Methods and Technologies for Enhancing and Optimizing Power Plant Inspection Procedures

Kamen Kanev, Zixue Cheng, Nikolay Mirenkov Department of Computer Software, The University of Aizu

Tsuruga, Ikkimachi, Aizu-Wakamatsu City, Fukushima-ken, 965-8580, Japan kanev|z-cheng|nikmir@u-aizu.ac.jp

Abstract

This paper considers different methods and approaches for improving power plant inspection procedures through innovative technological means. Main objectives are to provide timely, context dependent assistance and advice to human inspectors of power plant facilities, to minimize human errors and to increase inspection efficiency and reliability. A solution based on spatial awareness methods for inspector localization, registration and tracking through remote sensing of RFID tags and digital codes embedded in the surrounding environment is proposed. Possible extensions for industrial inspection robots are briefly discussed and potential applicability in nuclear power plant inspections is revealed. 1. Introduction

Reliability and safety of power plant facilities largely depend on inspection procedures that are carried out at scheduled intervals by dedicated personnel. In most cases inspections are conducted following specialized inspection charts, written instructions and checklists, where inspection results are recorded by hand. At some locations notebook computers are used to assist the inspection process and to provide for temporary storage of inspection results.

Traditional paper-based inspection procedures are not prone to human errors. In fact it is entirely up to the inspector to read, understand and follow the instruction charts in an appropriate way so misinterpretation could easily happen, especially for new, relatively inexperienced personnel. Since a simple mismatch between the inspection chart and the inspection spot may lead to severe consequences, different physical means such as marking plates, labels, matching keys, etc. are in use. Such methods however only attempt to minimize human errors by forcing inspectors to pay

more attention to specific details and thus provide no guarantee that the inspector is at the right spot, looking at the right chart and following the right instruction plate.

Notebook computers as currently applied are simply substituting existing printed inspection instruction materials and generally do not provide augmented functionality or enhancements in terms of safety and reliability. This is mainly due to the fact that used notebook computers are not online and have no position sensing capabilities so more advanced functionality and inspector assistance remain out of reach. In fact, with current inspection procedures it is next to impossible to guarantee that an inspector has actually gone to a prescribed inspection spot and has carried out a thorough inspection.

In the following sections we will consider different methods and functionality that could help increase power plant safety through automatic verification and enforcement of certain inspection steps and procedures. 2. Spatial awareness and inspector

localization

Inspecting a power plant is a complex, time consuming task that is carried out on a regular basis and is therefore a very good candidate for optimization. Benefits from any improvements in terms of increased reliability, inspector performance and time efficiency, etc. will cumulate with every repeated inspection. However, content and procedures of scheduled inspections differ from inspection to inspection. For example basic inspections at a limited number of checkpoints are conducted more often than thorough, detailed inspections with many checkpoints. For practical reasons, when a detailed inspection is scheduled it would also include the basic inspection steps as a subset. From the inspector perspective the basic and the detailed inspection procedures appear

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interleaved and carried at the same time, becoming rather difficult to remember.

To illustrate the inspection procedure interleaving we will use Fig.1 where weekly, monthly and yearly inspections are included. Inspection spots are denoted by circles and then linked by arrows that determine the visiting order of the inspection spots. By following arrows of specific types e.g., solid, dashed or dotted, one can easily recognize the weekly, monthly and yearly inspection paths. Please note that some inspection spots are always visited (e.g. A,B,C,G) while others are only visited once a month or once a year (e.g. E and D,F). Whether a specific inspection spot should be visited or not during a particular type of inspection depends on the inspection content, denoted by numbers in parentheses. Each number stands for a multiplicity of inspection sheets detailing different inspection steps and possibly backed by human and machine readable labels, etc.

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(1) weekly (2) monthly (3) yearly

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Fig.1. Interleaving of inspection procedures. One possible avenue for inspection optimization is to

gather spatial information about the inspector position in respect to the inspection spots and use it for context sensitive inspection guidance and verification. For example customized partial views of the chart including inspection step details could be automatically generated and shown on a portable screen. Audio or visual directions from one to another inspection spot can also be presented, and when a new inspection spot is reached the inspection chart for that specific inspection spot can be automatically activated. This way the entire inspection can be adequately planned and ample time for conducting all the necessary inspection procedures will be ensured.

In principle standard GPS functionality built into a PDA or a notebook PC can be used for position tracking. This however is impractical for electric power plants, where very strong electric and magnetic fields, present in the vicinity of the inspected equipment,

interfere with the GPS signals. Therefore spatial position and orientation should be preferably derived only based on local data embedded in the surrounding environment. It may be possible to use markers or barcodes for position tracking, but reliability and security of such a system is at risk since barcodes and markers stand out and are easy to damage and reproduce. To overcome this kind of difficulties we suggest applying surface based interaction methods [1] and using the Cluster Pattern Interface (CLUSPI®) [2,3], RFID tags [4] and related technologies [5].

