CN118501776B - Method and system for detecting connection state of electric connector - Google Patents
Method and system for detecting connection state of electric connector Download PDFInfo
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- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
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Abstract
The invention relates to the technical field of measuring electric variables, in particular to a method and a system for detecting the connection state of an electric connector. The method comprises the steps of obtaining a real-time current signal of an electric connector; obtaining each wave crest and each signal amplitude; obtaining a degradation coefficient according to each wave crest and each signal amplitude; acquiring a degradation characteristic factor and an abnormal strength factor according to the degradation coefficient and a preset degradation coefficient threshold; obtaining a self-adaptive intrinsic time scale according to the degradation characteristic factors, the abnormal intensity factors and the preset estimated intrinsic time scale; obtaining a signal anomaly coefficient of the current signal after removing noise according to the self-adaptive intrinsic time scale and the original current signal; and comparing the abnormal signal coefficient of the current signal after removing the noise with a preset judgment threshold value to obtain a detection result of the electric connector. The invention aims to solve the technical problem that the connection state of an electric connector is judged inaccurately due to the fact that the existing method cannot accurately distinguish a noise source from a real signal source.
Description
Technical Field
The invention relates to the technical field of measuring electric variables, in particular to a method and a system for detecting the connection state of an electric connector.
Background
In electronic devices, the connection state of the electrical connector is critical to the normal operation of the device, and an unstable connection state may cause problems such as data transmission errors and power supply, and even damage to the device. Therefore, it is important to monitor and detect the connection state of the electrical connector in real time.
At present, the traditional method for detecting the connection state of the electric connector is to analyze the connection state of the electric connector based on the current signal of the electric connector, wherein the current signal is easily influenced by factors such as electromagnetic interference, vibration, temperature change and the like in the external environment, so that more interference signal sources exist in the current signal, when the noise is removed, the noise source and the real signal source cannot be accurately distinguished by the existing method, the reconstructed current signal data loss is overlarge, and the connection state judgment of a system is inaccurate.
Disclosure of Invention
In order to solve the technical problems that the prior method cannot accurately distinguish a noise source from a real signal source, so that the reconstructed current signal data is excessively lost, and the connection state of an electric connector is not accurately judged, the invention aims to provide a method and a system for detecting the connection state of the electric connector, and the adopted technical scheme is as follows:
A method of electrical connector connection status detection, the method comprising:
Acquiring a real-time current signal of the electric connector;
performing signal processing on the real-time current signal to obtain each wave crest and each signal amplitude in a window area corresponding to each target sampling point in the real-time current signal;
Obtaining a degradation coefficient of each target sampling point according to each wave crest and each signal amplitude of a window area corresponding to each target sampling point in the real-time current signal;
according to the degradation coefficient of each target sampling point and a preset degradation coefficient threshold value, obtaining degradation characteristic factors of each degradation region and abnormal strength factors of local regions in the real-time current signals;
Obtaining an adaptive intrinsic time scale of each degradation degree region according to the degradation characteristic factors of each degradation degree region, the abnormal intensity factors of the local region in the real-time current signal and the preset estimated intrinsic time scale;
Obtaining signal anomaly coefficients of the current signals after noise removal according to the self-adaptive intrinsic time scale of each degradation degree region and the original current signals;
and comparing the abnormal signal coefficient of the current signal after removing the noise with a preset judgment threshold value to obtain a detection result of the electric connector.
Preferably, the specific step of obtaining the degradation coefficient of each target sampling point according to each peak and each signal amplitude of the window area corresponding to each target sampling point in the real-time current signal includes:
acquiring time differences between all two adjacent wave peaks according to each wave peak of a window area corresponding to each target sampling point in the real-time current signal;
And obtaining the degradation coefficient of each target sampling point according to the time differences between all two adjacent wave peaks and each signal amplitude.
Preferably, the specific step of obtaining the degradation coefficient of each target sampling point according to the time differences between all two adjacent peaks and each signal amplitude includes:
Averaging the time differences between all two adjacent wave peaks to obtain an average time interval of a window area corresponding to each target sampling point;
according to the amplitude of each signal, acquiring a current intensity weakening coefficient and a regional current mutation coefficient of a window region corresponding to each target sampling point;
And obtaining the degradation coefficient of each target sampling point according to the average time interval of the window area corresponding to each target sampling point, the current intensity weakening coefficient and the area current mutation coefficient of the window area corresponding to each target sampling point.
Preferably, the specific step of obtaining the degradation characteristic factor of each degradation degree region and the abnormal intensity factor of the local region in the real-time current signal according to the degradation degree coefficient of each target sampling point and the preset degradation degree coefficient threshold value includes:
Comparing the degradation coefficient of each target sampling point with a preset degradation coefficient threshold value to obtain all degradation regions;
Acquiring degradation characteristic factors of each degradation degree region according to the degradation degree coefficient of each target sampling point and all degradation degree regions;
and obtaining abnormal intensity factors of local areas in the real-time current signals according to all the degradation degree areas.
