The total harmonic distortion (THD) of the current is a key quantitative indicator used to measure the degree to which the current waveform deviates from a perfect sine wave. It is typically expressed as a percentage.

[0054] Specifically, after acquiring the power input voltage and loop current of the target electromagnetic heating coil, the acquired multiple power input voltages can first be denoised and filtered using preset data processing rules to obtain the main harmonic components. Then, data points within a preset data window are extracted from the continuous data to form the target power input voltage set and the target loop current set. Next, a Discrete Fourier Transform (DFT) is performed on the target power input voltage set to obtain the voltage spectrum corresponding to the target electromagnetic heating coil, and a DFT is performed on the target loop current set to obtain the current spectrum corresponding to the target electromagnetic heating coil. Further, based on the known fundamental frequency f1, its corresponding index position k1 = f1 / Δf in the spectrum is calculated, where Δf represents the spectral resolution, Δf = sampling frequency / number of data points. The index position k1 is then used to index the voltage and current spectra to obtain the complex voltage and complex current corresponding to index position k1. Furthermore, the complex voltage is calculated using the four-quadrant arctangent function to obtain the fundamental voltage phase. Similarly, the complex current is calculated using the same four-quadrant arctangent function to obtain the fundamental current phase. The difference between the fundamental voltage and current phases is then calculated as the fundamental phase difference. Simultaneously, the amplitudes of the second to fourth harmonics are extracted from the current spectrum. The square root of the sum of the squares of the effective values ​​of all harmonic components is then divided by the effective value of the fundamental component to obtain the total harmonic distortion rate of the current. Therefore, by using high-precision discrete Fourier transform to decompose the time-domain signal into a spectrum, and then determining the phase information of the fundamental wave and the amplitude information of each harmonic from the spectrum, and finally substituting these values ​​into the formula, the timeliness and accuracy of signal processing can be guaranteed, providing a solid foundation for subsequent operations.

[0055] S250. Based on a preset fundamental phase difference threshold, a threshold judgment is made on the fundamental phase difference to obtain a first threshold judgment result.

[0056] The preset fundamental phase difference threshold can refer to a pre-set value used to evaluate the fundamental phase difference. For example, in this embodiment of the invention, the preset fundamental phase difference threshold can be 5°. The threshold judgment result can refer to the judgment result obtained after judging the data using the preset threshold. For example, the threshold judgment result can be either exceeding the preset threshold or falling below the preset threshold. The first threshold judgment result can refer to the judgment result obtained after threshold judgment of the fundamental phase difference using the preset fundamental phase difference threshold. For example, the first threshold judgment result can be either the fundamental phase difference exceeding the preset fundamental phase difference threshold or the fundamental phase difference being lower than or equal to the preset fundamental phase difference threshold.

[0057] S260. Based on a preset total harmonic distortion rate threshold, a threshold judgment is made on the total harmonic distortion rate of the current to obtain a second threshold judgment result.

[0058] The preset total harmonic distortion (THD) threshold can refer to a pre-set value used to evaluate the THD. For example, in this embodiment of the invention, the preset THD threshold can be 5%. The second threshold judgment result can refer to the judgment result obtained after judging the THD using the preset THD threshold. For example, the second threshold judgment result can be that the THD exceeds the preset THD threshold, or that the THD is lower than or equal to the preset THD threshold.

[0059] S270. If the first threshold judgment result exceeds the preset fundamental phase difference threshold, or the second threshold judgment result exceeds the preset total harmonic distortion rate threshold, then it is determined that the target electromagnetic heating coil has a fault risk.

[0060] Specifically, after obtaining fault assessment indicators such as the fundamental phase difference and the total harmonic distortion (THD) of the current, a first threshold judgment result can be obtained by using a preset fundamental phase difference threshold. Simultaneously, a second threshold judgment result can be obtained by using a preset THD threshold. If the first threshold judgment result indicates that the fundamental phase difference is lower than or equal to the preset fundamental phase difference threshold, and the second threshold judgment result indicates that the THD is lower than or equal to the preset THD threshold, then the target electromagnetic heating coil is determined to be in a fault-free normal state, and monitoring continues. Conversely, if the first threshold judgment result exceeds the preset fundamental phase difference threshold, or the second threshold judgment result exceeds the preset THD threshold, then the target electromagnetic heating coil is determined to have a fault risk, and a sliding mode observer needs to be activated for precise diagnosis. Therefore, by using preset thresholds to perform a coarse fault assessment of the target electromagnetic heating coil, fault-free normal states can be eliminated, reducing computational costs for subsequent data processing.

[0061] S280. Calculate the input voltage of each power supply and the current of each loop using the observer control law and initial estimate value corresponding to the sliding mode observer to obtain the initial current estimate value.

