CN111931636A - Filter device inhibition evaluation method based on signal characteristic calculation - Google Patents
Filter device inhibition evaluation method based on signal characteristic calculation Download PDFInfo
- Publication number
- CN111931636A CN111931636A CN202010786882.4A CN202010786882A CN111931636A CN 111931636 A CN111931636 A CN 111931636A CN 202010786882 A CN202010786882 A CN 202010786882A CN 111931636 A CN111931636 A CN 111931636A
- Authority
- CN
- China
- Prior art keywords
- signal
- input signal
- coef
- filter
- calculation formula
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
- G06F2218/04—Denoising
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/08—Feature extraction
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Signal Processing (AREA)
- General Engineering & Computer Science (AREA)
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
Abstract
The embodiment of the invention discloses a filter inhibition evaluation method based on signal characteristic calculation, which relates to the technical field of signal testing and comprises the following steps: acquiring an input signal to be evaluated and a distortion signal generated after the input signal passes through a filter; respectively calculating the maximum value, the minimum value, the signal energy and the trend correlation of the waveforms of the input signal and the distorted signal in a time domain range; forming a disturbance similarity calculation formula based on the ratio of the maximum value, the minimum value, the signal energy and the trend correlation of the input signal and the distorted signal; and evaluating the inhibition effect of the filter device based on a calculation result obtained by the disturbance similarity calculation formula. By the scheme of the embodiment of the invention, the inhibition effect of the filter device can be evaluated in a quantitative mode.
Description
Technical Field
The invention relates to the technical field of signal testing, in particular to a filter inhibition evaluation method based on signal characteristic calculation.
Background
The current national standard GB/T7343-2017 'method for measuring the suppression characteristics of a passive EMC filter device' specifies a method for measuring the insertion loss, the impedance and the S parameter of the passive filter device, the above 3 parameters are all tested in a frequency domain, the measurement methods are similar, the suppression characteristics of the filter device in a certain frequency band can be evaluated, but the suppression effect of the filter device on time domain disturbance signals cannot be directly and effectively obtained.
The standard test method is to use a calibrated 50 Ω signal generator and a 50 Ω receiver, and the insertion loss is given by:
ae＝20log(V0/2V2)
aefor insertion loss, in decibels (is dB)
V0Is the open circuit voltage of a 50 omega signal generator with the unit of volt (V)
V2Is the output voltage of the filter device with the unit of volt (V)
The insertion loss test block diagram is shown in fig. 2, where G is a signal source, FI is a filter, and R is a receiver. When no bias current exists, the applicable frequency range is 10 kHz-10 GHz; when bias current exists (the bias current can reach 100A), the frequency range of 10 kHz-100 MHz can be applied.
Along with the development of science and technology, electronic equipment integrates, the modularization degree is higher and higher, the influence of more complicated electromagnetic environment effect that faces, each type signal cable port is facing the invasion of complicated electromagnetic environment interference signal, and the filter has become one of the necessary key device of equipment, and the suppression evaluation of filter also receives more and more attention from the user.
In the existing standard GB/T7343-2017 "method for measuring rejection characteristics of passive EMC filter device", it is mentioned that because the termination impedance in the measurement process is different from the termination impedance in the actual device or system, the characteristics obtained by the standard insertion loss unbiased measurement method may be different from the actual characteristics, and for the challenges faced by the current passive filter device, the following technical problems need to be solved:
1. in the product design stage, due to the fact that no quantized filter component inhibition index exists, in many cases, an equipment manufacturer can only select a plurality of proper filter components according to the insertion loss or cut-off frequency of the filter component, and then the inhibition effect of the filter component on the sensitive time domain disturbance signals is investigated through actual tests in a laboratory, so that the design cost and the time cost of the equipment manufacturer can be increased;
2. in the product shaping stage, the individual difference of the suppression characteristics of the filter devices in mass purchasing of the filter devices is not easy to find, so that the unqualified phenomenon occurs when the electromagnetic immunity test is performed on the sampled products;
3. parameters of the passive filter specified by the standard comprise insertion loss, impedance and S parameters which are frequency domain parameters, and when a time domain disturbance signal is faced, the suppression effect evaluation of the filter cannot be directly given by using the parameters.
