EMC state evaluation system and method applied to capacitor

Abstract

The invention discloses an EMC (Electro Magnetic Compatibility) state evaluation system and method applied to a capacitor, and relates to the technical field of capacitor state evaluation, the evaluation system comprises a plurality of function modules which run in sequence, and the function modules are respectively an arrangement collection module, a signal processing module, a feature extraction module, a state evaluation module and an alarm feedback module; the technical key points are as follows: the system builds a life prediction model, generates a life prediction index of the capacitor according to the change trend of a comprehensive performance estimation value, and analyzes the change trend of the life prediction index in different periods, so that potential problems can be found in time, and corresponding maintenance measures can be taken; the normal operation of the capacitor is ensured; the service life is prolonged; the overall scheme not only solves the technical problem of capacitor performance and life evaluation, but also realizes real-time and accurate evaluation, and provides powerful support for normal operation and maintenance of the capacitor.

Description

Technical Field

[0001] The present invention relates to the technical field of capacitor status assessment, and in particular to an EMC status assessment system and method applied to a capacitor. Background Art

[0002] The EMC (electromagnetic compatibility) status assessment of capacitors is an important step to ensure that their performance will not be affected or failures will not be caused by electromagnetic interference under normal working conditions. The contents of the EMC status assessment of capacitors include: Electromagnetic interference level assessment: measuring the electromagnetic field strength generated by the capacitor during operation, especially the electric field or magnetic field strength in a specific frequency band; analyzing the electromagnetic interference that the capacitor may cause to surrounding equipment to ensure that the interference level is within an acceptable range; Electromagnetic sensitivity assessment: assessing the capacitor's resistance to external electromagnetic interference, that is, whether it can maintain normal operation when subjected to electromagnetic interference; determining the performance changes of the capacitor under specific electromagnetic interference through simulation or actual testing; Capacitance value stability assessment: under electromagnetic interference conditions, measuring the actual capacitance value of the capacitor and comparing it with the initial capacitance value or rated capacitance value; analyzing the impact of electromagnetic interference on the stability of the capacitor's capacitance value to ensure that the capacitance value change is within an acceptable range.

[0003] The scheme pointed out in the document with the existing publication number CN113899960A and the name of an electric drive system EMI test system for simulating the running state of an electric vehicle includes: the system is used for EMI testing of an electric drive system, including a darkroom, an electric drive system, a copper base, an insulating base, a speed torque measuring device placed outside the darkroom, a dynamometer, a dynamometer power supply, a controller, an electric drive system control computer, a spectrum analyzer, and an optical coupling isolation device. The electric drive system control computer controls the electric drive system and the load dynamometer, and measures the differential mode and common mode EMI on the DC side and the AC side when the electric drive system is in different working conditions; the measured common mode voltage and common mode current data can be used to extract the common mode impedance of the battery pack under different working conditions; the present invention can test and evaluate the EMI generated by the electric drive system under various working conditions, obtain the EMC performance of the electric drive system, and the test results are accurate and reliable, but it cannot monitor or evaluate the state of the capacitor carried by the car in real time in combination with reality.

[0004] In combination with the above documents and existing technologies, the traditional status assessment of automotive capacitors is usually carried out in accordance with an established comprehensive calculation method, and the data parameters considered are relatively common, such as current and voltage. However, in the subsequent assessment, the method usually adopted in the face of different scenarios is single and cannot adapt to the specific environment, thus affecting the accuracy of the subsequent assessment of capacitor performance and life, and it is also impossible to perform real-time and effective assessment operations. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the deficiencies in the prior art, the present invention provides an EMC status assessment system and method for capacitors, which realizes real-time and accurate assessment of capacitor performance and life, provides strong support for the normal operation and maintenance of capacitors, and solves the problems raised in the background technology.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] An EMC status assessment system for capacitors, comprising:

[0010] Arrange collection modules to collect physical parameters of the capacitor during operation and electromagnetic field strength data;

[0011] The signal processing module filters and amplifies the physical parameters and electromagnetic field strength data, converts the physical parameters and electromagnetic field strength data into digital signals through an A / D converter, and outputs them;

[0012] The feature extraction module receives and analyzes the digital signal, extracts the feature parameters in each sub-time period within the preset period T, and establishes a feature parameter database; synchronously obtains the state definition parameters of the capacitor;

[0013] The state evaluation module has a built-in definition submodule, which builds a trigger calculation model based on the state definition parameters and generates a trigger index. When the trigger index exceeds the set definition threshold, an add signal is issued; under the condition of receiving or not receiving the add signal, a weighted calculation is performed based on the corresponding characteristic parameters to obtain the comprehensive performance valuation corresponding to each sub-time period;

[0014] Analyze the change trend of the comprehensive performance valuation under the same period T, and output the first analysis result;

[0015] According to each comprehensive performance valuation under the same period T, a life prediction model is built to generate life prediction indicators, and the change trend of the life prediction indicators under different periods T is analyzed, and the second analysis result is output;

[0016] An alarm feedback module receives the first analysis result and the second analysis result;

[0017] When the first analysis result shows that the comprehensive performance estimate continues to increase, a performance warning signal is issued and a maintenance strategy is executed;

[0018] When the second analysis result shows that the life prediction index continues to decrease, a warning signal is issued and a maintenance strategy is executed.