[0062] The observer control law can be a mathematical rule or algorithm that guides the observer on how to use system input and output information to dynamically correct its internal state estimates and force the estimation error to converge to zero. The initial estimate can refer to the value of the parameter to be estimated in the initial state. The current estimate can refer to the estimated inductor current output by the observer in real time. The initial current estimate can refer to the current estimate output during the first iteration.

[0063] For example, in an embodiment of the present invention, to reduce noise interference, a saturation function can be used instead of the sign function, and the observer control law can be designed as follows: .in, = It can represent the current estimate. It can represent capacitor voltage. It can represent the total equivalent resistance of a circuit. , It can represent the coil resistance. It can represent the equivalent resistance of inductive reactance. This can represent the additional resistance introduced by a fault. Typically, and These are inherent parameters of the system. For example, they can be calculated using voltage and current data under rated operating conditions. . It can represent the input voltage of a fixed-frequency power supply. , It can represent the voltage amplitude. It can represent angular frequency. It can represent sliding mode gain. It can represent a saturation function. The boundary layer thickness can be represented by s, and the sliding surface can be represented by s. = It can represent the estimated parameter values ​​that are updated online and in real time by the observer. . This can represent the gain of parameter updates. Typically, It is a manually defined positive scalar that directly controls the parameter to be estimated. The speed and magnitude of updates based on observation errors. This is equivalent to... This determines the rate and magnitude at which the observer should adjust its focus on key parameters when current tracking errors exist. The estimated value .

[0064] Meanwhile, the state equation can be expressed as: , ,in, It can represent the rate of change of capacitor voltage over time. It can represent the loop current acquired in real time, and C can represent the capacitance value. Usually, C is a known circuit parameter. It can represent the rate of change of inductor current over time. It can represent the capacitor voltage. Typically, it's a key parameter. L can represent the inductance value.

[0065] S290. The initial current estimate and the loop current are compared and processed to obtain the corresponding initial sliding surface. The initial sliding surface is then judged based on a preset sliding surface convergence threshold to obtain a third threshold judgment result.

[0066] Here, the sliding surface can refer to the estimation error of the current. For example, it can be represented by the formula: The initial sliding surface can refer to the sliding surface calculated using various parameters in the first iteration. The preset sliding surface convergence threshold can refer to a pre-set value used to evaluate the sliding surface. For example, the preset sliding surface convergence threshold can be 0. The third threshold judgment result can refer to the judgment result obtained after performing a threshold judgment on the initial sliding surface using the preset sliding surface convergence threshold. For example, the third threshold judgment result can be that the initial sliding surface is approximately equal to the preset sliding surface convergence threshold, or it can be that the initial sliding surface exceeds the preset sliding surface convergence threshold.

[0067] S2100. Based on the third threshold judgment result, the initial estimated value is optimized to obtain the estimated parameter used to measure the value of fault inductance.

[0068] Data optimization can refer to the process of dynamically adjusting the estimated parameters by adjusting the adjustment parameters so that the estimated parameters gradually meet the preset sliding surface convergence threshold.

[0069] Specifically, when a fault risk is identified in the target electromagnetic heating coil, a sliding mode observer can be activated. Given an initial estimate, and continuously inputting measured values ​​for the power input voltage, loop current, and capacitor voltage, the observer's control law calculates an initial current estimate, which is then compared with the actual measured loop current to generate an initial sliding surface. Further, it is determined whether the initial sliding surface approaches a preset sliding surface convergence threshold. If so, the observer has successfully converged, and the initial estimate is used as the final parameter to be estimated. Otherwise, the initial estimate needs to be optimized to obtain the parameter to measure the fault inductance. Therefore, by using a saturation function to optimize the sliding mode observer, its anti-interference capability can be improved, reducing the fault inductance estimation error, enabling the identification of early minor short circuits, and improving the accuracy of quantitative estimation.

[0070] In an optional implementation, the initial estimate is optimized based on the third threshold judgment result to obtain the parameters to be estimated for measuring the fault inductance value, including:

[0071] Step a1: If the third threshold judgment result is that the initial sliding surface exceeds the preset sliding surface convergence threshold, then the initial estimated value is adjusted based on the preset parameter update gain to obtain the updated current estimated value.

[0072] The preset parameter update gain can refer to the pre-set parameter update gain. The current estimated value can refer to the parameter to be estimated in the current processing round. Typically, the current processing round can be any round other than the first processing round.

[0073] Step a2: Calculate the input voltage of each power supply and the current of each circuit based on the current estimated value to obtain the current estimated value.

[0074] The current current estimate can refer to the current estimate corresponding to the current processing round, which is calculated using the current estimate and the observer control law.