Preferably, the specific step of obtaining the adaptive intrinsic time scale of each degradation degree region according to the degradation characteristic factor of each degradation degree region, the abnormal intensity factor of the local region in the real-time current signal and the preset estimated intrinsic time scale includes:
And obtaining the self-adaptive intrinsic time scale of each degradation degree region by utilizing a self-adaptive intrinsic time scale adjusting formula according to the degradation characteristic factors of each degradation degree region, the abnormal intensity factors of the local region in the real-time current signal and the preset estimated intrinsic time scale.
Preferably, the specific step of obtaining the signal anomaly coefficient of the current signal after removing the noise according to the adaptive intrinsic time scale and the original current signal of each degradation degree region includes:
Acquiring a current signal after noise removal according to the self-adaptive intrinsic time scale and the original current signal of each degradation degree region;
And performing signal processing on the current signal after noise removal to obtain a signal anomaly coefficient of the current signal after noise removal.
Preferably, the specific step of obtaining the noise-removed current signal according to the adaptive intrinsic time scale and the original current signal of each degradation degree region includes:
multiplying the self-adaptive intrinsic time scale of each degradation degree region with the original current signal to obtain a product signal;
Performing Hilbert transform on the product signal to obtain the instantaneous frequency of an analysis signal;
And obtaining the current signal after noise removal according to the instantaneous frequency of the analysis signal and the adaptive intrinsic time scale of each degradation degree region.
Preferably, the specific step of obtaining the current signal after noise removal according to the instantaneous frequency of the analysis signal and the adaptive intrinsic time scale of each degradation degree region includes:
Decomposing the original current signal according to the instantaneous frequency of the analysis signal and the self-adaptive intrinsic time scale of each degradation degree region to obtain components of all eigen-mode functions;
And adding the components of all the eigen-mode functions to obtain a current signal after noise removal.
Preferably, the specific step of performing signal processing on the current signal after noise removal to obtain a signal anomaly coefficient of the current signal after noise removal includes:
Performing signal processing on the current signal after noise removal to obtain all wave crest positions and all signal amplitudes of the current signal after noise removal;
and obtaining the signal anomaly coefficient of the current signal after removing the noise according to all wave crest positions and all signal amplitudes of the current signal after removing the noise.
The invention also provides a system for detecting the connection state of the electric connector, which comprises:
the acquisition module is used for acquiring a real-time current signal of the electric connector by a user;
The signal processing module is used for carrying out signal processing on the real-time current signal to obtain each wave crest and each signal amplitude in a window area corresponding to each target sampling point in the real-time current signal;
the first acquisition module is used for acquiring a degradation coefficient of each target sampling point according to each peak and each signal amplitude of the window area corresponding to each target sampling point in the real-time current signal;
the second acquisition module is used for acquiring a degradation characteristic factor of each degradation degree region and an abnormal strength factor of a local region in the real-time current signal according to the degradation degree coefficient of each target sampling point and a preset degradation degree coefficient threshold value;
The third acquisition module is used for obtaining the self-adaptive intrinsic time scale of each degradation degree region according to the degradation characteristic factors of each degradation degree region, the abnormal intensity factors of the local region in the real-time current signal and the preset estimated intrinsic time scale;
the fourth acquisition module is used for obtaining a signal anomaly coefficient of the current signal after removing noise according to the self-adaptive intrinsic time scale of each degradation degree region and the original current signal;
And the detection module is used for comparing the abnormal signal coefficient of the current signal after removing the noise with a preset judgment threshold value to obtain a detection result of the electric connector.
The invention has the following beneficial effects:
After signal processing is carried out on an obtained real-time current signal of the electric connector, a degradation coefficient of each target sampling point is obtained according to each wave crest and each signal amplitude of a window area corresponding to each target sampling point in the real-time current signal; according to the degradation coefficient of each target sampling point and a preset degradation coefficient threshold value, obtaining degradation characteristic factors of each degradation region and abnormal strength factors of local regions in the real-time current signals; obtaining an adaptive intrinsic time scale of each degradation degree region according to degradation characteristic factors of each degradation degree region, abnormal intensity factors of local regions in the real-time current signals and preset estimated intrinsic time scales; obtaining signal anomaly coefficients of the current signals after noise removal according to the self-adaptive intrinsic time scale of each degradation degree region and the original current signals; and comparing the abnormal signal coefficient of the current signal after removing the noise with a preset judgment threshold value to obtain a detection result of the electric connector. When the electric connector is used, the real-time current signal is divided into degradation degree areas of different areas along with the increase of time, and the self-adaptive intrinsic time scale is further obtained, so that the noise signal is separated from the real-time current signal more accurately, and the connection state of the electric connector is judged more accurately.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for detecting a connection state of an electrical connector according to an embodiment of the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the present invention to achieve the preset purpose, the following detailed description refers to specific embodiments, structures, features and effects of an electrical connector connection state detection method according to the present invention with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following specifically describes a specific scheme of a method for detecting a connection state of an electrical connector according to the present invention with reference to the accompanying drawings.
