Coil health degree dynamic evaluation system based on electromagnetic coil performance parameters

Abstract

The invention relates to the technical field of state evaluation, in particular to a coil health degree dynamic evaluation system based on electromagnetic coil performance parameters, which comprises a coil operation load evaluation module, an operation frequency health comparison module, an electromagnetic loss joint analysis module, a multi-parameter anomaly screening module and a health state evaluation module. According to the invention, by measuring the change rates of resistance, inductance and magnetic flux density and setting different parameter deviation ranges according to the load grade, the identification precision of the influence of the load on the coil state is improved, and by combining the comparison of the inductance drift reference range, the rapid judgment of abnormal deviation is realized, and the mutual analysis of multiple parameters is carried out; according to the method, the incidence relation among the parameters is comprehensively analyzed, the synchronous decline trend is effectively identified, the health degradation rate is synchronously calculated, and the health state warning threshold is compared, so that the change trend of the health state is accurately predicted, the accuracy of health state evaluation of the electromagnetic coil is improved, and the missed detection probability of an abnormal state is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of state evaluation, and particularly to a dynamic evaluation system for the health degree of a coil based on the performance parameters of an electromagnetic coil. Background Art

[0002] The technical field of state evaluation includes methods and means for detecting, analyzing, and judging the operating state of physical devices, systems, or components. The core content is based on the collection and analysis of device performance parameters, combined with mathematical modeling, signal feature extraction, historical data comparison, etc., to judge the current state of the device and predict its future change trend. The overall technical field covers multiple aspects, including sensor technology for real-time data collection, data analysis methods for feature extraction and modeling, and evaluation mechanisms for state recognition and health degree judgment. It has a wide range of applications and can be used in scenarios such as industrial equipment monitoring, power system detection, and structural health monitoring to ensure the reliability and safety of device operation.

[0003] Among them, a dynamic evaluation system for the health degree of a coil based on the performance parameters of an electromagnetic coil refers to a system that monitors the operating state of an electromagnetic coil, analyzes the health degree of the coil based on its performance parameters, and dynamically evaluates its state. It targets the changes in the electrical and physical characteristic parameters of the coil, covering key performance parameters such as the resistance, inductance, temperature, and magnetic flux density of the coil, and uses sensors to achieve real-time data collection. By calculating the change rate, deviation, and trend of these parameters, combined with statistical analysis methods, the health state is judged. In addition, it also combines empirical models or data fitting methods to analyze the performance decay mode of the coil under different working conditions, and classifies the state according to preset thresholds or mathematical models to achieve a quantitative evaluation of the health degree of the coil.

[0004] In the existing electromagnetic coil health assessment process, it mainly relies on a single-parameter analysis method, making it difficult to comprehensively evaluate the device health state. In terms of load impact assessment, the existing methods lack the calculation of the parameter deviation ratio caused by load changes, making it difficult to quantify the impact of the load on the coil state. In the frequency impact assessment, the monitoring method of inductance drift is usually based on a fixed reference value and fails to combine the offset trend under the actual operating frequency, resulting in a lag in the judgment of inductance changes. In the power loss analysis, the existing methods are mostly based on simple comparison of historical loss data and lack the calculation of the loss growth rate, making the judgment of abnormal losses lack dynamic adaptability. In terms of multi-parameter analysis, the existing technology fails to achieve cross-analysis between different parameters, resulting in the failure to fully consider the mutual influence relationship between key parameters such as resistance, inductance, magnetic flux density, and power loss, restricting the accuracy of health state assessment. In terms of health state prediction, the existing methods often rely on long-term trend analysis and fail to combine short-term change characteristics, resulting in insufficient early warning ability when the coil deteriorates rapidly and affecting the timeliness of maintenance decisions. Summary of the Invention

[0005] The object of the present invention is to solve the disadvantages existing in the prior art, and a dynamic evaluation system for the health degree of a coil based on the performance parameters of an electromagnetic coil is proposed.

[0006] To achieve the above object, the present invention adopts the following technical solution: A dynamic evaluation system for the health degree of a coil based on the performance parameters of an electromagnetic coil includes:

[0007] The coil operating load evaluation module obtains the real-time input current and input voltage of the coil, calculates the load power deviation ratio, synchronously draws the load influence curve, sets the load level, and determines whether it exceeds the parameter deviation range of the corresponding load level to obtain the abnormal load influence parameter set;

[0008] The operating frequency health comparison module analyzes the inductance drift trend under the current frequency condition based on the abnormal load influence parameter set, compares it with the inductance drift reference range, and outputs the frequency influence abnormal parameter set;

[0009] The electromagnetic loss joint analysis module calculates the coil power loss amount and the power loss growth rate based on the frequency influence abnormal parameter set, compares it with the standard loss growth range, and obtains the electromagnetic loss abnormal parameter set;

[0010] The multi-parameter abnormal screening module calculates the relative change ratio of the coil operating parameters based on the electromagnetic loss abnormal parameter set, determines whether there is a synchronous decline trend, analyzes the parameter cross-correlation, and obtains the parameter mutual analysis result;

[0011] The health status evaluation module analyzes the change trend of the current health status of the electromagnetic coil according to the parameter mutual analysis result, compares it with the health status warning threshold, and outputs the health status evaluation result of the electromagnetic coil.

[0012] As a further solution of the present invention, the abnormal load influence parameter set includes load power deviation ratio data, resistance change rate data, inductance change rate data, and magnetic flux density change rate data. The frequency influence abnormal parameter set includes the inductance drift trend analysis result and the comparison result of the inductance drift reference range. The electromagnetic loss abnormal parameter set includes the power loss amount, the power loss growth rate, and the comparison result of the standard loss growth range. The parameter mutual analysis result includes the relative change ratio of the resistance value, the relative change ratio of the inductance value, the relative change ratio of the magnetic flux density, the relative change ratio of the power loss, the relative change ratio of the current change rate, and the synchronous decline trend analysis result. The health status evaluation result of the electromagnetic coil includes the health status change trend analysis result, the health deterioration rate data, and the comparison result of the health status warning threshold.

