NASA Technical Memorandum 106980

/._".... IZ

In-Orbit Calibration of a S AMS Triaxial

Sensor Head

Louis S. Chestney

Aerospace Design & Fabrication, Inc.

Brook Park, Ohio

and

Ronald J. Sicker

Lewis Research Center

Cleveland, Ohio

June 1996

National Aeronautics and

Space Administration
IN-ORBIT CALIBRATION OF A SAMS TRIAXIAL SENSOR HEAD

Louis S. Chestney

Aerospace Design & Fabrication, Inc.

Brook Park, Ohio 44142

and

Ronald J. Sicker

National Aeronautics and Space Administration

Lewis Research Center

Cleveland, Ohio 44135

SUMMARY

This report describes the results of in-orbit calibration data collected for a Space Acceleration Measurement

System (SAMS) Triaxial Sensor Head (TSH) and the methods used to process the data for bias and gravity levels.

INTRODUCTION

Space Acceleration Measurement System (SAMS) Triaxial Sensor Heads (TSH's) are designed to measure lowlevel vibrations in a microgravity (lag) environment. Each TSH is composed of three identical circuit paths containing a Sundstrand QA-2000 accelerometer connected to a 1-pole combination low-pass filter and preamplifier,

followed by a 7-pole low-pass filter then an analog to digital converter (ADC). Each sensor outputs a signal that is

of the form M = G + B, where M is the magnitude of the data measured and recorded by the system, G is the magnitude of the input acceleration, and B is the magnitude of the bias of the sensor head electronics (particularly the

accelerometer bias). This equation can be manipulated in units of counts, volts, or I.tg's. Since actual measurements

are recorded in counts, an implicit conversion factor from counts to volts Cv, and a second conversion factor from

volts to lag (S) is necessary. For purposes of this report lag will be used in calculating the values of this equation.

The value of M is the quantity measured in space while the values of S and B are derived from a fourth order

equation as a function of temperature. C v is the conversion factor of 10 V/65536 counts. The coefficients used in the

equations for bias and scale factor are obtained from measurements obtained during a calibration procedure performed on Earth. Several errors arise during this process (ref. 1). Many of these errors arise because it is being done

in the 1-g environment of Earth while the SAMS TSH has been designed to operate in a lag environment. The procedure described in the following section was designed for the dual role of improving the current SAMS measurement

by reducing bias error and also characterizing the accuracy of measurements that may be obtained by using a similar

automated procedure in the SAMS-II, the follow-on advanced SAMS unit.

METHOD

During the Space Shuttle mission STS-60, SAMS unit A flew in the Spacehab-2 middeck augmentation

module. The SAMS calibration procedure was performed on a 5-Hz TSH at MET 005/11:12 (DDD/HH:MM) to

005/11:30, and again at MET 006/00:56 to 006/01:06 as part of SAMS nominal operations. The operation performed

at MET 005/11:12 to 005/11:30 was scheduled preflight, and was performed during a "semi-quiet" time, while the

operation performed at MET 006/00:56 to 006/01:06 was an in-flight adaption done while other operations were

going on, particularly movement of the Canadian robot arm. A quiet time is required to ensure that all accelerations

are symmetrical to avoid introducing a positive or negative bias in the data.

The SAMS calibration procedure consisted of rotating the SAMS TSH _ radians in the YZ-plane and collecting

data for a few minutes. A second set of data was obtained when the TSH was rotated back to its original orientation.

Rotation of the TSH in the YZ-plane provides data for Y- and Z-axis calibrations while maintaining X-axis data as a

control.
Themathematical rational for this procedure is as follows. With the TSH oriented at 0 radians, measurement M 0

is described as

M o = G O+ B 0 (1)

where G O is the constant acceleration, and B 0 is the DC bias of the system at 0 radians. With the TSH oriented at rc

radians, measurement Mrc is described as

Mrc = G_ + B1 (2)

where G_ is the constant acceleration and B 1 is the DC bias of the system at _ radians. If the time duration between

data sets M 0 and Mrc is kept sufficiently small, then bias B 0 equals bias B 1- Furthermore, acceleration G O equals

negative G n. Thus, equation (2) becomes

Algebraic manipulation yields the following:

Mn = -G O+ B 0 (3)

GO=(Mo (4)

B--(MO (5>

APPLICATION

Processing of the SAMS data was performed for the time slices containing each of the TSH orientations. Processing consisted of first sorting the raw data into sequential samples for each axis. The data sequence was then converted into units of gravity (G) using the ground-based calibration model for scale factor, calculated at the

temperatures measured in flight during each facet of the procedure.

The data collected at MET 005/11:12 to 005/11:30 were used to analyze data at the transition when the TSH

was rotated back to its initial position, 1 while the data collected at MET 006/00:56 to 006/01:06 were used to analyze data at the transitions when the TSH was rotated to its new position as well as back to its initial position.

Figure 1 shows acceleration data collected between MET 006/00:47 and MET 006/01:07 for the shuttle Y-axis.

The vertical axis is in units of microgravity (lag), which is 10--6Earth gravity units, while the horizontal axis is in

units of seconds from the start of the data file being shown. The large spikes in the center and right of the graph

were caused by the rotation of the sensor head during the calibration procedure. The first of these two spikes

occurred when the TSH was rotated _ radians from the normal position (shown between points B and C), while the

second spike occurred when the TSH was rotated back to its normal position of 0 radians (shown between points F

and G). The spike at time B-C corresponds to the time period labeled as time 2 while the spike at time F-G corresponds to the time period labeled as time 3 in the tables in this report. The spike at the left of the graph is a disturbance prior to the beginning of the procedure that has no effect on the procedure.

These data were converted from units Of SAMS counts into units of G by multiplying each sample by its ideal

scale factor. The ideal scale factors were computed for each axis and time period as a function of the average temperature and amplification level during the measurement period. These amplification levels were 100, 100, and 10

for the X-, Y-, and Z-axes, respectively. The average temperatures are given in table 1, while the average scale factors are given in table 2. Times labeled as forward are the times when the TSH was oriented in the direction it was at

during the predominant portion of the flight, while times labeled as reverse are times when the TSH was oriented in

the direction rotated x radians in the YZ-plane. Analysis was performed on segments of data just before the TSH

ISAMS data just prior to the TSH rotation at MET005111:12to 005111:30were not available because both of SAMS opticaldisks were filled

prior to implementationof the calibrationprocedure.
was rotated (represented by data segments A-B, and E-F), and just after the TSH was rotated (represented by data

segments C-D, and G-H). Selection of time segments that were close together in time was a high priority in order to

ensure that the basic acceleration environment remained as constant as possible.

Figure 2 shows the time slice of data used for calculating the Y-axis semiprocessed (data converted to lag without applying the bias compensation) mean for the time segment from MET 006/00:56:24 to MET 006/00:57:24. This

time period occurred just after the sensor head was rotated _ radians.

Table 3 shows the mean acceleration values obtained at each of the three TSH orientation transitions. Indicated

time 1 is at MET 005111:30, time 2 is at MET 006/00:56, and time 3 is at MET 006/01:06. Table 4 shows the calculated ambient acceleration for the Y- and Z-axes of the TSH at the respective time intervals. Study of these data

indicates a reasonable correspondence between the ambient acceleration measurements at each time interval for both

axes. The values displayed in table 4 were calculated with equation (4). The values displayed in table 5 were calculated with equation (6).

Because the sensor was rotated in the YZ-plane, G Oand G_ in equations (1) and (2) are equal for the X-axis.

Thus, equation (6) is obtained by subtracting equation (2) from equation (1).

(M0 -MTr) = [G0 +Bo-(G 0 + Bo)] = 0

(6)

This value should thus be zero. Since we know the actual value for the X-axis measurement is zero and the

measurements and calculations were performed in the same way for the X-axis as for the Y- and Z-axes, we can use

the X-axis as a control for the Y- and Z-axes. Specifically, the errors associated with the X-axis measurements are

typical of the bias and ambient gravity measurement error of all axes.