The invention aims at the specific scene: in the conventional intrinsic time scale decomposition process, the baseline extraction operator uses the spacing between adjacent extremum points as an estimated intrinsic time scale and approximates the baseline of the signal by a cubic spline interpolation technique. The process can help to decompose the signals into different components so as to better understand the structure and characteristics of the signals, but as the working time increases in the current signals of the electric connector, the internal temperature rises, a large amount of noise signal frequencies can be gradually introduced into the current signals, when the signals are decomposed by using an unchanging intrinsic time scale in the traditional ITD decomposition method (inherent time scale signal decomposition algorithm), the separation effect is better when the initial noise is less in the use of the connector, but the resource waste is caused, and when the noise components are more in the later use of the connector, the noise signals and the real current signals cannot be accurately separated, so that the judgment of the system on the connection state of the connector is affected. Therefore, aiming at the problem that the noise source and the real signal source cannot be accurately distinguished in the traditional method, the reconstructed current signal data loss is overlarge, and the connection state of the electric connector is inaccurate to judge; the invention optimizes the current signal decomposition process based on analyzing the current signal generated under the abnormal state of the electric connector, so that the denoising is more accurate, the current signal of the electric connector is reserved to the maximum extent, and the signal distortion caused by excessive denoising is avoided.
Referring to fig. 1, a flowchart of a method for detecting a connection state of an electrical connector according to an embodiment of the present invention is shown, where the method includes:
S100, acquiring a real-time current signal of the electric connector. In this embodiment, the current sensor is correctly connected to the electrical connector to be detected, and a real-time current signal of the electrical connector is obtained. In particular, the current sensor uses a hall effect sensor.
And S200, performing signal processing on the real-time current signal to obtain each wave crest and each signal amplitude in a window area corresponding to each target sampling point in the real-time current signal.
S300, obtaining a degradation coefficient of each target sampling point according to each peak and each signal amplitude of the window area corresponding to each target sampling point in the real-time current signal.
S400, according to the degradation coefficient of each target sampling point and a preset degradation coefficient threshold value, obtaining degradation characteristic factors of each degradation region and abnormal intensity factors of local regions in the real-time current signals.
S500, obtaining the self-adaptive intrinsic time scale of each degradation degree region according to the degradation characteristic factors of each degradation degree region, the abnormal intensity factors of the local region in the real-time current signal and the preset estimated intrinsic time scale.
S600, obtaining signal anomaly coefficients of the current signals after noise removal according to the self-adaptive intrinsic time scales of each degradation degree region and the original current signals.
S700, comparing the abnormal signal coefficient of the current signal after removing the noise with a preset judgment threshold value to obtain a detection result of the electric connector.
After signal processing is carried out on an obtained real-time current signal of the electric connector, a degradation coefficient of each target sampling point is obtained according to each wave crest and each signal amplitude of a window area corresponding to each target sampling point in the real-time current signal; according to the degradation coefficient of each target sampling point and a preset degradation coefficient threshold value, obtaining degradation characteristic factors of each degradation region and abnormal strength factors of local regions in the real-time current signals; obtaining an adaptive intrinsic time scale of each degradation degree region according to degradation characteristic factors of each degradation degree region, abnormal intensity factors of local regions in the real-time current signals and preset estimated intrinsic time scales; obtaining signal anomaly coefficients of the current signals after noise removal according to the self-adaptive intrinsic time scale of each degradation degree region and the original current signals; and comparing the abnormal signal coefficient of the current signal after removing the noise with a preset judgment threshold value to obtain a detection result of the electric connector. When the electric connector is used, the real-time current signal is divided into degradation degree areas of different areas along with the increase of time, and the self-adaptive intrinsic time scale of each degradation degree area is further obtained, so that the noise signal is more accurately separated from the real-time current signal, and the connection state of the electric connector is more accurately judged.
The specific steps of S200 include: in general, as the working time of the electric connector increases during use, the temperature generated by the current passing through the internal resistor of the electric connector gradually accumulates, so that the temperature of the electric connector increases, the thermal noise (the thermal noise is caused by the thermal motion of components and parts, the frequency range of the thermal noise is generally proportional to the temperature) in the electric connector increases, and the frequency of the introduced additional noise signal increases; in addition, when the connection state of the electrical connector is abnormal, poor contact or reduced contact area is caused, the contact impedance (resistance between contact ends of the connector) affecting the electrical connector is changed, so that the current transmission is unstable, and additional noise signal frequency is also introduced. When the ITD signal decomposition algorithm is used for processing, a smaller time scale decomposition window is required to be set for the region with large frequency of the additional noise signal, so that the noise signal and the real current signal are accurately decomposed.
Specifically, when the electric connector just starts to work, the internal temperature can rise rapidly due to the resistance factor, the current intensity can drop due to the increase of the internal resistance, and when the electric connector is in an abnormal connection state, instability and fluctuation of a current signal can be caused; meanwhile, since the internal resistance of the electrical connector may exhibit different characteristics under temperature change at the initial stage of use, the current may decrease at a faster rate, and particularly when the temperature of the electrical connector increases at the initial stage of use, noise components in signals may be further increased due to the influence of thermal noise and abnormal connection states. Further, when the temperature increases to a certain value, an arc phenomenon occurs, which is caused by electrical breakdown or electric gap discharge between components in the electrical connector, and the arc causes a sudden increase of the current signal, introducing a large additional noise signal frequency for the original current signal. Therefore, the electrical connector current signal may increase with the increase of the service time, and the electrical connector current signal may be affected by more and more additional noise, thereby resulting in a change of signal quality, i.e. a change of degradation coefficient at different sampling points.
In this embodiment, the first 20 sampling points including each target sampling point in the real-time current signal are used as a window area. So that the characteristic of the signal of the window area is taken as the degradation coefficient of the target sampling point.
Specifically, the real-time current signal is signal-processed using a signal processing algorithm, such as an existing peak detection algorithm, to identify the peak position of the real-time current signal. And further identifying each peak in the window area corresponding to each target sampling point in the real-time current signal and each signal amplitude in the window area corresponding to each target sampling point in the real-time current signal.
The specific steps of S300 include: and acquiring the time difference between all two adjacent peaks according to each peak of the window area corresponding to each target sampling point in the real-time current signal. And obtaining the degradation coefficient of each target sampling point according to the time differences between all two adjacent wave peaks and each signal amplitude. Specifically, the time difference between all two adjacent wave peaks is subjected to average processing, so that the average time interval of the window area corresponding to each target sampling point is obtained. And acquiring a current intensity weakening coefficient and a regional current mutation coefficient of a window region corresponding to each target sampling point according to each signal amplitude. And obtaining the degradation coefficient of each target sampling point according to the average time interval of the window area corresponding to each target sampling point, the current intensity weakening coefficient and the area current mutation coefficient of the window area corresponding to each target sampling point.
In this embodiment, for each peak of the window area corresponding to each identified target sampling point, a time interval between two adjacent peaks in the area, that is, a time difference between two adjacent peaks, is calculated. The time difference of all adjacent wave peaks in the window area corresponding to each target sampling point is calculated to be an average value, and the average time interval of the wave peaks in the window area is regarded asThe smaller the value, the more the current signal in the corresponding window area is connected abnormally, such as poor contact, disconnection reconnection and the like, the current signal is suddenly broken and rebuilt, so that the time interval between adjacent wave crests is shortened, and the degradation degree of the target sampling point is increased.
Calculating the difference value of the signal amplitudes of two adjacent sampling points in the window area corresponding to each target sampling point, averaging the signal amplitude difference values of all two adjacent sampling points in each target window area, and regarding the average value as the current intensity weakening coefficient of the window areaThe larger the value is, the faster the current signal in the window area corresponding to the target sampling point is reduced, at the moment, the faster the temperature is increased, the faster the current is reduced, and the degradation degree of the target sampling point is smaller; conversely, a smaller value indicates that the electrical connector is relatively stable or has degraded more severely.
The degradation coefficient of each target sampling point is obtained by using the following degradation coefficient formula of the target sampling point of the current signal.
；
Wherein, Represents the firstDegradation coefficient of each target sampling point.Represents the first of the original current signalsThe number of target sampling points is set to be equal,Represents the firstThe target sample points correspond to the maximum value of the signal amplitude in the window area,Represents the firstThe target sample points correspond to the average value of the signal amplitudes in the window area,Represents the firstThe target sample points correspond to the entropy of the signal amplitude in the window region,Represents the firstEach target sample point corresponds to an adjacent peak average time interval in the window region,Represents the firstThe target sample points correspond to current intensity decay coefficients in the window region,Is an exponential function with a natural constant as a base, and is intended toRepresent the firstThe absolute value of the difference between the maximum value of the signal amplitude and the average value of the signal amplitude (namely the region current abrupt change coefficient) in the window region corresponding to the target sampling point is larger, which indicates the firstThe situation that the current signal is suddenly increased in the window area corresponding to the target sampling points often corresponds to the situation that the electric arc is generated in the local area of the electric connector, and then the current signal is suddenly increased; Represents the first The product of the information entropy of the signal amplitude in the window area corresponding to the target sampling point and the average time interval of the adjacent wave peaks of the signals in the corresponding window area (namely the signal anomaly coefficient in the real-time current signal), the larger the value is, the description is thatThe fluctuation disorder degree of the signal amplitude values in the window areas corresponding to the target sampling points is higher, and meanwhile, the abnormal condition that the time interval between adjacent wave crests is shortened due to sudden fracture and reconstruction of current signals caused by the abnormal connection of the electric connectors, such as poor contact, disconnection reconnection and the like exists.Represents the firstThe larger the sum of the signal abnormality coefficient and the current intensity weakening coefficient of the window area corresponding to the target sampling point is, the more serious the signal abnormality degree and the current intensity weakening degree of the window area corresponding to the ith target sampling point is. Indicating that there is a more serious abnormality or degradation of the electrical connector. At the same time, the method comprises the steps of,Represent the firstThe corresponding window area current mutation coefficients and the sum of the area signal abnormal coefficients and the current intensity weakening coefficients are corresponding to the target sampling points, the sum of the area signal abnormal coefficients and the current intensity weakening coefficients is corrected through the area current mutation coefficients, when the current mutation coefficients are larger, the corresponding connectors possibly generate electric arcs, the connectors possibly generate short circuits at any time, and the fact that a large amount of noise signals suddenly appear in the current signals of the connectors at the moment is meant to be in an overload state; the larger the integral value of the formula is, the description is thatA large amount of noise signals exist in the current signals of the window area corresponding to the target sampling points, and the degradation degree of the target sampling points is larger at the momentThe larger the value of (2).
The specific step of S400 includes comparing the degradation coefficient of each target sampling point with a preset degradation coefficient threshold value to obtain all degradation regions.
Specifically, according to the degradation coefficient of each target sampling point in the real-time current signal of the electric connector, the degradation coefficient difference degree of adjacent sampling points in the current signal is used as a similarity measure, and the degradation coefficient threshold value is preset based on experienceAnd marking adjacent sampling points with similarity measurement smaller than the threshold value as the same area, otherwise, marking the adjacent sampling points without marking, interrupting the area division, and performing iteration to restart the area division until all the adjacent sampling points with similarity measurement smaller than the threshold value are marked as the same area, and finally dividing the real-time current signal into a plurality of signal areas with different degradation degrees to obtain all degradation degree areas, wherein each degradation degree area represents a section of continuous signal with similar degradation degree.
And acquiring a degradation characteristic factor of each degradation degree region according to the degradation degree coefficient of each target sampling point and all degradation degree regions.
In this embodiment, the degradation characteristic factor of each degradation degree region is obtained by analyzing the signal characteristic expressions thereof based on the degradation degree coefficient of each target sampling point and all degradation degree regions.
Wherein the degradation characteristic factor of each degradation degree region is obtained using the degradation characteristic factor formula of the degradation degree region:
；
In the method, in the process of the invention, Representative of the first of the current signalsThe degree of degradation of the image is determined by the degree of degradation,Represents the firstThe total number of signal sample points in each degradation region is set,Representative ofThe first in the collectionThe number of signal sampling points is one,Represents the firstThe degradation coefficient of each signal sample point,Represents the firstDegradation characteristic factors of the individual degradation degree regions.Representing the first of the pair of current signalsThe degradation coefficients of all the signal points in each degradation region are weighted and averaged, and the larger the value is, the larger the degradation characteristic of the local region signal is, the larger the degradation characteristic isThe larger the value of (c), the smaller the intrinsic time scale is needed in the subsequent set ITD time scale decomposition.
In this embodiment, the abnormal intensity factor of the local area in the real-time current signal is obtained according to all the degradation degree areas.
Specifically, when there is a strong abnormal change in the real-time current signal, the noise abnormal signal may completely cover the real connector current signal, which affects the decomposition accuracy of the ITD signal in decomposition, so that a smaller time scale decomposition is required to decompose the local signal thereof into a shorter period of time, so as to capture the transient change and the local feature in the signal more accurately, and further accurately position the abnormal state signal, so that the subsequent analysis and processing are more accurate and effective.
The frequency domain of the degradation degree region current signal is obtained by fourier transforming all degradation degree regions in the current signal. Calculating the power spectral density of a corresponding region according to the frequency domain, and deriving the calculated power spectral density to obtain a power spectral density derivative; meanwhile, fitting the local current signals in each degradation degree region by using a homopolynomial to obtain a fitting function of the local signals, and calculating an autocorrelation coefficient of the fitting function.
Constructing a specific signal abnormal intensity factor formula:
；
In the method, in the process of the invention, Represents the firstThe autocorrelation coefficients of the individual degradation regions,An exponential function representing the base of the natural constant is intended toThe normalization is carried out so that the data of the data are obtained,Represents the firstThe power spectral density derivatives of the individual degradation regions,Represents the firstSignal anomaly intensity factors for each degradation degree region.Represent the firstThe product of the autocorrelation coefficient of each degradation degree region and the signal anomaly strength factor shows that the larger the value isThe current signal in the degradation degree region is represented as poor in signal continuity, and has a discontinuous condition, and meanwhile, the larger the change rate of the signal frequency is, the unstable connection state of the electric connector is correspondingly existed, so that the poor in signal continuity is caused, the larger the change rate of the signal frequency is caused, the larger the abnormal strength of the signal is,The larger the value of (2).
The specific step of S500 includes obtaining an adaptive intrinsic time scale of each degradation degree region by utilizing an adaptive intrinsic time scale adjustment formula according to the degradation characteristic factors of each degradation degree region, the abnormal intensity factors of the local regions in the real-time current signals and the preset estimated intrinsic time scale.
Specifically, the adaptive intrinsic time scale of each degradation degree region is obtained using the following adaptive intrinsic time scale adjustment formula.
；
In the method, in the process of the invention,Represents the firstSignal anomaly intensity factors for the individual degradation regions,Represents the firstDegradation characteristic factors of the individual degradation degree regions,Represents the firstThe degradation regions are obtained by using the estimated intrinsic time scale (i.e. the preset estimated intrinsic time scale) obtained by the conventional method,Represents the firstThe estimated intrinsic time scale (i.e., the adaptive intrinsic time scale) after each degradation region correction.As a normalization function, willTaking the value and quantifying to be 0-1; represents the first The signal anomaly intensity factor of each degradation degree region is multiplied by the degradation characteristic factor. The larger the value, the description is thatThe stronger the abnormal condition exists in the signal of each degradation degree region, and the greater the degradation degree of the signal at the place, the poorer the quality of the signal at the place. That is, the signal contains a large amount of extra noise frequency and the signal changes frequently, which means that the signal area needs to be set with smaller estimated intrinsic time scale of each degradation area to separate the noise signal component of the original current signal and the real connector current signal component better and more accurately.
The specific steps of S600 include: and acquiring a current signal after noise removal according to the self-adaptive intrinsic time scale and the original current signal of each degradation degree region.
Specifically, the adaptive intrinsic time scale of each degradation region is multiplied by the original current signal to obtain a product signal. To emphasize components of a particular time scale and suppress noise of other time scales.
And performing Hilbert transform (i.e. Hilbert transform) on the product signal to obtain the instantaneous frequency of the analytic signal. Wherein the resolved signal includes amplitude and phase information of the original current signal. The instantaneous frequency of the resolved signal is obtained by calculating the instantaneous rate of change of the phase information of the resolved signal.
And obtaining the current signal after noise removal according to the instantaneous frequency of the analysis signal and the adaptive intrinsic time scale of each degradation degree region. Specifically, according to the instantaneous frequency of the analysis signal and the adaptive intrinsic time scale of each degradation degree region, the original current signal is decomposed to obtain components of all eigenmode functions. And adding the components of all the eigen-mode functions to obtain a current signal after noise removal.
And performing signal processing on the current signal after noise removal to obtain a signal anomaly coefficient of the current signal after noise removal. In this embodiment, the current signal after noise removal is subjected to signal processing, so as to obtain all peak positions and all signal amplitudes of the current signal after noise removal. And obtaining the signal anomaly coefficient of the current signal after removing the noise according to all wave crest positions and all signal amplitudes of the current signal after removing the noise.
The specific steps of S700 include: and comparing the signal abnormal coefficient of the current signal after removing the noise with a preset judgment threshold value (threshold value=0.3) to obtain a detection result of the electric connector. If the signal abnormality coefficient of the current signal after removing the noise is larger than a preset judgment threshold value, a detection result of the abnormality of the electric connector is obtained, and the current signal at the detection result is indicated to have an abnormal state, and the electric connector equipment needs to be subjected to relevant maintenance.
The electrical connector connection state detection system provided by the invention is described below, and the electrical connector connection state detection system described below and the electrical connector connection state detection method described above can be referred to correspondingly.
The invention provides an electric connector connection state detection system which comprises an acquisition module, a signal processing module, a first acquisition module, a second acquisition module, a third acquisition module, a fourth acquisition module and a detection module.
The acquisition module user acquires a real-time current signal of the electric connector.
The signal processing module is used for performing signal processing on the real-time current signal to obtain each wave crest and each signal amplitude in the window area corresponding to each target sampling point in the real-time current signal
The first acquisition module is used for acquiring a degradation coefficient of each target sampling point according to each peak and each signal amplitude of the window area corresponding to each target sampling point in the real-time current signal.
The second acquisition module is used for acquiring the degradation characteristic factors of each degradation degree region and the abnormal intensity factors of the local regions in the real-time current signals according to the degradation degree coefficient of each target sampling point and a preset degradation degree coefficient threshold value.
And the third acquisition module obtains the self-adaptive intrinsic time scale of each degradation degree region according to the degradation characteristic factors of each degradation degree region, the abnormal intensity factors of the local region in the real-time current signal and the preset estimated intrinsic time scale.
And the fourth acquisition module obtains the signal anomaly coefficient of the current signal after removing the noise according to the self-adaptive intrinsic time scale of each degradation degree region and the original current signal.
The detection module is used for comparing the abnormal signal coefficient of the current signal after removing the noise with a preset judgment threshold value to obtain a detection result of the electric connector.
The first acquisition module is specifically configured to acquire a time difference between all two adjacent peaks according to each peak of the window area corresponding to each target sampling point in the real-time current signal.
And obtaining the degradation coefficient of each target sampling point according to the time differences between all two adjacent wave peaks and each signal amplitude. Specifically, the method specifically comprises the following steps: and (3) carrying out average processing on the time difference between all two adjacent wave peaks to obtain the average time interval of the window area corresponding to each target sampling point. And acquiring a current intensity weakening coefficient and a regional current mutation coefficient of a window region corresponding to each target sampling point according to each signal amplitude. And obtaining the degradation coefficient of each target sampling point according to the average time interval of the window area corresponding to each target sampling point, the current intensity weakening coefficient and the area current mutation coefficient of the window area corresponding to each target sampling point.
The second obtaining module is specifically configured to compare the degradation coefficient of each target sampling point with a preset degradation coefficient threshold value, so as to obtain all degradation regions.
And acquiring a degradation characteristic factor of each degradation degree region according to the degradation degree coefficient of each target sampling point and all degradation degree regions.
And obtaining abnormal intensity factors of local areas in the real-time current signals according to all the degradation degree areas.
The third obtaining module is specifically configured to obtain an adaptive intrinsic time scale of each degradation degree region according to the degradation characteristic factor of each degradation degree region, the abnormal intensity factor of the local region in the real-time current signal, and a preset estimated intrinsic time scale, and by using an adaptive intrinsic time scale adjustment formula.
