Richard C. Oeftering and Raymond P. Wade

Glenn Research Center, Cleveland, Ohio

Alain Izadnegahdar

ASRC Aerospace Corporation, Cleveland, Ohio

Component-Level Electronic-Assembly Repair 

(CLEAR) Spacecraft Circuit Diagnostics by 

Analog and Complex Signature Analysis

NASA/TM—2011-216952

January 2011

CLEAR–RPT–003
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Richard C. Oeftering and Raymond P. Wade

Glenn Research Center, Cleveland, Ohio

Alain Izadnegahdar

ASRC Aerospace Corporation, Cleveland, Ohio

Component-Level Electronic-Assembly Repair 

(CLEAR) Spacecraft Circuit Diagnostics by 

Analog and Complex Signature Analysis

NASA/TM—2011-216952

January 2011

CLEAR–RPT–003

National Aeronautics and

Space Administration

Glenn Research Center

Cleveland, Ohio 44135
Available from

NASA Center for Aerospace Information

7115 Standard Drive

Hanover, MD 21076–1320

National Technical Information Service

5301 Shawnee Road

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Trade names and trademarks are used in this report for identifi cation 

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Space Administration.

Level of Review: This material has been technically reviewed by technical management. 
NASA/TM—2011-216952 iii

Summary

The Component-Level Electronic-Assembly Repair (CLEAR) project at the NASA Glenn Research 

Center is aimed at developing technologies that will enable space-flight crews to perform in situ 

component-level repair of electronics on Moon and Mars outposts, where there is no existing infrastructure for logistics spares. These technologies must provide effective repair capabilities yet meet the 

payload and operational constraints of space facilities. Effective repair depends on a diagnostic capability 

that is versatile but easy to use by crew members that have limited training in electronics. CLEAR studied 

two techniques that involve extensive precharacterization of “known good” circuits to produce graphical 

signatures that provide an easy-to-use comparison method to quickly indentify faulty components. 

Analog Signature Analysis (ASA) allows relatively rapid diagnostics of complex electronics by 

technicians with limited experience. Because of frequency limits and the growing dependence on broadband technologies, ASA must be augmented with other capabilities. To meet this challenge while 

preserving ease of use, CLEAR proposed an alternative called Complex Signature Analysis (CSA). Tests

of ASA and CSA were used to compare capabilities and to determine if the techniques provided an 

overlapping or complementary capability. The results showed that the methods are complementary.

NASA/TM—2011-216952 v

Contents

Summary......................................................................................................................................................iii

1.0 Introduction ..........................................................................................................................................1

2.0 Documents............................................................................................................................................2

2.1 Reference Documents.................................................................................................................2

2.2 Applicable Documents................................................................................................................2

3.0 Electronics Diagnostics in Space .........................................................................................................3

3.1 Lunar Mission Constraints..........................................................................................................3

3.2 Flight Crew Constraints..............................................................................................................3

4.0 Approach to Diagnostics......................................................................................................................4

4.1 Known Good, or “Gold,” Signature Circuit Characterization ....................................................4

4.2 Analog and Complex Signature Analysis Techniques................................................................4

5.0 Analog Signature Analysis...................................................................................................................5

5.1 Description of Huntron Unit .......................................................................................................5

5.2 Analog Signature Analysis Operating Principles........................................................................5

5.3 Huntron Tracker Model 30 Operating Settings...........................................................................6

6.0 Complex Signature Analysis................................................................................................................8

6.1 Introduction to the Radiofrequency Vector Network Analyzer..................................................8

6.2 Principles of Complex Impedance ..............................................................................................8

6.3 Complex Signature......................................................................................................................9

7.0 Operational Comparison of Analog Signature Analysis and Complex Signature Analysis...............11

7.1 Analog Signature Analysis Operations.....................................................................................11

7.2 Complex Signature Analysis Operations..................................................................................11

8.0 Side-by-Side Test Comparison of Analog Signature Analysis and Complex Signature Analysis.....12

8.1 Actual Test Targets...................................................................................................................12

8.2 Comparison Charts....................................................................................................................13

8.3 Comparison Summary for Analog Signature Analysis and Complex Signature Analysis......22

9.0 Future Development...........................................................................................................................23

9.1 Instrument Development for Analog Signature Analysis and Complex Signature Analysis....23

9.2 Noncontact Diagnostic..............................................................................................................23

10.0 Conclusions........................................................................................................................................24

Appendix.—Acronyms and Abbreviations.................................................................................................25

References...................................................................................................................................................26

NASA/TM—2011-216952 1

Component-Level Electronic-Assembly Repair (CLEAR) 

Spacecraft Circuit Diagnostics by Analog and 

Complex Signature Analysis

Richard C. Oeftering and Raymond P. Wade

National Aeronautics and Space Administration

Glenn Research Center

Cleveland, Ohio 44135

Alain Izadnegahdar

ASRC Aerospace Corporation

Cleveland, Ohio 44135

1.0 Introduction

The Component-Level Electronic-Assembly Repair (CLEAR) project is investigating techniques, 

tooling, and processes that could be used to perform nonterrestrial (space) repair of electronic assemblies.