Disclosure of Invention
In view of the above, embodiments of the present invention provide a method for evaluating suppression of a filter device based on signal feature calculation, which at least partially solves the problems in the prior art.
The embodiment of the invention provides a filter device inhibition evaluating method based on signal characteristic calculation
A method, comprising:
acquiring an input signal to be evaluated and a distortion signal generated after the input signal passes through a filter;
respectively calculating the maximum value, the minimum value, the signal energy and the trend correlation of the waveforms of the input signal and the distorted signal in a time domain range;
forming a disturbance similarity calculation formula based on the ratio of the maximum value, the minimum value, the signal energy and the trend correlation of the input signal and the distorted signal;
and evaluating the inhibition effect of the filter device based on a calculation result obtained by the disturbance similarity calculation formula.
According to a specific implementation manner of the embodiment of the present disclosure, forming a disturbance similarity calculation formula based on a ratio of the input signal to the distorted signal in a maximum value, a minimum value, a signal energy, and a trend correlation includes:
the ratio of the distorted signal output by the filter to the signal energy of the input signal is recorded as Scoef；
Setting a first weight value N for the ratio of the signal energy of the distorted signal to the input signal0；
Will N0*ScoefAs a first calculation parameter of the similarity calculation formula.
According to a specific implementation manner of the embodiment of the present disclosure, the forming a harassment similarity calculation formula based on a ratio of the maximum value, the minimum value, the signal energy and the trend correlation of the input signal and the distorted signal further includes:
the maximum ratio of the malformed signal output by the filter to the input signal is recorded as MAXcoef；
Setting a second weight value N for the maximum ratio of the distortion signal to the input signal1；
Will N1*MAXcoefAs a second calculation parameter of the similarity calculation formula.
According to a specific implementation manner of the embodiment of the present disclosure, the forming a harassment similarity calculation formula based on a ratio of the maximum value, the minimum value, the signal energy and the trend correlation of the input signal and the distorted signal further includes:
the minimum ratio of the abnormal signal output by the filter to the input signal is recorded as MINcoef；
Setting a third weight value N for the minimum ratio of the distortion signal to the input signal2；
Will N2*MINcoefAs a third calculation parameter of the similarity calculation formula.
According to a specific implementation manner of the embodiment of the present disclosure, the forming a harassment similarity calculation formula based on a ratio of the maximum value, the minimum value, the signal energy and the trend correlation of the input signal and the distorted signal further includes:
the trend correlation between the abnormal signal output by the filter and the input signal is denoted as Ccoef；
Setting a fourth weight value N for the trend correlation3；
Will N3*CcoefIs used as a fourth calculation parameter of the similarity calculation formula.
According to a specific implementation manner of the embodiment of the present disclosure, the forming a harassment similarity calculation formula based on a ratio of the maximum value, the minimum value, the signal energy and the trend correlation of the input signal and the distorted signal further includes:
is N0*Scoef+N1*MAXcoef+N2*MINcoef+N3*CcoefThe sum of (A) and (B) sets the magnification factor F, will (N)0*Scoef+N1*MAXcoef+N2*MINcoef+N3*Ccoef) The value of F is used as the final DS value of the similarity calculation formula.
According to a specific implementation manner of the embodiment of the present disclosure, the evaluating the suppression effect of the filter device based on the calculation result obtained by the disturbance similarity calculation formula includes:
judging whether the DS value is larger than a preset threshold value or not;
and if so, determining that the inhibition effect of the filter device meets the requirement.
According to a specific implementation of the embodiments of the present disclosure, the input signal is generated by a signal generator.
According to a specific implementation manner of the embodiment of the present disclosure, the input signal is a current waveform signal or a voltage waveform signal.
According to a specific implementation manner of the embodiment of the disclosure, when the input signal is a voltage waveform, the load is adjusted randomly to be consistent with the actual installation of the filter device, and the final filter suppression effect evaluation reflects the filter suppression effect of the filter device in the actual installation environment.