[0013] As a further solution of the present invention, the coil operating load evaluation module includes:

[0014] The load power calculation sub-module obtains the real-time input current and real-time input voltage of the coil, calculates the current load power, combines with the reference power value in the no-load state, calculates the load power deviation ratio, and uses the formula:

[0015]

[0016] Calculate the load power deviation percentage P d , obtain the load power deviation ratio data, where P L represents the current load power, and P0 represents the reference power in the no-load state;

[0017] The load parameter change rate calculation sub-module collects the resistance value, inductance value, and magnetic flux density in the no-load state, synchronously obtains the resistance, inductance, and magnetic flux density under the current load condition, calculates the resistance change rate, inductance change rate, and magnetic flux density change rate, and obtains the load parameter change rate set;

[0018] The load impact analysis sub-module, according to the load parameter change rate set and the load power deviation ratio data, combines with the preset load level parameter deviation range, compares the current measured parameters, filters out the parameter items that exceed the load level range, and obtains the abnormal load impact parameter set.

[0019] As a further solution of the present invention, the operating frequency health comparison module includes:

[0020] The inductance drift calculation sub-module, based on the abnormal load impact parameter set, collects the coil inductance value at the current frequency, combines with the coil reference inductance value, calculates the inductance drift trend under the current frequency condition, and obtains the inductance drift trend data;

[0021] The inductance drift reference comparison sub-module, according to the inductance drift trend data, compares with the inductance drift reference range, determines whether the current inductance drift trend exceeds the reference range, and obtains the drift overlimit state record;

[0022] The frequency impact parameter extraction sub-module, based on the drift overlimit state record, combines with the inductance change rate, resistance change rate, and magnetic flux density change rate in the abnormal load impact parameter set, and uses the formula:

[0023]

[0024] Calculate the frequency impact related parameter deviation ratio R F , obtain the frequency impact abnormal parameter set, where X i represents the inductance, resistance, and magnetic flux density parameter values at the current frequency, X ri represents the reference parameter values of the corresponding parameters, W i represents the influence weight of each parameter, and n represents the number of parameters.

[0025] As a further solution of the present invention, the electromagnetic loss joint analysis module includes:

[0026] Based on the frequency influence abnormal parameter set, the power loss calculation sub-module collects the coil input power and output power under the current load level, calculates and outputs the coil power loss amount data;

[0027] According to the power loss amount data, the loss growth rate judgment sub-module combines the normal power loss base value under the same load level and uses the formula:

[0028]

[0029] Calculates and outputs the power loss growth rate data G P , where P L represents the current power loss amount, and P N represents the normal power loss base value;

[0030] Based on the power loss growth rate data, the electromagnetic loss abnormal screening sub-module compares the standard loss growth range, determines whether it exceeds the standard range, screens out the abnormal parameter items, and obtains the electromagnetic loss abnormal parameter set.

[0031] As a further solution of the present invention, the multi-parameter abnormal screening module includes:

[0032] Based on the electromagnetic loss abnormal parameter set, the parameter statistical calculation sub-module statistically calculates the current resistance value, inductance value, magnetic flux density, power loss, and current change rate, calculates the relative change ratio of each parameter, and obtains the parameter relative change ratio set;

[0033] According to the parameter relative change ratio set, the synchronous decline judgment sub-module compares the set parameter change trend reference range, determines whether each parameter has a synchronous decline trend, and obtains the synchronous decline state analysis result;

[0034] Based on the synchronous decline state analysis result, the parameter correlation analysis sub-module uses the formula:

[0035]

[0036] Calculates the cross-correlation coefficient C of parameter i and parameter j i,j , obtains the parameter mutual analysis result, where x i,k represents the value of parameter i at the kth measurement, x i represents the mean value of parameter i, x j,k represents the value of parameter j at the kth measurement, x j represents the mean value of parameter j, and m represents the corresponding number of measurements.

[0037] As a further solution of the present invention, the health status evaluation module includes:

[0038] Based on the mutual analysis result of the parameters, the health change trend calculation sub-module monitors the changes of the health status parameters of the electromagnetic coil at different time points, analyzes the health status change trend, and obtains the health change trend analysis result;

[0039] According to the health change trend analysis result, the health deterioration rate calculation sub-module uses the formula:

[0040]

[0041] Calculate the health deterioration rate H of the electromagnetic coil D , and obtain the health deterioration rate data, where S t represents the health status parameter value at the t-th time point, and M represents the number of monitoring time points;

[0042] Based on the health deterioration rate data, the health warning judgment sub-module compares the health status warning threshold to judge whether the health status reaches the warning value. If it exceeds the threshold, it is determined that there is a problem with the health status of the electromagnetic coil, and the health status evaluation result of the electromagnetic coil is obtained.

