Data Abstraction Architecture for Monitoring and Control of Lunar Habitats

Transcription

1 09ICES-0239 Data Abstractin Architecture fr Mnitring and Cntrl f Lunar Habitats Sctt Bell and David Krtenkamp TRACLabs Inc, Hustn TX Jack Zaientz Sar Technlgies Inc., Ann Arbr MI 8105 Cpyright 2009 SAE Internatinal ABSTRACT A Lunar habitat will be highly sensred and generate large amunts f data r telemetry. Fr this data t be useful t humans mnitring these systems and t autmated algrithms cntrlling these systems it will need t be cnverted int mre abstract data. This abstracted data will reflect the trends, states and characteristics f the systems and their envirnments. Currently this data abstractin prcess is manual and ad hc. We are develping a Data Abstractin Architecture (DAA) that allws engineers t design sftware prcesses that iteratively cnvert habitat data int higher and higher levels f abstractin. The DAA is a series f mathematical r lgical transfrmatins f telemetry data t prvide apprpriate inputs frm a hardware system t a hardware system cntrller, system engineer, r crew. The DAA als frmalizes the relatinships between data and cntrl and the relatinships between the data themselves. We have cnnected ur Data Abstractin Architecture t a simulatin f a Lunar habitat in rder t test its ability t aid in the mnitring and cntrl functins. INTRODUCTION Space systems are grwing mre and mre cmplicated and cntaining mre and mre sensrs. The large amunt f data generated is verwhelming bth grund cntrllers and autmated cntrl systems. Cping with this sensr data will require develping sftware systems that can iteratively cnvert raw sensr data int mre meaningful, derived data that can be used by cntrllers, bth human and autmated. In this paper we describe a data abstractin architecture that allws engineers t design sftware prcesses that cnvert habitat data int higher levels f abstractin. First, we present the architecture including its cmpnents and representatins. Then we present sme use cases in which the architecture is used t mnitr and cntrl a Lunar habitat. We then describe ur experimental envirnment including a Lunar habitat simulatin and discuss the perfrmance f the data abstractin architecture in implementing the use cases. Next we talk abut related wrk in this area. Finally, we discuss future directins and cnclusins. DATA ABSTRACTION ARCHITECTURE A data abstractin architecture (DAA) frmalizes the relatinship between raw telemetry and derived data. A set f integrated cmpnents and representatins are part f the DAA, including: Data events define the data (bth raw and derived) upn which the architecture perates. Data events can be generated by hardware r sftware and happen asynchrnusly. Data abstractrs, which are sftware prgrams that perfrm a transfrmatin n data events. They cnsume certain kinds f data events and prduce different data events. Sensr event abstractin language (SEAL), which is an extensible Markup Language (XML) schema that defines a grammar fr cnnecting data abstractrs, events, surces and sinks. Data abstractin reasning engine (DARE), which instantiates a SEAL file int a cmputer prgram that cnnects t data surces and data sinks t perfrm abstractins. Develpment envirnment, which is an end-user sftware tl t aid in the cnstructin, debugging and viewing f SEAL files.

