Classifications

• • 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
  • G01R31/08—Locating faults in cables, transmission lines, or networks
  • G01R31/11—Locating faults in cables, transmission lines, or networks using pulse reflection methods

Definitions

• the present invention relates to a method for detecting faults in a network by reflectometry and a system implementing the method. It applies in particular to the fields of OTDR in electronics and optoelectronics. Cables are ubiquitous in all electrical systems, for powering or transmitting information. These cables are subject to the same constraints as the systems they connect and may be subject to failures. It is therefore necessary to be able to test their status and provide information on the detection of defects, but also their location and type, to help with maintenance and prevention. For this, so-called reflectometry methods are implemented. These can also be used to detect faults in an optical fiber network.
• OTDR OTDR
• the OTDR methods use a principle similar to that of the radar: an electrical signal, the test signal, often of high frequency or wide band, is injected in one or more places of the cable to be tested. Said signal propagates in the cable or network and returns a portion of its energy when it encounters an electrical discontinuity.
• An electrical discontinuity may result, for example, from a connection, the end of the cable or a fault.
• the analysis of the signals returned to the injection point makes it possible to deduce information on the presence and the location of these discontinuities, thus possible defects.
• An analysis in the time domain is usually performed.
• TDR Time Domain Reflectometry
• STDR Time Domain Reflectometry
• SSTDR Time Domain Reflectometry
• MCTDR MultiCarrier TDR
• the test signal depends on the OTDR method used.
• the signal resulting from the reflectometry is called reflectogram and consists of a plurality of peaks corresponding to the singularities of the network. There may be several peaks by singularity, some corresponding to multiple reflections.
• the objective is then to determine which peak corresponds to a fault and then isolate it correctly in order to precisely locate said fault.
• Frequency methods can also be used in the context of OTDR. However, when the duration of the measurement is an important criterion, temporal methods are preferable.
• an x-type notation designates a vector, i.e. a set of values organized in a matrix comprising a single column.
• An object of the invention is in particular to overcome the aforementioned drawbacks.
• the subject of the invention is a method for detecting defects of a network by reflectometry comprising a step of measuring the response CMr of the network, a step of detecting defects by analyzing the difference h Acur between this measurement. h ⁇ r and a reference response h mem .
• the reference h mem response is updated using measurements h oer stored in the network response.
• a network fault is detected by determining whether the standard of the difference signal h Acur is less than a predefined threshold T.
• the standard of the difference signal h Acur is of standard type L1 or L2 standard or L ⁇ standard.
• the reference response h mem is updated when no fault is detected.
• the invention provides that the reference response h mem is updated when a change of state of the network of a duration greater than a predefined value is detected.
• the reference h mem response can be updated using the following expression: ⁇ ) & where
• the exponent (k) designates the current measurement instant and the exponent (k-1) the instant preceding the instant (k);
• a represents the forgetting factor of the low-pass filter.
• the threshold T is set, for example, using the following expression:
• N is the number of samples of the signal
• c 2 is the average variance of the noise
• ⁇ is a margin factor
• the invention advantageously provides that when a fault is detected, the difference signal h Acur is deconvolved, the result of the deconvolution being used to locate and characterize the defects.
• the method comprises a step of detecting multiple occurrences belonging to the same defect, an average of the difference signals h Acur being determined when several values of h Acur obtained successively correspond to the same defect, said mean being stored for use in locating and characterizing said defect.
• Two difference signals A : and A 2 are considered to belong to the same defect when, for example, an estimator J Lx is less than a predefined threshold T J ⁇ the estimator being determined using the following expression:
• the invention also relates to a reflectometry system comprising means for measuring the response of a network, means for comparing this measured response with a reference response, means for detecting and locating faults appearing in the network.
• the system implements the method described above.
• FIG. 1 illustrates the principle of a time domain reflectometry system for the diagnosis of in-line cables
• FIG. 2 gives an example of a simplified diagram of the three main stages of a wired network diagnostic method by reflectometry
• FIGS. 3A and 3B give examples of reflectograms obtained for an example of a network with and without defects