[0075] Step a3: Compare the current current estimate and the loop current to obtain the corresponding current sliding surface, and perform threshold judgment on the current sliding surface based on the preset sliding surface convergence threshold to obtain the fourth threshold judgment result.

[0076] Here, the current sliding surface can refer to the sliding surface obtained after calculating the difference between the current estimated value and the loop current. The fourth threshold judgment result can refer to the judgment result obtained after performing a threshold judgment on the current sliding surface using a preset sliding surface convergence threshold. For example, the fourth threshold judgment result can be that the current sliding surface is approximately equal to the preset sliding surface convergence threshold, or it can be that the current sliding surface exceeds the preset sliding surface convergence threshold.

[0077] Step a4: Based on the fourth threshold judgment result, optimize the current estimated value until the fourth threshold judgment result is that the current sliding surface meets the preset sliding surface convergence threshold. Then, use the current estimated value corresponding to the current sliding surface as the parameter to be estimated for measuring the fault inductance value.

[0078] Specifically, when it is determined that the initial sliding surface exceeds the preset sliding surface convergence threshold, the initial estimate can be adjusted using the preset parameter update gain to obtain the updated current estimate. Then, the current estimate, the power supply input voltage, and the loop current are substituted into the observer control law to calculate the current current estimate. Further, the difference between the current current estimate and the loop current is calculated to obtain the current sliding surface. The preset sliding surface convergence threshold is then used to perform a threshold judgment on the current sliding surface, resulting in a fourth threshold judgment result. If the fourth threshold judgment result indicates that the current sliding surface is approximately equal to the preset sliding surface convergence threshold, then the current current estimate is used as the final parameter to be estimated. Otherwise, the current estimate needs to be further optimized, and the above process is repeated until the fourth threshold judgment result indicates that the current sliding surface is approximately equal to the preset sliding surface convergence threshold, at which point the sliding surface observer's processing flow ends.

[0079] S2110. Perform a reciprocal calculation on the parameter to be estimated, and use the result of the reciprocal calculation as the estimated value of the fault inductance.

[0080] Specifically, after obtaining the final parameter to be estimated, its reciprocal can be taken as the final estimated value of the fault inductance. For example, .

[0081] S2120. Obtain the basic coil inductance and mutual inductance coupling coefficient corresponding to the target electromagnetic heating coil.

[0082] The basic coil inductance refers to the measure of a coil's ability to generate and store magnetic field energy when a current flows through it in a healthy and fault-free state. Typically, the basic coil inductance can be the original design specification of the coil, or determined through measurement when the system is brand new or in good condition. In this embodiment of the invention, it is preferably obtained by measuring with an impedance analyzer. The mutual inductance coupling coefficient refers to a dimensionless coefficient used to describe the degree of magnetic field coupling between two independent circuits, such as a healthy section and a short-circuit ring. Typically, the mutual inductance coupling coefficient can be theoretically estimated based on the coil structure and the possible location of the short-circuit ring, or it can be determined experimentally by creating a sample with a known short-circuit percentage.

[0083] S2130. Substitute the estimated values ​​of the basic coil inductance, mutual inductance coupling coefficient, and fault inductance into the pre-constructed quantitative mapping relationship between fault inductance and short-circuit ratio to obtain the short-circuit ratio of the target electromagnetic heating coil.

[0084] Specifically, after obtaining the estimated fault inductance value corresponding to the target electromagnetic heating coil, the base coil inductance and mutual inductance coupling coefficient corresponding to the target electromagnetic heating coil can be obtained. The base coil inductance, mutual inductance coupling coefficient, and the estimated fault inductance value are then substituted into a pre-constructed quantitative mapping relationship between fault inductance and short-circuit percentage for calculation. For example, the quantitative mapping relationship between fault inductance and short-circuit percentage can be expressed as: ,in, It can represent the proportion of short circuits. It can represent the inductance of a basic coil. It can represent the estimated value of the fault inductance. It can represent the mutual inductance coupling coefficient.

[0085] Figure 3 The diagram shown is a structural schematic of a No. 7 wheel electromagnetic heating coil provided in an embodiment of the present invention. Figure 3 Based on the electromagnetic heating coil structure of wheel number seven shown, the process of constructing the quantitative mapping relationship between fault inductance and short-circuit ratio can be as follows: For example, with the total number of coil turns as N, the number of short-circuit turns as n, and the short-circuit ratio... The single-turn inductance is L0, and the winding coupling coefficient is... , For example, the coil inductance under normal conditions can be expressed as: Meanwhile, if the number of turns in the un-short-circuited portion can be expressed as Nn, then the equivalent inductance can be expressed as: The equivalent resistance can be expressed as: .in, It can represent the resistivity of a wire. It can represent the length of the wire. It can represent the cross-sectional area of ​​a conductor. A short-circuit loop is equivalent to an inductor. When connected in series with the contact resistance Rs, the mutual inductance between the un-short-circuited portion and the short-circuited turn loop can be expressed as: Because the electromagnetic heating circuit of the No. 7 wheel operates under high-frequency fixed-frequency conditions, it meets the requirements. Furthermore, the inductive reactance of the short-circuited turn is much greater than the contact resistance; therefore, the total equivalent inductance of the faulty coil is... It can be simplified to: Substitute the above formulas one by one into... From this, a quantitative mapping relationship between fault inductance and short-circuit ratio can be obtained: The inverse formula for calculating the short-circuit ratio is obtained after deformation: .

