Electrical Testing TRIZ Cases

A semiconductor device with multiple arithmetic cores executes programs in analysis mode to compare result data for defect detection.

A power displaying system records battery capacity before device shutdown to detect recharging or voltage impulse anomalies.

A pre-test conditioning station removes oxidation layers from integrated circuit contacts using abrasion or chemical treatment.

A test circuit uses multiple data generation units and a functional safety module to process varied input types.

Trace graph models predict battery faults by evaluating temporal operating variable curves, avoiding the inaccuracy of rule-based threshold detection methods.

A monitoring system selects communication schemes based on user device battery levels to ensure message delivery.

Replacing analog comparators and DACs with digital input pins eliminates circuit complexity while maintaining electromagnetic field detection accuracy.

A comparator circuit with feedback loops compares test data across identical electronic devices to detect errors without direct observation.

Pre-generated vectors and AIG hashing skip formal analysis, reducing runtime for repeated subcircuit checks.

Estimating electromagnetic torque using a Kalman filter eliminates external sensors, reducing aircraft weight and complexity.

A battery management apparatus determines state sensitivity to adjust algorithm execution parameters dynamically.

A battery lifetime prediction device corrects charge/discharge test data by replacing temporary capacity recovery sections with alternative values.

A varistor failure detector counts surges shunted by the component to signal replacement needs.

Calculating internal temperature gradients via ambient correction differentiates heat sources, reducing false alarms from external influences.

A monitoring system adapts battery voltage measurement timing based on consumed energy to detect low power states early.

Segmenting the test lead from the control interface eliminates circuit interference and boosts testing efficiency.

A battery cell classification system extracts a uniformity factor from charging voltage differential curves to identify defective cells and group similar units.

A neural net analyzes battery monitor data to identify changeouts automatically.

A method selects multiple models and measuring methods to determine the state of health of an electrical energy store.

A diagnosis apparatus gradually increases the diagnosis pulse width to detect response pulses from output switch circuits.

Shared boundary scan elements reduce circuit area and testing time by serving multiple I/O pins sequentially.

The system distributes monitoring data across multiple control units to prevent loss when the central server fails, ensuring continuous data availability.

A battery deterioration calculation system integrates charge-discharge currents and open-circuit voltage to determine state of health.

A battery diagnostic device stores cell voltages and driving information to calculate states of charge for rapid abnormal state identification.

Multiplexers switch interface circuits between data compressing base units, reducing pin count and production costs while increasing testing throughput.

Monitoring threshold voltage shifts enables dynamic forward body biasing that compensates for negative bias temperature instability degradation.

Segmented test carriers with universal interfaces resolve the contradiction between comprehensive testing thoroughness and system complexity.

Converts serial vector format files into tester vectors to program FPGAs directly, eliminating external computers and vendor pods.

Controller estimates battery capacity using multiple state of charge estimations based on time and temperature constraints.

A multifrequency signal generator applies simultaneous excitation modes to a material sensor, producing spectrally spread response signals for digital evaluation.

Locking segment insertion bits and trap bits protect hidden content from unauthorized network mapping by requiring authentication keys.

A battery management system calculates internal impedance to determine state of health without voltage stabilization delays.

Integrates oil quality parameters like acidity and dissolved gas data to detect incipient failures in load tap changers before unplanned outages occur.

A computer-implemented method combines passive and active measurements using a feature extraction module to develop internal battery parameters.

Switching mechanisms decouple non-linear harvesting elements during demand and fault modes, enabling accurate high-current readings via Hall sensors.

A system processes captured video and audio signals to automatically generate executable test scripts for devices under test.

A magnetic sensor uses a bridge circuit with alternating current to enhance detection sensitivity.

A battery pack voltage converter drops cell voltage to power the charge-discharge controller using parallel diodes and transistors.

Grid segmentation classifies wafer regions by pattern density, enabling accurate defect size distribution analysis and yield prediction.

Segmented housing grooves with projections retain probe bodies to prevent electrical miscommunication while simplifying structural complexity.

Nonlinear equivalent circuit model predicts secondary battery power parameters by calculating polarization voltages across segmented RC structures.

A memory device latches values via a shared path controlled by an enable signal to synchronize output timing across operational modes.

A nonlinear electrical model identifies supercapacitor effective capacity using least-square parameter identification.

Timer unit measures charge and discharge duration to determine secondary battery degraded state.

Automatically locates source code and dependencies to establish a debugging environment, reducing manual effort in hierarchical PCELL workflows.

Voltage divider and counter form an oscillator to detect selector electrical changes.

A battery detection device uses a resistive circuit to monitor cell deformation through impedance changes.

A battery state estimation device calculates stable open circuit voltage using simple timing ratios derived from transient voltage changes.

Strain gauges measure battery volume changes to calculate capacity degradation, resolving accuracy limits in existing testing procedures.

Magnetic susceptibility analysis resolves inaccuracy in non-new battery condition assessment.