The invention provides a filter inhibition evaluation method based on signal characteristic calculation, which comprises the steps of obtaining an input signal to be evaluated and a distortion signal generated after the input signal passes through a filter; respectively calculating the maximum value, the minimum value, the signal energy and the trend correlation of the waveforms of the input signal and the distorted signal in a time domain range; forming a disturbance similarity calculation formula based on the ratio of the maximum value, the minimum value, the signal energy and the trend correlation of the input signal and the distorted signal; and evaluating the inhibition effect of the filter device based on a calculation result obtained by the disturbance similarity calculation formula. Compared with the prior art, the scheme of the application quantizes the characteristic value of the time domain disturbance signal and summarizes the characteristic value into the filter inhibition evaluation parameter; the disturbance similarity test system provides a method for measuring in a time domain aiming at a time domain disturbance signal, and is different from a frequency domain parameter measuring method induced in the existing standard; when the disturbance signal is a voltage waveform, the load can be adjusted at will to be consistent with the actual installation of the filter device, and the final filter suppression effect evaluation can reflect the filter suppression effect of the filter device in the actual installation environment, but the existing standard measurement method can only meet a 50 omega test system, cannot be consistent with the actual installation environment of the filter device, and cannot evaluate the actual filter suppression effect;
compared with the existing standard test method, the scheme has the following advantages:
1. quantitative evaluation of time domain disturbance signal inhibition effect of filter device
By replacing a receiver or a network analyzer in the existing standard with an oscilloscope, the conversion of disturbance signals between a time domain and a frequency domain is avoided, the characteristics of the time domain disturbance signals can be intuitively and efficiently obtained, parameters are provided for the suppression of the time domain signals by the quantized filter device, and the quantitative evaluation of the suppression of the time domain disturbance signals by the filter device is realized.
2. The simulation of the actual installation environment of the filter device can evaluate the real filter inhibition
Under most circumstances, the time domain disturbance signal is the voltage waveform, and the load size can be adjusted wantonly under this circumstances and make it unanimous with the filter device actual erection, and the filter suppression effect evaluation can reflect the filter suppression effect of filter device under the actual installation environment finally, provides true and reliable selection basis for the chooseing for use of follow-up filter device to save the process of verifying test repeatedly in the experiment installation environment, reduce time cost and experimental cost for the user.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic diagram of a filter suppression evaluation method based on signal characteristic calculation according to an embodiment of the present invention;
FIG. 2 is a block diagram of a test circuit for insertion loss measurement without bias according to an embodiment of the present invention;
FIG. 3 is a time domain signal waveform diagram according to an embodiment of the present invention;
fig. 4a-4b are schematic diagrams of a test system according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, 3 and 4a and 4b, the present invention provides a set of filtering based on signal feature calculation
A device inhibition evaluation method comprising the steps of:
s101, acquiring an input signal to be evaluated and a distortion signal generated after the input signal passes through a filter;
s102, respectively calculating the maximum value, the minimum value, the signal energy and the trend correlation of the waveforms of the input signal and the distorted signal in a time domain range;
s103, forming a disturbance similarity calculation formula based on the ratio of the input signal to the distortion signal in the maximum value, the minimum value, the signal energy and the trend correlation;
and S104, evaluating the inhibition effect of the filter device based on a calculation result obtained by the disturbance similarity calculation formula.
In the process of implementing steps S101 to S104, a disturbance test may be set, in the time domain disturbance test, after a disturbance signal (input signal) passes through the filter device, a waveform of the disturbance signal may generate "distortion", a magnitude of the "waveform distortion" determines an interference suppression capability of the filter device for interference, and a similarity between the distorted waveform and a standard interference waveform may evaluate the suppression capability of the filter device. The waveform after the distortion can directly influence the tested equipment connected behind the filter device, so the size of the disturbance similarity is directly related to the disturbance rejection capability of the tested equipment.
The requirements of the installation environment of the filter device for the suppression include: the energy, amplitude and signal intensity change rate of the input signal are regulated by related parameters, so that the factors which have the largest influence on the tested equipment by the time domain disturbance signal are divided into the energy of the disturbance signal, the maximum value and the minimum value of the disturbance signal and the trend correlation of the disturbance signal, and the ratio of the output waveform parameter of the filter device to the input standard waveform parameter is used as the 'disturbance similarity' by utilizing the three factors.
The signal energy and the maximum and minimum values of the time domain signals are easily obtained from the time domain waveforms, the harassing signal trend correlation utilizes the concept of cross correlation, and the cross correlation coefficient represents the correlation degree between two time sequences, namely the correlation degree between values of describing signals x (t) and y (t) at any two different moments t1 and t 2. In the signal analysis theory of basis, the mathematical expectation of the product of two random variables, called correlation, characterizes the degree of correlation between X, Y.