2 Tgether these cmpnents prvide a mechanism fr creating mre abstract data frm raw telemetry. Each f them will be discussed in the rest f this sectin. Tempral Alignment: Ouputs a single new data event cntaining a set f events that are all temprally cmmn. DATA EVENTS Data events define the data upn which the DAA perates. Events are hetergeneus, hierarchical, multivalues message and may ccur asynchrnusly. They can be generated frm sensrs, cntrllers r frm data abstractrs. These generatrs are called data surces. Data events are nt simply a number, but instead are cmplicated data structures that can cntain attributes such as cnfidence, timing, prcessing histry, cunts and arrays. Here is an example data event fr a Lunar habitat scenari { sensrs: [ { name: cabin pressure sensr, units: kpa, value: 101 } { name: airlck pressure sensr, units: kpa, value: 85 } average: 93 } In this case the data event cntains tw sensed values, their units and their average. This wuld be prduced frm an averaging data abstractr. DATA ABSTRACTORS Data abstractrs transfrm data events by perfrming prcessing n them. There is n limit t the number r kinds f data abstractrs that can be built. Each data abstractr is implemented in a cmmn prgramming language such as Java. The abstractr must cnfrm t an Applicatin Prgrammers Interface (API) that allws it t receive and generated data events and t be cntrlled. We have implemented the fllwing kinds f data abstractrs: Reducing Average: Cllects a series f values and prduces their average (chice f mean r median) Timing Min/Max: Cllects a series f values and prduces their minimum r maximum value Sampling: Accumulates a buffer f discrete events ver a defined bservatin perid and prduces a single data event. Symbl Prcessing Prpgatin Categrical Binner: Reduce real value data events int symbl categries. Fr example, a temperature input culd be reduced t high, medium r lw. Prpgate n Change: Only generates an utput data event when the input data event has a different value frm the previus event Quiescence: Only generates a data event when the input data event has remained cnstant fr a set perid f time. Mathematical and Lgical Basic mathematical and lgical peratins Several f these will be described in the use cases presented later in the paper. SENSOR EVENT ABSTRACTION LANGUAGE The Sensr Event Abstractin Language (SEAL) is an XML grammar that defines data abstractin netwrks. It encdes the data abstractrs and their parameters, the data events, the data surces and sinks and the cnnectins between all f them. It als defines the data events. The SEAL syntax and semantics are intended t supprt the cmputatinal requirements f NASA telemetry and telemetry management prcesses and align t the cnceptual mdel f thse prcesses held by expert NASA flight cntrl engineers. The language is intended t supprt rapid visual develpment and inspectin f data transfrmatin by skilled engineers wh are typically trained in disciplines ther than sftware engineering. DATA ABSTRACTION REASONING ENGINE The Data Abstractin Reasning Engine r DARE, is a distributed, message-based sftware prgram that takes as input a SEAL file, instantiates the listed abstractrs, cnnects the abstractrs t each ther, the surces, and

3 the sinks. When DARE is finished initializing, data surces are prducing events frm live data, abstractrs are cmputing n thse generated events, and sinks are cnsuming the resultant events. EDITING AND DEBUGGING SEAL The SEAL visual editing envirnment has been develped in Eclipse, a Java pen surce editing platfrm and prvides the expected basic functinality including drag and drp placement f abstractrs, autmatic ruting f message-path lines, lcal save and lad and static validatin f SEAL expressins, cnnectin with the DARE engine fr run-time debugging including remte start and stp, variable-watches, and breakpints. T supprt NASA telemetry applicatins, the editr natively supprts the XML Telemetric and Cmmand Exchange (XTCE) standard descriptins and identifiers fr telemetry data surces. USE CASES We examined tw separate use cases fr the data abstractin architecture. Bth use cases receive sensr data frm a simulated Lunar habitat. In rder t understand the use cases we first describe the simulated lunar habitat. A simulated crew mdule is implemented using mdels described by [3]. The number, gender, age and weight f the crew are changeable. The crew cycles thrugh activities such as sleep, maintenance, recreatin, etc. During each activity they cnsume different levels f O 2 fd and water and prduce CO 2, dirty water and slid waste. The crew mdule is cnnected t a crew envirnment that cntains an mixture f gases (an atmsphere) that they breathe. The initial size and gas cmpsitin (percentages f O 2, CO 2, H 2, O 2 and inert gases) are input parameters. As the simulatin prgresses the cmpsitin f gases in the atmsphere changes. Fr this wrk, BiSIm was cnfigured t cntain a main crew cabin with a vlume f 27 meters cubed and a cnnected airlck with a vlume f 10 meters cubed. There are three cntrllers fr the airlck. One cntrller pulls air ut f the airlck and depsits it int the main crew cabin. Anther cntrller puts air int the airlck frm the main cabin. A third cntrller puts xygen int the airlck frm an xygen stre. Figure 1 shws the habitat simulatin with a main cabin and an airlck (which is greyed ut when at vacuum). Figure 1: The BiSim habitat simulatin BIOSIM The Lunar habitat ECLSS simulatin is based n BiSim mdels develped ver the past several years [4]. BiSim is a discrete-event simulatin f a space habitat that mdels each f the life supprt cmpnents as prcesses that cnsume certain resurces and prduce ther resurces. Fr example, the air revitalizatin system mdel cnsumes air with a specific cncentratin f gases (e.g., high in CO 2 and lw in O 2 ) and pwer and prduces air with a different mixture f gases (e.g., lw in CO 2 and high in O 2 ). Figure 2: A data abstractin netwrk fr detecting a sensr failure CARBON DIOXIDE SENSOR MONITORING In the first use case, we created an abstractin netwrk t mnitr five sensrs that measured the carbn dixide in the crew cabin. Nminally, the sensrs shuld all be reprting the same value (aside frm a bit f nise). Hwever, we planned t fail ne sensr and have a DAA