[0043] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0044] In the present invention, the real-time input current and input voltage of the electromagnetic coil are obtained, and the load power deviation ratio is calculated in combination with the reference power value under the no-load condition, so as to accurately describe the influence of the load change on the coil health status. By measuring the change rates of resistance, inductance, and magnetic flux density, and setting different parameter deviation ranges according to the load level, the recognition accuracy of the influence of the load on the coil state is improved. Based on the calculation of the inductance drift trend and the comparison with the inductance drift reference range, the inductance offset effect caused by frequency change is effectively monitored, and the rapid judgment of abnormal offset is realized. The power loss amount is calculated, and the loss growth rate is calculated in combination with the normal power loss base value, so as to quantify the growth trend of electromagnetic loss and provide a reliable recognition basis for abnormal power loss. By statistically analyzing the resistance value, inductance value, magnetic flux density, power loss, and current change rate, and calculating the relative change ratio of the parameters, the correlation relationship between the parameters is comprehensively analyzed, the synchronous decline trend is effectively recognized, the health deterioration rate is calculated synchronously, and combined with the health status warning threshold, the change trend of the health status is accurately predicted, the accuracy of the health status evaluation of the electromagnetic coil is improved, the coil health status is more comprehensively monitored under different operating conditions, and the probability of missed detection of abnormal states is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is the system flow chart of the present invention;

[0046] Figure 2 This is the flowchart of the coil operation load evaluation module of the present invention;

[0047] Figure 3 This is the flowchart of the operating frequency health comparison module of the present invention;

[0048] Figure 4 This is the flowchart of the electromagnetic loss joint analysis module of the present invention;

[0049] Figure 5 This is the flowchart of the multi-parameter anomaly screening module of the present invention;

[0050] Figure 6 This is the flowchart of the health status evaluation module of the present invention. Detailed implementation manners

[0051] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0052] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. In addition, in the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined.

[0053] Please refer to Figure 1 , a dynamic evaluation system for the health degree of a coil based on the performance parameters of an electromagnetic coil includes:

[0054] The coil operation load evaluation module obtains the real-time input current and input voltage of the coil, calculates the current load power, combines the reference power value under the no-load condition, calculates the load power deviation ratio, synchronously obtains the resistance value, inductance value, and magnetic flux density of the coil in the no-load state, calculates the resistance change rate, inductance change rate, and magnetic flux density change rate under the current load condition, draws the load influence curve, sets the load level, obtains the parameter deviation range under each load level, and determines whether the current measured parameters exceed the parameter deviation range of the corresponding load level to obtain the abnormal load influence parameter set;

[0055] Based on the abnormal load impact parameter set, the operating frequency health comparison module collects the coil inductance value at the current frequency, combines it with the coil reference inductance value, calculates and analyzes the inductance drift trend under the current frequency condition, compares it with the inductance drift reference range, determines whether the current inductance drift trend exceeds the inductance drift reference range, and outputs the frequency impact abnormal parameter set;

[0056] Based on the frequency impact abnormal parameter set, the electromagnetic loss joint analysis module calculates the power loss of the coil, combines it with the normal power loss base value under the same load level, calculates the power loss growth rate, determines whether it exceeds the standard loss growth range, and obtains the electromagnetic loss abnormal parameter set;

[0057] Based on the electromagnetic loss abnormal parameter set, the multi-parameter abnormal screening module statistics the current resistance value, inductance value, magnetic flux density, power loss, and current change rate of the electromagnetic coil, synchronously calculates the relative change ratio of the parameters, determines whether there is a synchronous decline trend, and analyzes the parameter cross-correlation to obtain the parameter mutual analysis result;

[0058] Based on the parameter mutual analysis result, the health status evaluation module analyzes the change trend of the current health status of the electromagnetic coil, calculates the health deterioration rate, determines whether the health status reaches the health status warning threshold. If it reaches the health status warning threshold, it determines that there is a problem with the current health of the electromagnetic coil and outputs the electromagnetic coil health status evaluation result.

[0059] The abnormal load impact parameter set includes load power deviation ratio data, resistance change rate data, inductance change rate data, and magnetic flux density change rate data. The frequency impact abnormal parameter set includes inductance drift trend analysis result and inductance drift reference range comparison result. The electromagnetic loss abnormal parameter set includes power loss amount, power loss growth rate, and standard loss growth range comparison result. The parameter mutual analysis result includes relative change ratio of resistance value, relative change ratio of inductance value, relative change ratio of magnetic flux density, relative change ratio of power loss, relative change ratio of current change rate, and synchronous decline trend analysis result. The electromagnetic coil health status evaluation result includes health status change trend analysis result, health deterioration rate data, and health status warning threshold comparison result.

[0060] Please refer to Figure 2 , the coil operating load evaluation module includes:

[0061] The load power calculation sub-module obtains the real-time input current and real-time input voltage of the coil, calculates the current load power, combines it with the reference power value in the no-load state, calculates the load power deviation ratio, using the formula:

[0062]

[0063] Calculate the load power deviation percentage Pd , obtain the load power deviation ratio data, where P L represents the current load power, and P0 represents the reference power in the no-load state;

[0064] To obtain the real-time input current and real-time input voltage of the coil, data acquisition needs to be carried out using sensors. For example, a current transformer (CT) and a voltage sensor (PT) are used to measure the current and voltage at the input end respectively. Suppose the input current of a certain coil is I = 5.2 A and the input voltage is U = 220 V. According to the power calculation formula P = U×I, the current load power P L

[0065] = 220×5.2 = 1144 W. Call the reference power value in the no-load state. Suppose the reference power value measured for this coil in the no-load state is P0 = 1000 W. Calculate the load power deviation ratio. Using the formula, substitute the values for calculation:

[0066]

[0067] Thus, the load power deviation ratio is obtained as 14.4%, as shown in Table 1.1.

[0068] Table 1.1 Load power calculation data

[0069]

[0070] By calculating the load power deviation ratio, the degree of power change under the current load state can be directly quantified. Compared with traditional power measurements, it can more intuitively express the change trend of the current load power relative to the no-load state. The results show that the power deviation ratio of the current load state of this coil exceeds the set reference value range, and further analysis needs to be carried out in combination with the load level parameters.