The ratio of the signal energy of the output signal of the filter device to the input standard signal is recorded as ScoefThe maximum ratio of the output signal of the filter to the input standard signal is recorded as MAXcoefThe minimum ratio of the output signal of the filter to the input standard signal is recorded as MINcoefThe correlation of the trend of the output signal of the filter device with the input standard signal is denoted as CcoefThen "disturbance similarity" DS:
DS＝(N0*Scoef+N1*MAXcoef+N2*MINcoef+N3*Ccoef)*F
wherein N is0、N1、N2、N3The weights of different 'harassment similarity' elements are respectively, and as the ratio is possibly too small, a magnification factor is set to be recorded as F, so that the DS values are convenient to compare.
When the capability of the passive filter device for resisting time domain disturbance signals is evaluated, the standard disturbance signals are input, the disturbance signal waveform output by the filter device is obtained, and then the DS value of the filter device is obtained. The larger the DS value is, the higher the similarity between the output signal of the filter device and the input standard signal is, and the poorer the filtering effect is, and the smaller the DS value is, the better the filtering effect of the filter device is. The evaluation means is not only visual and efficient, but also can evaluate and compare the filtering effects of different filtering devices on the same disturbance signal, and can evaluate the filtering effects of the same filtering device on different disturbance signals.
The signal generator preferably adopts a signal generator capable of generating a concerned time domain disturbance signal; the oscilloscope with the bandwidth of more than 500MHz is recommended to be adopted; when the time domain disturbance signal is a voltage waveform, the load can adopt the impedance of the actual installation environment of the filter device, and when the time domain disturbance signal is a current waveform, the load can adopt 50 omega.
In the process of testing, the testing system can be connected according to the modes of fig. 4a and 4b, but the filtering device is not connected, the signal generator generates a time domain disturbance signal meeting the requirements, and the oscilloscope collects a standard disturbance signal;
secondly, installing a filter device to be tested to a test system (the filter device is placed in a shielding metal box, the ground of the filter device is correctly connected to the ground of the metal box to ensure low-inductance grounding), generating a time domain disturbance signal by a signal generator, and collecting a signal at the output end of the filter device by an oscilloscope;
the method comprises the steps of carrying out weighted analysis according to actual installation environment requirements of the filter device, comparing characteristic parameters of signals at the output end of the filter device with characteristic parameters of standard disturbance signals, calculating disturbance similarity according to a formula, repeating the above test steps on different filter devices, and carrying out quantitative comparison on different disturbance similarities.
According to a specific implementation manner of the embodiment of the present disclosure, forming a disturbance similarity calculation formula based on a ratio of the input signal to the distorted signal in a maximum value, a minimum value, a signal energy, and a trend correlation includes:
the ratio of the distorted signal output by the filter to the signal energy of the input signal is recorded as Scoef；
Setting a first weight value N for the ratio of the signal energy of the distorted signal to the input signal0；
Will N0*ScoefAs a first calculation parameter of the similarity calculation formula.
According to a specific implementation manner of the embodiment of the present disclosure, the forming a harassment similarity calculation formula based on a ratio of the maximum value, the minimum value, the signal energy and the trend correlation of the input signal and the distorted signal further includes:
the maximum ratio of the malformed signal output by the filter to the input signal is recorded as MAXcoef；
Setting a second weight value N for the maximum ratio of the distortion signal to the input signal1；
Will N1*MAXcoefAs a second calculation parameter of the similarity calculation formula.
According to a specific implementation manner of the embodiment of the present disclosure, the forming a harassment similarity calculation formula based on a ratio of the maximum value, the minimum value, the signal energy and the trend correlation of the input signal and the distorted signal further includes:
the minimum ratio of the abnormal signal output by the filter to the input signal is recorded as MINcoef；
Setting a third weight value N for the minimum ratio of the distortion signal to the input signal2；
Will N2*MINcoefAs a third calculation parameter of the similarity calculation formula.