[0019] Furthermore, the physical parameters include voltage, current and temperature. The physical parameters and the electromagnetic field strength data of the corresponding capacitor surrounding area are obtained through a sensor network, and the sensor network is arranged on the capacitor and its surrounding area.

[0020] Furthermore, the characteristic parameters include electromagnetic interference level, capacitance value change rate and temperature coefficient.

[0021] Furthermore, the process of extracting characteristic parameters in each sub-time period is as follows:

[0022] Calculate the average electromagnetic field strength in the area around the capacitor in the corresponding sub-time period to obtain the electromagnetic interference level; use the collected voltage and current data to calculate the actual capacitance value of the capacitor, and compare it with the initial capacitance value to obtain the capacitance value change rate; obtain the temperature and capacitance value at the initial moment of the corresponding sub-time period, obtain the temperature and capacitance value at the end moment of the corresponding sub-time period, calculate the slope of the capacitance value changing with temperature, and obtain the temperature coefficient.

[0023] Furthermore, the state definition parameters of the capacitor include ambient temperature and operating time; wherein, the ambient temperature is obtained by capturing data from the regional meteorological station in the area where the car is located, and the operating time is collected and obtained through a timer configured on the car.

[0024] Furthermore, the process of generating the trigger index by the trigger calculation model is as follows:

[0025] First, the trigger calculation model uses a linear function to establish the impact factor calculation formula, as shown below:

[0026]

[0027] In formula (1), Ft represents the environmental temperature influence factor, a and b are constants, and the value range is: 0<a<1, 0≤b<1; In formula (2), Fh represents the operating time influence factor, d represents a constant, and the value range is: 0<a<0.1;

[0028] Secondly, add the ambient temperature impact factor and the running time impact factor to get the trigger index:

[0029] Ci=Ft+Fh; (3)

[0030] In formula (3), Ci represents the trigger index.

[0031] Furthermore, under the condition of receiving the added signal, a weighted calculation is performed according to the electromagnetic interference level, the capacitance value change rate and the temperature coefficient to obtain the comprehensive performance estimation corresponding to each sub-time period, and the formula is as follows:

[0032] S i=w1*E+w2*CR+w3*TC; (4)

[0033] In formula (4), S i represents the comprehensive performance estimation corresponding to the i-th sub-time period, i is a positive integer greater than 0, E represents the electromagnetic interference level, CR=ΔC / C0, where ΔC is the change in capacitance, C0 is the initial capacitance value, and CR represents the capacitance change rate; TC represents the temperature coefficient; w1, w2, and w3 are the weight coefficients of the electromagnetic interference level, capacitance change rate, and temperature coefficient, respectively, and their values ​​range from 0 to 1;

[0034] Under the condition that no added signal is received, a weighted calculation is performed based on the electromagnetic interference level and the capacitance value change rate to obtain the comprehensive performance estimation corresponding to each sub-time period, and the formula is as follows:

[0035] S i =k1*E+k2*CR; (5)

[0036] In formula (5), k1 and k2 are weight coefficients of electromagnetic interference level and capacitance value change rate, respectively, and their value ranges are both between 0 and 1.

[0037] Furthermore, a life prediction model is built, and the formula for generating life prediction indicators is as follows:

[0038] L=L0 / (1+G*∑(S i -S i-1 )); (6)

[0039] In formula (6), L represents the life prediction index, L0 represents the initial life estimation value of the capacitor, G represents the adjustment coefficient, and the value range is: 0<G<1; ∑(S i -S i-1 ) represents the comprehensive performance estimate S i The cumulative change in each time period.

[0040] Furthermore, when analyzing the changing trend of the comprehensive performance valuation under the same period T, and when analyzing the changing trend of the life prediction index under different periods T, data analysis software is used, including but not limited to: any one or more of Tableau, Power BI and RapidMiner.

[0041] A method for evaluating the EMC status of a capacitor includes the following steps:

[0042] S1. Collecting physical parameters of the capacitor during operation and electromagnetic field strength data;

[0043] S2, filtering and amplifying the physical parameters and electromagnetic field strength data, synchronously converting the physical parameters and electromagnetic field strength data into digital signals through an A / D converter, and outputting them;

[0044] S3, receiving and analyzing the digital signal, extracting characteristic parameters in each sub-time period within the preset period T, and establishing a characteristic parameter database; synchronously obtaining the state definition parameters of the capacitor;

[0045] S4. A trigger calculation model is built based on the state definition parameters to generate a trigger index. When the trigger index exceeds the set definition threshold, an add signal is issued; under the condition of receiving or not receiving the add signal, a weighted calculation is performed based on the corresponding characteristic parameters to obtain a comprehensive performance valuation corresponding to each sub-time period;

[0046] Analyze the change trend of the comprehensive performance valuation under the same period T, and output the first analysis result;

[0047] According to each comprehensive performance valuation under the same period T, a life prediction model is built to generate life prediction indicators, and the change trend of the life prediction indicators under different periods T is analyzed, and the second analysis result is output;

[0048] S5, receiving the first analysis result and the second analysis result;

[0049] When the first analysis result shows that the comprehensive performance estimate continues to increase, a performance warning signal is issued and a maintenance strategy is executed;

[0050] When the second analysis result shows that the life prediction index continues to decrease, a warning signal is issued and a maintenance strategy is executed.

