CN117420350B - Loss testing method, system, equipment and medium for power filter - Google Patents
Loss testing method, system, equipment and medium for power filter Download PDFInfo
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Abstract
The application relates to a loss test method, a system, equipment and a medium of a power filter, wherein the loss test method of the power filter comprises the following steps: acquiring actual values of an input voltage Vi, an output voltage Vo and an output current Io of a power filter; the loss of the power filter is calculated according to the actual value, and the formula is used: loss p_loss= (Vi-Vo) ×io; based on the known loss value as reference data, a loss compensation model and a curve are established, wherein the model and the curve relate the input voltage Vi, the output voltage Vo and the output current Io with the actual loss value; calculating a compensation value by using a loss compensation model and a curve according to the current input voltage Vi, the output voltage Vo and the output current Io; the compensation value is applied to the measurement to eliminate errors and to obtain power filter losses. The application has the effect of improving the loss detection accuracy of the power filter.
Description
Technical Field
The application relates to the technical field of power filter detection, in particular to a loss testing method, a loss testing system, loss testing equipment and loss testing media for a power filter.
Background
Conventional power filters play an important role in power systems for removing high frequency noise and harmonics from the power supply to ensure proper operation of the power equipment. However, as the service life of the power filter increases, the internal components thereof may suffer from aging, damage or wear, resulting in a decrease in the performance of the filter and an increase in the energy loss. Therefore, it becomes important to accurately detect the loss of the power supply filter.
In conventional loss detection methods, the loss of the power filter is typically inferred using indirect means, such as estimating the loss based on temperature changes or other indirect indicators.
With respect to the related art in the above, there are the following drawbacks: the loss of the power filter is judged by detecting the temperature change, and the power filter is influenced by the temperature of the detection environment and the temperature rising effect, so that the detection accuracy is low, and the loss test accuracy of the power filter is reduced, and therefore, the improvement is needed.
Disclosure of Invention
In order to improve the loss detection accuracy of a power filter, the application provides a loss test method, a loss test system, loss test equipment and a loss test medium of the power filter.
The first object of the present application is achieved by the following technical solutions:
A loss test method of a power filter comprises the following steps:
Acquiring actual values of an input voltage Vi, an output voltage Vo and an output current Io of a power filter;
the loss of the power filter is calculated according to the actual value, and the formula is used: loss p_loss= (Vi-Vo) ×io;
Based on the known loss value as reference data, a loss compensation model and a curve are established, wherein the model and the curve relate the input voltage Vi, the output voltage Vo and the output current Io with the actual loss value;
calculating a compensation value by using a loss compensation model and a curve according to the current input voltage Vi, the output voltage Vo and the output current Io;
the compensation value is applied to the measurement to eliminate errors and to obtain power filter losses.
By adopting the technical scheme, the high-precision detection of the loss of the power filter can be realized by acquiring the current and voltage signals in the power filter and performing digital processing, and the numerical values of the current and the voltage can be accurately acquired by digital conversion and data processing, so that the loss of the power filter is more accurately calculated, and the high-precision loss test is realized; and the current and voltage data are comprehensively analyzed by utilizing a big data storage system and a data analysis technology, so that the loss detection accuracy of the power filter is improved.
The present application may be further configured in a preferred example to: in the step of establishing a loss compensation model and curve that correlates the input voltage Vi, the output voltage Vo, the output current Io with the actual loss value based on the known loss value as reference data, the method comprises the steps of:
Obtaining reference data of a plurality of known loss values to establish a loss compensation model and a loss compensation curve, wherein the reference data comprises loss values under different input voltages (Vi), output voltages (Vo) and output currents (Io);
the loss compensation model and curve are established using linear regression, polynomial fitting, or neural network algorithms.
By adopting the technical scheme, a loss compensation model or curve is established, the compensation of the loss of the power filter is more accurate, the accuracy and reliability of the detection result are improved, and the performance of the power filter is further optimized.
