FR2965629A1 - METHOD FOR DETECTING FAULTS OF A NETWORK BY REFLECTOMETRY AND SYSTEM IMPLEMENTING THE METHOD - Google Patents

Abstract

The subject of the invention is a method for detecting defects of a network by reflectometry comprising a step (200) for measuring the response h of the network, a step (201) for detecting defects by analyzing the difference h between this measure h and a reference response h. The reference response h is updated using stored measurements h of the network response. The invention also relates to a reflectometry system implementing the method.

Description

The present invention relates to a method for detecting defects of a network by reflectometry and a system implementing the method. It applies in particular to the fields of OTDR in electronics and optoelectronics.

1 Cables are ubiquitous in all electrical systems, for the supply or transmission of 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 state and to provide information on fault detection, but also their location and type, in order to assist 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. The principle of OTDR is based on the injection of a test signal. The shape of this signal changes significantly during their propagation back and forth in a cable, these changes being the consequence of the physical phenomena of attenuation and dispersion. OTDR methods use a principle similar to that of radar: an electrical signal, the test signal, often of high frequency or broadband, is injected at one or more points 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 30 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. Several time methods exist such as the Time Domain Reflectometry (TDR) method, the Sequence Time Domain Reflectometry (STDR) method, the TDR Spread Spectrum (SSTDR) method, and the MultiCarrier TDR (MCTDR) method. 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. In a complex network, 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. 1 o For the detection of a fault, the time approaches currently adopted, for example in an on-board system, rely on the detection of the largest peak as described in patent US6868357 or on the detection of the first peak exceeding one threshold given as described in international application WO / 2010/032040. In order to correctly detect a fault within an arbitrarily complex network, it is necessary to measure variations in the electrical response of said network. The difficulty is then to identify the first peak that corresponds to the defect in order to deduce its position. Thus, the comparison of the successive measurements of this electrical response can make it possible to detect the appearance of a fault but also to efficiently localize said fault by calculating the difference of the measured responses with and without the defect. However, for a reliable detection, the analysis of the difference signals h eh-hc (ur - »between two successive responses h (: ~, and h (i) in two instants k-1 and k is not sufficient This approach, described in patent application US2009 / 0228223, is problematic, particularly when the defect is slowly established.In the entire description, a notation of the type x designates a vector; that is to say a set of values organized in a matrix comprising a single column 30 Moreover, in the case where there is a clear appearance of the defect, we have the answers before and after the defect but we can not have that an occurrence of this difference It is notably impossible to improve the signal-to-noise ratio by means of several difference signals.

It is also possible to compare each measurement with a fixed reference as is the case in US6937944. However, in addition to the fact that this requires a calibration phase of the diagnostic system, this solution lacks robustness in that the normal state of the network tested may vary over time. An object of the invention is in particular to overcome the aforementioned drawbacks.

For this purpose, the subject of the invention is a method for detecting

1 o defects of a reflectometry network comprising a step of measuring the response h, of the network, a step of detecting defects by analysis of

the difference hA, between this measurement h, and a reference response h, nem The reference response h, nen is updated using measurements

h .. memorized the network response. According to one aspect of the invention, a network fault is detected by determining whether the standard of the hot difference signal is less than a predefined threshold T.

According to another aspect of the invention, the standard of the difference signal hA is of standard type L1 or standard L2 or standard L-0. In one embodiment, the hmem reference response is updated when no fault is detected. The invention provides that the reference response h, nem is updated when a change of state of the network of a duration greater than a value

predefined is detected. The reference response h, nem can be updated using the following expression: k) (k) (k-1) hmem = (1- a) hcur + ah e, in which

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: T = / 3N6-2, wherein: N is the number of samples of the signal; 6-2 is the average variance of the noise; 5, 13 is a margin factor. The invention advantageously provides that when a fault is detected, the difference signal hocuY is deconvolved, the result of the deconvolution being used to locate and characterize the defects. According to one aspect of the invention, the method comprises a step of detecting multiple occurrences belonging to the same defect, an average of the difference signals hocuY being determined when several values of hAau. successively obtained correspond to the same defect, said average being stored for use in locating and characterizing said defect. Two difference signals 41 and a2 are considered to belong to the same defect when, for example, an estimator JL is less than a predefined threshold T ,, the estimator being determined using the following expression: JLx (at1, A2 The invention also relates to a reflectometry system comprising means for measuring the response of a network, means for comparing this measured response to a reference response, means for detecting and locating faults appearing in the network. . The system implements the method described above. The network is, for example, an electrical cable network or an optical fiber network.