4 detect and reprt the failing sensr immediately. The netwrk we created is shwn in Figure 2. First, each carbn dixide sensr is sampled t 1Hz. This means each Sampler abstractr is generating ne event every 1 secnd. These Sampler events are all cnsumed by the Tempral Alignment abstractr. This abstractr was cnfigured t cllect the Sampler events until ne event frm each Sampler had arrived. When this happens, a new event was published by Tempral Alignment cntaining the list f events frm each Sampler. The Outliers abstractr wuld prcess this list, lking at each sensr reading fr an anmalus sensr reading. If ne is fund, it is added t a list f utliers. If nt, an empty list is passed. The Outliers fires a new message as sn as it's able t prcess its input. Cunt takes the event frm Outliers and determines the length f the utliers list in its input event. Cunt fires a new event as sn as its able t determine this, which is sent t the Prpagate On Change abstractr. If the cunt value in the message has changed, a new event is sent t the display. If nt, Prpagate On Change discards the event. gals and used utputs frm DARE fr state estimatin. The data abstractin netwrk fr this use case is shwn in Figure 3. HABITAT AIRLOCK CONTROL Fr the secnd use case, we created an abstractin netwrk that was used by a high-level cntrller t manage an airlck fr an EVA. The cntrller uses DARE t signal it when high-level gals have been accmplished. A data abstractin netwrk was built t determine the airlck state by sampling the ttal airlck pressure and the partial pressure f xygen. The airlck culd be in ne f several states: NORMAL: Airlck pressure and xygen levels are the same as the crew cabin PREBREATHE: Airlck has a higher xygen level VACUUM: Airlck has a very lw pressure HIGH: Airlck has higher pressure than the crew cabin LOW: Airlck has a lwer pressure than the crew cabin UNKNOWN: Airlck is nt in ne f the abve states (usually because it is transitining) Several categrical binners are used t utput a symblic state. A quiescence abstractr was used t ensure that the system was in a stable state befre the high-level cntrller tk anther actin. The high-level cntrller adjusted actuatrs in BiSim t accmplish Figure 3: A data abstractin netwrk fr determining the airlck state The high level cntrller executed a prcedure written in the Prcedure Representatin Language (PRL), which is being used by NASA fr the next generatin f prcedures fr human space flight [5]. The prcedure was as fllws:

5 Figure 4: The utput frm the airlck state data abstractin netwrk Get airlckʼs ttal pressure and xygen level t NORMAL Get the xygen level in the airlck t PREBREATHE Wait three hurs Reduce the ttal pressure t VACUUM In the use case, a human cntrller started executin f the prcedure, which cmmanded the airlck cntrllers. The data abstractin architecture prvided the high-level cntrller with state infrmatin. Figure 4 shws a run f this use case. The pressure starts ut lw and is raised first t NORMAL, then t PREBREATHE, then held there fr three hurs and then the pressure is drpped t VACUUM. Each clred vertical line is the data abstractin netwrk generating a new state fr the airlck. RELATED WORK NASA flight cntrllers currently use an ad hc cmputatins r cmps system t cnvert lw-level telemetry int higher-level data. Cmps are limited t single values and must be prgrammed by cmputer experts. NASA flight cntrllers als have a number f tls by which they can match telemetry against limits and shw trends. These tls are difficult t change and limited t running n flight cntrllerʼs cmputers nly. Several autnmus cntrl architectures had explicit data abstractin. One clear example is the Supervenience architecture [7]. The architecture cnsisted f cmmunicating levels in which lwer levels pass data abut the wrld t higher levels. At the same time higher levels pass gals dwn t lwer levels. It is implemented using a blackbard architecture at each level. Each level als cntains its wn unifrm data representatin. The Reactive Actin Packages System (RAPS) [1] had its wn data abstractin cmpnent that was added in the early 90s [6]. This functined mre as a cnceptual netwrk in which data culd be represented at many levels. It was primarily used as a way t cmmunicate with humans. RAPS als led t a pattern recgnitin architecture called the Cmplex Event Recgnitin Architecture (CERA) [2]. It was primarily cncerned with expressing parsers that wuld recgnize cmplex patterns in streams f data. In neither f these cases culd nvice prgrammers create data abstractins. FUTURE WORK We are cntinuing t develp the data abstractin architecture. We are implementing an ability t create cmpsite abstractrs. That is, allwing fr the creatin f abstractrs f abstractrs. This will make it significantly easier t build cmplicated abstractin netwrks.

