Individual Particle Analysis TRIZ Cases

A machine learning model predicts membrane fouling levels using electrochemical information values derived from influent water quality parameters.

Segmented measurement passes with optical identifiers resolve spectral overlap to increase marker detection accuracy.

Refractive index optimizer adjusts optical focal points to detect nanoscale particles, eliminating manual recalibration downtime when switching carrier fluids.

Data extracting unit isolates maximum intensity values from fluorescence spectra for precise particle analysis.

Intensity modulated excitation sources direct light beams onto spatially separated optical interrogation zones within a flow channel.

Dual labeling of cytokeratin markers with distinct fluorochromes enables precise identification of circulating tumor cells in blood samples.

Digital holographic microscope eliminates optical focusing mechanisms to increase object throughput rates while maintaining measurement precision.

A flow cytometer transmits particle distribution diagram data directly to hospital information systems.

A condensation particle counter calibration system uses a nebulizer and ion mobility classifier to supply test particles of known diameter.

A pulse baseline calculation method for hematology analyzers selects qualified sampled data using a dynamic threshold to determine accurate particle counts.

A pore-based sample detection apparatus applies electrical current through an insulating partition to identify target particles via conductive state changes.

Multi-spectral photostimulation detects cell membrane potential changes, resolving the contradiction between measurement completeness and system complexity.

Multi-element photodetector assemblies isolate optical signals using dichroic blocks and confocal apertures to minimize interference between sensing locations.

Flow cytometry detects neoplastic lymphocytes using fluorescence and scattered light signals.

Multiple sensor blocks in a single particle counter improve measurement precision and enable equipment failure detection.

Large depth of field captures blood sample objects in one image, eliminating multi-plane focusing time loss.

Adjusting fluid conductivity to 5,000–50,000 μS/cm enables electrical impedance spectroscopy to differentiate labeled from non-labeled particles.

A monitoring device outputs two indication values to a display for simultaneous optical axis and gain adjustments in particle analysis.

A particle image analyzing method acquires overall sample images to extract and classify components based on feature parameters.

Wavelet or Fourier transforms extract waveform coefficients to identify cell types and doublets without discarding detailed signal data.

A blood analysis apparatus calculates cell ratios across multiple counting chambers to verify specimen volume.