According to a specific implementation manner of the embodiment of the present disclosure, the forming a harassment similarity calculation formula based on a ratio of the maximum value, the minimum value, the signal energy and the trend correlation of the input signal and the distorted signal further includes:
the trend correlation between the abnormal signal output by the filter and the input signal is denoted as Ccoef；
Setting a fourth weight value N for the trend correlation3；
Will N3*CcoefIs used as a fourth calculation parameter of the similarity calculation formula.
According to a specific implementation manner of the embodiment of the present disclosure, the forming a harassment similarity calculation formula based on a ratio of the maximum value, the minimum value, the signal energy and the trend correlation of the input signal and the distorted signal further includes:
is N0*Scoef+N1*MAXcoef+N2*MINcoef+N3*CcoefThe sum of (A) and (B) sets the magnification factor F, will (N)0*Scoef+N1*MAXcoef+N2*MINcoef+N3*Ccoef) The value of F is used as the final DS value of the similarity calculation formula.
According to a specific implementation manner of the embodiment of the present disclosure, the evaluating the suppression effect of the filter device based on the calculation result obtained by the disturbance similarity calculation formula includes:
judging whether the DS value is larger than a preset threshold value or not;
and if so, determining that the inhibition effect of the filter device meets the requirement.
According to a specific implementation of the embodiments of the present disclosure, the input signal is generated by a signal generator.
According to a specific implementation manner of the embodiment of the present disclosure, the input signal is a current waveform signal or a voltage waveform signal.
According to a specific implementation manner of the embodiment of the disclosure, when the input signal is a voltage waveform, the load is adjusted randomly to be consistent with the actual installation of the filter device, and the final filter suppression effect evaluation reflects the filter suppression effect of the filter device in the actual installation environment.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments.
In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof.
In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A filter inhibition evaluation method based on signal characteristic calculation is characterized by comprising the following steps:
acquiring an input signal to be evaluated and a distortion signal generated after the input signal passes through a filter;
respectively calculating the maximum value, the minimum value, the signal energy and the trend correlation of the waveforms of the input signal and the distorted signal in a time domain range;
forming a Disturbance Similarity (DS) calculation formula based on the ratio of the input signal to the distorted signal in the maximum value, the minimum value, the signal energy and the trend correlation;
and evaluating the inhibition effect of the filter device based on a calculation result obtained by the disturbance similarity calculation formula.
2. The method of claim 1, wherein forming a disturbance similarity calculation formula based on a ratio of the input signal and the distorted signal in a maximum, a minimum, a signal energy, and a trend correlation comprises:
the ratio of the distorted signal output by the filter to the signal energy of the input signal is recorded as Scoef；
Setting a first weight value N for the ratio of the signal energy of the distorted signal to the input signal0；
Will N0*ScoefAs a first calculation parameter of the similarity calculation formula.
3. The method of claim 2, wherein forming a disturbance similarity calculation formula based on a ratio of the maximum value, the minimum value, the signal energy, and the trend correlation of the input signal and the distorted signal further comprises:
the maximum ratio of the malformed signal output by the filter to the input signal is recorded as MAXcoef；
Setting a second weight value N for the maximum ratio of the distortion signal to the input signal1；
Will N1*MAXcoefAs a second calculation parameter of the similarity calculation formula.
4. The method of claim 3, wherein forming a disturbance similarity calculation formula based on a ratio of the maximum, minimum, signal energy, and trend correlation of the input signal and the distorted signal further comprises:
the minimum ratio of the abnormal signal output by the filter to the input signal is recorded as MINcoef；
Setting a third weight value N for the minimum ratio of the distortion signal to the input signal2；
Will N2*MINcoefAs a third calculation parameter of the similarity calculation formula.
5. The method of claim 4, wherein forming a disturbance similarity calculation formula based on a ratio of the maximum value, the minimum value, the signal energy, and the trend correlation of the input signal and the distorted signal further comprises:
the trend correlation between the abnormal signal output by the filter and the input signal is denoted as Ccoef；
Setting a fourth weight value N for the trend correlation3；
Will N3*CcoefIs used as a fourth calculation parameter of the similarity calculation formula.
6. The method of claim 1, wherein forming a disturbance similarity calculation formula based on a ratio of the maximum, minimum, signal energy, and trend correlation of the input signal and the distorted signal further comprises:
is N0*Scoef+N1*MAXcoef+N2*MINcoef+N3*CcoefThe sum of (A) and (B) sets the magnification factor F, will (N)0*Scoef+N1*MAXcoef+N2*MINcoef+N3*Ccoef) The value of F is used as the final DS value of the similarity calculation formula.