[0086] S2140. Based on the preset fault classification rules, the short-circuit ratio and fault inductance estimation value of the target electromagnetic heating coil are classified and judged to obtain the fault assessment result of the target electromagnetic heating coil.

[0087] Specifically, after calculating the short-circuit ratio and estimated fault inductance of the target electromagnetic heating coil, a preset fault classification rule can be used to classify the short-circuit ratio and estimated fault inductance to obtain the fault assessment result of the target electromagnetic heating coil. For example, the preset fault classification rule is as follows: If... and If it is, then there is no fault; if and If it is, then it is a minor short circuit; if and If it is, then it is a moderate short circuit; if and If it is a severe short circuit; if and For example, a severe short circuit. Therefore, by implementing a five-level assessment system for fault-free, minor, moderate, severe, and extremely severe short circuits, the escalation of faults can be effectively prevented, ensuring the continuous and stable operation of the tobacco packaging machine and reducing maintenance costs.

[0088] It is worth noting that, in this embodiment of the invention, after obtaining the fault assessment result of the target electromagnetic heating coil, if the fault assessment result is a medium or higher short circuit fault, an emergency warning can be output and a high-frequency power supply soft shutdown can be triggered to avoid irreversible damage to the equipment.

[0089] The technical solution of this invention involves real-time acquisition of the power input voltage and loop current of a target electromagnetic heating coil at a preset acquisition frequency. Then, based on preset data processing rules, the acquired multiple power input voltages are filtered to obtain a target power input voltage set, and the acquired multiple loop currents are filtered to obtain a target loop current set. A Discrete Fourier Transform (DFT) is performed on the target power input voltage set to obtain the voltage spectrum corresponding to the target electromagnetic heating coil, and a DFT is performed on the target loop current set to obtain the current spectrum corresponding to the target electromagnetic heating coil. Further, the fundamental frequency corresponding to the target electromagnetic heating coil is obtained, and data indexing calculations are performed on the voltage and current spectra based on the fundamental frequency to obtain at least one fault assessment index value matching the target electromagnetic heating coil. A threshold judgment is performed on the fundamental phase difference based on a preset fundamental phase difference threshold to obtain a first threshold judgment result. Simultaneously, a threshold judgment is performed on the total harmonic distortion (THD) rate based on a preset current threshold to obtain a second threshold judgment result. If the first threshold judgment result exceeds the preset fundamental phase difference threshold, or the second threshold judgment result exceeds the preset total harmonic distortion rate threshold, then the target electromagnetic heating coil is determined to have a fault risk. Further, the input voltage of each power supply and the current of each loop are calculated using the observer control law corresponding to the sliding mode observer and the initial estimated value to obtain the initial current estimate. The initial current estimate and the loop current are compared and processed to obtain the corresponding initial sliding surface. A threshold judgment is then performed on the initial sliding surface based on the preset sliding surface convergence threshold to obtain the third threshold judgment result. Further, the initial estimate is optimized based on the third threshold judgment result to obtain the parameter to be estimated, used to measure the fault inductance value. The parameter to be estimated is calculated in reciprocal, and the result is used as the fault inductance estimate. The base coil inductance, mutual inductance coupling coefficient, and fault inductance estimate are substituted into the pre-constructed quantitative mapping relationship between fault inductance and short-circuit ratio to obtain the short-circuit ratio of the target electromagnetic heating coil. Finally, based on preset fault classification rules, the short-circuit ratio and estimated fault inductance of the target electromagnetic heating coil are classified and judged to obtain the fault assessment result of the target electromagnetic heating coil. By using magnetic coupling block modeling, sliding mode observer estimation, and classification assessment processes, the degree of fault is accurately quantified, solving the problems of existing technologies such as reliance on manual inspection, inability to monitor in real time, difficulty in early fault identification, lack of quantitative assessment standards, and weak anti-interference ability. This enables real-time online monitoring of inter-turn short-circuit faults in the coil, accurate identification of early minor short circuits, and quantitative classification assessment of fault severity, improving the accuracy and efficiency of fault assessment and providing solid technical support for predictive health management and intelligent maintenance of tobacco packaging equipment.