The fourth acquisition module is specifically configured to acquire a current signal after noise removal according to the adaptive intrinsic time scale and the original current signal of each degradation degree region.
And performing signal processing on the current signal after noise removal to obtain a signal anomaly coefficient of the current signal after noise removal.
In this embodiment, the specific steps of obtaining the current signal after removing the noise include: and multiplying the self-adaptive intrinsic time scale of each degradation degree region by the original current signal to obtain a product signal. And performing Hilbert transformation on the product signal to obtain the instantaneous frequency of the analysis signal. And obtaining the current signal after noise removal according to the instantaneous frequency of the analysis signal and the adaptive intrinsic time scale of each degradation degree region.
The specific steps of obtaining the current signal after noise removal include: and decomposing the original current signal according to the instantaneous frequency of the analysis signal and the self-adaptive intrinsic time scale of each degradation degree region to obtain components of all eigen-mode functions. And adding the components of all the eigen-mode functions to obtain a current signal after noise removal.
Meanwhile, the specific steps for obtaining the signal anomaly coefficient of the current signal after removing the noise comprise:
And performing signal processing on the current signal after noise removal to obtain all peak positions and all signal amplitudes of the current signal after noise removal.
And obtaining the signal anomaly coefficient of the current signal after removing the noise according to all wave crest positions and all signal amplitudes of the current signal after removing the noise.
It should be noted that: the sequence of the embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
Claims (3)
1. A method for detecting a connection state of an electrical connector, the method comprising:
Acquiring a real-time current signal of the electric connector;
performing signal processing on the real-time current signal to obtain each wave crest and each signal amplitude in a window area corresponding to each target sampling point in the real-time current signal;
Obtaining a degradation coefficient of each target sampling point according to each wave crest and each signal amplitude of a window area corresponding to each target sampling point in the real-time current signal;
according to the degradation coefficient of each target sampling point and a preset degradation coefficient threshold value, obtaining degradation characteristic factors of each degradation region and abnormal strength factors of local regions in the real-time current signals;
Obtaining an adaptive intrinsic time scale of each degradation degree region according to the degradation characteristic factors of each degradation degree region, the abnormal intensity factors of the local region in the real-time current signal and the preset estimated intrinsic time scale;
Obtaining signal anomaly coefficients of the current signals after noise removal according to the self-adaptive intrinsic time scale of each degradation degree region and the original current signals;
Comparing the abnormal signal coefficient of the current signal after removing the noise with a preset judgment threshold value to obtain a detection result of the electric connector;
The specific step of obtaining the degradation coefficient of each target sampling point according to each peak and each signal amplitude of the window area corresponding to each target sampling point in the real-time current signal comprises the following steps:
acquiring time differences between all two adjacent wave peaks according to each wave peak of a window area corresponding to each target sampling point in the real-time current signal;
obtaining a degradation coefficient of each target sampling point according to the time differences between all two adjacent wave peaks and each signal amplitude;
The specific step of obtaining the degradation coefficient of each target sampling point according to the time difference between all two adjacent wave peaks and each signal amplitude comprises the following steps:
Averaging the time differences between all two adjacent wave peaks to obtain an average time interval of a window area corresponding to each target sampling point;
according to the amplitude of each signal, acquiring a current intensity weakening coefficient and a regional current mutation coefficient of a window region corresponding to each target sampling point;
Obtaining a degradation coefficient of each target sampling point according to the average time interval of the window area corresponding to each target sampling point, the current intensity weakening coefficient and the area current mutation coefficient of the window area corresponding to each target sampling point;
Wherein, the calculation formula of the degradation coefficient is:
；
wherein, Represents the firstThe degradation coefficient of each target sampling point,Represents the first of the original current signalsThe number of target sampling points is set to be equal,Represents the firstThe target sample points correspond to the maximum value of the signal amplitude in the window area,Represents the firstThe target sample points correspond to the average value of the signal amplitudes in the window area,Represents the firstThe target sample points correspond to the entropy of the signal amplitude in the window region,Represents the firstEach target sample point corresponds to an adjacent peak average time interval in the window region,Represents the firstThe target sample points correspond to current intensity decay coefficients in the window region,An exponential function with a natural constant as a base;
Calculating the difference value of signal amplitudes of two adjacent sampling points in a window area corresponding to each target sampling point, and averaging the signal amplitude difference values of all two adjacent sampling points in each target window area to serve as a current intensity weakening coefficient of the window area;
the absolute value of the difference value between the maximum value of the signal amplitude and the average value of the signal amplitude in the window area corresponding to the target sampling point is the area current mutation coefficient of the window area;
the specific steps of obtaining the degradation characteristic factor of each degradation degree area and the abnormal intensity factor of the local area in the real-time current signal according to the degradation degree coefficient of each target sampling point and the preset degradation degree coefficient threshold value include:
Comparing the degradation coefficient of each target sampling point with a preset degradation coefficient threshold value to obtain all degradation regions;
Acquiring degradation characteristic factors of each degradation degree region according to the degradation degree coefficient of each target sampling point and all degradation degree regions;