7. The method as claimed in claim 6, wherein the evaluating the suppression effect of the filter device based on the calculation result obtained by the disturbance similarity calculation formula comprises:
judging whether the DS value is larger than a preset threshold value or not;
and if so, determining that the inhibition effect of the filter device meets the requirement.
8. The method of claim 1, wherein:
the input signal is generated by a signal generator.
9. The method of claim 1, wherein:
the input signal is a current waveform signal or a voltage waveform signal.
10. The method of claim 9, wherein:
when the input signal is a voltage waveform, the load is adjusted randomly to be consistent with the actual installation of the filter device, and finally the filter inhibition effect evaluation reflects the filter inhibition effect of the filter device in the actual installation environment.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010786882.4A CN111931636A (en) | 2020-08-07 | 2020-08-07 | Filter device inhibition evaluation method based on signal characteristic calculation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010786882.4A CN111931636A (en) | 2020-08-07 | 2020-08-07 | Filter device inhibition evaluation method based on signal characteristic calculation |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111931636A true CN111931636A (en) | 2020-11-13 |
Family
ID=73306918
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010786882.4A Pending CN111931636A (en) | 2020-08-07 | 2020-08-07 | Filter device inhibition evaluation method based on signal characteristic calculation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111931636A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117434426A (en) * | 2023-11-20 | 2024-01-23 | 芯火微测(成都)科技有限公司 | Test method, system and device of switched capacitor filter |
-
2020
- 2020-08-07 CN CN202010786882.4A patent/CN111931636A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117434426A (en) * | 2023-11-20 | 2024-01-23 | 芯火微测(成都)科技有限公司 | Test method, system and device of switched capacitor filter |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhang et al. | A novel wavelet transform technique for on-line partial discharge measurements. 1. WT de-noising algorithm | |
| Zhang et al. | A novel wavelet transform technique for on-line partial discharge measurements. 2. On-site noise rejection application | |
| US7139668B2 (en) | Wire event detection | |
| Contin et al. | Classification and separation of partial discharge signals by means of their auto-correlation function evaluation | |
| EP1477820A2 (en) | Wire fault detection | |
| EP2406643B1 (en) | Time domain electromagnetic interference monitoring method and system | |
| Yao et al. | Fast S-transform for time-varying voltage flicker analysis | |
| Azpúrua et al. | Improving time-domain EMI measurements through digital signal processing | |
| Franchet et al. | Soft fault detection in cables using the cluster time-frequency domain reflectometry | |
| Bajwa et al. | An investigation into partial discharge pulse extraction methods | |
| US7221167B2 (en) | Signal distortion measurement and assessment system and method | |
| Azpúrua et al. | On the statistical properties of the peak detection for time-domain EMI measurements | |
| CN111931636A (en) | Filter device inhibition evaluation method based on signal characteristic calculation | |
| Thirumala et al. | An improved adaptive filtering approach for power quality analysis of time-varying waveforms | |
| Carminati et al. | A neuro-fuzzy approach for the detection of partial discharge | |
| Cerri et al. | Theoretical and experimental evaluation of electromagnetic fields radiated by ESD | |
| Quizhpi-Cuesta et al. | Classification of partial discharge in pin type insulators using fingerprints and neural networks | |
| dos Santos et al. | Multi-resolution wavelet analysis for noise reduction in impulse puncture voltage measurements | |
| Yu et al. | A Fast Method for Predicting the Quasi-Peak Radiated EMI Spectrum of Power Converters | |
| Masugi | Multiresolution analysis of electrostatic discharge current from electromagnetic interference aspects | |
| CN112485616A (en) | Cable insulation aging detection method and device, storage medium and processor | |
| Mohammad et al. | Analysis on multiple acoustic and electrical emission of PD signal based on signal to noise ratio (SNR) on power cable | |
| Zhang et al. | Signal processing of on-line partial discharges measurements in HV power cables | |
| Wickert et al. | A method for representing non-standard waveform in factory tests using impulse waveforms | |
| Ambikairajah et al. | The modeling of partial discharge waveforms in power systems equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |