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CN-122017468-A - Network communication coaxial cable detection method based on intelligent sensor

CN122017468ACN 122017468 ACN122017468 ACN 122017468ACN-122017468-A

Abstract

The invention relates to the technical field of cable nondestructive testing, and discloses a network communication coaxial cable detection method based on an intelligent sensor, which comprises the steps of collecting a double-frequency reflected voltage signal, mapping the double-frequency reflected voltage signal to a complex analytic domain, counteracting common-mode phase shift caused by cable temperature gradient by using a cross power spectrum, and extracting amplitude weighted phase gradient for avoiding singular points of an arctangent function; the method comprises the steps of calculating transient accumulated energy to construct self-adaptive index compensation weight, reversely modulating phase gradient characteristics to amplify remote weak fault characteristics, further extracting dimensionless transient characteristic probability density and local transient information entropy based on the characteristics, extracting transient accumulated entropy duty ratio according to the extracted dimensionless transient characteristic probability density and the local transient information entropy duty ratio, constructing dynamic punishment factors to intercept extremely remote noise background which is out of control due to index amplification, finally, combining high-frequency electromagnetic wave nominal transmission speed to output fault point physical distance, solving the problems of phase winding and remote noise out of control and realizing precision positioning of weak faults.

Inventors

  • XUE SHENGLING
  • XUE JINGHUA

Assignees

  • 江阴凯博通信科技有限公司

Dates

Publication Date
20260512
Application Date
20260403

Claims (9)

  1. 1. The network communication coaxial cable detection method based on the intelligent sensor is characterized by comprising the following steps of: s1, synchronously injecting a first frequency continuous test wave and a second frequency continuous test wave into a cable, and respectively extracting a first frequency reflected voltage signal and a second frequency reflected voltage signal; S2, mapping the first frequency reflection voltage signal to a complex resolution domain to obtain a first frequency resolution voltage signal; s3, calculating the product of the complex conjugate of the first frequency analysis voltage signal and the second frequency analysis voltage signal to obtain a transient cross power spectrum; s4, calculating transient accumulated energy based on the first frequency analysis voltage signal and the second frequency analysis voltage signal, constructing adaptive index compensation weight based on the transient accumulated energy, multiplying the adaptive index compensation weight by an amplitude weighted phase gradient, and obtaining an index modulated phase gradient characteristic; S5, extracting dimensionless transient characteristic probability density based on the phase gradient characteristics subjected to exponential modulation, calculating local instantaneous information entropy based on the dimensionless transient characteristic probability density, extracting transient accumulated entropy duty ratio based on the local instantaneous information entropy, and constructing a dynamic penalty factor based on the transient accumulated entropy duty ratio; And S6, multiplying the dynamic penalty factor by the phase gradient characteristic subjected to index modulation to obtain a final cable fault characteristic index, and converting and outputting the physical distance of the fault point by combining the nominal transmission speed of the high-frequency electromagnetic wave of the coaxial cable and the final cable fault characteristic index.
  2. 2. The method for detecting the network communication coaxial cable based on the intelligent sensor according to claim 1, wherein the step S2 specifically comprises: performing Hilbert principal value integral transformation on the first frequency reflection voltage signal to construct a first frequency analysis voltage signal; And executing the same analysis domain mapping operation on the second frequency reflection voltage signal, namely performing Hilbert principal value integral transformation to construct a second frequency analysis voltage signal.
  3. 3. The intelligent sensor-based network communication coaxial cable detection method of claim 1, wherein the step of calculating the transient accumulated energy comprises: respectively acquiring absolute amplitudes of a first frequency analysis voltage signal and a second frequency analysis voltage signal; calculating the square sum of two absolute amplitudes to obtain the total transient energy density; and performing time axis integral operation on the transient total energy density to obtain transient accumulated energy.
  4. 4. The method for detecting a network communication coaxial cable based on an intelligent sensor according to claim 1, wherein the steps of constructing the adaptive exponential compensation weight and obtaining the exponential modulated phase gradient feature comprise: Acquiring total test energy obtained when integration reaches a time end point; Calculating the ratio of the transient accumulated energy to the total test energy, and calculating the ratio as an independent variable of a natural exponential function to obtain an adaptive exponential compensation weight; multiplying the amplitude weighted phase gradient by the adaptive index compensation weight to complete modulation, and obtaining the phase gradient characteristic after index modulation.
  5. 5. The method for detecting a network communication coaxial cable based on an intelligent sensor according to claim 1, wherein the step of extracting the dimensionless transient feature probability density comprises: Extracting the global maximum value of the index-modulated phase gradient characteristic absolute value in the whole objective observation time window; extracting absolute values of instantaneous phase gradient characteristics subjected to exponential modulation; dividing the instantaneous absolute value by the global maximum value, and carrying out extremum normalization operation to obtain dimensionless transient characteristic probability density.
  6. 6. The method for detecting a network communication coaxial cable based on an intelligent sensor according to claim 1, wherein the step of calculating the local instantaneous information entropy comprises: Calculating natural logarithmic value of dimensionless transient characteristic probability density; multiplying the dimensionless transient characteristic probability density by the natural logarithmic value; and taking a negative value of the product result to obtain the local instantaneous information entropy.
  7. 7. The method for detecting a network communication coaxial cable based on an intelligent sensor according to claim 1, wherein the step of extracting the transient accumulated entropy duty cycle comprises: performing time axis integration operation on the local instantaneous information entropy in the current time range to obtain a current moment integration result; performing time axis integration operation on the local instantaneous information entropy in the whole objective observation time window to obtain a total time window integration result; Dividing the integration result of the current moment by the integration result of the total time window to obtain the transient accumulated entropy duty ratio.
  8. 8. The method for detecting a network communication coaxial cable based on an intelligent sensor according to claim 1, wherein the step of constructing the dynamic penalty factor comprises: acquiring a directly set entropy acute coefficient of a known system; Calculating the system entropy sharp coefficient power of the transient accumulated entropy duty ratio; the power value obtained by the calculation is subtracted by the number one to generate a dynamic penalty factor.
  9. 9. The method for detecting a network communication coaxial cable based on an intelligent sensor according to claim 1, wherein the steps of obtaining the final cable fault characteristic index and outputting the physical distance of the fault point comprise: multiplying the phase gradient characteristic subjected to index modulation by a dynamic penalty factor to obtain a final cable fault characteristic index; extracting a specific time node corresponding to the final cable fault characteristic index reaching the maximum value; multiplying the nominal high-frequency electromagnetic wave transmission speed of the coaxial cable by the specific time node to obtain a reference distance span value; dividing the reference distance span value by a number two, and outputting the physical distance from the weak fault point of the cable to the test head end.