System maintenance on the International Space Station is based on orbital replaceable units (ORUs),

which are encapsulated functional modules that allow the crew to remove and replace units with a 

minimum level of crew activity. These replaceable modules, however, are not optimized to minimize 

payload mass. In contrast, the ability to perform electronic repair at the board or component level would 

result in significant mass and volume savings. 

To be effective, the repair process must first diagnose the specific components that contain the fault.

Because of spacecraft and operational constraints, the equipment used in diagnosis should be small,

compact, and simple to operate with a minimally trained crew member.

CLEAR investigated analog signature analysis (ASA) and complex signature analysis (CSA) techniques. Both techniques require extensive precharacterization to produce signatures of “known good”

circuits. If the crew was supplied with known good, or “gold,” signatures, a simple comparison of the 

faulty circuit signature against the gold signature would indicate the faulty component. The operator 

would not need extensive electronics skill to perform this type of diagnosis.

ASA is an established technique that is widely used by the U.S. Navy for shipboard diagnostics.

There are, however, limitations to ASA effectiveness, particularly for circuits like radiofrequency (RF)

communications circuits. Therefore, the CLEAR project proposed an alternative technique more suitable 

for high frequencies and capable of exploiting circuit and component resonance properties. This study 

was performed to determine where ASA and CSA techniques would be effective and to determine if the 

techniques provided a complementary capability.

The CLEAR effort is being performed at the NASA Glenn Research Center and managed as part of 

the Exploration Technology Development Program’s Supportability Project based at the NASA Langley 

Research Center. The work also is being performed in concert with the U.S. Navy and the NASA Johnson 

Research Center. Acronyms used in this document are defined in the Appendix.
NASA/TM—2011-216952 2

2.0 Documents

The following documents contain supplemental information related to the CLEAR task.

2.1 Reference Documents

Document number Document title

CLEAR–ANA–002 Component-Level Electronic-Assembly Repair (CLEAR) Noncontact Coupling 

Techniques for Performing Signature Analysis

2.2 Applicable Documents

Document number Document title

CLEAR–ANA–001 Component-Level Electronic-Assembly Repair (CLEAR) Life-Cycle Cost 

Impacts of Different Approaches for In Situ Maintenance of Electronics 

Hardware

CLEAR–DOC–001 Component-Level Electronic-Assembly Repair (CLEAR) Component Repair 

Experiment 1 (CRE–1) Flight System Requirements Document

CLEAR–DOC–002 Component-Level Electronic-Assembly Repair (CLEAR) Component Repair

Experiment 1 (CRE–1) Concept and Hardware Summary

CLEAR–DOC–003 Component-Level Electronic-Assembly Repair (CLEAR) Recommendations for 

the Design of Electronic Assemblies for NASA's Exploration Program

CLEAR–DOC–004 Component-Level Electronic-Assembly Repair (CLEAR) Trade Study: Current 

Technologies and Instruments for Electronic Fault Diagnosis and Repair

CLEAR–DOC–005 Component-Level Electronic-Assembly Repair (CLEAR) Analysis of the 

Problem Reporting and Corrective Action (PRACA) Database of the 

International Space Station On-Orbit Electrical Systems 

CLEAR–DOC–006 Component-Level Electronic-Assembly Repair (CLEAR) Assessment of 

Constellation Program In-Space Electronic Diagnostics and Repair Needs

CLEAR–DOC–007 Component-Level Electronic-Assembly Repair (CLEAR) Operational Concept 

CLEAR–DOC–008 Component-Level Electronic-Assembly Repair (CLEAR) System Architecture

CLEAR–DOC–009 Component-Level Electronic-Assembly Repair (CLEAR) Recommendations for 

Enabling Manual Component-Level Electronic Repair for Future Space Missions

CLEAR–RPT–001 Component-Level Electronic-Assembly Repair (CLEAR) Component Repair 

Experiment 1 (CRE–1) System Requirements Review (SRR) Panel Report

CLEAR–RPT–002 Component-Level Electronic-Assembly Repair (CLEAR) Soldering in Reduced 

Gravity Experiment (SoRGE) Mission Test Report

CLEAR–RPT–004 Component-Level Electronic-Assembly Repair (CLEAR) Synthetic Instrument 

Capabilities Assessment and Test Report
NASA/TM—2011-216952 3

3.0 Electronics Diagnostics in Space

3.1 Lunar Mission Constraints 

Future space exploration missions will require highly efficient methods for repairing electronic 

equipment to ensure the safety of the crew. For the International Space Station (ISS), the systems are 

composed of modular ORUs. When system faults are discovered on ISS, they are traced down to the 

specific faulty ORU, which is then replaced with an on-orbit spare. The faulty ORUs are returned to Earth 

via the space shuttle for repair and then relaunch aboard a later space shuttle flight. The ORU approach 

simplifies the maintenance of flight systems, but it is based on the premise that the crew is supported by a 

robust and timely logistics infrastructure.