Other features and advantages of the invention will become apparent with the aid of the description which follows, which is given by way of nonlimiting illustration, with reference to the appended drawings in which: FIG. 1 illustrates the principle of a reflectometry system in the time domain for online cable diagnostics; 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 exemplary 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. Reflectometric analysis is performed online when this is performed on a system while the system is operating. 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 having been converted to an analog signal x (t) with the aid of FIG. a digital-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. Thus, an averaging operation 105 is applied after the analog-to-digital conversion to improve the signal-to-noise ratio. By way of example, M measurements of 10 electrical signals are performed and then their results are accumulated in a noted mean vector. The time Tmes required to perform a complete measurement can be determined using the following expression: Tes = MNT (1) where Ts represents the sampling period of the test signal x (t); 1 where N is the number of samples of the signal. In order to have a lower technological constraint on the digital analog converter 103, it is possible to use equivalent time sampling methods as described in the international application WO / 2009/087045, in order to reach a frequency sampling of the signal measured higher than that allowed by the converter. In this case, the duration of the measurement is given by the expression: T, es = MK'NT (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 rest of the description, this type of defect is called an 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. It is on the basis of the signal received y (t) after digital-to-analog conversion that the reflectometry system will estimate the h uY response representative of the state of the network using, for example, a suitable filter. . The measured response can also be chosen, for example, such that ha, Y =, this choice depending on the properties of the noise and the test signal. We then obtain a series of estimates of the response of the channel denoted h, where k denotes the moment at which each estimate is captured. [0113] A differential detection 106 for detecting defects is then carried out. to compare successive measurements of the electrical response with, for example, a reference response When a fault is detected, the difference signal between a reference response corresponding to the response of the network considered to be flawless and that measured with the reference. The difference signal is processed by deconvolution 107 in order to separate the different peaks that compose it, and different pulse deconvolution algorithms can be used for this. second, to determine the distance separating the reflectometer from the defect at shooting the position of the first peak of the result obtained.

FIG. 2 gives an example of a simplified diagram of the three main steps of a reflectometry cable diagnostic method. 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 tested network and a third step, performed when there is detection, corresponds to the localization 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. These reflectograms correspond to reflectometry results obtained on a lattice with and without flaws before 305, 307 and after 306, 308 high resolution processing. The network 300 considered in this example comprises four line sections. A first length segment lo corresponding to a coaxial line 5052 has one of its ends used as input network. Its other end is connected directly to the first end of a second twisted pair type segment 302 and length 11. The second end of the second section 302 corresponds to a junction between three sections, the latter being connected to the first end. two twisted pair type sections 303, 304 and respective lengths 12 and 13, 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, 311, 312, 313 corresponding to the ends of lines 303, 304 of lengths 12 and 13. FIG. 3B shows curves 307, 308 representative of the state of the network in the presence of a fault. In this example, the fault corresponds to a short circuit appearing at the junction. When the short-circuit occurs, 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. 1 o Automatic processing to interpret these curves to deduce the presence of a defect is in practice difficult to implement. It is possible to use topology reconstruction algorithms as disclosed in US7282922. However, it is difficult to implement this type of solution when real-time and on-board detection is required.

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 stable reference state h, nem taking into account the changes in the state of the network over time. The responses h (c ~ r) measured at each instant k are then compared to this reference. Thus, as a first step, the most recent measurement h is acquired 400. This measurement is compared with the reference steady state. This comparison is carried out initially by determining the norm of the difference signal h.sub.ur corresponding to the difference between h, and the reference steady state h, n, n. The norm of this difference is then compared to a threshold T. This comparison corresponds to the inequality:

Hurrow <T with ho, = h ~ Y - h 'e' (3) As recalled earlier in the description, 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 infinite standard known to those skilled in the art. In the absence of a change, 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. It is also possible to use the standard called L2 and 5 defined by the following expression: X 2 = I ~ xn (4) n In which the sign 11-2 refers to the L2 standard.