[0090] Figure 4The diagram shows a flowchart of an optional inter-turn short-circuit fault assessment method for the electromagnetic heating coil of a No. 7 wheel according to an embodiment of the present invention. Specifically, firstly, the power input voltage and loop current of the target electromagnetic heating coil are acquired in real time according to a preset acquisition frequency, and the inductance and mutual coupling coefficient of the base coil corresponding to the target electromagnetic heating coil are obtained. Then, based on preset data processing rules, the acquired multiple power input voltages are filtered to obtain a target power input voltage set, and the acquired multiple loop currents are filtered to obtain a target loop current set. A Discrete Fourier Transform is performed on the target power input voltage set to obtain the voltage spectrum corresponding to the target electromagnetic heating coil, and a Discrete Fourier Transform is performed on the target loop current set to obtain the current spectrum corresponding to the target electromagnetic heating coil. The fundamental frequency corresponding to the target electromagnetic heating coil is obtained, and data indexing calculation is performed on the voltage spectrum and current spectrum based on the fundamental frequency to obtain the fundamental phase difference and total harmonic distortion rate of the current matching the target electromagnetic heating coil. Furthermore, a coarse fault judgment process is performed, and a threshold judgment is made on the fundamental phase difference based on a preset fundamental phase difference threshold to obtain a first threshold judgment result. Simultaneously, a threshold judgment is performed on the total harmonic distortion (THD) of the current based on a preset threshold, yielding a second threshold judgment result. If the first threshold judgment result exceeds a preset fundamental phase difference threshold, or the second threshold judgment result exceeds a preset THD threshold, a fault risk is identified in the target electromagnetic heating coil, and the sliding mode observer is activated. Further, the input voltages of each power supply and the current of each loop are input into the pre-built sliding mode observer for iterative calculation to obtain the parameters to be estimated for measuring the fault inductance value, and the estimated fault inductance value is calculated based on these parameters. Further, based on the pre-built quantitative mapping relationship between fault inductance and short-circuit ratio, the short-circuit ratio of the target electromagnetic heating coil is obtained. Finally, based on preset fault classification rules, the short-circuit ratio and the estimated fault inductance value of the target electromagnetic heating coil are classified and judged to obtain a fault assessment result for the target electromagnetic heating coil. When the fault assessment result is a moderate or higher short-circuit fault, an emergency warning is output, triggering a soft shutdown of the high-frequency power supply to avoid irreversible damage to the equipment.

[0091] Example 3

[0092] Figure 5 This is a schematic diagram of the structure of a short-circuit fault assessment device for an electromagnetic heating coil of wheel number seven provided in Embodiment 3 of the present invention. Figure 5 As shown, the device includes: a data acquisition module 310, a fault measurement module 320, a quantitative mapping module 330, and a fault assessment module 340;

[0093] The data acquisition module 310 is used to acquire the power input voltage and loop current of the target electromagnetic heating coil in real time according to a preset acquisition frequency, and calculate at least one fault measurement index value that matches the target electromagnetic heating coil based on the acquired multiple power input voltages and multiple loop currents.

[0094] The fault measurement module 320 is used to input the input voltage of each power supply and the current of each circuit into a pre-built sliding mode observer for iterative calculation when it is determined that the target electromagnetic heating coil has a fault risk based on the values ​​of each fault measurement index, so as to obtain the estimated parameters for measuring the fault inductance value; wherein, the sliding mode observer is designed based on the state equation of the inductor-capacitor series resonant circuit.

[0095] The quantitative mapping module 330 is used to calculate the estimated value of the fault inductance based on the parameters to be estimated, and to obtain the short-circuit ratio of the target electromagnetic heating coil based on the pre-constructed quantitative mapping relationship between the fault inductance and the short-circuit ratio.

[0096] The fault assessment module 340 is used to classify and judge the short circuit ratio and fault inductance estimate of the target electromagnetic heating coil based on the preset fault classification rules, and obtain the fault assessment result of the target electromagnetic heating coil.

[0097] The technical solution of this invention involves real-time acquisition of the power input voltage and loop current of a target electromagnetic heating coil at a preset acquisition frequency. Based on the acquired power input voltages and loop currents, at least one fault assessment index value matching the target electromagnetic heating coil is calculated. Then, when a fault risk is determined for the target electromagnetic heating coil based on the fault assessment index values, each power input voltage and loop current is input into a pre-constructed sliding mode observer for iterative calculation to obtain parameters to be estimated for measuring the fault inductance value. Further, an estimated fault inductance value is calculated based on the estimated parameters, and the short-circuit ratio of the target electromagnetic heating coil is obtained based on a pre-constructed quantitative mapping relationship between fault inductance and short-circuit ratio. Finally, the short-circuit ratio and estimated fault inductance value of the target electromagnetic heating coil are graded according to preset fault classification rules to obtain the fault assessment result of the target electromagnetic heating coil. By employing magnetically coupled block modeling, sliding mode observer estimation, and graded evaluation processes, the degree of fault can be accurately quantified. This solves the problems of existing technologies, such as reliance on manual inspection, inability to monitor in real time, difficulty in early fault identification, lack of quantitative evaluation standards, and weak anti-interference capabilities. It enables real-time online monitoring of coil turn-to-turn short circuit faults, accurate identification of early minor short circuits, and quantitative grading evaluation of fault severity, thereby improving the accuracy and efficiency of fault assessment and providing solid technical support for predictive health management and intelligent maintenance of tobacco packaging equipment.