Wherein, the calculation formula of the degradation characteristic factor is:
；
wherein, Representative of the first of the current signalsThe degree of degradation of the image is determined by the degree of degradation,Represents the firstThe total number of signal sample points in each degradation region is set,Representative ofThe first in the collectionThe number of signal sampling points is one,Represents the firstThe degradation coefficient of each signal sample point,Represents the firstDegradation characteristic factors of the individual degradation degree regions;
Obtaining abnormal intensity factors of local areas in the real-time current signals according to all degradation degree areas;
the calculation formula of the abnormal intensity factor is as follows:
；
wherein, Represents the firstThe autocorrelation coefficients of the individual degradation regions,Represents an exponential function with a natural constant as a base,Represents the firstThe power spectral density derivatives of the individual degradation regions,Represents the firstSignal anomaly intensity factors for each degradation degree region;
the specific step of obtaining the adaptive intrinsic time scale of each degradation degree region according to the degradation characteristic factor of each degradation degree region, the abnormal intensity factor of the local region in the real-time current signal and the preset estimated intrinsic time scale comprises the following steps:
According to the degradation characteristic factors of each degradation degree region, the abnormal intensity factors of the local regions in the real-time current signals and the preset estimated intrinsic time scale, obtaining the adaptive intrinsic time scale of each degradation degree region by utilizing an adaptive intrinsic time scale adjusting formula;
the calculation formula of the adaptive intrinsic time scale of each degradation degree region is as follows:
；
In the method, in the process of the invention, Represents the firstSignal anomaly intensity factors for the individual degradation regions,Represents the firstDegradation characteristic factors of the individual degradation degree regions,Represents the firstThe estimated intrinsic time scale obtained by the conventional method is a preset estimated intrinsic time scale,Represents the firstThe estimated intrinsic time scale after the correction of each degradation degree region is the self-adaptive intrinsic time scale; Is a normalization function;
The specific step of obtaining the signal anomaly coefficient of the current signal after removing noise according to the self-adaptive intrinsic time scale of each degradation degree region and the original current signal comprises the following steps:
Acquiring a current signal after noise removal according to the self-adaptive intrinsic time scale and the original current signal of each degradation degree region;
Performing signal processing on the current signal after noise removal to obtain a signal anomaly coefficient of the current signal after noise removal;
the specific step of performing signal processing on the current signal after noise removal to obtain the signal anomaly coefficient of the current signal after noise removal comprises the following steps: performing signal processing on the current signal after noise removal to obtain all wave crest positions and all signal amplitudes of the current signal after noise removal; obtaining a signal anomaly coefficient of the current signal after removing the noise according to all wave crest positions and all signal amplitudes of the current signal after removing the noise;
the calculation formula of the signal anomaly coefficient is as follows: ; wherein, Is the firstThe target sample points correspond to the entropy of the signal amplitude in the window region,Represents the firstEach target sample point corresponds to an adjacent peak average time interval in the window region.
2. The electrical connector connection state detection method according to claim 1, wherein the specific step of obtaining the noise-removed current signal from the original current signal and the adaptive intrinsic time scale of each degradation degree region comprises:
multiplying the self-adaptive intrinsic time scale of each degradation degree region with the original current signal to obtain a product signal;
Performing Hilbert transform on the product signal to obtain the instantaneous frequency of an analysis signal;
obtaining a current signal after noise removal according to the instantaneous frequency of the analytic signal and the self-adaptive intrinsic time scale of each degradation degree region;
The specific step of obtaining the current signal after noise removal according to the instantaneous frequency of the analysis signal and the adaptive intrinsic time scale of each degradation degree region comprises the following steps:
Decomposing the original current signal according to the instantaneous frequency of the analysis signal and the self-adaptive intrinsic time scale of each degradation degree region to obtain components of all eigen-mode functions;
And adding the components of all the eigen-mode functions to obtain a current signal after noise removal.
3. An electrical connector connection state detection system for implementing the electrical connector connection state detection method of any one of claims 1-2, comprising:
the acquisition module is used for acquiring a real-time current signal of the electric connector by a user;
The signal processing module is used for carrying out signal processing on the real-time current signal to obtain each wave crest and each signal amplitude in a window area corresponding to each target sampling point in the real-time current signal;
the first acquisition module is used for acquiring a degradation coefficient of each target sampling point according to each peak and each signal amplitude of the window area corresponding to each target sampling point in the real-time current signal;
the second acquisition module is used for acquiring a degradation characteristic factor of each degradation degree region and an abnormal strength factor of a local region in the real-time current signal according to the degradation degree coefficient of each target sampling point and a preset degradation degree coefficient threshold value;
The third acquisition module is used for obtaining the self-adaptive intrinsic time scale of each degradation degree region according to the degradation characteristic factors of each degradation degree region, the abnormal intensity factors of the local region in the real-time current signal and the preset estimated intrinsic time scale;
the fourth acquisition module is used for obtaining a signal anomaly coefficient of the current signal after removing noise according to the self-adaptive intrinsic time scale of each degradation degree region and the original current signal;
And the detection module is used for comparing the abnormal signal coefficient of the current signal after removing the noise with a preset judgment threshold value to obtain a detection result of the electric connector.
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