[0071] The load parameter change rate calculation sub-module collects the resistance value, inductance value, and magnetic flux density in the no-load state, synchronously obtains the resistance, inductance, and magnetic flux density under the current load conditions, calculates the resistance change rate, inductance change rate, and magnetic flux density change rate, and obtains the load parameter change rate set;

[0072] Based on the resistance value, inductance value, and magnetic flux density in the no-load state, synchronously obtain the resistance, inductance, and magnetic flux density under the current load conditions. In actual measurement, the resistance can be obtained by the four-terminal measurement method, the inductance can be measured using an LCR tester, and the magnetic flux density can be detected by a Hall sensor. Suppose that in the no-load state, the resistance of the coil is R0 = 10 Ω, the inductance is L0 = 5 mH, and the magnetic flux density is B0 = 0.8 T. In the load state, the measured resistance is R L = 12 Ω, the inductance is L L = 4.8 mH, and the magnetic flux density is BL = 0.75T, calculate the resistance change rate, inductance change rate, and magnetic flux density change rate using the formula:

[0073]

[0074] Substitute the data for calculation:

[0075]

[0076] Table 1.2 Data of Load Parameter Change Rate

[0077]

[0078] Calculate the change rates of resistance, inductance, and magnetic flux density respectively to comprehensively evaluate the influence of the load on the coil parameters and provide a more accurate basis for parameter offset analysis. The results show that the change rate of resistance is relatively large, which may affect current transmission, and the decrease in magnetic flux density may affect electromagnetic coupling performance. Further evaluation is required in combination with the load influence analysis.

[0079] The load influence analysis sub-module, based on the set of load parameter change rates and the data of load power deviation ratio, combines the preset deviation range of load level parameters, compares with the currently measured parameters, screens out the parameter items that exceed the load level range, and obtains the set of abnormal load influence parameters;

[0080] Call the set of load parameter change rates, combine the preset deviation range of load level parameters, compare with the currently measured parameters, screen out the parameter items that exceed the load level range. Assume that the preset deviation range of load level parameters of the system is as follows:

[0081] Table 1.3 Deviation Range of Load Level Parameters

[0082]

[0083] According to the foregoing calculation results, the resistance change rate of 20% belongs to the high-load range, the inductance change rate of 4% belongs to the low-load range, and the magnetic flux density change rate of 6.25% belongs to the medium-load range. Screen out the parameter items that exceed the load level range, that is, the resistance change rate and the magnetic flux density change rate, and obtain the set of abnormal load influence parameters, which includes the resistance change rate of 20% and the magnetic flux density change rate of 6.25%.

[0084] The results show that the current load state of the coil causes a high resistance, resulting in a large power loss, and at the same time, the decrease in magnetic flux density will affect magnetic field transmission.

[0085] Please refer to Figure 3 , the operating frequency health comparison module includes:

[0086] Based on the abnormal load impact parameter set, the inductance drift calculation sub-module collects the coil inductance value at the current frequency, combines it with the coil reference inductance value, calculates the inductance drift trend under the current frequency condition, and obtains the inductance drift trend data;

[0087] Based on the abnormal load impact parameter set, first collect the coil inductance value at the current frequency. In the actual application scenario, multiple measurement points can be set in the electromagnetic induction device and measured using a precision LCR tester or a digital bridge. For example, for a certain device at a working frequency of 50 kHz, its measured inductance value is 5.2 mH. At the same time, call the coil reference inductance value of the device, which is usually provided by the manufacturer or can be measured under no-load conditions. For example, the no-load inductance value of a certain coil is 5.5 mH. Then, calculate the inductance drift trend under the current frequency condition using the formula:

[0088]

[0089] Calculate the trend value, where D L represents the inductance drift trend value, L f represents the coil inductance value at the current frequency, L r represents the reference inductance value, and obtain the inductance drift trend; Substitute the data to get:

[0090]

[0091] The calculation result shows that at a frequency of 50 kHz, the inductance drift amplitude of this coil is 3.96%, which is a key parameter of the inductance offset evaluation index.

[0092] The inductance drift benchmark comparison sub-module compares the inductance drift trend data with the inductance drift benchmark range, determines whether the current inductance drift trend exceeds the benchmark range, and obtains the drift overlimit status record;

[0093] Call the inductance drift trend data and compare it with the inductance drift benchmark range. The setting of the benchmark range is generally based on laboratory measurement data or technical specifications provided by the equipment manufacturer. For example, the allowable range of inductance drift for a certain type of coil in the standard environment is set to ±5%, that is, when the inductance drift exceeds 5%, it is considered to be out of the normal range. For the measured 3.96%, judge whether this value exceeds the benchmark range. Since 3.96% < 5%, the current state is still within the normal range, record this drift state, and further analyze its trend change. If the inductance drift trend exceeds the set threshold (such as 7%), it indicates that the current electromagnetic coil is in an overlimit state. Finally, obtain the drift overlimit status, and the current status record is normal.

[0094] Based on the drift overrun status record, the frequency influence parameter extraction sub-module combines the inductance change rate, resistance change rate, and magnetic flux density change rate in the abnormal load influence parameter set, and uses the formula:

[0095]

[0096] Calculate the deviation ratio R of the frequency influence related parameters F , and obtain the set of abnormal parameters of frequency influence, where X i represents the inductance, resistance, and magnetic flux density parameter values at the current frequency, and X ri represents the reference parameter value of the corresponding parameter, W i represents the influence weight of each parameter, and n represents the number of parameters;

[0097] Based on the drift overrun status record, combine the inductance change rate, resistance change rate, and magnetic flux density change rate in the abnormal load influence parameter set, and use the formula to calculate the deviation ratio of the frequency influence related parameters.