The errors associated with the X-axis in table 5 are not of great concern for ambient gravity measurements when

the environment was noisy because the values of acceleration for both the Y- and Z-axes are an order of magnitude

greater than that of the bias and ambient gravity measurement error reported for the X-axis. This may not be the case

when the environment is quiet, however. These errors are never a problem with the bias measurements because the

errors are always at least two orders of magnitude or less than the bias as is shown in table 6.

Table 6 shows the calculated biases (using eq. (5) and data from table 3) for the Y- and Z-axes of the TSH at the

respective time intervals. The X-axis data are, however, invalid because the sensor was rotated in the YZ-plane.

Because of this, G O and Grc in equations (1) and (2) are equal. Thus, equation (3) is invalid and equation (5) for the

X-axis calculation becomes

B'= (M 0 + Mn)/2 --_ (G O + Bo + G O + B0)/2 _ G O+ B 0 = M 0

(7)

This equation is only true when the acceleration GO= 0 and thus it provides no useful information to us.

A closer look at the data in table 6 shows a close correspondence for the Y- and Z-axes. Study of these data

indicates a reasonable correspondence between the bias measurements at each time interval for the Y-axis, and for

the Z-axis between times 2 and 3, which were close together. The difference in Z-axis bias at time 1 can be associated with many factors. Two possible factors are a general difference in environment between time 1 and the set of

times 2 and 3 for a combination of Z-axis temperature and acceleration. Additional factors are a change in the

environment during the procedure, making it invalid, or an actual sensor bias shift. The Z-axis temperature had an

inherent uncertainty due to the way the data was collected, however, the Y-axis temperature differed by only 0.4 °C

between the two data set groups. The temperature profile did show a change in the slope in the middle of the procedure however. This is illustrated in figure 3. This factor would have introduced the effect of sensor hysteresis on

the calculation. This effect would also affect the ambient acceleration measurement. The method just described

works well in an ideal situation but has drawbacks in the real world. Of primary concern is how to use this data to

improve our acceleration data, while compensating for bias changes induced by changes in the temperature of the

accelerometers.

In order to incorporate the on-orbit-bias-measurement calibration into the flight data, this procedure needs to be

repeated at various temperatures. This may be impractical. An alternative approach would be to adjust the groundbased calibration data by an amount determined from the in-flight calibration method. This can be accomplished by

comparing the in-flight bias calculation with the bias calculated with the ground-based calibration model at the same

temperature, then shifting the ground-based bias model to fit the in-flight measured bias.
A method of checking the accuracy of the ground-based bias calculation is to apply the complete processing

model, including bias compensations to the flight data, then repeat the process for determining the bias as it was

performed above. The resultant bias derived from these calculations would be zero if the ground-based bias compensation model was perfect. Any difference represents the error in the ground-basod bias model. Towards this goal

processing of the data was done using zero offset correction, 2 as well as bias, scale factor, and axis misalignment ,

processing. 3

Figure 4 shows the processed acceleration data collected between MET 006/00:47 and MET 006/01:07 for the

shuttle Y-axis. As with the semiprocessod data in figure 1, the large spikes in the center and right of the graph were

caused by the rotation of the sensor head during the calibration procedure. As previously, analysis was performed on

segments of data just before and after the TSH was rotated. Figure 5 shows the time slice of data used for calculating

the processed Y-axis mean for the time segment from MET 006/00:56:35 to MET 006/00:57:15.

Table 7 shows the mean acceleration values obtained at each of the three TSH orientation transitions. Times 1

to 3 and orientations of forward and reverse are the same times and orientations used in the previous tables. The

term unfiltered is used to distinguish this data from data in the next section that is low-pass filtered.

Table 8 shows the calculated ambient acceleration for each axis of the TSH at the respective time intervals.