The present application may be further configured in a preferred example to: the step of obtaining reference data of a plurality of known loss values to establish a loss compensation model and a curve includes the following steps:
Acquiring current and voltage signals in a power filter, and performing analog-to-digital conversion on the acquired current and voltage signals to obtain digitized current and voltage data;
Storing the digitized current and voltage data into a preset big data storage model;
Extracting current and voltage data from the big data storage model;
Carrying out data preprocessing on the extracted current and voltage data;
extracting the frequency domain features, the time domain features and the statistical features of the current and voltage data;
a data correlation analysis is performed to analyze the correlation and correlation between the current and voltage data.
By adopting the technical scheme, the potential information in the data is deeply mined by storing a large amount of current and voltage data and applying the data preprocessing, feature extraction and data correlation analysis technology, and the features and modes of the loss of the power filter are found, so that the accuracy and reliability of loss detection are improved.
The present application may be further configured in a preferred example to: the step of applying the compensation value to the measurement result to eliminate the error and obtain the power filter loss includes the steps of:
Performing loss calculation, and calculating the loss of the power filter based on current and voltage data and a pre-established loss model;
generating a power filter loss detection report including statistical summaries of current and voltage data, alerts of abnormal conditions, loss calculations and recommended maintenance measures.
By adopting the technical scheme, the data statistics summary can provide an overview of the overall situation of the power filter, and a basis is provided for subsequent analysis and judgment; the warning of abnormal conditions can discover problems in time and take corresponding measures to avoid further damage or faults of the power filter.
The present application may be further configured in a preferred example to: after the step of applying the compensation value to the measurement result to eliminate the error and obtain the power filter loss, the steps of:
detecting abnormality of the current and voltage data, and detecting abnormal values and abnormal modes in the current and voltage data;
if the abnormal value or the abnormal mode exists, generating an abnormal condition warning report.
By adopting the technical scheme, the abnormal situation in the power filter is found in time, so that a worker can make and execute a maintenance plan according to the abnormal situation of the power filter.
The present application may be further configured in a preferred example to: in the step of generating a power filter loss detection report, the power filter loss detection report is presented in the form of a visual interface.
By adopting the technical scheme, the visual interface provides a visual, easy-to-understand and operation mode to display the information of the power filter loss, and an operator can adjust the display mode, select the interested parameter or time period, and perform operations such as amplifying, shrinking or deriving data so as to meet the specific requirements and analysis purposes of the operator through simple interactive operation.
The second object of the present application is achieved by the following technical solutions:
A loss test system of a power filter comprises a measurement module, a data calculation module, an error compensation module and a data calibration module,
The measuring module is used for detecting the actual values of the input voltage, the output voltage and the output current of the power filter in real time and transmitting detection data to the data calculating module;
the data calculation module is used for receiving the detection data and calculating the loss value of the power filter according to the detection data value;
the error compensation module is used for storing the loss value data of the power filter of the data calculation module, establishing a loss compensation model and a curve, and calculating a compensation value according to the current input voltage, the current output voltage and the current output current;
the data calibration module is used for applying the compensation value to the actual value measured by the measurement module so as to eliminate errors and enable the data calculation module to calculate more accurate power filter loss.
By adopting the technical scheme, the big data storage model can adopt a data compression and optimization technology, so that the storage space and the storage cost of current and voltage data are reduced. The storage occupation of the data can be effectively reduced by a compression algorithm and a data coding mode, and the data can be rapidly decompressed and restored during data extraction, so that the integrity and the accuracy of the data are ensured.
Preferably, the system further comprises a visual data module for displaying the power filter loss detection report and the abnormal condition warning report in the form of visual interfaces.
By adopting the technical scheme, the detection personnel can read the data conveniently, and the detection efficiency is improved.
The third object of the present application is achieved by the following technical solutions:
A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of a method for loss testing a power filter as described above when the computer program is executed.