In lunar surface operations, spares are expected to be very scarce because of the extreme payload 

limitations. The availability of logistics is also expected to be much more constrained. Return of hardware 

to Earth for repair is not an option. This drives the program toward a low logistics strategy where faulty 

hardware repairs are performed in situ at the component level. In comparison, a component may weigh 

between 1/100 and 1/1000 of the weight of the complete ORU. As a result, the mass dedicated to spare 

components is much less and far more efficient than with ORU spares.

Component repair must be supported by effective diagnostics. If the process of diagnosing the fault, 

replacing the component, and functionally testing the repaired unit consumes too much time and requires 

substantial mass in equipment, then the benefits of component-level repair are diminished. The diagnostics tools must be effective, compact, and easy to use. 

3.2 Flight Crew Constraints

The size of space-flight crews will continue to be small. Lunar missions are expected to be composed 

of no more than four crew members. Because of the many crew activities required to achieve mission 

objectives, crew time and training are very constrained. The crew can perform routine maintenance, but 

when faults arise in complex electronic systems, the crew must rely on ground support to locate faults via 

telemetry. The normal telemetry on ISS is effective at identifying faults to the ORU level, but the problem 

history has shown that component-level problems are beyond the reach of telemetry. A similar situation is 

expected to exist for lunar operations. External equipment is required for component-level diagnostics.

This equipment must be easy to use and quickly understood by a crew that has a minimum level of training in electronics diagnostics.
NASA/TM—2011-216952 4

4.0 Approach to Diagnostics

4.1 Known Good, or “Gold,” Signature Circuit Characterization 

Comparative signature techniques allow nonspecialist personnel to identify defective components 

on an electronic board. A power-off technique called ASA developed by Huntron has been used by the 

U.S. Navy as a simple, but effective, form of diagnostics. The basic idea comes from a voltage-current

(V–I) curve tracer that is used for individual component characterization. The U.S. Navy’s Gold Disk 

program records and distributes known-good-board ASA data on specific circuits throughout the Navy.

The Gold Disk (a compact disk) in combination with an ASA unit provides a simple-to-use, initial 

screening test that can isolate many simple faults. The concept of characterizing known good circuits and 

using the characteristic signatures as a basis of comparison is common throughout the electronics industry 

for electronics, from circuit board assemblies to individual silicon dies.

4.2 Analog and Complex Signature Analysis Techniques

The ASA technique characterizes the performance of individual networks and compares them with 

known-good-board data. This is done by connecting to a common ground point on the board being tested, 

and injecting a signal into a network. The signal is a low-level, low-frequency, sinusoidal input. This 

signal is used to generate a V–I relationship for the components attached to the specific network curve. A 

faulty component changes the shape of the V–I curve. When the faulty trace is overlaid on a “gold” trace,

any difference is easy to identify. 

CLEAR is advancing the approach by measuring complex impedance in the frequency domain. The 

CSA approach exploits network analyzer technology to reveal frequency-dependent behaviors and exploit 

self-resonant and network-resonant characteristics to isolate faults. It can also reveal the resonant behaviors of devices that are physically isolated from the node. It can even detect breaks in circuit card vias

and traces. The high-frequency capability also makes it suitable for direct measurement of high-frequency 

RF circuits.
NASA/TM—2011-216952 5

5.0 Analog Signature Analysis

5.1 Description of Huntron Unit

A power-off technique called ASA developed by Huntron, Inc., is a simple, but effective, form of 

diagnostics based on comparison with a known good board. It provides the advantage of diagnosing a 

circuit in the power-off condition, which negates the need for power supplies and the risks posed by 

powering up a faulty circuit.

The ASA technique applies a current-limited sine-wave voltage to an unpowered circuit or electronic 

component. The resulting V–I characteristic (analog signature) is then stored and displayed for comparisons to signatures of a known good circuit card or electronic component. Circuit cards and electronic 

components can be diagnosed without applying external power.

5.2 Analog Signature Analysis Operating Principles

A single component that can be isolated provides a very predictable curve. However circuits usually 

have multiple devices on each node; thus a node will have a signature that is a composite of multiple 

devices. As long as the settings and probe positions are consistent, the signature should accurately 

duplicate the known-good-board signature (Ref. 1).