1 o With respect to the threshold T, this one makes it possible to distinguish the cases where there is no variation of the cases where there is variation compared to the reference answer. In the case where there is no variation, hocur only contains

noise. The value of the threshold T used in the expression (3) should be judiciously chosen. For example, the threshold T can be set using the expression:

T = flNo-2, (5) wherein N is the number of samples of the signal; a-2 is the average variance of the noise; , l3 is a factor corresponding to a margin, the latter being chosen from

so that the energy of the noise never exceeds the threshold T; the value of fl depends on the shape of the noise over time, so for a noise of

impulse nature a higher value will be chosen. Alternatively, the norm of the difference signal hocnY can be

determined on the basis of the so-called standard L1 defined by the expression: X 1 = .xi, n (6) in which the sign - 1 refers to the standard L1.

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 standard L2 is taken as an example in the remainder of the description without this choice limiting the scope of the invention. The generic symbol - to refer to any chosen standard. In practice, the value of 6 is rarely known in advance, so it is advantageous to be able to estimate it automatically. For this, the 1 o variance of the instantaneous difference can be used, which can be determined using the following expression: h = h (k) -h (kl) -4 nst -cur -cur 15 It is possible to demonstrate that the variance of the noise in honst is 2o-2. An average estimate of the variance noted 6-2 can then be calculated using a first-order filter. At time k, the estimated variance 6-2 can be determined using the expression: (7) 2 2 = aQg (k_I) + 1 (8) where: a6 is the forgetting factor of the filter. Estimate 6 can then be used directly to calculate the threshold value T in real time. When a standard other than the L2 standard is used, the expression (8) can be used by replacing the L2 standard with another standard. In the case where the difference hert is greater than or equal to 401 at the threshold T, that is to say in the case where there is a significant variation in the state of the network, a time counter count is compared 407 to a threshold countn .. The threshold countm z is, for example, the maximum duration of a fault for it to be considered transient or intermittent. If count> countn., The reference h, nem must be updated. In the case where

count countn., the count counter is incremented 408. The test 407 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.

A step 410 then aims to select the memorized recording record having the maximum energy level. 1 o This selection makes it possible to avoid keeping records corresponding to a transient state of the network. Thus, if VhocuY> VhAinen] then the value stored in the difference hmLe / is hmLe / = hocur. The signal homem is the final result of the detection which will be analyzed later for the localization of the defects.

On the other hand, by keeping the larger difference, the signal-to-noise ratio of the homem signal is improved. In the case 401 where the difference is less than the threshold T, that is to say in the case where there has been no significant variation in the state of the

In the network, the counter count is set to zero 402. A test 403 then checks whether homem> 0. If so, then there is a fault and the signal homem is analyzed 404 for example by deconvolution to precisely locate faults in the network. homem is then set to zero 405.

Whatever the value of homem, the heur measure is used to update the reference state h, nem 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:

30 k) (k) k-1) -men) -cur -men) in which

the exponent (k) designates the current moment; (9) a represents the forgetting factor of the low pass filter, this factor being the ones directly related to the time constant by a = e z where z is the filter time constant expressed in seconds. Advantageously, the averaging effect induced by this filtering 5 leads to a quasi-zero noise on the hmem reference signal. 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: SNRh = 1 + aSNRh mem 1 - a cur (10) in which SNRh is the signal-to-noise ratio noise of acquired signals. heart

Advantageously, the method can be implemented in a distributed OTDR system such as that described in the article by A.

15 Lelong, L. Sommervogel, N. Ravot, and MO Carrion titled Distributed Reflectometry Method for Selective Localization, Sensors Journal, IEEE, pages 300-310, February 2010. Figure 5 gives a second example of the implementation of the Differential detection method according to the invention.

The deconvolution methods used for homem 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 that the same

Intermittent fault occurs 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.