[0098] Optionally, the data acquisition module 310 can be used for:

[0099] The target power input voltage set is obtained by filtering multiple power input voltages based on preset data processing rules, and the target loop current set is obtained by filtering multiple loop currents based on preset data processing rules.

[0100] The voltage spectrum corresponding to the target electromagnetic heating coil is obtained by performing a discrete Fourier transform on the target power input voltage set, and the current spectrum corresponding to the target electromagnetic heating coil is obtained by performing a discrete Fourier transform on the target circuit current set.

[0101] Obtain the fundamental frequency corresponding to the target electromagnetic heating coil, and perform data indexing calculation on the voltage spectrum and current spectrum based on the fundamental frequency to obtain at least one fault measurement index value that matches the target electromagnetic heating coil.

[0102] Optionally, fault measurement metrics may include fundamental phase difference or total harmonic distortion of current.

[0103] The fault measurement module 320 can be used for:

[0104] Based on a preset fundamental phase difference threshold, a threshold judgment is performed on the fundamental phase difference to obtain a first threshold judgment result;

[0105] The total harmonic distortion rate of the current is judged based on a preset threshold, and a second threshold judgment result is obtained.

[0106] If the first threshold judgment result exceeds the preset fundamental phase difference threshold, or the second threshold judgment result exceeds the preset total harmonic distortion rate threshold, then it is determined that the target electromagnetic heating coil has a fault risk.

[0107] Optional, the fault measurement module 320 can be used for:

[0108] The initial current estimate is obtained by calculating the input voltage of each power source and the current of each loop using the observer control law and initial estimate value corresponding to the sliding mode observer.

[0109] The initial current estimate and the loop current are compared and processed to obtain the corresponding initial sliding surface. The initial sliding surface is then judged based on a preset sliding surface convergence threshold to obtain a third threshold judgment result.

[0110] Based on the third threshold judgment result, the initial estimate is optimized to obtain the parameter to be estimated for measuring the fault inductance value.

[0111] Optional, the fault measurement module 320 can be used for:

[0112] If the third threshold judgment result is that the initial sliding surface exceeds the preset sliding surface convergence threshold, then the initial estimated value is adjusted based on the preset parameter update gain to obtain the updated current estimated value;

[0113] Based on the current estimated value, the input voltage of each power supply and the current of each loop are calculated to obtain the current estimated value;

[0114] The current current estimate and the loop current are compared and processed to obtain the corresponding current sliding surface. The current sliding surface is then judged based on a preset sliding surface convergence threshold to obtain a fourth threshold judgment result.

[0115] Based on the fourth threshold judgment result, the current estimated value is optimized until the fourth threshold judgment result is that the current sliding surface meets the preset sliding surface convergence threshold. Then, the current estimated value corresponding to the current sliding surface is used as the parameter to be estimated for measuring the fault inductance value.

[0116] Optionally, the quantitative mapping module 330 can be used to: perform a reciprocal calculation on the parameter to be estimated, and use the reciprocal calculation result as the estimated value of the fault inductance.

[0117] Optional, the quantitative mapping module 330 can be used for:

[0118] Obtain the base coil inductance and mutual inductance coupling coefficient corresponding to the target electromagnetic heating coil;

[0119] The short-circuit ratio of the target electromagnetic heating coil is obtained by substituting the basic coil inductance, mutual inductance coupling coefficient and fault inductance estimate into the pre-constructed quantitative mapping relationship between fault inductance and short-circuit ratio.

[0120] The short-circuit fault assessment device for the No. 7 wheel electromagnetic heating coil provided in this embodiment of the invention can execute the short-circuit fault assessment method for the No. 7 wheel electromagnetic heating coil provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0121] Example 4

[0122] Figure 6A schematic diagram of an electronic device 410 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0123] like Figure 6 As shown, the electronic device 410 includes at least one processor 420 and a memory, such as a read-only memory (ROM) 430 or a random access memory (RAM) 440, communicatively connected to the at least one processor 420. The memory stores computer programs executable by the at least one processor. The processor 420 can perform various appropriate actions and processes based on the computer program stored in the ROM 430 or loaded into the RAM 440 from storage unit 490. The RAM 440 may also store various programs and data required for the operation of the electronic device 410. The processor 420, ROM 430, and RAM 440 are interconnected via a bus 450. An input / output (I / O) interface 460 is also connected to the bus 450.