As shown in Figure 1, a personal computer workstation with ASA software graphically displays the 

analog signature. This approach can be applied to any type of passive component like a resistor, capacitor, 

or inductor. It can also be applied to solid-state semiconductor components like diodes, transistors, 

silicon-controlled rectifiers, and digital, analog, or mixed-signal (ICs).

Alternatively, the signature can be compared with known node faults, where individual components 

with various fault modes can be precharacterized and thus provide a more precise diagnosis (Figure 2). A 

skilled user that is familiar with the circuit design and each component's function can determine exactly 

which component is faulty. If the user is not skilled and no known good reference is available, then the 

results will be ambiguous. 

Figure 1.—Analog Signature Analysis (ASA) relies on measuring the response 

to a very low power sine wave signal, V–I, voltage-current.
NASA/TM—2011-216952 6

Figure 2.—Analog Signature Analysis (ASA) characterization may involve several individual devices 

contributing to the node’s characteristic signature. A fault in any component should alter the signature.

5.3 Huntron Tracker Model 30 Operating Settings

Operating settings for the Huntron device follow:

 Open-circuit peak voltage (24 settings)

− 200, 400, 600, and 800 mV

− 1 to 20 V (in 1-V steps)

 Internal source resistance

− 10, 20, 50, 100, 200, and 500 Ω

− 1, 2, 50, and 100 kΩ

− 54, 1.2, and 26.7 kΩ

 Short-circuit current limit, 200 mA

 Signal frequency

− 20 to 190 Hz (in 10-Hz steps)

− 200 Hz to 1.9 kHz (in 100-Hz steps)

− 2 to 5 kHz (in 1-kHz steps)

A power supply board and an RF amplifier were used as an example application of the ASA procedure. Huntron equipment provides a maximum driving alternative signal of 3.0 V and a maximum 

frequency of 200 Hz. See the sample output in Figure 3.
NASA/TM—2011-216952 7

Figure 3.—Analog Signature Analysis (ASA) 

sample output of current-voltage curve 

obtained with the Huntron unit.
NASA/TM—2011-216952 8

6.0 Complex Signature Analysis

6.1 Introduction to the Radiofrequency Vector Network Analyzer 

CSA becomes an extension of ASA by using the capability of an RF vector network analyzer. Not to 

be confused with network protocol analyzers, an RF vector network analyzer (see Figure 4) is intended to 

test networks of components in high-frequency alternating-current (AC) signal circuits. These devices 

share certain capabilities with a spectrum analyzer. They are generally used for high-frequency or RF 

circuits, where operating frequencies can range from 10 kHz to 110 GHz. 

Vector network analyzers are used to measure the frequency-domain properties of component networks rather than the properties of single components. They inject a signal into a network and measure 

the signal reflecting back from the circuit and the signal transmitted through the circuit. They are commonly used to test high-frequency amplifiers, filters, and tuning networks and can also test piezoelectric 

devices like crystal resonators. They operate at very low wattage and inject signals into unpowered 

passive networks, such as filters, or powered active devices, such as amplifiers.

6.2 Principles of Complex Impedance

For CLEAR, the Agilent 8712ET RF Network Analyzer provides a complex impedance measurement. Network analyzers make their measurements relative to a reference impedance value (typically 

50 Ω for RF systems). The scale can be very large, and thus a log scale is often used and impedance ratio 

is displayed in decibels (Ref. 2). 

Complex impedance (Z) is a complex value; that is, it is composed of real and imaginary components:

Z = R + Xi

where R is resistance (the real component) and Xi is reactance (represented by an imaginary component).

The resistance term R is commonly measured with a direct-current (DC) resistance meter. The reactance 

term (X) typically involves inductors or capacitors and is only meaningful for AC signals. The reactance 

is frequency dependent:

X L

C

Xi = ω

ω= or

1

where C is capacitance, L is inductance, and ω is frequency.

Figure 4.—Full-featured radiofrequency vector network analyzer that 

operates in the 300-kHz to 1.3-GHz frequency range.
NASA/TM—2011-216952 9

Figure 5.—Normal resonance of a known good five-component network 

(markers 1 to 5 on the solid trace) and a faulty component in a test 

circuit where element 2 has failed (marker 2 on the dashed trace).

A network analyzer uses a 50-Ω internal reference. The signal injected into the target and the 

subsequent reflections are compared with the same signal injected into a calibrated 50-Ω load. 

The 50-Ω reference limits the sensitivity of the network analyzer for impedances that are substantially 

different from 50 Ω. For example, a circuit with a constant impedance of 100 000 Ω will show a flat 

response. However, inductor and capacitor impedance values will change substantially over a wide 

frequency range. As with the ASA approach, the user should select settings that enhance the sensitivity of 

the measurement.

