Keywords

1 Background

According to IEC 61513 [1], the faults and errors should be fully detected, and sufficient and correct fault diagnosis information should be provided. Therefore, The self-diagnostic function is very important for the I&C system in NPPs. The design of the self-diagnostic function directly affects the maintainability of KDS, and can effectively improve the safety of NPPs [2,3,4,5].

The FitRel platform is a FPGA-based product developed by China Techenergy Co. Ltd., and has been formally applied in ACPR1000 NPP [6]. However, there is no precedent and experience to follow for KDS based on FPGA technology. Therefore, it is urgent to design a set of self-diagnostic solutions suitable for FPGA technology. Based on the practical experience in the FitRel product development, and maintainability design theory, this paper raises a self-diagnostics solution suitable for KDS in NPPs.

2 Methodology of Self-diagnosis

The system self-diagnosis function is based on the basic principles of self-diagnosis design, which includes 3 steps.

Step 1: Completeing the classification of the fault, and determining the severity of the impact of the control station function where the faulty device is located.

Step 2: Determining the fault diagnosis method based on the severity of the fault.

Step 3: Fault indication for the operation and maintenance personnel (Fig. 1).

Fig. 1.
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Methodology of self-diagnosis diagram

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For the FPGA based platform, There are many fault modes that need to be defined, and for the fault diagnosis design and indication, there are some principles that need to follow.

3 Self-diagnosis Design

Through the failure mode effects analysis (FMEA) of KDS system [7], The diagnostic measures, handling measures and alarm indication mechanisms of the failure modes are designed based the failure mode effects.

Especially, because the FPGA is very complex, and the self-dignosis for FPGA is not easy to analysis and design, so this paper difines FPGA failure as an special part, and the self-diagnosis diagram can be shown in Fig. 2.

Fig. 2.
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Self-diagnosis diagram of KDS

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3.1 Fault Classification

Fault classification is to classify the fault according to the severity of the fault, and the fault level will be the basis for the fault alarm indication. In this document, the severity of the faults will be judged based on the severity of the impact of the fault modes on the function of the control station where the fault device is located.

The failure modes are shown in the following Table 1:

Table 1. List of failure modes
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3.2 Fault Diagnosis Design

In order to cover the faults of the KDS system to the greatest extent, the fault diagnosis design principles are as following:

  1. 1)

    The overall design principle follows IEC 60671 [8], self-diagnosis shall cover all diagnosable faults;

  2. 2)

    In order to prevent the system from spurious actuation, the fault handing shall led to fail-safe, and mainly indicate fault information in detail.

The self-diagnosis of the KDS system include two parts, the self-diagnosis function of the FitRel platform and the self-diagnosis of the engineering application. The self-diagnostic function of the FitRel platform refers to the inherent fault diagnosis measures of the FitRel product; the application self-diagnostic measures are designed according to specific engineering applications.

Platform self-diagnosis measures are shown in Table 2 For FPGA failure, this paper involes 7 self-diagnosis measures to keep all the dignosable failure mode can be detected and handled.

Application self-diagnostic measures are shown in Table 3.

Table 2. Platform self-diagnosis measures
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Application self-diagnostic measures: Application self-diagnostic measures are aimed at failure modes related to the application, and are a supplement to platform self-diagnostic measures. The application self-diagnostic measures of KDS system in ACPR1000 NPP are as follows.

Table 3. Application self-diagnostic measures
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3.3 Fault Indication

Principles of alarm indication:

  1. 1)

    Indicate fault information on the human-machine interface;

  2. 2)

    The failure information display needs to be consistency with different human-machine interface.

After the fault is diagnosed, each cabinet of the KDS system will give an alarm indication in the following three ways:

Main control room alarm indication: alert the operator and maintenance personnel of KDS failure in the first time;

Local display alarm indication: the fault diagnosis information is transmitted to the LOC-VDU through the network to indicate the faulty equipment;

Local cabinet indication: process the fault information with turning off the cabinet lamp and other module lamps, and help maintenance personnel locate the faulty cabinet (Fig. 3).

Fig. 3.
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Fault indication flow diagram

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4 Test

The test results are shown as follow in KDS in Yangjiang 5&6 NPP and engineering prototype. All the failure mode of KDS can be detected and indicated, and if the FPGA failure, the output of failure module can be set as fail-safe. There is no spurious trip in KDS (Table 4).

Table 4. Test results
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5 Conclusion

This paper presents a self-diagnostic solution for the KDS in ACPR1000 NPP. The self-diagnostic solution draws on the best practical experience in the field safety I&C. At present, the self-diagnostic solution has been applied in Yangjiang 5&6, The Hongyanhe 5&6 project, and has undergone testing and verification, including R&D testing, in-plant testing, owner’s factory commissioning. The results show that the solution can cover all diagnosable faults of the FitRel platform based on FPGA technology, can indicate the diagnosis information in real-time, and can provide sufficient information for the daily maintenance of nuclear power plants. After adaptive adjustment, it can meets the requirements of AP1000, EPR reactor-type NPP, and has broad application prospects.