The fourth object of the present application is achieved by the following technical solutions:
a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of a loss test method for a power filter described above.
In summary, the present application includes at least one of the following beneficial technical effects:
1. The high-precision detection of the loss of the power filter can be realized by acquiring current and voltage signals in the power filter and performing digital processing, and the numerical values of the current and the voltage can be accurately acquired through digital conversion and data processing, so that the loss of the power filter is more accurately calculated, and the high-precision loss test is realized; the current and voltage data are comprehensively analyzed by utilizing a big data storage system and a data analysis technology, so that the loss detection accuracy of the power filter is improved;
2. The loss compensation model or curve is established, so that the compensation of the loss of the power filter is more accurate, the accuracy and reliability of a detection result are improved, and the performance of the power filter is further optimized;
3. By storing a large amount of current and voltage data and applying data preprocessing, feature extraction and data association analysis technologies, potential information in the data is deeply mined, and the features and modes of loss of the power filter are found, so that the accuracy and reliability of loss detection are improved.
Drawings
Fig. 1 is a schematic flow chart of a loss testing method of a power filter according to an embodiment of the application;
Fig. 2 is a schematic flow chart of step S30 in a loss testing method of a power filter according to an embodiment of the application;
Fig. 3 is a schematic flow chart in step S301 in a loss testing method of a power filter according to an embodiment of the present application;
Fig. 4 is a schematic flow chart after step S50 in a loss testing method of a power filter according to an embodiment of the application;
FIG. 5 is a schematic block diagram of a loss testing system for a power filter according to an embodiment of the present application;
Fig. 6 is a schematic diagram of an internal structure of a computer device.
Reference numerals illustrate:
1. a measurement module; 2. a data calculation module; 3. an error compensation module; 4. a data calibration module; 5. and a visual data module.
Detailed Description
The present application will be described in further detail with reference to the accompanying drawings.
In the embodiment, as shown in fig. 1-5, the application discloses a loss testing method of a power filter, which specifically comprises the following steps:
s10: acquiring actual values of an input voltage Vi, an output voltage Vo and an output current Io of a power filter;
Specifically, compared with the traditional method that the loss of the power filter is judged by measuring the temperature change, the method directly measures the actual values of the input voltage Vi, the output voltage Vo and the output current Io, reduces the measurement error caused by environmental factors, and improves the loss detection accuracy of the power filter.
S20: the loss of the power filter is calculated according to the actual value, and the formula is used: loss p_loss= (Vi-Vo) ×io;
specifically, the loss P_loss is calculated according to the measured actual value, so that the loss value of the power supply filter is directly calculated, and compared with the loss data obtained through indirect measurement, the loss data of the scheme is more accurate.
S30: based on the known loss value as reference data, a loss compensation model and a curve are established, wherein the model and the curve relate the input voltage Vi, the output voltage Vo and the output current Io with the actual loss value;
S40: calculating a compensation value by using a loss compensation model and a curve according to the current input voltage Vi, the output voltage Vo and the output current Io;
s50: applying the compensation value to the measurement result to eliminate errors and obtain power filter loss;
Specifically, by acquiring current and voltage signals in the power filter and performing digital processing, high-precision detection of the loss of the power filter can be realized, and numerical values of the current and the voltage can be accurately acquired through digital conversion and data processing, so that the loss of the power filter is more accurately calculated, and high-precision loss test is realized; and the data analysis technology related to loss supplement is utilized to comprehensively analyze the current and voltage data, so that the loss detection accuracy of the power filter is improved.
At S30: based on the known loss value as reference data, a loss compensation model and curve are established, and the step of correlating the input voltage Vi, the output voltage Vo and the output current Io with the actual loss value comprises the following steps:
S301, acquiring reference data of a plurality of known loss values to establish a loss compensation model and a loss compensation curve, wherein the reference data comprises loss values under different input voltages Vi, output voltages Vo and output currents Io;
Specifically, different input voltage Vi, output voltage Vo and output current Io are input, the sample capacity of data is increased, an algorithm is formed conveniently, and the compensation value is more accurate, so that the error value is reduced, and the loss detection accuracy of the power filter is improved.