Study of this data also indicates a reasonable correspondence between the ambient acceleration measurements at

each time interval for both the Y- and Z-axes. The errors associated with the X-axis in table 9 are of similar magnitude to those shown in table 5.

Table 10 shows the calculated model-bias errors for the Y- and Z-axes of the TSH at the respective time intervals. While the values of calculated model-bias error in table 10 are far smaller then the calculated absolute bias

calculations in table 6, the numbers in table 10 are at least an order of magnitude larger than the bias measurement

errors for the procedure shown in table 9, and are therefore not a problem. Similar to the absolute bias measurements

made previously, the method just described has some drawbacks as well. Of particular concern are changes in the G

environment during the calibration procedure. One disturbance of particular concern was movement of the Canadian

robot arm when our calibration procedures were being performed.

By definition the bias is an approximately constant signal. Because of this, our results should be improved by

filtering out the higher frequency disturbances that may cause asymmetrical accelerations. When one is filtering the

data for analysis, special care must be taken to avoid transient effects caused by the response time of the filter to

steplike inputs. These effects were avoided in our processing by ensuring that a sufficient number of data points had

been processed through the filter before the analysis was performed.

Figure 6 shows the same data as in figure 4, after it has been filtered by a low-pass filter with a pass band of

0.01 Hz. As with the previous data, the large spikes in the center and right of the graph are caused by the rotation of

the sensor head at times 2 and 3 during the calibration procedure.

Figure 7 shows the subset of data used for calculating the X-axis filtered mean. The time period shown is the

same used for the unfiltered mean in figure 5.

Tables 11 to 14 show results of the same calculations in tables 7 to 10, except that the calculations were performed on data that have been low-pass filtered at a pass band of 0.01 Hz. Comparisons between the filtered and

unfiltered data for ambient gravity level can best be done on the controlled TSH axis X because this actual value is

known to be zero because the X-axis sensor was not rotated (refer to eq. (6)), while the value for the Y- and Z-axis

values are unknown. Comparison of the X-axis values show that the average filtered magnitude is 0.3718 lag versus

0.3682 l.tg for unfiltered data, thus a slightly better answer is obtained from the unfiltered data. The sum of both data

sets indicates that the accuracy of the data is _4-0.6142 lag as determined by the largest difference from zero. A value

of 0.2491 gg is more realistic, however, as will be discussed later in this report when an analytical accuracy is presented with the t-statistic used as the basis.

Comparisons between the filtered and unfiltered data for calculated model bias error can only be done on the

measured TSH axes Y and Z because no information was obtained on the controlled X-axis. Comparison of the

2Zero offset processinginvolvessubtractingoutthebias of the SAMSelectronics.Zerooffset datais collectedby disconnecting the QA-2000

accelerometer from the SAMS electronics and connecting the input wiresto each other to create an input voltage potential of 0 V. The difference

obtained by averaging these data samplesis then subtracted from each data sample.

3Axismisalignment correction involves correcting the data for each axis from the cross talk of acceleration whose sourceis from a direction

perpendicular to the respective axis. This is accomplished by a fourth order equation, but its effects are small in comparison to bias and scale

factoreffects.
Y-axisvaluesshowthathestandarddeviationis3.326lag for the filtered data versus 3.079 lag for unfiltered data,

thus a slightly better answer is obtained from the unfiltered data. When considering the effect of sensor hysteresis in

the analysis, we get considerably better results of 0.092 lag for filtered data versus 0.172 lag for unfiltered data. 4

The effects of using data that have been corrected for angular misalignment were also considered. This leads to

some unique problems. Since bias is corrected before angular misalignment, we should have done the calculations ,

on data that were not corrected for angular misalignment. This would have given us bias-free data to correct for

angular misalignment. The problem with this is that the bias correction does not take measurement cross talk into

account, unless the angular misalignment is taken into account. If the bias errors are calculated after correcting the

data for angular misalignment, then the corrections must be applied after correcting the data for angular misalignment. This is not how we processed SAMS data, however.