• FIG. 4 gives a first example of implementation of the differential detection method according to the invention
• FIG. 5 gives a second example of implementation of the differential detection method according to the invention.
• FIG. 6 gives an example of a reflectogram obtained after application of the method according to the invention.
• Figure 1 illustrates the principle of a time domain reflectometry system for the diagnosis of in-line cables.
• the reflectometric analysis is performed online when it is performed on a system while it is running.
• the system comprises a test signal generator 100.
• the test signal is usually generated in digital form and then introduced into the test cable network 102 after being converted to an analog signal x (t) using a digital-to-analog converter CNA 101.
• the analog signal y (t) resulting in particular from the reflection of x (t) by the network 102 is then converted into a digital signal by a CAN-to-digital converter 103.
• the converters 101, 103 are connected to the cable network 102 via for example, a coupling system with or without galvanic isolation.
• An electrical response measurement is generally affected by a not inconsiderable noise adding to the useful signal.
• an averaging operation 105 is applied after the analog-to-digital conversion to improve the signal-to-noise ratio. For example, M measures of electrical signals are realized then their results are accumulated in an average vector noted y.
• the time T mes required to perform a complete measurement can be determined using the following expression:
• T s represents the sampling period of the test signal x (t);
• N is the number of samples of the signal.
• T mes MK'NT s (2) in which K 'represents the equivalent time factor.
• the measurement time is particularly important for the detection of network faults appear intermittently because the duration of these faults can be very low. In the following description, this type of fault is called intermittent fault. In the presence of such defects, the number of measurements M remains limited in order to guarantee an acceptable capture speed. Therefore, it may be necessary to increase the signal-to-noise ratio upstream with other treatments.
• the reflectometry system will estimate the response heart representative of network conditions using, for example, a matched filter.
• the difference signal is processed by deconvolution 107 to separate the different peaks that compose it.
• deconvolution 107 Different pulse deconvolution algorithms can be used for this.
• a location processing 108 then aims to determine the distance separating the reflectometer from the fault from the position of the first peak of the result obtained.
• Figure 2 gives an example of a simplified diagram of the three main steps of a cable diagnosis method by reflectometry.
• a first step 200 corresponds to the acquisition of the measurements of the response of the tested network
• a second step corresponds to the detection of the defects 201 of the network tested
• a third step performed when there is detection, corresponds to the location 202 of these defects in said network.
• FIGS. 3A and 3B give examples of reflectograms obtained for an example of a network with and without faults.
• the network 300 considered in this example comprises four line sections.
• a first section of length l 0 corresponding to a 50 ⁇ coaxial line has one of its ends used as input of the network. Its other end is connected directly to the first end of a second section 302 twisted pair type and length //.
• the second end of the second section 302 corresponds to a junction between three sections, the latter being connected to the first end of two sections 303, 304 of twisted pair type and of respective lengths h and h, the other ends of these two sections being left in open circuit.
• Figure 3A shows the case where there is no fault.
• a negative peak 309 appears at the junction followed by positive peaks 310, 31 1, 312, 313 corresponding to the ends of lines 303, 304 of lengths h and
• FIG. 3B shows curves 307, 308 representative of the state of the network in the presence of a fault.
• the fault corresponds to a short circuit appearing at the junction.
• the negative peak 314 corresponding to the junction becomes larger and the peaks 315, 316, 317 correspond to the secondary echoes of this short-circuit.
• the ends of lines are no longer visible.
• FIG. 4 gives a first example of implementation of the differential detection method according to the invention.
• the principle of the method is to use for the detection of defects a reference stable state h mem taking into account the changes in the state of the network over time.
• the responses h ⁇ ! - measured at each instant k are then compared to this reference.
• the latest measure heart is acquired 400.
• This measurement is compared to the steady state reference.
• This comparison is made initially by determining the standard of the difference signal Acur corresponding to the difference between ⁇ and the stable state of reference mem .
• the norm of this difference is then compared 401 to a threshold T.
• This comparison corresponds to the inequality: l .Acur I ⁇ T with
• the presence of a defect is manifested in particular by a peak in the reflectogram.
• the most natural choice for determining the standard is thus to use the maximum or the infinite standard known to those skilled in the art.