By performing a wide frequency sweep, one may be able to identify specific components. By comparing the sweep signature to a known good, or “gold,” signature, one can quickly spot a failed component. 

As shown in Figure 5, the data may be very difficult to interpret directly but will provide a very distinct 

and unique signature, particularly for a circuit where the input impedance is near the reference 

impedance. 

6.3 Complex Signature

As shown in Figure 5, a filter composed of several inductor/capacitor (LC) nodes has a distinct 

resonant condition for each node. The plots produced by the network analyzer could be used to characterize the network. The actual measurement is taken at the input end.

Note that markers 1 to 5 indicate distinct nodes and each node’s contribution to the characterization

curve. Therefore, it is possible to characterize the network without measuring every node, which is particularly useful when the circuit is encapsulated and individual components are inaccessible. Note that the 

measurement is taken from the signal-injection side of the circuit rather than from the output. If any 

internal devices fail, it would appear as a distortion of the curve at that point. If internal component values 

are known from design data, then the problem component can be identified quickly.

Figure 6 shows an actual CSA data trace. The data are displayed as a combination of phase shift and 

polar plots from the Agilent Technologies 8712ET RF Network Analyzer. In the lab tests, these plots 

were determined to be the easiest for comparing good versus faulty components. Other plots such as the 

Smith Chart and various linear and log scale charts can be used depending on the level of impedance

mismatch between the target and the internal reference. 
NASA/TM—2011-216952 10

Figure 6.—Complex Signature Analysis (CSA) sample output showing 

both a phase plot and polar plots. Other data display options, such as 

a reflected power chart and a complex-impedance Smith Chart, are 

available but are more difficult to interpret by an untrained user.
NASA/TM—2011-216952 11

7.0 Operational Comparison of Analog Signature Analysis and Complex 

Signature Analysis

7.1 Analog Signature Analysis Operations

ASA operation was performed using a Huntron instrument. A power supply board and an RF 

amplifier were used as example application for the ASA procedure. Huntron equipment provides a 

driving alternative signal of maximum 3.0 V and a frequency of 200 Hz. In order to verify the extent of 

usage of this technique, a variety of components were selected on the board. This selection includes 

passive components such as resistors and capacitors as well as active components: diodes, analog ICs, and 

digital ICs. An RF amplifier also was used for testing. However, because of the frequency limits of the 

Huntron unit, inductors at the input and output stages of the amplifier appear as short circuits. The 

captured data are in the form of a V–I graph.

7.2 Complex Signature Analysis Operations

The Agilent 8712T RF Network Analyzer used for testing the CSA approach has a range of setup

parameters:

 Frequency sweep 

− Minimum start frequency, 300 kHz

− Maximum stop frequency, 1.3 GHz

 Number of samples per sweep, 201 to 1601

 Sweep rate, samples per second 

 RF power input, –2 to 17 dBm

For our experiments, the highest frequency was limited to 100 MHz to prevent radiation through printed 

circuit board conductive lines. The same components that were tested with the Huntron instrument were 

tested with the network analyzer.

The analyzer has different options for presenting output data. These include amplitude and phase, or 

real and imaginary components in Cartesian (x/y plot) or polar graphs. For ease of visual inspection, a 

linear graph and a polar graph were selected. The measured quantities could be presented as real and 

imaginary or as amplitude and phase. In some cases, the change in the phase was more significant than 

the change in the amplitude of the output signal. Table I summarizes the comparative range of operating 

parameters for ASA and CSA.

TABLE I.—SUMMARY OF OPERATING PARAMETERS FOR ANALOG SIGNATURE 

ANALYSIS (ASA) AND COMPLEX SIGNATURE ANALYSIS (CSA)

Characteristic ASA CSA

Operating domain Time domain Frequency domain

Signal input Low-frequency alternating current (AC) Frequency sweep

Frequency range 20 Hz to 5 kHz 300 kHz to more than 1.2 GHz

Internal impedance 10 Ω to 100 kΩ 50 Ω

Voltage or power range 200 mV to 20 V 0 to 17 dBm

Target state Power off Power off
NASA/TM—2011-216952 12

8.0 Side-by-Side Test Comparison of Analog Signature Analysis and 

Complex Signature Analysis

8.1 Actual Test Targets

For comparison tests, an available circuit board from a space experiment (Figure 7) was used. A 

custom power supply board and electronic components were used for tests by Huntron (ASA) and the 

network analyzer (CSA). Table II lists the tested components.