In most cases real-time tracking of inspector movements may be unnecessary, while the inspector presence or absence at a particular inspection spot still needs to be reliably recorded for providing context sensitive assistance and augmented inspection functionality. This in fact can be easily achieved if the inspector registers when he reaches the target inspection spot. For reliability and security reasons such a registration should not depend on the inspector will alone and therefore should be based on automatic extraction of some unique data associated with the specific inspection spot.

One possible approach could be embedding of different RFID tags that can be remotely sensed and uniquely identified at each inspection spot. To explore this idea we have assembled the portable system, based on a TOSHIBA GENIOe PDA with built in WiFi and Bluetooth connectivity shown in Fig.2. For remote spot identification our system uses a compact flash sized RFID reader/writer, inserted in one of the PDA slots. We have conducted initial experiments in a controlled laboratory environment and we believe that next stage should be feasibility investigation and field test to ensure that reliable spot identification could be achieved under the severe environment conditions at an electric power plant.

Fig.2. A portable Pocket PC based RFID scanner.

As an alternative or in combination with RFID tags [4] the unobtrusive CLUSPI® surface encoding method [2,3] could also be used. In contrast to barcodes,

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CLUSPI® encoding remains almost invisible for the naked human eye, it can be blended with equipment surfaces at or near the inspection spots, and it is not easily reproducible [1]. Standard printing technologies can be used for creating inexpensive transparent labels with CLUSPI® surface codes that can be directly applied to the inspected equipment at appropriate places. For more durable solutions laser marking of machine parts and surfaces or other permanent marking technologies could also be applied.

3. Computer assisted inspections

Once the inspector reaches a specific inspection spot the corresponding computer assisted inspection procedure can be activated. This may be done automatically through inspector position tracking or inspector position registration as explained above. Alternatively the inspector himself can manually activate the computer-assisted inspection procedure, by directly scanning a registration label at the inspection spot. For illustration we give a simplified description of an inspection procedure applicable to the turbine inspection spot shown on Fig.3.

Fig.3. Inspection spot at a hydroelectric power

plant. In Fig.3a a sample inspection spot on the top of a

turbine at a hydroelectric power plant is shown. The inspector has to climb the stairs on the opposite side of the turbine in order to reach the actual inspection spot and then has to open the inspection hatch as shown in Fig.3b. Then inspection is carried out as shown in Fig.3c, where the inspector conducts visual and manual

checks of specific components in the turbine body following a predetermined inspection chart.

For a computer assisted inspection appropriate environment enhancements must be provided. First of all, inspection spot identification information should be supplied and this can be, for example in the form of a label attached to the turbine surface in the vicinity of the inspection spot. The human readable visual content of the label can be some indicative text e.g. "Inspection Point No.5" or it can contain more detailed inspection descriptions as shown in Fig.4a and even diagrams.

(a) (b)

Fig.4. Sample inspection spot labels In addition to the human readable content, the label

can be augmented with machine-readable data through a RFID tag or by CLUSPI® based digital encoding that covers the label surface and blends with the label visual content. Large, easy to spot labels can be used so that even relatively inexperienced inspectors can easily locate them. Once the inspector approaches the inspection spot, a portable computing device with an RFID scanner and image input capabilities could be used to conduct a partial scan of the label surface. This leads to immediate recognition and decoding of the digitally encoded data associated with the label resulting to label identification and consequent determination of the precise position and orientation of the device in respect to the label. Based on this data, augmented functionality and inspection assistance can be easily provided. For example, if an inspector scans the area of the label describing the inspections spot (in Fig.4 enclosed in a dashed rectangle for clarity) the inspection checklist for that specific inspection spot can be automatically shown and activated on the portable computing device. On the other hand, scanning the area on the label enclosed in the dotted rectangle however, may lead to a schematic or even an AV reminder of the hatch opening procedure.

Specialized hardware that is carried by the inspector and used for objective checks and measurement of specific parameters can be connected and directly controlled through software installed in the handheld

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computing device. For example when the second line "2.Listen for sound anomalies" of the label shown in Fig.2a is scanned, specialized sound analysis software can be activated to input and evaluate sound samples from a microphone attached to the handheld device. Similarly, image input can be used for taking pictures that can be processed, analyzed and matched to a database with reference images for inspector assistance.

For image-based experiments we used the WILCOM WS003SH model in Fig.5 that provides a full PDA functionality with WiFi and mobile PHS connectivity and includes a 1.3 Mpixel CMOS camera. With this portable device, records could be created interactively during the inspection process and stored locally in the device for late uploading through a wireless or USB connection. We have verified that inspection assistance actions can be linked to different label areas and matched to the human readable label content whenever needed. This approach can be directly extended to support registration of inspection results if functional buttons similar to those shown in Fig.4b are added. In this case the inspector records the inspection results by scanning appropriate areas of the label e.g. the green area for NOTHING ABNORMAL, the blue area for SERVICE REQUIRED and the red area for URGENT ATTENTION, etc.