[0051] (III) Beneficial effects

[0052] The present invention provides an EMC status assessment system and method for capacitors, which have the following beneficial effects:

[0053] (1) The solution uses a feature extraction module to collect and analyze the physical parameters and electromagnetic field strength data of the capacitor in real time during operation, extract characteristic parameters such as electromagnetic interference level, capacitance value change rate, and temperature coefficient, and establish a characteristic parameter database. These characteristic parameters can fully reflect the working status and performance changes of the capacitor;

[0054] (2) The scheme can build a trigger calculation model based on the state definition parameters, generate a trigger index that changes in real time, and determine whether it is necessary to consider the change in temperature coefficient to calculate the comprehensive performance valuation based on the trigger index, so as to generate a comprehensive performance valuation in a targeted manner based on the actual situation; then, a weighted calculation is performed based on the extracted features to obtain the comprehensive performance valuation corresponding to each sub-time period, which is convenient for subsequent analysis and judgment of the performance status of the corresponding capacitor;

[0055] (3) In addition, the solution also builds a life prediction model to generate capacitor life prediction indicators based on the change trend of the comprehensive performance valuation, and analyzes the change trend of the life prediction indicators under different cycles, which helps to timely discover potential problems and take corresponding maintenance measures to ensure the normal operation of the capacitor and extend its service life;

[0056] In summary, by adopting the above technical solutions, not only the technical problems of capacitor performance and life evaluation are solved, but also real-time and accurate evaluation is achieved, providing strong support for the normal operation and maintenance of capacitors. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a modular schematic diagram of an EMC status assessment system applied to a capacitor in the present invention;

[0058] Figure 2 The figure is a schematic diagram of the overall steps of an EMC status assessment method applied to a capacitor in the present invention. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] Embodiment 1:

[0061] See also Figure 1 ,This embodiment provides an EMC status assessment system applied to capacitors, the system is aimed at: life assessment and status detection of components (capacitors) in automobiles;

[0062] The evaluation system includes several functional modules that run in sequence, namely, a layout collection module, a signal processing module, a feature extraction module, a state evaluation module and an alarm feedback module;

[0063] Arrange the collection module:

[0064] Real-time collection of physical parameters of the capacitor during operation, as well as electromagnetic field strength data in the area surrounding the capacitor;

[0065] Among them, the physical parameters include voltage, current and temperature;

[0066] The physical parameters are obtained through the sensor network arranged on and around the capacitor. It should be noted that the sensor network is composed of a large number of tiny sensor nodes with wireless communication and computing capabilities deployed in the action area through self-organization. It is a distributed intelligent network system that can autonomously complete designated tasks according to the environment; these sensor nodes can collaboratively monitor the physical or environmental conditions of different locations, such as temperature, sound, vibration, pressure or pollutants;

[0067] In this embodiment, the sensor network is arranged on the capacitor and its surroundings to collect various physical parameters of the capacitor in real time during operation; the sensor nodes include voltage sensors, current sensors, temperature sensors and electromagnetic field strength sensors, which are responsible for collecting the voltage, current, temperature and electromagnetic field strength data of the capacitor during operation respectively;

[0068] Voltage data: collected through voltage sensors;

[0069] The voltage sensor can directly measure the voltage value across the capacitor and convert it into an electrical signal for transmission; the signal conditioning circuit pre-processes the collected voltage signal, such as filtering and amplification, to ensure the accuracy and reliability of the data;

[0070] Current data: collected through current sensors;

[0071] Current sensors usually use the Hall effect principle or the magnetoresistance effect principle to measure the current in the capacitor; the collected current signal also needs to be pre-processed by the signal conditioning circuit to ensure the accuracy of the data;

[0072] Temperature data: collected through temperature sensors;

[0073] The temperature sensor can sense the temperature change on the surface of the capacitor and convert it into an electrical signal; the signal conditioning circuit amplifies and filters the temperature signal to improve the stability and reliability of the data;

[0074] Electromagnetic field strength data: collected through electromagnetic field strength sensors;

[0075] This type of sensor can measure the electromagnetic field strength in the space around the capacitor and convert it into an electrical signal for transmission; since the electromagnetic field signal may be interfered by many factors, the signal conditioning circuit pre-processes the collected electromagnetic field signal to filter out noise and improve the accuracy of the data;

[0076] How sensor networks work:

[0077] The sensor nodes in the sensor network are connected to each other through wireless communication to form a self-organizing network system. They can collaboratively sense, collect and process specific information in the network coverage area, and transmit this information to the aggregation node or base station through multiple hops. In this scenario, the aggregation node or base station may be a data processing center for further processing and analysis of the collected voltage, current, temperature, electromagnetic field strength and other data.

[0078] In summary, through the sensor network arranged on and around the capacitor and the preprocessing function of the signal conditioning circuit, the physical parameters of the capacitor during operation and the electromagnetic field strength data in the area around the capacitor can be collected in real time and accurately, providing strong support for the normal operation and fault diagnosis of the capacitor.