Figure 7.—Analog Signature Analysis (ASA) and complex signature analysis 

(CSA) test target composed of analog and digital circuit components. The 

highlighted components were subjected to ASA and CSA testing.
NASA/TM—2011-216952 13

TABLE II.—COMPONENTS TESTED

Component 

designation

Component 

description

Test 

parameters

Resistors

R10 0.25 W, 10 kΩ Simulated fault value, 390 Ω

R12 0.5 W, 1 kΩ Simulated fault value, 15 Ω; not detected as a bad part by ASA

Capacitors

C14 4.7-μF electrolytic Open

C25 0.22-μF ceramic Simulated fault value, 0.001 μF

Diodes

D4 IN914 diode Shorted

Analog components

U4 6N137 analog optocoupler Damaged five of eight pins (1,3,6, 7, and 8)

U9 555 analog timer Damaged three of eight pins (1, 6, and 8)

Digital components

U8 7473 JK flip flop Damaged 13 of 14 pins (1 to 4 and 6 to 14)

Radiofrequency (RF) circuit

RF CA282C Motorola 1-W

wideband, linear RF 

amplifier

RF input and RF output pins

Creating damaged components is much more difficult than initially anticipated. Many components 

fail because of slow processes, such as corrosion or internal metal migration, and are very difficult to 

reproduce even in specially controlled environments. Faults due to overstressing by high current, over 

voltage or thermal damage tend to fail as open or short circuits. For discrete components, it was easier to 

simulate a fault by replacing the good component with another good component of a different value.

After many attempts, a set of faulty integrated circuits (ICs) were produced that were used as plug-in 

faults. They were functionally equivalent to the component in the original circuit card but some had slight 

differences in the electrical specifications. Since the objective is to evaluate ASA and CSA as an initial 

fault-finding technique, the differences were deemed to be acceptable for the test.

A 1-W wideband RF amplifier module was tested separately to demonstrate ASA and CSA for RF 

circuits. In this case, both damaged and good units were already available. 

8.2 Comparison Charts

Figure 8 to Figure 20 provide samples of the tests performed and illustrate both ASA and CSA. The 

graphs for good and damaged components are shown side by side.

The analysis of the RF amplifier illustrates that ASA has limitations when used in high-frequency RF 

circuits. ASA data are not shown for RF circuits because ASA was unable to distinguish between a 

known good and a faulty amplifier circuit. It is common to use a special high-frequency transformer 

called a transmission line transformer. These RF devices respond to high frequency, but at low-frequency 

or DC currents they will appear as a short circuit. Although CSA should be well suited to RF devices, the 

differences between the good and faulty circuit are not dramatic. The original amplifier damage was due 

to overheating of the amplifier semiconductors. This fault is isolated somewhat by the intervening line 

transformers. 

For consistency, in the amplifier tests, the amplitude versus frequency was plotted in linear and polar 

coordinates. For RF applications, reflected power and a Smith Chart to display complex impedance were 

more effective tools.
NASA/TM—2011-216952 14

Figure 8.—Resistor (R10) tested by Analog Signature Analysis (ASA) at 3 V 

and 200 Hz on pins 1 and 2. It is easy to discern the differences between 

the ASA characteristics of the known good resistor and the faulty resistor 

at various ASA settings.

Figure 9.—Ceramic capacitor (C25) tested by Analog Signature Analysis

(ASA) at 3 V and 200 Hz on pins 1 and 2. It is easy to discern the 

differences between the ASA characteristics of the known good 

capacitor and the faulty capacitor at various ASA settings. Internal 

resistances of 100 Ω and 10 kΩ provide roughly the same sensitivity.
NASA/TM—2011-216952 15

Figure 10.—Diode 1N914 (D4) tested by Analog Signature Analysis (ASA) 

at 3 V and 200 Hz on pin 2.

Figure 11.—Analog optocoupler 6N137 (U4) tested by Analog Signature 

Analysis (ASA) at 3 V and 200 Hz on pins 2 and 3 (internal diode 

connections). The 10-kΩ internal resistance setting is preferred.
NASA/TM—2011-216952 16

Figure 12.—Analog timer NE555 (U9) tested by Analog Signature Analysis 

(ASA) at 3 V and 200 Hz on pins 1, 6, and 8.

Figure 13.—Digital circuit 7473 flip flop (U8) tested by Analog Signature 

Analysis (ASA) at 3 V and 200 Hz on pins 1 and 4. Digital circuits have 

relatively high impedance at the input ports; thus, the 10-kΩ setting is a 

more responsive indicator of faults.
NASA/TM—2011-216952 17

Figure 14.—Resistor (R12) tested by Complex Signature Analysis (CSA) from 10 to 100 MHz on pins 1 and 2. 