However, before averaging multiple detections, it is useful to ensure that these occurrences correspond to the same intermittent fault. In practice, it is not possible to guarantee that an intermittent fault produces an echo of the same amplitude from one occurrence to another, but the position of the peak corresponding to the fault is always the same. Thus, to check whether the results of two detections for two difference signals AI and A2 correspond to the same defect, it is possible to test the value of an estimator J, which value can be obtained by using the expression:

J (Al, A2) = min -X42 (11) in which: 2 is a real coeficient whose function is to compensate for any difference in amplitude that may exist between the two occurrences. The test of the value of J is to test the collinearity of the vectors AI and A2. If the L2 standard is used, the value of this minimum can be calculated directly using the expression: T 2 JL2 (A1, to2) - Al 2 - ~ 2-2 11A2112

When another standard is used, we can use the more generic result of the following expression: (12) Jzx (to1, to2) = 41 _VIDA 42 '(13) 20 It is then possible to use this relation to compare the two difference signals AI and A2. An alternative of the exemplary implementation of the method of FIG. 4 is obtained, this alternative being presented in FIG. 5. It should be noted that we speak of similarity between two signals 25 when the value of J as defined by the expression (13) is considered weak. Thus, it is possible in practice to compare the value J (hocur, homen) with a threshold T, which can be parametered in the same way as for the threshold T described above. This makes it possible to determine if hoa, Y is similar to hmLe /, 500. Instead of keeping only the maximum of the difference signals hie obtained as with the example of FIG. 4, they are all used in order to allow the determination to be made. of an average over several values 501 and thus improve the value of the signal-to-noise ratio.

Otherwise, the defect is considered new, and the average is reset 502. When several occurrences of hocur have been accumulated in ho, ne / n, the signal obtained can be analyzed by deconvolution. It is then possible to determine the location of the intermittent fault.

FIG. 6 gives an example of a reflectogram obtained after application of the method according to the invention. The example given here resumes the case presented with FIG. 1. The dashed line curve 600 gives the difference between the responses with and 1 o without defect. After a high resolution treatment that can be performed by pulse deconvolution, the high resolution curve can be obtained in full line 601. The number of samples n separating the first peak of the origin makes it possible to calculate the distance between the position of the defect in the cable network and the reflectometer. This distance can be determined using the following expression: nT v d = (14), where: T is the sampling period of the acquired signal and v is the propagation speed in the network. 25

Claims (13)

CLAIMS1- A method of detecting faults in a network by reflectometry comprising a step (200) for measuring the high response of the network, a step (201) for detecting defects by analyzing the difference hAau. between this measurement hcuY and a reference response h, ne, n, characterized in that the reference response h, nem is updated using measurements h, stored in the network response. 2- Method according to claim 1 characterized in that a fault of the network is detected (401) by determining if the norm of the difference signal hocuY is less than a predefined threshold T. 3- Method according to any one of claims 1 or 2 characterized in that the norm of the difference signal hocuY is standard type L1 or L2 standard or L-0 standard. 4. Method according to any one of the preceding claims, characterized in that the reference response h, nen is updated when no fault is detected. 5. Method according to any one of the preceding claims, characterized in that the reference response h, nen is updated when a change of state of the network of a duration greater than a predefined value is detected. 6. Process according to any one of the preceding claims, characterized in that the reference response h, nem is updated by using the following expression: k) (k) (k-1) hmem = (1- a) n + ah e, -cur in which the exponent (k) designates the current measurement instant and the exponent (k-35 1) the moment preceding the instant (k); 30a represents the filter forgetting factor lowpass. 7- Method according to any one of the preceding claims characterized in that the threshold T is set using the following expression: T = flNo-2, wherein N is the number of samples of the signal; a-2 is the average variance of the noise; , l3 is a margin factor. 8- Method according to any one of the preceding claims characterized in that when a fault is detected, the difference signal hAau. is deconvolved, the result of the deconvolution being used to locate and characterize the defects. 9- Method according to any one of the preceding claims characterized in that it comprises a step of detecting multiple occurrences belonging to the same defect (500), an average (501) of the difference signals hocuY being determined when several values of water. successively obtained correspond to the same defect, said average being stored for use in locating and characterizing said defect. 25 10- Method according to claim 9 characterized in that two difference signals 41 and 42 are considered to belong to the same defect when an estimator J ~ is less than a predefined threshold T ,, the estimator being determined using the expression next: J] m (at 1, A2) = 30 11-OTDR 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 defects appearing in the network, characterized in that it implements the process according to any one of the preceding claims. 12- System according to claim 11 characterized in that the network is a network of electric cables. 13- System according to claim 11 characterized in that the network is an optical fiber network.