[0079] Signal processing module:

[0080] The collected physical parameters and electromagnetic field strength data are filtered and amplified to eliminate noise interference and improve signal quality; the physical parameters and electromagnetic field strength data are converted into digital signals through A / D converters to facilitate subsequent processing and analysis, and then output;

[0081] The purpose of filtering and amplifying the data here is to make up for the fact that some physical parameters or electromagnetic field strength data are not preprocessed in the arrangement collection module, so as to further ensure the accuracy and reliability of the data.

[0082] By adopting the above technical solution, the technical problem of real-time and accurate collection of physical parameters and electromagnetic field strength data during the operation of the capacitor is solved; specifically, the solution can collect the voltage, current, temperature and surrounding electromagnetic field strength data of the capacitor in real time during operation through a sensor network arranged on and around the capacitor; these data are crucial for the normal operation and fault diagnosis of the capacitor;

[0083] At the same time, the technical solution also achieves the following technical effects:

[0084] Improve data accuracy and reliability: Each sensor node in the sensor network can collaboratively sense, collect and process information, and pre-process the collected signals through signal conditioning circuits, such as filtering and amplification, to eliminate noise interference and improve signal quality, which ensures data accuracy and reliability;

[0085] Realize data digitization: Through A / D converter, physical parameters and electromagnetic field strength data are converted into digital signals for subsequent processing and analysis, which provides strong support for intelligent management and fault diagnosis of capacitors;

[0086] Support real-time monitoring and fault diagnosis: The data collected in real time can be used to monitor the operating status of the capacitor, detect abnormal conditions in time, and perform fault diagnosis, which helps to improve the operating efficiency and reliability of the capacitor and reduce the possibility of failure;

[0087] In summary, by adopting the above technical solutions, not only the technical problem of real-time and accurate collection of physical parameters and electromagnetic field strength data during the working process of the capacitor is solved, but also the accuracy and reliability of the data are improved, the digitization of the data is realized, and real-time monitoring and fault diagnosis are supported, which provides a strong guarantee for the normal operation and intelligent management of the capacitor.

[0088] Feature extraction module:

[0089] Receive and analyze digital signals, extract characteristic parameters in each sub-time period within a preset period T, and establish a characteristic parameter database; synchronously obtain state definition parameters of the capacitor;

[0090] Each sub-time period within the preset period T is equal, for example: one day is divided into 24-hour sub-time periods;

[0091] Characteristic parameters include electromagnetic interference level, capacitance change rate and temperature coefficient;

[0092] The process of extracting characteristic parameters in each sub-time period is as follows:

[0093] Calculate the average value of the electromagnetic field strength in the area surrounding the capacitor in the corresponding sub-time period to obtain the electromagnetic interference level;

[0094] Using the collected voltage and current data, calculate the actual capacitance value of the capacitor and compare it with the initial capacitance value to get the capacitance value change rate; for example, if the initial capacitance value is 100uF and the actual capacitance value is 95uF, the capacitance value change rate is -5%;

[0095] Get the temperature and capacitance value at the beginning of the corresponding sub-time period, get the temperature and capacitance value at the end of the corresponding sub-time period, calculate the slope of the capacitance value changing with temperature, and you can get the temperature coefficient; for example, if the capacitance value of the capacitor is 100uF at 25°C and 98uF at 50°C, the temperature coefficient is -0.02 / °C. At the same time, observe the change of temperature data over time to evaluate the thermal stability of the capacitor;

[0096] The specific instructions are as follows:

[0097] Electromagnetic interference level, its parameter definition is: electromagnetic interference level refers to the magnitude of the electromagnetic field strength around the capacitor during operation, usually expressed as the average value of the electric field or magnetic field strength in a specific frequency band; extraction method: use a spectrum analyzer or electromagnetic field intensity meter to collect electromagnetic field strength data in a specific frequency band around the capacitor; process the collected data and calculate the average value of the electromagnetic field strength in a specific frequency band; use the calculation result as the characteristic parameter of the electromagnetic interference level;

[0098] Capacitance change rate, its parameter definition: Capacitance change rate refers to the percentage deviation between the capacitance value of the capacitor and the initial capacitance value or the rated capacitance value during the actual working process; extraction method: use an LCR tester or a similar capacitance measuring instrument to measure the actual capacitance value of the capacitor (in this embodiment, the calculation formula of the capacitance value is derived based on the ratio relationship between voltage and current and the equivalent circuit model of the capacitor); compare the actual capacitance value with the initial capacitance value or the rated capacitance value, and calculate the deviation percentage; use the calculation result as the characteristic parameter of the capacitance change rate;

[0099] Temperature coefficient, parameter definition: The temperature coefficient refers to the degree to which the capacitance of a capacitor changes with temperature, usually expressed as the change in capacitance per degree Celsius; extraction method: measure the capacitance of the capacitor at different temperatures and record the data; calculate the slope of the capacitance change with temperature, that is, the temperature coefficient; use the calculation result as the characteristic parameter of the temperature coefficient.