S302: establishing the loss compensation model and the curve by using linear regression, polynomial fitting or a neural network algorithm;
Specifically, the loss compensation model or curve is built by adopting algorithms such as linear regression, polynomial fitting or neural network, and the algorithms can build a corresponding model or curve according to the actual values of the input voltage, the output voltage and the output current and loss value reference data corresponding to the actual values of the input voltage, the output voltage and the output current, so that the accurate compensation of the loss of the power filter is realized.
At S301: the step of obtaining reference data of a plurality of known loss values to establish a loss compensation model and a loss compensation curve comprises the following steps:
S3011: acquiring current and voltage signals in a power filter, and performing analog-to-digital conversion on the acquired current and voltage signals to obtain digitized current and voltage data;
s3012: storing the digitized current and voltage data into a preset big data storage model;
S3013: extracting current and voltage data from the big data storage model;
s3014: carrying out data preprocessing on the extracted current and voltage data;
specifically, the data preprocessing comprises removing noise, smoothing data and interpolating data, and the method of data preprocessing is added to reduce data errors caused by data noise; the data preprocessing can remove abnormal values, noise and interference in the current and voltage data, and improve the quality and accuracy of the data. Noise and outliers in the data can be removed by applying filters, smoothing algorithms or outlier detection methods, so that subsequent data analysis and modeling are more reliable.
S3015: extracting the frequency domain features, the time domain features and the statistical features of the current and voltage data;
s3016: a data correlation analysis is performed to analyze the correlation and correlation between the current and voltage data.
At S50: after the step of applying the compensation value to the measurement result to eliminate the error and obtain the power filter loss, the steps include:
S501: performing loss calculation, and calculating the loss of the power filter based on current and voltage data and a pre-established loss model;
Specifically, the loss compensation model or curve is dynamically adjusted based on historical loss data and environmental parameters so as to realize real-time compensation of the loss of the power filter; the compensation value is adaptively adjusted according to the working state and the load characteristic of the power filter so as to provide more accurate loss compensation; the compensation value is compensated and adjusted according to the temperature change of the power filter, so that the influence of temperature on loss is considered, and the accuracy of loss measurement is improved; the compensation value is compensated and adjusted according to the service life of the power filter so as to consider the loss change of the filter along with time, and more reliable loss compensation value is provided to be compensated and adjusted according to the frequency response characteristic of the power filter so as to consider the loss change of the filter under different frequencies and optimize the performance of the filter.
S502: generating a power filter loss detection report including a statistical summary of current and voltage data, loss calculation results, and recommended maintenance measures;
s503: detecting abnormality of the current and voltage data, and detecting abnormal values and abnormal modes in the current and voltage data;
By carrying out statistical analysis on the current and voltage data, key statistical indexes such as average value, standard deviation, maximum value, minimum value and the like can be extracted, so that the working state and performance of the power filter can be known. The data statistics summary can provide an overview of the overall situation of the power filter, and provides a basis for subsequent analysis and judgment; abnormal condition warning: by performing abnormality detection and analysis on the current and voltage data, abnormal conditions such as current fluctuation, voltage deviation, and the like, which exist in the power supply filter, can be found. The warning of abnormal conditions can timely find problems and take corresponding measures to avoid further damage or failure of the power filter; loss calculation result: based on the current and voltage data, the loss condition of the power filter can be calculated. Loss calculation the energy loss in the power supply filter can be estimated by the relation between current and voltage. The loss calculation result can provide the evaluation of the efficiency and the performance of the power filter, and provides basis for subsequent maintenance and improvement; suggested maintenance measures: based on the loss calculation result and the analysis of the abnormal situation, maintenance suggestions and improvement measures for the power filter can be given; these suggestions may include periodic cleaning, replacement of damaged components, adjustment of operating parameters, etc., to improve the efficiency and extend the life of the power filter; the advice of the maintenance measures can help the user to take corresponding actions, maintaining a good working state of the power filter.