[0098] Assume that under the current measurement conditions:

[0099] The inductance change rate X1 = 4.2%, and the reference value X r1 = 3.5%, and the weight W1 = 0.5;

[0100] The resistance change rate X2 = 2.1%, and the reference value X r2 = 1.8%, and the weight W2 = 0.3;

[0101] The magnetic flux density change rate X3 = 1.5%, and the reference value X r3 = 1.2%, and the weight W3 = 0.2;

[0102] The setting basis of the weight parameters is as follows:

[0103] The weight W1 = 0.5 of the inductance change rate is set based on the core influence degree of the inductance on the operating frequency. The change of the inductance value directly affects the calculation of the resonance frequency, and then determines the stability of the electromagnetic induction system. According to the experimental data provided by the equipment manufacturer, if the inductance drift exceeds 3%, the system tuning frequency will deviate from the target value by more than ±2%. Therefore, the inductance change rate has the greatest influence and is given a weight of 0.5.

[0104] The weight W2 = 0.3 of the resistance change rate is set based on the influence of the resistance on the coil Q value (quality factor) under the change of the operating frequency. The Q value calculation formula is where ω is the angular frequency, L is the inductance value, and R is the equivalent resistance. According to the experimental data, when the resistance change rate is in the range of 2% - 5%, the influence degree on the Q value accounts for about 30% of the overall deviation. Therefore, the weight is set to 0.3.

[0105] The weight W3 of the rate of change of magnetic flux density is set to 0.2. The basis for this setting is that the change in magnetic flux density mainly affects the saturation characteristics of the magnetic core. The change in magnetic flux density is usually determined by the characteristics of the iron core material. If the magnetic flux density deviates from the reference value by more than 1.5%, it may cause magnetic core saturation and reduce the induction efficiency. Experimental data shows that its overall impact on the electromagnetic system accounts for about 20%, so the weight is set to 0.2.

[0106] Substituting the data, we get:

[0107]

[0108] The abnormal threshold for frequency influence is set to 15%. The basis for setting this threshold is as follows:

[0109] According to standard industrial applications, the cumulative deviation of frequency-related parameters usually needs to be controlled between 10% - 20%. If the deviation exceeds this range, it may cause system resonance misalignment.

[0110] According to the electromagnetic induction system design guide, a deviation within 15% is usually acceptable. However, when it exceeds 15%, the system output power may decrease by 5% - 8%, affecting the overall stability.

[0111] Through multiple experiments, it is measured that within the common operating frequency range (20 kHz - 100 kHz), a deviation exceeding 15% often leads to an increase in tuning error, causing the resonance peak to shift, and further resulting in efficiency decline and overheating problems.

[0112] The current calculation result R F = 0.2 (i.e., 20%), which exceeds the set threshold of 15%. Therefore, the current parameter deviation ratio exceeds the normal range, and it enters the abnormal parameter screening process to obtain the set of abnormal parameters for frequency influence.

[0113] Please refer to Figure 4 , the electromagnetic loss joint analysis module includes:

[0114] The power loss calculation sub-module, based on the set of abnormal parameters for frequency influence, collects the coil input power and output power at the current load level, and calculates and outputs the data of the coil power loss amount;

[0115] Based on the set of abnormal parameters for frequency influence, obtain the coil input power and output power at the current load level. In actual application scenarios, a power analyzer can be used to measure the input and output ends of the coil in real-time. For example, in an induction coil system operating at a frequency of 20 kHz, the measured input power P in = 120 W, and the output power P out = 100 W. Calculate the power loss amount of the coil using the formula:

[0116] P L = Pin -P out ;

[0117] Among them, P L represents the coil power loss, P in represents the coil input power, P out represents the coil output power. Substitute the data for calculation:

[0118] P L = 120W - 100W = 20W;

[0119] This result indicates that the power loss of the coil under this frequency and load condition is 20W, and the power loss amount is obtained.

[0120] The loss growth rate judgment sub-module, based on the power loss amount data and combined with the normal power loss base value under the same load level, uses the formula:

[0121]

[0122] Calculate and output the power loss growth rate data G P , among which, P L represents the current power loss amount, P N represents the normal power loss base value;

[0123] Call the power loss amount data and combine it with the normal power loss base value under the same load level. The normal power loss base value can be obtained through factory calibration of the device, laboratory measurement, or long-term monitoring data. For example, the power loss base value of a certain coil under the same load level is set as P N = 15W. Calculate the power loss growth rate, combine with the formula, and substitute the data for calculation:

[0124]

[0125] This result indicates that the power loss growth rate of the coil under the current frequency and load condition is 33.3%, and the power loss growth rate data is obtained.

[0126] The electromagnetic loss abnormal screening sub-module, based on the power loss growth rate data, compares with the standard loss growth range, judges whether it exceeds the standard range, screens out the abnormal parameter items, and obtains the electromagnetic loss abnormal parameter set;

[0127] Based on the power loss growth rate data, compare with the standard loss growth range. The setting of the standard loss growth range is based on the influence of electromagnetic loss on the coil performance and heat loss under different load levels. In practical applications, the growth rate of power loss is mainly affected by the resistance change of the coil conductor, core eddy current loss, and hysteresis loss. Among them, the resistance change rate R cIt is directly proportional to the operating temperature. For every 10°C increase in temperature, the resistance increases by approximately 4%, which will directly affect the calculation of the loss. At the same time, the eddy current loss is proportional to the square of the frequency, that is, P e ∝f 2 , so at higher frequencies (such as above 50 kHz), the loss increases at a faster rate. The hysteresis loss is mainly affected by the magnetic flux density, and its growth rate will increase exponentially after the magnetic flux density exceeds 0.8 T.

[0128] The normal loss growth range is set to be less than 20%. This range is based on the allowable temperature rise range of the coil material. Industrial standards stipulate that the operating temperature rise of most copper coils is limited to below 85°C, that is, when the loss growth rate does not exceed 20%, the temperature change is still within the controllable range. When the loss growth rate exceeds 30%, according to the heat conduction calculation, the coil temperature may rise above 100°C, which may cause insulation layer deterioration or even local overheating and burnout. Therefore, 30% is taken as the abnormal threshold.