6 We are explring uses f the data abstractin architecture in NASA's Missin Cntrl Center (MCC). The current methd f ding data abstractin in missin peratins is t write special sftware called cmputatins (r cmps' ) that take in a few values f raw telemetry and create a new telemetry value that is added t the telemetry stream. Cmps are nt an ideal slutin fr several reasns. First, they require sftware prgramming skills n the part f the peratr (r reliance upn sftware prgrammers). Secnd, there is ften a significant delay between recgnizing the need fr a cmp and its instantiatin. Finally, cmps nly cnvert numeric values int ther numeric values and nly ccur at the lwest level f the data stream. This last drawback prevents the creatin f higher and higher levels f data abstractin that all feed ne anther. Our apprach imprves the prcess by allwing cmps t be built and evaluated n-the-fly and in a frmal manner. CONCLUSIONS We have designed and implemented a prttype data abstractin architecture and used it in several simple scenaris. The data abstractin architecture and its assciated SEAL grammar frmalizes the transfrmatin f data frm raw sensry telemetry t higher-level data. Such abstractins are critical in mnitring and cntrlling cmplicated space systems. By standardizing the representatins and prcesses we are creating a tlkit that engineers can use t build data abstractins. Initial cnversatins with NASA flight cntrllers and cntrl engineers has revealed a grwing need fr architectures such as the ne presented in this paper. ACKNOWLEDGMENTS Several prgrammers at Sar Technlgies were invlved in the creatin f the data abstractin architecture, including Kyle Aarn and Dave Ray. Jeremy Frank f NASA Ames Research Center prvided significant insight int data abstractin architecture. Alan Crcker and Brian OʼHagan f NASA Jhnsn Space Centerʼs Missin Operatins Directrate prvided insight int current missin peratins and the requirements fr data abstractin. This wrk is funded under a NASA Ames Research Center Small Business Innvatin Research Grant. David Alfan f NASA Ames Research Center is the SBIR COTR. REFERENCES 1. R. James Firby, An Investigatin int Reactive Planning in Cmplex Dmains, in Prceedings f the Natinal Cnference n Artificial Intelligence, Fitzgerald, W., R. J. Firby, A. Phillips, and J. Kairys, Cmplex Event Pattern Recgnitin fr Lng-Term System Mnitring, Prceedings f the AAAI 2003 Spring Sympsium n Human Interactin with Autnmus Systems in Cmplex Envirnments, (available frm AAAI Press at Gudarzi, Sara and K.C. Ting, Tp Level Mdeling f the Crew Cmpnent f ALSS, in Prceedings f the Internatinal Cnference n Envirnmental Systems (ICES), Sciety f Autmtive Engineers (SAE), Krtenkamp, D., and Bell, S., Simulating Advanced Life Supprt Systems fr Integrated Cntrls Research, in Prceedings f the 33rd Internatinal Cnference n Envirnmental Systems (ICES), Sciety f Autmtive Engineers (SAE), Krtenkamp, D., R. Peter Bnass and Debra Schreckenghst, Managing Life Supprt Systems Using Prcedures in Prceedings f the 37 th Internatinal Cnference n Envirnmental Systems (ICES), Sciety f Autmtive Engineers (SAE), Martin, C. E. and R. J. Firby, Generating Natural Language Expectatins frm a Reactive Executin System, Prceedings f the 13 th Cgnitive Sciety Cnference, Spectr, L. and J. Hendler, Planning and Reacting acrss Supervenient Levels f Representatin, Internatinal Jurnal f Intelligent and Cperative Infrmatin Systems, Vl. 1, N. 3, CONTACT The authrs may be cntacted thrugh at sctt@traclabs.cm.