S504: if the abnormal value or the abnormal mode exists, generating an abnormal condition warning report.
The power filter loss detection report and the abnormal condition warning report are displayed in a visual interface mode, and specifically, real-time monitoring and feedback are carried out: the visual interface can display the loss condition of the power filter in real time, so that operators can monitor and know the performance state of the filter in time. Through visual charts, graphs or indicators, operators can quickly obtain information about wear levels, trends and anomalies;
Visual analysis and comparison: the visual interface may provide analysis and comparison of losses over different time periods, different filters, or different operating conditions. Through the graphs, the trend graphs or the comparison graphs, operators can intuitively know the loss changes under different conditions, and identify potential problems or optimization opportunities;
Fault diagnosis and early warning: the visual interface can help operators to diagnose and early warn faults through graphical representation of losses. Abnormal loss trend or mutation points can be intuitively displayed on a visual interface, so that operators can be reminded of possible faults or abnormal conditions, and accordingly measures can be timely taken for maintenance or adjustment;
Data recording and history analysis: the visual interface may record and present historical data of power filter loss for subsequent analysis and comparison. Through the visual interface, operators can check the past loss trend and change, identify the problem of long-term performance change or periodicity, and carry out corresponding improvement and optimization;
User-friendliness and ease of operation: the visual interface provides an intuitive, easy to understand and operate way to reveal information about the power filter loss. The operator can adjust the display mode, select the interested parameter or time period through simple interactive operation, and perform operations such as amplifying, shrinking or deriving data so as to meet the specific requirements and analysis purposes.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present application.
In an embodiment, a power filter loss test system is provided, where the power filter loss test system corresponds to one of the power filter loss test methods in the above embodiment. As shown in fig. 5, the loss test system of the power filter comprises a measurement module 1, a data calculation module 2, an error compensation module 3, a data calibration module 4 and a visual data module 5,
The measuring module 1 is used for detecting the actual values of the input voltage, the output voltage and the output current of the power filter in real time and transmitting detection data to the data calculating module 2;
the data calculation module 2 is used for receiving detection data and calculating a power filter loss value according to the detection data value;
The error compensation module 3 is used for storing the loss value data of the power filter of the data calculation module 2, establishing a loss compensation model and a curve, and calculating a compensation value according to the current input voltage, output voltage and output current;
The data calibration module 4 is configured to apply a compensation value to the actual value measured by the measurement module 1, so as to eliminate errors and enable the data calculation module 2 to calculate a more accurate power filter loss;
And the visual data module 5 is used for displaying the power filter loss detection report and the abnormal condition warning report in a visual interface mode.
The big data storage model can adopt data compression and optimization technology to reduce the storage space and the storage cost of current and voltage data. Through a compression algorithm and a data coding mode, the storage occupation of data can be effectively reduced, and rapid decompression and recovery are performed during data extraction, so that the integrity and accuracy of the data are ensured, and a visual data module 5 enables a detector to conveniently read the data, so that the detection efficiency is improved
For a specific limitation of the loss test system of a power filter, reference may be made to the limitation of the loss test method of a power filter hereinabove, and the description thereof will not be repeated here. Each of the modules in the loss test system of the power filter can be implemented in whole or in part by software, hardware, and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 6. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The computer program when executed by a processor implements a method for loss testing of a power filter.
In one embodiment, a computer device is provided comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of when executing the computer program:
in one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.