• the maximum of the signal corresponds to the amplitude of the noise, when this value is greater than the maximum amplitude of the noise a variation is detected.
• the value of the threshold T used in expression (3) should be judiciously chosen.
• the threshold T can be set using the expression:
• N is the number of samples of the signal
• c 2 is the average variance of the noise
• ⁇ is a factor corresponding to a margin, the latter being chosen so that the energy of the noise never exceeds the threshold T; the value of ⁇ depends on the shape of the noise over time, so for a noise of a pulse nature a higher value will be chosen.
• the standard of the difference signal h & cur can be determined on the basis of the so-called standard L1 defined by the expression:
• refers to the L1 standard.
• the use of the L1 standard is interesting in some cases in terms of performance and computational complexity. It is particularly preferred in the presence of a noise of impulsive nature. In other words, the choice of the standard is optimized according to the nature of the noise.
• the value of ⁇ is rarely known in advance, so it is advantageous to be able to estimate it automatically.
• the variance of the instantaneous difference can be used, which can be determined by using the following expression: î hLMnst It is possible to demonstrate that the variance of the noise in h Ainst is equal to 2 ⁇ 2 . An average estimate of the variance noted at 2 can then be calculated using a first-order filter.
• the estimated variance at 2 can be determined using the expression:
• ⁇ ⁇ is the forgetting factor of the filter.
• the estimate can then be used directly to calculate the value of the threshold T in real time.
• the expression (8) can be used by replacing the L2 standard with another standard.
• a count time counter 407 is compared to a threshold count max .
• the threshold count max corresponds, for example, to the maximum duration of a fault for it to be considered transitory or intermittent. If count> count max , the h mem must be updated. In the case where count ⁇ count max , the count counter is increments 408.
• the 407 test makes it possible to take into account the permanent state changes of the network and not to treat them in the same way as a default appearing and disappearing. In the example of Figure 4, it avoids being stuck at the detection of a change of state.
• the h Amem signal is the final result of the detection which will be analyzed later for the location of the defects.
• the counter count is set to zero 402.
• a test 403 then checks if
• the h fflr measurement is used to update the reference state h mem 406 using a low-pass filter in order to avoid taking into account too fast changes in the state of the network.
• This low-pass filtering can be implemented using for example the expression: in which
• the averaging effect induced by this filtering leads to a quasi-zero noise on the reference signal h mem . It can be shown that in the case of a white noise, the signal-to-noise ratio of the reference is given by the expression:
• SNR h is the signal-to-noise ratio of the acquired signals.
• the method may be implemented in a distributed reflectometry system such as that described in the article by A. Lelong, L. Sommervogel, N. Ravot, and MO Carrion titled Distributed Reflectometry Method for Wire-fault Leasing Using Selective Average , Sensors Journal, IEEE, pages 300-310, February 2010.
• FIG. 5 gives a second example of implementation of the differential detection method according to the invention.
• Deconvolution methods used for Amem difference processing usually require a high level of signal-to-noise ratio. In a disturbed environment, it may happen that the signal-to-noise ratio of the result of a detection is low. But it is common for the same intermittent fault to occur several times in a row. It is then possible to use the multiple occurrences of the same defect to average the difference signals and thus improve the signal-to-noise ratio obtained.
• ⁇ is a real coeficient whose function is to compensate for any difference in amplitude that may exist between the two occurrences.
• test of the value of J amounts to testing the collinearity of the vectors i and ⁇ 2 . If the L2 standard is used, the value of this minimum can be calculated directly using the expression:
• FIG. 6 gives an example of a reflectogram obtained after application of the method according to the invention.
• the dashed line curve 600 gives the difference between the responses with and without defects.
• the high resolution curve 601 can be obtained.
• the number of samples n separating the first peak of the origin makes it possible to calculate the distance between the position of the fault in the cable network and the reflectometer. This distance can be determined using the following expression:
• T s is the sampling period of the acquired signal and v is the speed of propagation in the network.

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• 2010
  • 2010-09-30 FR FR1057922A patent/FR2965629B1/fr active Active
• 2011
  • 2011-09-07 WO PCT/FR2011/052038 patent/WO2012042142A1/fr active Application Filing
  • 2011-09-07 EP EP11773037.4A patent/EP2622360A1/de not_active Withdrawn

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