No significant change is visible. The reason may be that 2.2 kΩ is relatively high in comparison to the 50-Ω

reference impedance. A resistor will have only a very small reactive component, so complex impedance is 

not an effective indicator for this application.
NASA/TM—2011-216952 18

Figure 15.—Ceramic capacitor (C25) tested by Complex Signature Analysis (CSA) from 10 to 

100 MHz on pins 1 and 2. For pin 1, there is a subtle difference (dashed circles) shown on the 

polar phase diagram. Large-value capacitors do not show significant difference. This is due to 

the frequency dependence of capacitance, where increasing frequency reduces impedance. 

At the operating frequency of the network analyzer (10 to 100 MHz), the capacitor is seen as 

short. For pin 2, which is connected to ground, the signal should not be significantly different.

Figure 16.—Diode 1N914 (D4) tested by Complex Signature Analysis (CSA) on pin 2. Pin 1 of the diode 

was connected to a low-impedance power-supply side and, thus, would not respond to the frequency 

sweep. Differences are highlighted by the dashed circles.
NASA/TM—2011-216952 19

Figure 17.—Analog optocoupler 6N137 (U4) tested by Complex Signature Analysis (CSA) on pins 2 and 

3 (diode connections). Note that it is easier to identify the fault in the polar plot. (See the dashed 

circles.)
NASA/TM—2011-216952 20

Figure 18.—Analog timer NE555 (U9) tested by Complex Signature Analysis (CSA) on pins 1, 6, and 8. CSA 

fault detection may be more subtle than ASA, and measurement markers on the polar plot for selected 

frequencies help phase shift because of reactance. Polar plots (and Smith Charts) can be more precise 

than simply comparing curve shapes. However, for pin 6 the simple linear plot was less ambiguous. (See 

the dashed circles.)
NASA/TM—2011-216952 21

Figure 19.—Digital circuit 7473 flip flop (U8) tested by Complex Signature Analysis (CSA) on pins 1, 2, 8, 

and 9. CSA performed better than expected for digital applications, and once again, the polar plots with 

frequency markers are easier to use for fault detection than a linear plot. (See the dashed circles.)
NASA/TM—2011-216952 22

Figure 20.—Motorola CA282C 1-W wide-band linear radiofrequency (RF) amplifier tested by 

Complex Signature Analysis (CSA) on pins 1 and 2. Input stages do not show significant 

differences, but the difference is visible in the output stage. (See the dashed circles.)

8.3 Comparison Summary for Analog Signature Analysis and Complex 

Signature Analysis

Table III shows a modest overlap in the fault-detection capabilities of ASA and CSA. There are areas 

where the selection of either ASA or CSA is a clear choice. Generally, ASA is more effective in the lowfrequency (or baseband) range, whereas CSA is more effective at high frequencies. There are techniques 

and features that can be used to extend the effective range of both techniques.

TABLE III.—APPLICATIONS OF ANALOG SIGNATURE ANALYSIS (ASA) 

AND COMPLEX SIGNATURE ANALYSIS (CSA)

ASA Huntron analyzer CSA Agilent network 

analyzer

Resistors X X

Large capacitors X

Small capacitors (<100 pF) X

Large inductors X

Small inductors (<100 μH) X

Active components X X

Radiofrequency circuits X
NASA/TM—2011-216952 23

9.0 Future Development 

9.1 Instrument Development for Analog Signature Analysis and Complex 

Signature Analysis

The ASA unit was an unaltered commercially available model developed by Huntron and could be 

converted to a flight unit with limited repackaging and qualification tests. This particular model was 

“panelless”; that is, it did not provide external user control features or a display. The input and display 

functions were handled by a user computer. 

For this study, CSA tests involved an unaltered commercially available Agilent 8712ET RF Network 

Analyzer that was designed for other applications. In addition, it was a conventional instrument with 

full-featured interface controls and a display panel. For space flight this instrument would need to be 

redesigned for CSA applications. Certain features would need to be tailored for CSA, and other network 

analyzer features would be eliminated. For CSA, software will need to be developed to streamline and 

automate the setup, control, and data management functions. Eliminating the front panel controls and data 

display could reduce the size of the CSA instrument dramatically. 

The RF network analyzer could be tailored for CSA applications in two ways. The reference impedance is typically 50 Ω, which is a standard used in RF systems. Variable impedance would expand the 

sensitivity to circuits to cover the wide impedance range of common non-RF electronics.

CSA tests revealed that frequencies above 100 MHz began creating RF field emissions from the 

circuit board traces. Aside from generating unwanted interference with other equipment, the field emissions interact with lead wires, conductive hardware, and even the user’s hands in the vicinity of the 

circuit. These interactions alter the impedance properties of the test circuit and in effect invalidate the 

known good circuit data. This leads to false errors, ambiguous results, and misdiagnosis. Therefore,

the frequency range of a RF network analyzer used as a CSA instrument will be limited to less than 

100 MHz. Furthermore, the low-frequency limit of the RF network analyzer was 300 kHz, which is too 

high to effectively analyze low-frequency circuits. The lower frequency limit of a CSA unit should extend 

down to 10 kHz or less. 