Fortunately the data that were not corrected for angular misalignment provide slightly better results as shown in

tables 15 to 18. Time IN represents calculations performed on the data at time 1 which were uncorrected for angular

misalignment. The designator F represents filtered data, while U represents unfiltered data.

CALIBRATION MODEL EFFECTS

As previously mentioned, it is desirable from a practical point of view to use the in-flight calibration data as a

means to improve measurements taken in the controlled environment on Earth. Having examined the effects of each

portion of the calibration processing on the data, we can now compare differences caused by the overall processing

on the data in contrast to using the semiprocessed data itself.

To compare the absolute sensor bias of the semiprocessed measurement to the processed measurement, we need

to first calculate the bias as predicted by the bias model at each of the respective temperatures for each axis and

amplification level. This was done previously producing table 6. These calculated biases are labeled "predicted bias"

in table 19. The sum of the calculated biases and the calibration model bias error measurement biases are labeled

"corrected bias" in table 19, while the in-orbit measured biases are labeled "measured bias" in this table.

The Y-axis shows strong agreement between the measured bias and the bias obtained with the combination of

ground measurement and in-flight correction. The errors that do exist are primarily associated with the source data

being processed at different times causing different data sets to be selected for the calculations. This problem can be

overcome by processing the different types of data at the same time. Additionally, using filtered data eases the task

of selecting stable data segments for the calculations as illustrated by comparisons of figures 2, 4, and 6.

Additional information is available by comparing the differences between data processed by the new SAMS

calibration temperature range data versus the old data. It was hoped that comparisons of this type would indicate

how much better the new model predicts the bias than the old one did. The data shown in the three tables that follow

were calculated based upon the same time intervals as those used in the previous tables. 5 One important difference

in this data does exist, however. These old model calibration data were collected 8 months before STS-60 flew,

while the new calibration data were collected only 2 weeks after STS-60 landed. The uncertainty caused by the bias

drift over time may be corrected by repeating this procedure with a TSH that has calibrated with both models, or

alternatively, repeating the calibration process for the new data after 7 months have passed.

Tables 20 to 23 show results of the same calculations in tables 7 to 10, except that the calculations were performed on data that have been processed with the old calibration model. Comparison of these data with the new

model data show that the bias error of the new model are 6 to 20 lag smaller, while the values of absolute acceleration are comparable. The more typical value of 20 lag is within the margin of error introduced by the 8-month old

data (ref. 1). It is worth mentioning that the old controlled X-axis G values are 0.1 lag closer to the ideal value of

zero than are the new model readings. The cause of this unexpected improvement requires additional analysis.

4Consideration ofsensor head hysteresis was primarilyconcernedwiththermally inducedeffects. These effects wereaddressed by throwing

away samples taken when the slope of temperature plot changed while the calibration procedure wasbeing performed.

5Thetime interval used for the X-axis means at time 2 reverse, and time 3 forward, as well asthe Y-axis time 3 reverse, were modified slightly

to remove large asymmetrical disturbances seen in these data.
ACCURACY

Thet-statisticmodelmaybeusedasthebasisofcalculating the accuracy of the calculations performed. This

can be used by determining the accuracy of the mean accelerations before and after the rotation process is calculated. The sum of the uncertainties then becomes the accuracy of our bias measurement.

Each of the two data sets used in the calculation must first be subdivided into n-subsets in order to provide a

large enough sample size for the t-statistic. In our test we used ten sets of 6 see each for our calculations. This gave

interval widths for t95 of +0.2077 lag for the forward calculation and _+0.1557 lag for the reverse calculation. The

interval widths for t99 were +0.3148 lag for the forward calculation and _+0.2239 lag for the reverse calculation. This

yields accuracies of 0.3634 lag and 0.5387 lag with confidence intervals of 95 and 99 percent, respectively. These

numbers confirm the basis for using the bias measurement on the control axis for the accuracy. The accuracies calculated with the t-statistic will be worse than those calculated by the bias measurement because the t-statistic uses

shorter time intervals limiting the natural filtering of the mean calculation.