[0124] Multiple components in electronic device 410 are connected to I / O interface 460, including: input unit 470, such as keyboard, mouse, etc.; output unit 480, such as various types of monitors, speakers, etc.; storage unit 490, such as disk, optical disk, etc.; and communication unit 4100, such as network card, modem, wireless transceiver, etc. Communication unit 4100 allows electronic device 410 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0125] Processor 420 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 420 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 420 performs the various methods and processes described above, such as the inter-turn short-circuit fault assessment method for the electromagnetic heating coil of wheel number seven.

[0126] The method includes:

[0127] The power input voltage and loop current of the target electromagnetic heating coil are collected in real time according to the preset collection frequency. Based on the collected power input voltage and loop current, at least one fault measurement index value matching the target electromagnetic heating coil is calculated.

[0128] When determining the risk of failure of the target electromagnetic heating coil based on the values ​​of various fault measurement indicators, the input voltage of each power supply and the current of each loop are input into a pre-built sliding mode observer for iterative calculation to obtain the estimated parameters used to measure the fault inductance value; wherein, the sliding mode observer is designed based on the state equation of the inductor-capacitor series resonant circuit.

[0129] Based on the parameters to be estimated, the estimated value of the fault inductance is calculated, and based on the pre-constructed quantitative mapping relationship between the fault inductance and the short-circuit ratio, the short-circuit ratio of the target electromagnetic heating coil is obtained.

[0130] Based on the preset fault classification rules, the short-circuit ratio and fault inductance estimate of the target electromagnetic heating coil are classified and judged to obtain the fault assessment result of the target electromagnetic heating coil.

[0131] In some embodiments, the method for assessing inter-turn short-circuit faults in the No. 7 wheel electromagnetic heating coil can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 490. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 410 via ROM 430 and / or communication unit 4100. When the computer program is loaded into RAM 440 and executed by processor 420, one or more steps of the method for assessing inter-turn short-circuit faults in the No. 7 wheel electromagnetic heating coil described above can be performed. Alternatively, in other embodiments, processor 420 can be configured to perform the method for assessing inter-turn short-circuit faults in the No. 7 wheel electromagnetic heating coil by any other suitable means (e.g., by means of firmware).

[0132] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0133] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0134] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0135] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0136] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0137] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0138] This application also discloses a computer program product, which includes a computer program that, when executed by a processor, implements the method for assessing inter-turn short-circuit faults of the No. 7 wheel electromagnetic heating coil provided in any embodiment of this application. This program product shares the same inventive concept as the method for assessing inter-turn short-circuit faults of the No. 7 wheel electromagnetic heating coil disclosed in the embodiments of this application, and therefore will not be described in detail here.

[0139] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0140] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for assessing inter-turn short-circuit faults in the electromagnetic heating coil of wheel No. 7, characterized in that, include: The power input voltage and loop current of the target electromagnetic heating coil are collected in real time according to the preset collection frequency. Based on the collected power input voltage and loop current, at least one fault measurement index value matching the target electromagnetic heating coil is calculated. When determining the risk of failure of the target electromagnetic heating coil based on the values ​​of various fault measurement indicators, the input voltage of each power supply and the current of each loop are input into a pre-built sliding mode observer for iterative calculation to obtain the estimated parameters used to measure the fault inductance value; wherein, the sliding mode observer is designed based on the state equation of the inductor-capacitor series resonant circuit. Based on the parameters to be estimated, the estimated value of the fault inductance is calculated, and based on the pre-constructed quantitative mapping relationship between the fault inductance and the short-circuit ratio, the short-circuit ratio of the target electromagnetic heating coil is obtained. Based on the preset fault classification rules, the short-circuit ratio and fault inductance estimate of the target electromagnetic heating coil are classified and judged to obtain the fault assessment result of the target electromagnetic heating coil.

2. The method according to claim 1, characterized in that, Based on the collected multiple power input voltages and multiple circuit currents, at least one fault metric value matching the target electromagnetic heating coil is calculated, including: The target power input voltage set is obtained by filtering multiple power input voltages based on preset data processing rules, and the target loop current set is obtained by filtering multiple loop currents based on preset data processing rules. The voltage spectrum corresponding to the target electromagnetic heating coil is obtained by performing a discrete Fourier transform on the target power input voltage set, and the current spectrum corresponding to the target electromagnetic heating coil is obtained by performing a discrete Fourier transform on the target circuit current set. Obtain the fundamental frequency corresponding to the target electromagnetic heating coil, and perform data indexing calculation on the voltage spectrum and current spectrum based on the fundamental frequency to obtain at least one fault measurement index value that matches the target electromagnetic heating coil.