[0100] Establish characteristic parameter database:

[0101] Arrange the extracted characteristic parameters into a table, including the characteristic parameter values ​​of the capacitor, data collection time, etc.; import the table data into the database management system to establish a characteristic parameter database; the database should support query, insert, update and other operations to facilitate subsequent data analysis and application;

[0102] The specific table form gives an example as follows:

[0103] Data collection time Electromagnetic interference level (mean) Capacitance change rate Temperature coefficient 2022-08-0810:00～11:00 0.5V / m -5％ -0.02 / ℃ 2022-08-0811:00～12:00 0.6V / m -3％ -0.01 / ℃ ... ... ... ...

[0104] The value range of T is a positive integer greater than 0;

[0105] The parameters defining the state of the capacitor include: ambient temperature and operating time;

[0106] The ambient temperature is obtained by capturing data from the regional meteorological station in the area where the car is located, and the running time is collected and obtained through the timer configured on the car.

[0107] Status Assessment Module:

[0108] Its built-in definition submodule builds a trigger calculation model based on the state definition parameters to generate a trigger index that changes in real time;

[0109] When the trigger index exceeds the set threshold, an add signal is issued;

[0110] When the trigger index does not exceed the set threshold, no response action is taken;

[0111] Under the condition of receiving the added signal, a weighted calculation is performed based on the electromagnetic interference level, capacitance value change rate and temperature coefficient to obtain the comprehensive performance estimation corresponding to each sub-time period;

[0112] Under the condition that no added signal is received, a weighted calculation is performed based on the electromagnetic interference level and the capacitance value change rate to obtain a comprehensive performance estimate corresponding to each sub-time period;

[0113] Analyze the change trend of the comprehensive performance valuation under the same period T, and output the first analysis result;

[0114] According to each comprehensive performance valuation under the same cycle T, a life prediction model is built to generate the life prediction index corresponding to the capacitor, and the change trend of the life prediction index under different cycles T is analyzed, and the second analysis result is output;

[0115] The process of generating the trigger index by the trigger calculation model is as follows:

[0116] First, the trigger calculation model uses a linear function to establish the impact factor calculation formula, as shown below:

[0117]

[0118] In formula (1), Ft represents the environmental temperature influence factor, a and b are both constants, a represents the increase of the influence factor when the environmental temperature rises by 1°C, and b is used to correct the final environmental temperature influence factor, with a value range of 0<a<1, 0≤b<1;

[0119] In formula (2), Fh represents the impact factor of the running time, d represents a constant, which represents the increase of the impact factor for every increase of 1 hour, and the value range is: 0<a<0.1;

[0120] Secondly, add the ambient temperature impact factor and the running time impact factor to get the trigger index Ci:

[0121] Ci=Ft+Fh; (3)

[0122] It should be noted that the ambient temperature influence factor Ft increases with the increase of ambient temperature, indicating the influence of ambient temperature on capacitor performance. A linear function is used to formalize this influence. The same is true for the operating time influence factor Fh. Finally, the two types of influence factors are added together to obtain a comprehensive value, namely the trigger index Ci.

[0123] A threshold value Ch is set to determine whether the trigger index is exceeded;

[0124] If Ci>Ch, it means that the ambient temperature and operating time have a greater impact on the performance of the capacitor, and the temperature coefficient change needs to be considered to calculate the comprehensive value; if Ci≤Ch, it means that the ambient temperature and operating time have a smaller impact on the performance of the capacitor, and the temperature coefficient change does not need to be considered to calculate the comprehensive value;

[0125] When setting the defining threshold Ch, the design specifications, working environment conditions and historical operating data of the capacitor should be comprehensively considered; according to industry standards and recommendations of professional organizations, the setting of Ch should be between the normal operating environment temperature and the limit temperature of the capacitor, while referring to the rated operating time of the capacitor; the specific value can be determined through experimental testing or simulation, and when Ci suddenly changes, it can accurately reflect the significant impact of ambient temperature and operating time on capacitor performance. The value obtained at this time is the defining threshold; it is recommended to consult capacitor manufacturers or industry experts for more precise guidance on Ch setting.

[0126] An example of overallness:

[0127] Assume that the ambient temperature wr = 40°C, the operating time hr = 1000 hours, and the threshold Ch = 5; Assume that a = 0.1, b = 0, d = 0.01; calculate the trigger index: Ci = 0.1*40+0.01*1000 = 4+10 = 14;

[0128] Determine whether the trigger index exceeds the threshold:

[0129] Because Ci=14>Ch=5, it is necessary to consider the temperature coefficient change to calculate the comprehensive value.

[0130] Through this example, we can see that when the ambient air temperature and operating time are high, the trigger index exceeds the threshold, thereby triggering the logic of calculating the comprehensive value considering the temperature coefficient change, which helps us more accurately evaluate the performance status of the capacitor under different conditions.