CONCLUSIONS

In-flight calibration of micro-accelerometers provides the capability to measure quasi-steady-state accelerations

with an accuracy of 250 _tg. The data presented here indicate bias uncertainties approaching 40 lag can be removed

from the gravity data with a minimal amount of extra crew time required during the flight and only a few hours of

analysis required post flight.

The procedure presented in this report will be repeated on future flights to obtain a larger sample size to better

characterize the results. In addition, it will be repeated several times during the flight to characterize drift and repeatability. Additional tests on all three triaxial sensor heads are desired to test whether two sensors can be used to

calibrate a third one by using the two sensors to determine the environment at the third one.

REFERENCE

1. Thomas, J.E.; Peters, R.B.; and Finley, B.D.: Space Acceleration Measurement System Triaxial Sensor Head

Error Budget. NASA TM-105300, Jan. 1992.
TABLE 1 .--AVERAGE TEMPERATURES FOR IDEAL SCALE FACTOR COMPUTATION (°C)

Time 1 reverse Time 1 forward Time 2 forward Time 2 reverse Time 3 reverse Time 3 forward

X-axis

Y-axis

Z-axis

16.65 16.66

18.15 17.98

17.95 17.82

17.81

18.18

17.96

17.79

18.06

17.90

17.66

17.89

17.75

17.62

17.86

17.72

TABLE 2.--AVERAGE IDEAL SCALE FACTORS (V _)

Time 1 reverse Time 1 forward Time 2 forward

X-axis 938.264 938.264 938.379

Y-axis 969.555 970.509 999.504

Z-axis -1272.300 -! 273.520 -1272.150

Time 2 reverse Time 3 reverse

938.377 938.364

1000.260 1001.360

-1272.800 -1274.530

Time 3 forward

938.360

1001.550

-1274.240

X-axis

Y-axis

Z-axis

TABLE 3.--MEAN ACCELERATIONS ON SEMIPROCESSED DATA ([.t_)

Time 1 reverse

-1269.34

981.48

-1260.04

Time 1 forward Time 2 forward Time 2 reverse

-1271.61 -1264.74 -1264.98

981.60 973.77 984.33

-1258.73 -1249.69 -1258.82

Time 3 reverse

-1263.83

984.42

-1260.10

Time 3 forward

-1263.65

975.66

-1252.94

TABLE 4.--AMBIENT GRAVITY ON SEMIPROCESSED DATA (lag

Time 1 Time 2 Time 3

Y-axis 0.057 -5.282 -4.379

Z-axis 0.657 4.568 3.580

TABLE 5.--BIAS AND AMBIENT GRAVITY MEASUREMENT

ERROR ON SEMIPROCESSED DATA (.t_:)

Time l Time 2 Time 3

X-axis -1.136 0.116 0.090
TABLE &--BIAS ERRORS ON SEMIPROCESSED DATA (_t_)

Y-axis

Z-axis

Time 1

981.541

-1259.382

Time 2 Time 3

979.049 980.039

-1254.253 -1256.515

TABLE 7.--MEAN ACCELERATIONS ON UNFILTERED DATA (p._)

Time 1 reverse Time I forward Time 2 forward Time 2 reverse

X-axis -11.052 -9.834 -3.832 -4.491

Y-axis -22.176 -21.155 -11.324 -18.805

Z-axis 36.788 38.898 38.323 31.087

Time 3 reverse

-3.295

-21.498

30.792

Time 3 forward

-2.963

-16.309

39.289

TABLE 8.--AMBIENT GRAVITY ON UNFILTERED DATA (_t_)

Time 1 Time 2 Time 3

Y-axis 0.167 -4.892 -4.719

Z-axis 0.797 3.618 4249

TABLE 9.--BIAS AND AMBIENT GRAVITY MEASUREMENT ERROR

ON UNFILTERED DATA (_._)

Time l Time 2 Time 3

X-axis --0.345 0.331 0.166

TABLE 10.---CALCULATED MODEL BIAS ERRORS ON UNFILTERED

DATA (_._)

Time l Time 2 Time 3

Y-axis 21.837 16.215 16.459

Z-axis 38.056 34.705 35.040

Time 1 reverse

X-axis -9.899

Y-axis -22.69 !