Both ASA and CSA are candidates for development as synthetic instruments. Synthetic instruments 

exploit software and the flexibility and performance of field-programmable gate array (FPGA) 

technology. ASA can be reproduced easily as a synthetic instrument. CSA, however, will require a special 

RF front end.

9.2 Noncontact Diagnostic 

A preliminary feasibility study of the noncontact technique was conducted, and the results are 

reported separately in CLEAR–ANA–002, Component-Level Electronic-Assembly Repair (CLEAR) 

Noncontact Coupling Techniques for Performing Signature Analysis. This technique is intended to 

address the problems of node access in circuits that are protected by conformal coatings. Both ASA and 

CSA operate by injecting AC signals into the test circuit and examining the response. If a probe can be 

coupled by capacitive, inductive, or RF coupling, it may be feasible to inject signals without removing the 

conformal coating.

Conformal coatings can be difficult and time consuming to remove and often result in damage to the 

underlying circuit. Probing by penetrating through the conformal coating layer can also result in damage 

to both the coating and circuit. A noncontact method of coupling will reduce the risk of damage and will 

simplify the overall process.
NASA/TM—2011-216952 24

10.0 Conclusions

Analog Signature Analysis (ASA) and Complex Signature Analysis (CSA) have similar approaches

but measure distinctly different circuit behaviors. ASA operates in the time domain, whereas CSA

operates in the frequency domain and displays values using complex variable mathematics.

ASA measures the response to a small voltage input like a component tester, whereas CSA measures 

complex impedance, which is a multicomponent value that can be analyzed in different ways.

 Both ASA and CSA can be used in a signature comparison mode where the test signal is 

compared with a known good reference.

 Both ASA and CSA can be applied to an unpowered test circuit.

 Both ASA and CSA have frequency limitations but at opposite ends. ASA works in the lowfrequency range (20 Hz to 5 kHz), whereas CSA works best at high frequencies (100 kHz and 

up). 

 ASA does not perform well with RF circuits where high-frequency coupling methods are used. 

For example, RF circuits with transmission line transformers look like short circuits to ASA. 

 CSA, in the tested configuration, does not perform well with large components or with lowfrequency circuits that may include large capacitor or inductor elements.

The techniques have little overlap in their range, thus one technique does not encompass the capability of the other technique. Therefore, ASA and CSA diagnostics are considered to be complementary 

techniques. Further refinement of both ASA and CSA should provide users with a good initial faultfinding capability that is easy to use. 
NASA/TM—2011-216952 25

Appendix.—Acronyms and Abbreviations

AC alternating current

ASA analog signature analysis

CLEAR Component-Level Electronic-Assembly Repair

CSA complex signature analysis

DC direct current

FPGA field-programmable gate array

IC integrated circuit

ISS International Space Station

LC inductor/capacitor

ORU orbital replaceable unit

V–I voltage-current
NASA/TM—2011-216952 26

References

1. Huntron Diagnostic Systems Product Literature, 31–0087, Rev. D, Huntron Inc., 2005. 

http://www.huntron.com/products/diagnostics.htm Accessed Jan. 27, 2009

2. User’s Guide—HP 8712ET and HP 8714ET RF Network Analyzers. HP Part No. 08714–90011, 

Hewlett-Packard Co., Oct. 1999.
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Component-Level Electronic-Assembly Repair (CLEAR) Spacecraft Circuit Diagnostics by 

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14. ABSTRACT

The Component-Level Electronic-Assembly Repair (CLEAR) project at the NASA Glenn Research Center is aimed at developing 

technologies that will enable space-flight crews to perform in situ component-level repair of electronics on Moon and Mars outposts, where 

there is no existing infrastructure for logistics spares. These technologies must provide effective repair capabilities yet meet the payload and 

operational constraints of space facilities. Effective repair depends on a diagnostic capability that is versatile but easy to use by crew 

members that have limited training in electronics. CLEAR studied two techniques that involve extensive precharacterization of “known 

good” circuits to produce graphical signatures that provide an easy-to-use comparison method to quickly indentify faulty components. 

Analog Signature Analysis (ASA) allows relatively rapid diagnostics of complex electronics by technicians with limited experience. 

Because of frequency limits and the growing dependence on broadband technologies, ASA must be augmented with other capabilities. To 

meet this challenge while preserving ease of use, CLEAR proposed an alternative called Complex Signature Analysis (CSA). Tests of ASA 

and CSA were used to compare capabilities and to determine if the techniques provided an overlapping or complementary capability. The 

results showed that the methods are complementary. 

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