[0129] For the warning range between 20% - 30%, this range is set based on the thermal stability of the coil during the load change process. Within this range, although the power loss increases, it does not reach the critical abnormal value. However, if the coil continues to operate within this range, it may cause a cumulative effect, resulting in a slow increase in temperature and eventually reaching the abnormal range. Therefore, continuous monitoring should be carried out within the warning range.

[0130] The currently measured power loss growth rate is 33.3%, which clearly exceeds the standard loss growth range. Therefore, it is determined as abnormal loss, and the abnormal parameter items are screened out to obtain the electromagnetic loss abnormal parameter set.

[0131] As shown in Table 1, the loss growth rate and abnormal judgment criteria under different load levels are listed.

[0132] Table 3.1 Standard Table of Load Level and Power Loss Growth Rate

[0133]

[0134] Referring to Table 3.1, under the medium load level, a loss growth rate exceeding 30% will be judged as abnormal. Therefore, the current 33.3% has entered the abnormal range, and the abnormal parameter set needs to be further screened.

[0135] Please refer to Figure 5 , the multi-parameter abnormal screening module includes:

[0136] Based on the electromagnetic loss abnormal parameter set, the parameter statistical calculation sub-module statistically calculates the current resistance value, inductance value, magnetic flux density, power loss, and current change rate, calculates the relative change ratio of each parameter, and obtains the parameter relative change ratio set;

[0137] Based on the set of abnormal electromagnetic loss parameters, the current resistance value, inductance value, magnetic flux density, power loss, and current change rate are obtained. In practical applications, a high-precision digital multimeter can be used to measure the resistance value, an LCR meter to obtain the inductance value, a Hall sensor to obtain the magnetic flux density, a power analyzer to obtain the power loss, and a current sensor to detect the current change rate. For example, in a certain electromagnetic induction system, the measured resistance value is 0.35 Ω, the inductance value is 4.8 mH, the magnetic flux density is 0.6 T, the power loss is 12.5 W, and the current change rate is 3.2%. Subsequently, the relative change ratios of each parameter are calculated as follows:

[0138] The reference resistance value is 0.3 Ω, then the relative change ratio of the resistance is:

[0139]

[0140] The reference inductance value is 5.0 mH, then the relative change ratio of the inductance is:

[0141]

[0142] The reference magnetic flux density is 0.65 T, then the relative change ratio of the magnetic flux density is:

[0143]

[0144] The reference power loss is 11.0 W, then the relative change ratio of the power loss is:

[0145]

[0146] The reference current change rate is 2.8%, then the relative change ratio of the current change rate is:

[0147]

[0148] Finally, obtain the set of relative change ratios of the parameters: {16.67%, 4.00%, 7.69%, 13.64%, 14.29%}.

[0149] The synchronous decline judgment sub-module compares the set reference range of parameter change trends based on the set of relative change ratios of the parameters, judges whether each parameter has a synchronous decline trend, and obtains the analysis result of the synchronous decline state;

[0150] According to the set of relative change ratio of parameters, calculate the change consistency of each parameter. If the change trends of all parameters are close, it indicates that they have a synchronous decline trend. Set the synchronous decline benchmark range. When the standard deviation of the parameter change ratio is lower than 5%, it is considered that the parameter changes show a synchronous trend. The setting of this 5% standard is based on the stability requirements of the electromagnetic induction system. When the change standard deviation of the system parameters is small, it indicates that multiple parameters change synchronously under the action of the same influencing factors during operation. Common influencing factors include temperature drift, frequency offset, electromagnetic interference, etc. Specifically, in high-frequency electromagnetic equipment, the influence of temperature change on resistance is more obvious. When the temperature change exceeds 10°C, the resistance of the copper coil may increase by 3%-5%. If the relative changes of the inductance value and magnetic flux density are also within the same range at this time, it can be judged that the parameters show a synchronous decline trend. In addition, the coupling relationship between power loss and current change rate is relatively strong. If the offset trends of the current change rate and power loss are consistent, and the change ratio of power loss is within **10%**, it indicates that the operating state of the system is still within the stable range. If the synchronous change amplitude exceeds 5%, it may cause abnormal system tuning.

[0151] Calculate the average relative change ratio:

[0152]

[0153] Calculate the standard deviation:

[0154]

[0155] Since 4.68% < 5%, it is judged that the change trends of each parameter are synchronous, and the analysis result of the synchronous decline state is obtained, that is, the parameters have a synchronous decline trend. The standard deviation of 4.68% is lower than the 5% benchmark, indicating that the change trends of multiple parameters are relatively consistent and no sudden abnormal phenomena occur. If the standard deviation of a certain parameter exceeds 5% in the future, the source of its change, such as interference factors like temperature drift and current harmonics, should be further analyzed.

[0156] Based on the analysis result of the synchronous decline state, the parameter correlation analysis sub-module uses the formula:

[0157]

[0158] Calculate the cross-correlation coefficient C between parameter i and parameter j i,j , and obtain the mutual analysis result of the parameters. Among them, x i,k represents the value of parameter i at the k-th measurement, represents the mean value of parameter i, x j,k represents the value of parameter j at the k-th measurement, represents the mean value of parameter j, and m represents the corresponding number of measurements;

[0159] Based on the results of the synchronous decay state analysis, the cross-correlation coefficients between various parameters are calculated using formulas.

[0160] Suppose five groups of data are obtained from a certain measurement, as shown in Table 4.1:

[0161] Table 4.1 Parameter Measurement Data Table

[0162]

[0163] Calculate the mean value of each parameter:

[0164]

[0165]

[0166] Calculate the cross-correlation coefficient between resistance and power loss:

[0167]

[0168] After calculation, C R,P = 0.92, which is very close to 1, indicating a high correlation between the resistance value and the power loss. Calculate other parameter pairs using a similar method to obtain the results of parameter mutual analysis.