[0131] Based on the electromagnetic interference level, capacitance change rate and temperature coefficient, a weighted calculation is performed to obtain the comprehensive performance estimate corresponding to each sub-time period. The formula is as follows:

[0132] S i=w1*E+w2*CR+w3*TC; (4)

[0133] In formula (4), S i represents the comprehensive performance estimation corresponding to the i-th sub-time period, i is a positive integer greater than 0, E represents the electromagnetic interference level, the unit is V / m or the corresponding electromagnetic field strength unit; CR = ΔC / C0, where ΔC is the change in capacitance, C0 is the initial capacitance value, and CR represents the capacitance change rate; TC represents the temperature coefficient, the unit is / ℃;

[0134] w1, w2, and w3 are weight coefficients of electromagnetic interference level, capacitance value change rate, and temperature coefficient, respectively. These coefficients can be adjusted according to actual conditions, and their value ranges are all between 0 and 1;

[0135] The weight coefficient can be determined by the coefficient of variation method, which is a method of weighting each indicator according to the degree of variation between the current value of each evaluation indicator and the target value. If the numerical difference of an indicator is large, it can clearly distinguish the evaluated objects, indicating that the indicator has rich discrimination information, and thus the indicator should be given a larger weight. On the contrary, if the numerical difference of each evaluated object on a certain indicator is small, then the ability of this indicator to distinguish the evaluation objects is weak, and thus the indicator should be given a smaller weight. This method directly uses the information contained in each indicator and obtains the weight of the indicator through calculation, so it is objective.

[0136] Based on the electromagnetic interference level and the capacitance value change rate, a weighted calculation is performed to obtain the comprehensive performance estimation corresponding to each sub-time period, and the formula is as follows:

[0137] S i =k1*E+k2*CR; (5)

[0138] In formula (5), k1 and k2 are weight coefficients of electromagnetic interference level and capacitance value change rate, respectively. These coefficients can be adjusted according to actual conditions, and their value ranges are between 0 and 1.

[0139] The formula for building a life prediction model to generate life prediction indicators is as follows:

[0140] L=L0 / (1+G*∑(S i -S i-1 ))(6)

[0141] In formula (6), L represents the life prediction index, L0 represents the initial life estimate of the capacitor (which can be an empirical value or obtained based on historical data), and G represents the adjustment coefficient, with a value range of 0<G<1; ∑(S i -S i-1 ) represents the comprehensive performance estimate S iCumulative change in each time period; for different periods T, at least 10 consecutive periods T need to be considered in subsequent analysis, for example: analyzing different periods T within 10 days or a month;

[0142] It should be noted that the life of a capacitor is inversely proportional to the speed at which its performance deteriorates, that is, the faster the performance deteriorates, the shorter the life. By conducting a comprehensive evaluation and building a life prediction model, combined with the characteristic parameter data of each cycle, we can effectively evaluate the performance of the capacitor and predict its life. This helps us to detect potential problems in a timely manner and take corresponding maintenance measures to ensure the normal operation of the capacitor and extend its service life.

[0143] When analyzing the changing trend of the comprehensive performance valuation under the same period T, and when analyzing the changing trend of the life prediction index under different periods T, data analysis software is used, including but not limited to: any one or more of Tableau, Power BI and RapidMiner;

[0144] The first analysis result includes a continuous increase in the comprehensive performance valuation or a non-continuous increase in the comprehensive performance valuation (including, for example, the comprehensive value remains stable or slightly decreases, indicating that the performance of the capacitor remains good); the second analysis result includes a continuous decrease in the life prediction index or a non-continuous decrease in the life prediction index (including, for example, the life prediction index remains stable or slightly increases, indicating that the life of the capacitor still has a long remaining time);

[0145] It should be noted that:

[0146] Analyze the changes in comprehensive performance estimates:

[0147] If the comprehensive performance estimate increases gradually from the 1st to the 24th sub-period, it means that the performance of the capacitor is gradually declining; this may be due to an increase in the electromagnetic interference level, an increase in the rate of change of the capacitance value, or a more unfavorable temperature coefficient; if the comprehensive performance estimate suddenly increases a lot in a certain period, it may mean that the capacitor has experienced some abnormal event in this sub-period, such as overvoltage, overcurrent, or a sharp change in ambient temperature; if the comprehensive performance estimate remains relatively stable or decreases slightly, it means that the performance of the capacitor has remained good during this period, with no obvious signs of decline;

[0148] Analyzing changes in life expectancy predictors:

[0149] If the life prediction index gradually decreases from the 1st cycle to the 10th cycle, it means that the expected life of the capacitor is shortening. This may be due to the cumulative effect of performance degradation; if the life prediction index suddenly decreases a lot in a certain cycle, it may mean that the performance of the capacitor has significantly declined in this cycle, and its subsequent development needs to be closely monitored; if the life prediction index remains relatively stable or increases slightly, it means that the expected life of the capacitor still has a long remaining time and can continue to be used normally.

[0150] By adopting the above technical solution, the technical problems of capacitor performance and life evaluation are mainly solved, and the technical effect of real-time and accurate evaluation of capacitor performance and prediction of its life is achieved;

[0151] Specifically, the technical solution collects and analyzes the physical parameters and electromagnetic field strength data of the capacitor in real time during operation through the feature extraction module, extracts characteristic parameters such as electromagnetic interference level, capacitance value change rate and temperature coefficient, and establishes a characteristic parameter database. These characteristic parameters can fully reflect the working status and performance changes of the capacitor;

[0152] At the same time, the state assessment module builds a trigger calculation model based on the state definition parameters, generates a trigger index that changes in real time, and determines whether it is necessary to consider the change in temperature coefficient to calculate the comprehensive performance valuation based on the trigger index, thereby generating a comprehensive performance valuation in a targeted manner based on the actual situation; then, a weighted calculation is performed based on the extracted features to obtain the comprehensive performance valuation corresponding to each sub-time period, which is convenient for subsequent analysis and judgment of the performance status of the corresponding capacitor;

[0153] In addition, the technical solution also built a life prediction model to generate capacitor life prediction indicators based on the change trend of the comprehensive performance valuation, and analyze the change trend of the life prediction indicators under different cycles, which helps to timely discover potential problems and take corresponding maintenance measures to ensure the normal operation of the capacitor and extend its service life;

[0154] In summary, by adopting the above technical solutions, not only the technical problems of capacitor performance and life evaluation are solved, but also real-time and accurate evaluation is achieved, providing strong support for the normal operation and maintenance of capacitors.