Description

Network communication coaxial cable detection method based on intelligent sensor Technical Field The invention relates to the technical field of nondestructive testing of cables, in particular to a network communication coaxial cable detection method based on an intelligent sensor. Background The network communication system can use coaxial cables to carry out high-frequency data transmission in a large amount, and the cables are easy to generate weak damages such as micro oxidation of a shielding layer and micro deformation of an insulating layer, so that accurate detection of deep weak faults is important to guaranteeing communication quality; At present, the common coaxial cable detection technology is mostly based on a high-frequency reflection method, a transmitter injects continuous test waves into a cable and collects reflected signals by a sensor to perform time domain or frequency domain analysis, however, the prior art faces a plurality of limitations in practical application, firstly, a long-distance cable is always in a complex external environment, the transmission delay of electromagnetic waves is caused by uneven temperature gradient along the long-distance cable, the prior art is difficult to effectively offset the phase shift interference of a common temperature mode to cause detection reference distortion, secondly, when the phase characteristics of the reflected signals are extracted, the traditional algorithm is highly dependent on an arctangent function, when encountering high-frequency noise, the arctangent function is extremely easy to cause severe phase winding phenomenon, mathematical singular points of derivative operation are generated to generate false pulses, the subsequent characteristics are seriously interfered, and again, the high-frequency signals have inherent energy attenuation when propagating in the cable, so that the real weak fault characteristics at the far end of the cable are extremely easy to be covered up by the second time, if the prior art adopts a global compensation strategy, the far-end weak signals are enhanced, the extremely pure noise at the far end is extremely easy to be out of control, and the sharp noise is extremely easy to be out of control, and the false noise is extremely seriously erroneous, so that the false system is output; Therefore, a network communication coaxial cable detection method based on an intelligent sensor is needed to overcome temperature common mode drift, avoid phase winding singular points, accurately cut off the noise background of a far end while reversely amplifying weak characteristics of the far end, and realize high-precision positioning of faults. Disclosure of Invention The invention provides a network communication coaxial cable detection method based on an intelligent sensor, which facilitates solving the problems mentioned in the background art. The invention provides a network communication coaxial cable detection method based on an intelligent sensor, which comprises the following steps: The initial operation and data acquisition steps comprise accessing a high-frequency intelligent voltage sensor and a double-frequency continuous wave transmitter at the test head end of a tested network communication coaxial cable, controlling the transmitter to synchronously inject a first frequency continuous test wave and a second frequency continuous test wave into the cable, controlling the intelligent voltage sensor to continuously acquire reflected voltage time domain data of the cable head end in a set objective observation time window, and respectively extracting a first frequency reflected voltage signal and a second frequency reflected voltage signal; The conversion step of the dual-frequency signal analysis domain comprises the steps of mapping a first frequency reflection voltage signal to a complex analysis domain by utilizing a conversion algorithm to obtain a first frequency analysis voltage signal; The cross power spectrum and phase gradient extraction step comprises the steps of calculating the product of the complex conjugate of a first frequency analysis voltage signal and a second frequency analysis voltage signal to obtain a transient cross power spectrum, calculating the product of the complex conjugate of the transient cross power spectrum and the first-order time derivative of the transient cross power spectrum, extracting the imaginary part of the product result to obtain an amplitude weighted phase gradient; The energy reverse index adaptive modulation step comprises the steps of calculating transient accumulated energy based on a first frequency analysis voltage signal and a second frequency analysis voltage signal, constructing adaptive index compensation weight based on the transient accumulated energy, multiplying the adaptive index compensation weight by an amplitude weighted phase gradient, and obtaining an index modulated phase gradient characteristic; The non-dimensional entropy driving dynamic