Method of fault diagnosis based on propagation model

• US 6,374,196 B1
• Filed: 03/16/1999
• Issued: 04/16/2002
• Est. Priority Date: 03/16/1998
• Status: Expired due to Fees

• Current Assignee: KDDI Corporation
• Original Assignee: KDD Corporation (KDDI Corporation)
• Inventors: Matsumoto, Kazunori, Hashimoto, Kazuo
• Primary Examiner(s): Grimloy, Arthur T.
• Assistant Examiner(s): Charioui, Mohamed
• Application Number:
  US09/270,664
• Time in Patent Office: 1,127 Days
• Field of Search: 702/181, 702/183, 702/184, 702/185, 702/79, 702/116, 714/25, 714/26, 455/661, 700/79
• US Class Current: 702/183
• CPC Class Codes: H04L 41/0677 Localisation of faults

Abstract

An alarm propagation model of a transmission line is expressed by an equation. A fault portion on the transmission line is estimated by using the alarm propagation model. As a result, it is possible to estimate the fault portion by minimum observation time without lack of precision.

Claims

1. A method of fault diagnosis based on using, as observed information, a model of alarm propagation comprising the steps of:

presuming a fault hypothesis as a time-series model prescribed by a parameter of time delay;

defining a likelihood of the fault hypothesis by a product of a probability density of an observation delay time about an alarm which is observed at a fault occurrence;

deciding the most probable fault hypothesis by comparing a likelihood between the observed alarm time-series and the fault hypotheses; and

estimating a fault portion based on the decision.

2. The method claimed in claim 1 further comprising the steps of:

obtaining AIC (Akaike'"'"'s Information-theoretic Criterion) of each fault hypothesis;

arranging the fault hypotheses in order of small AIC; and

identifying, as the most probable fault hypothesis, the fault hypothesis whose AIC is the minimum.

3. The method claimed in claim 1 further comprising the steps of:

constructing a fault tree which node corresponds to each device and which link corresponds to each connection between the devices;

defining a probability distribution and a probability density function of the observation delay time of alarm, by giving alarm detection delay to each node and giving alarm propagation delay to the link, respectively as alarm delay parameter associated with a route of the fault tree;

estimating, before alarm arrival, a likelihood of the fault hypothesis at a time t when alarm is observed, by the probability density function;

defining, after alarm arrival, as the likelihood of the fault hypothesis at the time t when alarm is observed, a value of the probability density function when alarm arrived; and

defining the likelihood of each fault hypothesis by the product of the probability density function of the occurred alarm.

4. A method of fault diagnosis in a network, which has a plurality of nodes which define communication devices and a plurality of links which define lines between the nodes, based on using an alarm notified to a monitoring device from an alarm generating unit provided for each of the nodes, said method comprising steps of:

pre-determining, by each fault hypothesis, an alarm propagation model with an alarm detecting delay and an alarm propagation delay according to a topology of the network;

wherein said alarm detection delay being a random variable of probability density function of a required time to send an alarm notification from each of the alarm generating units to the monitoring device and said alarm propagation delay being a random variable of probability density function of a required time for a fault to propagate from one of the nodes to another of the nodes along the link;

obtaining a likelihood of each fault hypothesis by convoluting said alarm detection delay and said alarm propagation delay at a certain fault occurrence;

obtaining Akaike'"'"'s Information-theoretic Criterion of each obtained likelihood;

arranging the fault hypotheses in order of small Akaike'"'"'s Information-theoretic Criterion;

identifying, as the most probable fault hypothesis, the fault hypothesis whose Akaike'"'"'s Information-theoretic Criterion is the minimum; and

estimating a fault portion in the network based on said identification.