The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (8)
1. The loss test method of the power filter is characterized by comprising the following steps of: acquiring actual values of an input voltage Vi, an output voltage Vo and an output current Io of a power filter;
calculating the loss of the power filter according to the actual value, wherein the loss calculation formula is P_loss= (Vi-Vo) ×Io;
Using the known loss value as reference data, establishing a loss compensation model and a loss compensation curve, wherein the loss compensation model and the loss compensation curve relate the input voltage Vi, the output voltage Vo and the output current Io with the actual loss value;
calculating a compensation value by using a loss compensation model and a curve according to the current input voltage Vi, the output voltage Vo and the output current Io;
Applying the compensation value to the measurement result to eliminate errors and obtain power filter loss;
The step of establishing a loss compensation model and curve, which relate the input voltage Vi, the output voltage Vo, and the output current Io to actual loss values, using the known loss values as reference data, includes: acquiring reference data of a plurality of known loss values to establish a loss compensation model and a loss compensation curve, wherein the reference data comprises loss values under different input voltages Vi, output voltages Vo and output currents Io;
Establishing the loss compensation model and the curve by using linear regression, polynomial fitting or a neural network algorithm;
The step of obtaining reference data of a plurality of known loss values to establish a loss compensation model and curve includes: acquiring current and voltage signals in a power filter, and performing analog-to-digital conversion on the acquired current and voltage signals to obtain digitized current and voltage data;
Storing the digitized current and voltage data into a preset big data storage model;
Extracting current and voltage data from the big data storage model;
Carrying out data preprocessing on the extracted current and voltage data;
extracting the frequency domain features, the time domain features and the statistical features of the current and voltage data;
performing a data correlation analysis to analyze the correlation and correlation between the current and voltage data;
In the step of applying the compensation value to the measurement result to eliminate the error and obtain the power filter loss, it includes: the loss of the power filter is calculated based on the current and voltage data and a pre-established loss compensation model, wherein the loss compensation model and curve are dynamically adjusted based on historical loss data and environmental parameters.
2. The method for testing the loss of the power filter according to claim 1, wherein: in the step of applying the compensation value to the measurement result to eliminate the error and obtain the power filter loss, further comprising:
generating a power filter loss detection report including statistical summaries of current and voltage data, alerts of abnormal conditions, loss calculations and recommended maintenance measures.
3. The method for testing the loss of the power filter according to claim 2, wherein: after the step of applying the compensation value to the measurement result to eliminate the error and obtain the power filter loss, it further comprises:
detecting abnormality of the current and voltage data, and detecting abnormal values and abnormal modes in the current and voltage data;
if the abnormal value or the abnormal mode exists, generating an abnormal condition warning report.
4. A loss testing method for a power filter according to claim 3, wherein: in the step of generating a power filter loss detection report, the power filter loss detection report is presented in the form of a visual interface.
5. A loss testing system for a power filter, applied to the loss testing method for a power filter according to any one of claims 1 to 4, characterized in that: comprises a measuring module (1), a data calculating module (2), an error compensating module (3) and a data calibrating module (4),
The measuring module (1) is used for detecting the actual values of the input voltage, the output voltage and the output current of the power filter in real time and transmitting detection data to the data calculating module (2);
the data calculation module (2) is used for receiving detection data and calculating a power filter loss value according to the detection data value;
The error compensation module (3) is used for storing the power filter loss value data obtained by calculation of the data calculation module (2) and establishing a loss compensation model and a curve;
The data calibration module (4) is used for applying the compensation value to the actual value measured by the measurement module (1) so as to eliminate errors and enable the data calculation module (2) to calculate the compensated power filter loss.
6. The loss testing system of a power filter of claim 5, wherein: the system also comprises a visual data module (5) which is used for displaying the power filter loss detection report and the abnormal condition warning report in the form of a visual interface.
7. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements the steps of a method for wear testing a power filter according to any one of claims 1 to 4.
8. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of a loss testing method of a power supply filter according to any one of claims 1 to 4.
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