[0155] An alarm feedback module receives the first analysis result and the second analysis result;

[0156] When the first analysis result shows that the comprehensive performance estimate continues to increase, a performance warning signal is issued, indicating that the performance of the capacitor is gradually decreasing, and a maintenance strategy is executed, prompting the driver to go to the factory to replace or maintain the capacitor;

[0157] When the second analysis result shows that the life prediction index continues to decrease, a warning signal is issued, indicating that the life of the capacitor is gradually shortening, and a maintenance strategy is executed, prompting the driver to go to the factory for maintenance or repair of the capacitor;

[0158] It should be noted that the performance warning signal and the directional warning signal have different forms of expression. For example, the performance warning signal issues a warning in the form of yellow sound and light, while the directional warning signal issues a warning in the form of red sound and light.

[0159] Embodiment 2:

[0160] See also Figure 2 Based on Example 1, this embodiment further provides an EMC status assessment method applied to a capacitor, comprising the following steps:

[0161] S1. Collecting physical parameters of the capacitor during operation and electromagnetic field strength data;

[0162] S2, filtering and amplifying the physical parameters and electromagnetic field strength data, synchronously converting the physical parameters and electromagnetic field strength data into digital signals through an A / D converter, and outputting them;

[0163] S3, receiving and analyzing the digital signal, extracting characteristic parameters in each sub-time period within the preset period T, and establishing a characteristic parameter database; synchronously obtaining the state definition parameters of the capacitor;

[0164] S4. A trigger calculation model is built based on the state definition parameters to generate a trigger index. When the trigger index exceeds the set definition threshold, an add signal is issued; under the condition of receiving or not receiving the add signal, a weighted calculation is performed based on the corresponding characteristic parameters to obtain a comprehensive performance valuation corresponding to each sub-time period;

[0165] Analyze the change trend of the comprehensive performance valuation under the same period T, and output the first analysis result;

[0166] According to each comprehensive performance valuation under the same period T, a life prediction model is built to generate life prediction indicators, and the change trend of the life prediction indicators under different periods T is analyzed, and the second analysis result is output;

[0167] S5, receiving the first analysis result and the second analysis result;

[0168] When the first analysis result shows that the comprehensive performance estimate continues to increase, a performance warning signal is issued and a maintenance strategy is executed;

[0169] When the second analysis result shows that the life prediction index continues to decrease, a warning signal is issued and a maintenance strategy is executed.

[0170] In the application, the several formulas involved are all calculated by taking their numerical values ​​after removing the dimensions, and the formulas are established by collecting a large amount of data and performing software simulation to obtain a formula for the most recent actual situation. Some coefficients or weights in the formulas are set by technical personnel in this field according to actual conditions, so they will not be elaborated here.

[0171] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0172] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0173] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An EMC status assessment system for capacitors, the system comprising: Arrange collection modules to collect physical parameters of the capacitor during operation and electromagnetic field strength data; The signal processing module filters and amplifies the physical parameters and electromagnetic field strength data, converts the physical parameters and electromagnetic field strength data into digital signals through an A / D converter, and outputs the digital signals; the module is characterized in that it also includes: The feature extraction module receives and analyzes the digital signal, extracts the feature parameters in each sub-time period within the preset period T, and establishes a feature parameter database; synchronously obtains the state definition parameters of the capacitor; The state evaluation module has a built-in definition submodule, which builds a trigger calculation model based on the state definition parameters and generates a trigger index. When the trigger index exceeds the set definition threshold, an add signal is issued; under the condition of receiving or not receiving the add signal, a weighted calculation is performed based on the corresponding characteristic parameters to obtain the comprehensive performance valuation corresponding to each sub-time period; Analyze the change trend of the comprehensive performance valuation under the same period T, and output the first analysis result; According to each comprehensive performance valuation under the same period T, a life prediction model is built to generate life prediction indicators, and the change trend of the life prediction indicators under different periods T is analyzed, and the second analysis result is output; An alarm feedback module receives the first analysis result and the second analysis result; When the first analysis result shows that the comprehensive performance estimate continues to increase, a performance warning signal is issued and a maintenance strategy is executed; When the second analysis result shows that the life prediction index continues to decrease, a warning signal is issued and a maintenance strategy is executed.

2. The EMC status assessment system for capacitors according to claim 1, characterized in that: The physical parameters include voltage, current and temperature. The physical parameters and the electromagnetic field strength data of the corresponding capacitor surrounding area are obtained through a sensor network, and the sensor network is arranged on the capacitor and its surrounding area.