[0169] The results show that there is a strong correlation between the resistance value, inductance value, magnetic flux density, power loss, and current change rate. Among them, the correlation between resistance and power loss, and between magnetic flux density and inductance value is relatively high, indicating that these parameters may have a coupling relationship under abnormal electromagnetic loss conditions, affecting the overall system performance.

[0170] Please refer to Figure 6 , the health status assessment module includes:

[0171] The health change trend calculation sub-module monitors the changes in the health status parameters of the electromagnetic coil at different time points based on the results of parameter mutual analysis, analyzes the health status change trend, and obtains the health change trend analysis result;

[0172] Based on the results of parameter mutual analysis, obtain the health status parameters at multiple time points, usually including the inductance value, resistance value, magnetic flux density, power loss, etc. of the electromagnetic coil, and obtain the parameter values at different time points to analyze the change trend of the health status. Suppose the inductance values of a certain electromagnetic coil at four time points (t1, t2, t3, t4) are 4.8 mH, 4.6 mH, 4.3 mH, and 4.0 mH respectively, and the magnetic flux densities are 1.2 T, 1.1 T, 1.05 T, and 0.95 T respectively. By calculating the change trends of each parameter, determine its decay rate over time. For example, the decline rate of the inductance value can be calculated through (L t+1 -L t) / (t + 1 - t) is calculated to obtain the changing trend of the health status. Combining these trend data, health change trend parameters are calculated for subsequent analysis.

[0173] Table 5.1 Table of the health status parameters of the electromagnetic coil changing with time

[0174]

[0175] As shown in Table 5.1, as time goes by, the inductance value, resistance value, and magnetic flux density all show a downward trend, indicating that the health status of the electromagnetic coil is deteriorating. By calculating the change rate of the health status parameters, the analysis result of the health change trend is obtained.

[0176] The health deterioration rate calculation sub-module, based on the analysis result of the health change trend, uses the formula:

[0177]

[0178] Calculate the health deterioration rate H of the electromagnetic coil D , and obtain the health deterioration rate data, where S t represents the health status parameter value at the t-th time point, and M represents the number of monitoring time points;

[0179] Call the analysis result of the health change trend, and calculate the health deterioration rate of the electromagnetic coil using the formula. The health status parameter is comprehensively calculated from the inductance value and the magnetic flux density. The health status parameter can be defined as:

[0180]

[0181] Among them, L t and B t respectively represent the inductance value and the magnetic flux density at the t-th time point, and L0 and B0 respectively represent the initial inductance value and magnetic flux density of the system. Substituting the data in Table 1, the calculation results are:

[0182]

[0183] Further calculate the health deterioration rate:

[0184]

[0185] This result shows that the health deterioration rate is 0.125, that is, the health status parameter decreases by about 12.5% on average at each time point, and the health deterioration rate data is obtained.

[0186] Based on the health deterioration rate data, the health warning judgment sub-module compares the health status warning threshold to judge whether the health status reaches the warning value. If it exceeds the threshold, it is determined that there is a problem with the health status of the electromagnetic coil, and the evaluation result of the health status of the electromagnetic coil is obtained;

[0187] Based on the health deterioration rate, compare it with the health status warning threshold to determine whether the health status exceeds the warning range. The health status warning threshold is set to 0.1. The setting of this threshold is based on the long-term operation stability analysis of electromagnetic devices. During the operation of high-frequency electromagnetic devices, the attenuation rates of key parameters such as inductance, resistance, and magnetic flux density directly affect the device performance. Through laboratory tests, the health status data of different types of electromagnetic coils are summarized as follows:

[0188] Table 5.2 Characteristics Table of Health Status Deterioration of Electromagnetic Coils

[0189]

[0190] As shown in Table 5.2, when the health deterioration rate exceeds 0.1, the performance degradation rate of the device generally exceeds 8%. Among them, the deterioration rate of Type B devices reaches 0.18, and the corresponding performance degradation rate is as high as 12.2%, indicating that the device may face serious losses. Therefore, 0.1 is selected as the warning threshold to evaluate the health status of electromagnetic coils.

[0191] Based on the above setting, comparing the calculation result 0.109 > 0.1 indicates that the health status has exceeded the warning range. Therefore, it is determined that there is a problem with the health status of the electromagnetic coil, and it enters the abnormal state, and the health status evaluation result of the electromagnetic coil is obtained.

[0192] Table 5.3 Comparison Table of Health Deterioration Rate and Warning Threshold

[0193]

[0194] As shown in Table 5.3, the health deterioration rate has exceeded the set warning threshold. Therefore, it is determined that the health status of the electromagnetic coil is abnormal, and the health status evaluation result of the electromagnetic coil is obtained.

[0195] The above is only the preferred embodiment of the present invention, and it does not limit the present invention in other forms. Any person skilled in the art may use the technical content disclosed above to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A coil health dynamic evaluation system based on electromagnetic coil performance parameters, characterized in that: The system comprises: The coil operation load evaluation module obtains the real-time input current and input voltage of the coil, calculates the load power deviation ratio, synchronously draws the load impact curve, sets the load level, determines whether it exceeds the parameter deviation range of the corresponding load level, and obtains the abnormal load impact parameter set; The operating frequency health comparison module analyzes the inductance drift trend under the current frequency condition based on the abnormal load impact parameter set, compares the inductance drift reference range, and outputs the frequency impact abnormal parameter set; The electromagnetic loss joint analysis module calculates the coil power loss amount and the power loss growth rate based on the frequency-affected abnormal parameter set, compares the standard loss growth range, and obtains the electromagnetic loss abnormal parameter set; The multi-parameter abnormal screening module calculates the relative change ratio of the coil operation parameters based on the electromagnetic loss abnormal parameter set, determines whether there is a synchronous decay trend, analyzes the cross-correlation of the parameters, and obtains the mutual analysis results of the parameters; The health status assessment module analyzes the change trend of the current health status of the electromagnetic coil according to the mutual analysis results of the parameters, compares the health status warning threshold, and outputs the health status assessment result of the electromagnetic coil.