Z-axis 39.510

TABLE 11.--MEAN ACCELERATIONS

Time 1 forward

-10.343

-23.339

41.103

Time 2 forward

-4.172

-11.862

41.172

)N FILTERED DATA (_t_)

Time 2 reverse Time 3 reverse

-4.670 -4.104

-22.740 -22.526

33.030 32.581

Time 3 forward

-3.030

-12.340

41.433

TABLE 12.--AMBIENT GRAVITY ON FILTERED DATA (_t_)

Time 1 Time 2 Time 3

Y-axis -0.324 5.439 5.096

Z-axis 0.865 4.071 4.426
TABLE 13.--BIAS AND AMBIENT GRAVITY MEASUREMENT

ERROR ON FILTERED DATA (_)

Time 1 Time 2 Time 3

X-axis -0.222 0.249 0.252

TABLE 14.---CALCULATED MODEL BIAS ERRORS ON

FILTERED DATA (Ft_)

Time I Time 2 Time 3

Y-axis -23.015 -17.301 -17.430

Z-axis 40.307 37.101 37.007

TABLE 15.mANGULAR ALIGNMENT EFFECTS ON MEAN ACCELERATIONS (_t_)

Time 1 reverse Time 1 forward Time IN reverse Time IN forward

X-axis F

U

Y-axis F

U

Z-axis F

U

-11.641

-11.052

-23.450

-10A13 -11.584 -10.449

-9.834 -9.869

-22.801

-10.097

-23.717 -25.302

-22.176 -21.155 -22.177 -23.451

38.839 40.807 38.821 40.791

36.788 38.898 36.771 38.883

TABLE 16.--ANGULAR ALIGNMENT EFFECTS ON

AMBIENT GRAVITY ([.t_

Y-axis F

U

Z-axis F

U

Time 1 Time IN

0.324 0.926

0.511 -0.770

0.984 -0.985

1.055 -1.056

TABLE 17.--ANGULAR ALIGNMENT _CTS ON BIAS

AND AMBIENT GRAVITY MEASUREMENT ERRORS (_t_i

Time 1 Time IN

X-axis F 0.614 -0.567

U 0.609 0.549

TABLE 18.--ANGULAR ALIGNMENT EFFECTS ON

CALCULATED MODEL BIAS ERRORS (Ix[)

Time 1 Time 1N

Y-axis F

U

Z-axis F

U

-23.126 -23.126

-21.666 -21.666

39.823 39.806

37.843 37.827
TABLE 19.--EFFECTS OF PROCESSING ON ABSOLUTE BIAS MEASUREMENTS

Y-axis

Z-axis

Time 2 predicted

bias,

-999.882

-1272.475

Time 3 predicted

bias,

-1001.455

-1274.385

Time 2 corrected

bias,

-982.581

-1235.374

Time 3 corrected

bias,

-984.025

-1237.378

Time 2 measured Time 3 measured

bias, bias,

-979.049 -980.039

-1254.253 -1256.515

TABLE 20.---CALIBRATION EFFECTS ON MEAN ACCELERATIONS (_t_)

X-axis

Y-axis

Z-axis

Time 1 reverse

F 2.090

U 1.959

F 50.703

U 47.925

F 5.284

U 5.067

Time 1 forward Time 2 forward Time 2 reverse Time 2 reverse Time 2 forward

3.203 9.603 9.267 10.246 10.444

3.037 9. i 92 8.734 9.681 10.040

51.164 42.054 31.652 31.981 40.408

48.760 39.642 30.294 30.044 42.823

7.227 48.005 39.615 38.857 47.546

7.154 44.786 37.314 36.721 45.067

TABLE 21.-----CALIBRATION EFFECTS ON BIAS ERRORS (_t_)