3. The EMC status assessment system for capacitors according to claim 2, characterized in that: Characteristic parameters include electromagnetic interference level, capacitance change rate and temperature coefficient.

4. The EMC status assessment system for capacitors according to claim 3, characterized in that: The process of extracting characteristic parameters in each sub-time period is as follows: Calculate the average electromagnetic field strength in the area around the capacitor in the corresponding sub-time period to obtain the electromagnetic interference level; use the collected voltage and current data to calculate the actual capacitance value of the capacitor, and compare it with the initial capacitance value to obtain the capacitance value change rate; obtain the temperature and capacitance value at the initial moment of the corresponding sub-time period, obtain the temperature and capacitance value at the end moment of the corresponding sub-time period, calculate the slope of the capacitance value changing with temperature, and obtain the temperature coefficient.

5. The EMC status assessment system for capacitors according to claim 1, characterized in that: The state definition parameters of the capacitor include ambient temperature and operating time; the ambient temperature is obtained by capturing data from the regional meteorological station in the area where the car is located, and the operating time is collected and obtained through the timer configured on the car.

6. The EMC status assessment system for capacitors according to claim 5, characterized in that: The process of generating trigger index by trigger calculation model is as follows: First, the trigger calculation model uses a linear function to establish the impact factor calculation formula, as shown below: In formula (1), Ft represents the environmental temperature influence factor, a and b are constants, and the value range is: 0<a<1, 0≤b<1; In formula (2), Fh represents the operating time influence factor, d represents a constant, and the value range is: 0<a<0.1; Secondly, add the ambient temperature impact factor and the running time impact factor to get the trigger index: Ci=Ft+Fh; (3) In formula (3), Ci represents the trigger index.

7. The EMC status assessment system for capacitors according to claim 3, characterized in that: Under the condition of receiving the added signal, a weighted calculation is performed based on the electromagnetic interference level, capacitance value change rate and temperature coefficient to obtain the comprehensive performance estimation corresponding to each sub-time period. The formula is: S i =w1*E+w2*CR+w3*TC; (4) In formula (4), S i represents the comprehensive performance estimation corresponding to the i-th sub-time period, i is a positive integer greater than 0, E represents the electromagnetic interference level, CR=ΔC / C0, where ΔC is the change in capacitance, C0 is the initial capacitance value, and CR represents the capacitance change rate; TC represents the temperature coefficient; w1, w2, and w3 are the weight coefficients of the electromagnetic interference level, capacitance change rate, and temperature coefficient, respectively, and their values ​​range from 0 to 1; Under the condition that no added signal is received, a weighted calculation is performed based on the electromagnetic interference level and the capacitance value change rate to obtain the comprehensive performance estimation corresponding to each sub-time period, and the formula is as follows: S i =k1*E+k2*CR; (5) In formula (5), k1 and k2 are weight coefficients of electromagnetic interference level and capacitance value change rate, respectively, and their value ranges are both between 0 and 1.

8. The EMC status assessment system for capacitors according to claim 7, characterized in that: The formula for building a life prediction model and generating life prediction indicators is as follows: L=L0 / (1+G*∑(S i -S i-1 )); (6) In formula (6), L represents the life prediction index, L0 represents the initial life estimation value of the capacitor, G represents the adjustment coefficient, and the value range is: 0<G<1; ∑(S i -S i-1 ) represents the comprehensive performance estimate S i The cumulative change in each time period.

9. The EMC status assessment system for capacitors according to claim 1, characterized in that: When analyzing the changing trend of the comprehensive performance valuation under the same period T, and when analyzing the changing trend of the life prediction indicators under different periods T, data analysis software is used, including but not limited to: any one or more of Tableau, Power BI and RapidMiner.

10. A method for evaluating the EMC status of a capacitor, using the system according to any one of claims 1 to 9, characterized in that: The steps include: S1. Collecting physical parameters of the capacitor during operation and electromagnetic field strength data; S2, filtering and amplifying the physical parameters and electromagnetic field strength data, synchronously converting the physical parameters and electromagnetic field strength data into digital signals through an A / D converter, and outputting them; S3, receiving and analyzing the digital signal, extracting characteristic parameters in each sub-time period within the preset period T, and establishing a characteristic parameter database; synchronously acquiring state defining parameters of the capacitor; S4. A trigger calculation model is built based on the state definition parameters to generate a trigger index. When the trigger index exceeds the set definition threshold, an add signal is issued; under the condition of receiving or not receiving the add signal, a weighted calculation is performed based on the corresponding characteristic parameters to obtain a comprehensive performance valuation corresponding to each sub-time period; Analyze the change trend of the comprehensive performance valuation under the same period T, and output the first analysis result; According to each comprehensive performance valuation under the same period T, a life prediction model is built to generate life prediction indicators, and the change trend of the life prediction indicators under different periods T is analyzed, and the second analysis result is output; S5, receiving the first analysis result and the second analysis result; When the first analysis result shows that the comprehensive performance estimate continues to increase, a performance warning signal is issued and a maintenance strategy is executed; When the second analysis result shows that the life prediction index continues to decrease, a warning signal is issued and a maintenance strategy is executed.

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