Fig.5. Image input with WS003SH Since laser marking technologies enable direct

embossing of machine components, it may be possible to provide inspection assistance even without printed labels. In such cases, scanning a specific spot on a marked machine component can serve as a proof of a properly conducted visual inspection.

The proposed image based inspection assistance method augments traditional human computer interactions in a significant way and opens possibilities for exploring point-and-click functionalities that require no physical keyboards and traditional input. Further, direct partial scanning of digitally enhanced surfaces in combination with a reliable audio interface can bring to

new types of inspection assistance devices that require no traditional screen based interfaces.

While the systems in Fig.2 and Fig.5 have been used to verify different aspects of our method, a fully functional PDA based system is still difficult to implement due to some hardware limitations and incompatibilities. Therefore, for experimental purposes we have focused on integrating the RFID and the CLUSPI® technologies within a portable notebook based system. For this purpose we have combined a RFID scanner and a CLUSPI® optical input device into the prototype handheld tool shown in Fig.6.

Fig.6. A combined RFID/CLUSPI® USB scanner When connected through USB to a note PC the

prototype registers as two functionally distinct devices, namely a modem corresponding to the RFID device and a web camera, corresponding to the CLUSPI® device. We are currently working on combining the drivers and the control software of the two devices into a single, integrated application. 4. Inspection robots and camera networks

Replacing human inspectors by industrial inspection robots is not just a cost saving activity. There are many situations, for example at nuclear power plants [6] and other facilities, where inspections have to be conducted in environments hazardous for humans. This is where remote controlled or autonomous industrial inspection robots become indispensable.

Ensuring good spatial awareness for industrial inspection robots remains quite a challenging task. In [6] for example, a nuclear power plant inspection robot vision is considered and environmental markers for visual attention control are implemented.

We believe that our approach, although originally devised for assisting human inspectors, could also be applied for industrial inspection robots. Indeed, surface

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based spatial awareness for mobile robots has been already discussed in some detail in [7] and a CLUSPI® based position and orientation sensing implementation for remote controlled model cars has been reported in [8]. In principle, CLUSPI® carpet encoding could be applied to the floor and other surfaces at the power plant and thus used for position and orientation sensing in a similar way. Further enhancements could be introduced through the camera-based surveillance networks for remote observation and control, already available at most of the power plants. 5. Conclusion

We have proposed a novel approach for context sensitive guidance, assistance and verification of human inspector activities at electric power plant facilities. An innovative spatial awareness method, based on RFID and CLUSPI® technologies is used for inspector localization and for sensing of inspection activities. This provides for timely, context dependent inspector support that helps reduce human errors, increase reliability and improve inspection efficiency.

Applicability of our approach could be extended to human inspections of other types of facilities and even to inspections conducted by industrial robots. To facilitate this process we are currently designing a specialized software system for visual interaction supports. The system will allow management of inspection spot visuals, inspection sequencing and spatial path planning, environmental code mapping and embedding of references for inspection assistance and verification.

Acknowledgements: We would like to thank TEPCO management for the financial support and the access to the power plant facilities. We also thank all personnel that were involved in the power plant visits, explanatory meetings and consequent discussions. References [1] Kanev, K., Kimura, S., Direct Point-and-Click

Functionality for Printed Materials, The Journal of Three Dimensional Images, Vol. 20, No. 2, pp. 51-59, 2006.

[2] Kanev, K., Kimura, S., Digital Information Carrier, JP, Patent No 3635374.

[3] Kanev K., Kimura S., Digital Information Carrier, WO 2005/055129, International Patent Application Published under PCT, WIPO.

[4] Hassan, T., Chatterjee, S., A Taxonomy for RFID, Proceedings of the 39th Annual Hawaii International Conference on System Sciences, Vol. 8, 2006.

[5] Krahnstoever, N., Rittscher, J., Tu, P., Chean, K., Tomlinson, T., Activity Recognition using Visual Tracking and RFID, Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05), Vol. 1, pp. 494-500, 2005.

[6] N. Kita, Visual Attention Control for Nuclear Power Plant Inspection, Proceedings of the 15th Internal Conference on Pattern Recognition (ICPR2000), September 3-8, 2000, Barcelona, Spain.

[7] Kanev, K., Kimura, S., Surface Based Spatial Awareness for Mobile Robots, Proceedings of the Eleventh International Symposium on Artificial Life and Robotics AROB'06, Beppu, Jan. 23-25, 2006.

[8] Kanev, K., Mirenkov, N., Urata, A., Parking Simulation and Guidance in a Model Environment, Proceedings of the Japan-China Joint Workshop on Frontier of Computer Science and Technology (FCST2006), Aizu-Wakamatsu, Nov. 17- 18, 2006.

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