2. The coil health dynamic evaluation system based on electromagnetic coil performance parameters according to claim 1 is characterized in that: The abnormal load impact parameter set includes load power deviation ratio data, resistance change rate data, inductance change rate data, and magnetic flux density change rate data; the frequency impact abnormal parameter set includes inductance drift trend analysis results and inductance drift benchmark range comparison results; the electromagnetic loss abnormal parameter set includes power loss amount, power loss growth rate, and standard loss growth range comparison results; the parameter mutual analysis results include resistance value relative change ratio, inductance value relative change ratio, magnetic flux density relative change ratio, power loss relative change ratio, current change rate relative change ratio, and synchronous decay trend analysis results; the electromagnetic coil health status assessment results include health status change trend analysis results, health degradation rate data, and health status warning threshold comparison results.

3. The coil health dynamic evaluation system based on electromagnetic coil performance parameters according to claim 1 is characterized in that: The coil operation load evaluation module comprises: The load power calculation submodule obtains the real-time input current and real-time input voltage of the coil, calculates the current load power, and calculates the load power deviation ratio in combination with the reference power value under no-load state, using the formula: Calculate the load power deviation percentage P d , obtain the load power deviation ratio data, where P L represents the current load power, and P0 represents the reference power in the no-load state; The load parameter change rate calculation submodule collects the resistance value, inductance value, and magnetic flux density under no-load condition, and simultaneously obtains the resistance, inductance, and magnetic flux density under current load condition, calculates the resistance change rate, inductance change rate, and magnetic flux density change rate, and obtains the load parameter change rate set; The load impact analysis submodule compares the current measured parameters based on the load parameter change rate set and the load power deviation ratio data, combined with the preset load level parameter deviation range, screens out parameter items that exceed the load level range, and obtains the abnormal load impact parameter set.

4. The coil health dynamic evaluation system based on electromagnetic coil performance parameters according to claim 1 is characterized in that: The operating frequency health comparison module includes: The inductance drift calculation submodule collects the coil inductance value at the current frequency based on the abnormal load impact parameter set, calculates the inductance drift trend under the current frequency condition in combination with the coil reference inductance value, and obtains the inductance drift trend data; The inductance drift reference comparison submodule compares the inductance drift reference range according to the inductance drift trend data, determines whether the current inductance drift trend exceeds the reference range, and obtains a drift over-limit state record; The frequency influence parameter extraction submodule adopts the formula based on the drift over-limit state record and the inductance change rate, resistance change rate and magnetic flux density change rate in the abnormal load influence parameter set: Calculation frequency affects the deviation ratio of related parameters R F , get the frequency impact abnormal parameter set, where X i Represents the inductance, resistance, and magnetic flux density parameter values ​​at the current frequency. Represents the reference parameter value of the corresponding parameter, W i represents the influence weight of each parameter, and n represents the number of parameters.

5. The coil health dynamic evaluation system based on electromagnetic coil performance parameters according to claim 1 is characterized in that: The electromagnetic loss joint analysis module includes: The power loss calculation submodule collects the coil input power and output power under the current load level based on the frequency impact abnormal parameter set, calculates and outputs the coil power loss data; The loss growth rate judgment submodule uses the formula based on the power loss data and the normal power loss base value under the same load level: Calculate and output power loss growth rate data G P , where P L Represents the current power loss, P N Represents the normal power loss base value; The electromagnetic loss abnormal screening submodule compares the power loss growth rate data with the standard loss growth range, determines whether it exceeds the standard range, screens out abnormal parameter items, and obtains an electromagnetic loss abnormal parameter set.

6. The coil health dynamic evaluation system based on electromagnetic coil performance parameters according to claim 1 is characterized in that: The multi-parameter abnormal screening module includes: The parameter statistics calculation submodule counts the current resistance value, inductance value, magnetic flux density, power loss, and current change rate based on the electromagnetic loss abnormal parameter set, calculates the relative change ratio of each parameter, and obtains a parameter relative change ratio set; The synchronous decay judgment submodule compares the parameter relative change ratio set with the set parameter change trend reference range, judges whether each parameter has a synchronous decay trend, and obtains a synchronous decay state analysis result; The parameter correlation analysis submodule adopts the formula based on the synchronous decay state analysis result: Calculate the cross-correlation coefficient C between parameter i and parameter j i,j , obtain the results of parameter mutual analysis, where x i,k represents the value of parameter i at the kth measurement, represents the mean of parameter i, x j,k represents the value of parameter j at the kth measurement, represents the mean of parameter j, and m represents the corresponding number of measurements.

7. The coil health dynamic evaluation system based on electromagnetic coil performance parameters according to claim 1 is characterized in that: The health status assessment module includes: The health change trend calculation submodule monitors the change of the health state parameters of the electromagnetic coil at different time points based on the mutual analysis results of the parameters, analyzes the health state change trend, and obtains the health change trend analysis results; The health degradation rate calculation submodule uses the formula: Calculate the health degradation rate H of the electromagnetic coil D , get the health degradation rate data, where S t represents the health status parameter value at the tth time point, and M represents the number of monitoring time points; The health warning judgment submodule compares the health degradation rate data with the health status warning threshold to determine whether the health status reaches the warning value. If it exceeds the threshold, it is determined that there is a problem with the health status of the electromagnetic coil and the health status assessment result of the electromagnetic coil is obtained.

Images