3. The method according to claim 1, characterized in that, The fault measurement index values ​​include the fundamental phase difference or the total harmonic distortion rate of the current. The target electromagnetic heating coil is identified as having a fault risk based on various fault measurement index values, including: Based on a preset fundamental phase difference threshold, a threshold judgment is performed on the fundamental phase difference to obtain a first threshold judgment result; The total harmonic distortion rate of the current is judged based on a preset threshold, and a second threshold judgment result is obtained. If the first threshold judgment result exceeds the preset fundamental phase difference threshold, or the second threshold judgment result exceeds the preset total harmonic distortion rate threshold, then it is determined that the target electromagnetic heating coil has a fault risk.

4. The method according to any one of claims 1-3, characterized in that, The input voltages of each power supply and the currents of each loop are input into a pre-built sliding mode observer for iterative calculation to obtain the parameters to be estimated for measuring the fault inductance, including: The initial current estimate is obtained by calculating the input voltage of each power source and the current of each loop using the observer control law and initial estimate value corresponding to the sliding mode observer. The initial current estimate and the loop current are compared and processed to obtain the corresponding initial sliding surface. The initial sliding surface is then judged based on a preset sliding surface convergence threshold to obtain a third threshold judgment result. Based on the third threshold judgment result, the initial estimate is optimized to obtain the parameter to be estimated for measuring the fault inductance value.

5. The method according to claim 4, characterized in that, The process of optimizing the initial estimate based on the third threshold judgment result to obtain the parameters to be estimated for measuring the fault inductance value includes: If the third threshold judgment result is that the initial sliding surface exceeds the preset sliding surface convergence threshold, then the initial estimated value is adjusted based on the preset parameter update gain to obtain the updated current estimated value; Based on the current estimated value, the input voltage of each power supply and the current of each loop are calculated to obtain the current estimated value; The current current estimate and the loop current are compared and processed to obtain the corresponding current sliding surface. The current sliding surface is then judged based on a preset sliding surface convergence threshold to obtain a fourth threshold judgment result. Based on the fourth threshold judgment result, the current estimated value is optimized until the fourth threshold judgment result is that the current sliding surface meets the preset sliding surface convergence threshold. Then, the current estimated value corresponding to the current sliding surface is used as the parameter to be estimated for measuring the fault inductance value.

6. The method according to any one of claims 1-3, characterized in that, Based on the parameters to be estimated, the estimated value of the fault inductance is calculated, including: The reciprocal of the parameter to be estimated is calculated, and the result of the reciprocal calculation is used as the estimated value of the fault inductance.

7. The method according to any one of claims 1-3, characterized in that, Based on the pre-established quantitative mapping relationship between fault inductance and short-circuit ratio, the short-circuit ratio of the target electromagnetic heating coil is obtained, including: Obtain the base coil inductance and mutual inductance coupling coefficient corresponding to the target electromagnetic heating coil; The short-circuit ratio of the target electromagnetic heating coil is obtained by substituting the basic coil inductance, mutual inductance coupling coefficient and fault inductance estimate into the pre-constructed quantitative mapping relationship between fault inductance and short-circuit ratio.

8. A device for assessing inter-turn short-circuit faults in the electromagnetic heating coil of a No. 7 wheel, characterized in that, include: The data acquisition module is used to acquire the power input voltage and loop current of the target electromagnetic heating coil in real time according to a preset acquisition frequency, and calculate at least one fault measurement index value that matches the target electromagnetic heating coil based on the acquired multiple power input voltages and multiple loop currents. The fault measurement module is used to input the input voltage of each power supply and the current of each loop into a pre-built sliding mode observer for iterative calculation when it is determined that the target electromagnetic heating coil has a fault risk based on the values ​​of each fault measurement index. The sliding mode observer is designed based on the state equation of the inductor-capacitor series resonant circuit. The quantitative mapping module is used to calculate the estimated value of the fault inductance based on the parameters to be estimated, and to obtain the short-circuit ratio of the target electromagnetic heating coil based on the pre-constructed quantitative mapping relationship between the fault inductance and the short-circuit ratio. The fault assessment module is used to classify and judge the short-circuit ratio and fault inductance estimate of the target electromagnetic heating coil based on preset fault classification rules, and obtain the fault assessment result of the target electromagnetic heating coil.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the method for evaluating inter-turn short circuit faults of the electromagnetic heating coil of wheel No. 7 as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method for assessing inter-turn short-circuit faults of the electromagnetic heating coil of wheel number seven as described in any one of claims 1-7.

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