X-axis F

U

Y-axis F

U

Z-axis F

U

Time I

2.647

2.498

50.934

48.342

6.256

6.111

Time 2

9.435

8.963

36.853

34.968

43.810

41.050

Time 3

10.345

9.861

37.402

35.422

43.202

40.894

TABLE 22.--CALIBRATION EFFECTS ON AMBIENT GRAVITY (_t_)

X-axis F

U

Y-axis F

U

Z-axis F

U

Time I Time 2 Time 3

0.556 0.168 0.099

-0.539 0.229 0.179

0.231 5.201 5.421

0.418 4.674 4.986

0.972 4.195 4.344

1.044 3.736 4.173

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Figure 5 . -Triaxial Sensor Head C" processed Shuttle Y-axis time slice.

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Figure 6 .-Triaxial Sensor Head C: filtered Y-axis.

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Figure 7 .-Filtered time slice.

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$ec

14

Form Approved

REPORT DOCUMENTATION PAGE OMB No. 0704-0188

Publicreportingburdenforthiscollectionof Inlorrnationisestirr_ed.toaverage1 hourper.ree_r_, includln.gtheUric.forrav.kpwin_ Inp.true.ions,searchingexistklgdatasours=,

gatheringandmaintainingthedataneeded,andcornldetlngeno ravBwmgthecollectionolmtormmmn.=senocommentsr.ugarol.ngm_ouroen.e._Jrnme.orenyomeraslllllllPe_...ol mls collectionofInfo_, Includingsuggestionsfor reducingthisburden,to WashingtonHeadquartersSmvlces,D.k_e¢_.te vorinlormatlonUpel_... _ Hepon_1215_nemon

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1. AGENCY USE ONLY (Leave blank) 2. IPI_PORT DATE 3. REPuH¥ TYPE AND DATES COVERED

June 1996 Technical Memorandum

4. TITLE AND SUBTITLE 5. FUNDING NUMBERS

In-Orbit Calibration of a SAMS Triaxial Sensor Head

6. AUTHOR(S)

LouisS.Chesmey andRonaldJ.Sicker

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS{ES)

National Aeronautics and Space Administration

Lewis Research Center

Cleveland, Ohio 44135-3191

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)

National Aeronautics and Space Administration

Washington, D.C. 20546-0001

WU-949-63-60

8. PERFORMING ORGANIZATION

REPORT NUMBER

E -9746

10. SPONSORING/MONITORING

AGENCY REPORT NUMBER

NASA TM- 106980

11. SUPPLEMENTARY NOTES

Louis S. Chesmey, Aerospace Design & Fabrication, Inc., 3003 Aerospace Parkway, Brook Park, Ohio 44142, subcontractor to NYMA, Inc. (work funded by NASA Conlract NAS3-27186) and Ronald J. Sicker, NASA Lewis Research Center.

Responsible person, Ronald J. Sicker, organization code 6743, (216) 433--6498.

12a. DISTRIBUTION/AVAILABILITY STATEMENT

Unclassified -Unlimited

Subject Categories 19 and 88

This publication is available from the NASA Center for Ac_rospacc Information, (301) 621-0390.

12b. DISTRIBUTION CODE

13. ABSTRACT (Maximum 200 words)

This report describes the results of in orbit calibration data coUcctedfor a Space Acceleration Measurement System

(SAMS) Triaxial Sensor Head (TSI-I) and the methods used to process the data for bias and gravity levels.

14. SUBJECT TERMS

Shuttle mission; Calibration; Bias; Acceleration; STS-60; Spacehab-02

17. SECURITY CLASSIFICATION

OF REPORT

Unclassified

NSN 7540-01-280-5500

18. SECURITY CLASSIFICATION

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Unclassified

19. SECURITY CLASSIFICATION

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Unclassified

15. NUMBER OF PAGES

16

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A03

20. LIMITATION OF ABSTRACT

Standard Form 298 (Rev. 2-89)

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