The present disclosure relates to a method and apparatus for cleaning a 3D printed article, in particular a 3D printed heat exchanger. After 3D printing, an article may have internal passages formed from bonded powder and said passages may contain unbonded powder that needs to be removed before further use of/processing of the article. To remove this unbonded powder, the article is filled with a cleaning fluid and vibrated. The cleaning fluid is then pumped out of the article and past a sensor that generates a magnetic field. The sensor detects the presence of powder particles in the fluid by detecting a perturbation of the magnetic field caused by said particles. The fluid is then filtered and returned to a reservoir for use. The sensor may indicate the article is sufficiently clean when a detected concentration of particles in the fluid drops below a threshold.

The present disclosure relates to a method and apparatus for cleaning a 3D printed article, in particular a 3D printed heat exchanger. After 3D printing, an article may have internal passages formed from bonded powder and said passages may contain unbonded powder that needs to be removed before further use of/processing of the article. To remove this unbonded powder, the article is filled with a cleaning fluid and vibrated. The cleaning fluid is then pumped out of the article and past a sensor that generates a magnetic field. The sensor detects the presence of powder particles in the fluid by detecting a perturbation of the magnetic field caused by said particles. The fluid is then filtered and returned to a reservoir for use. The sensor may indicate the article is sufficiently clean when a detected concentration of particles in the fluid drops below a threshold.

A system for detecting deposit formation on electrically-conductive materials in vapor and liquid phases includes a test cell for receiving a test liquid (e.g., a lubricant). A heater heats the test liquid to generate a vapor phase of the test liquid in the test cell. A support frame supports at least a first set of electrical conductors in the test liquid and at least a second set of electrical conductors in the vapor phase, each of the first and second sets of conductors including a live electrical conductor and a neutral electrical conductor. A power source supplies an electric current to each of the live electrical conductors. A sensor component detects an electrical property each of the sets of conductors, the electrical property changing in response to formation of an electrically-conductive deposit which connects the first and second conductors in a respective set of conductors. Preferably, the electrical properties are detected by magnetic sensors, such as Hall effect sensors or eddy current sensors.

A system for detecting deposit formation on electrically-conductive materials in vapor and liquid phases includes a test cell for receiving a test liquid (e.g., a lubricant). A heater heats the test liquid to generate a vapor phase of the test liquid in the test cell. A support frame supports at least a first set of electrical conductors in the test liquid and at least a second set of electrical conductors in the vapor phase, each of the first and second sets of conductors including a live electrical conductor and a neutral electrical conductor. A power source supplies an electric current to each of the live electrical conductors. A sensor component detects an electrical property each of the sets of conductors, the electrical property changing in response to formation of an electrically-conductive deposit which connects the first and second conductors in a respective set of conductors. Preferably, the electrical properties are detected by magnetic sensors, such as Hall effect sensors or eddy current sensors.

The invention relates to a sensor device (100) and a method for the detection of magnetic particles (1) in a sample chamber (2) with a contact surface (11). The sensor device (100) comprises a sensor unit (120, 130) for detecting magnetic particles (1) in a target region (TR) and/or in at least one reference region on the contact surface. Moreover, it comprises a magnetic field generator (140) for generating a magnetic field that shall guide magnetic particles to the contact surface. With the help of these components, an “auxiliary parameter” is determined that is related to the magnetic particles (1) and/or their movement but that is independent of binding processes taking place in the target region between magnetic particles and the contact surface. The auxiliary parameter may for example be related to the degree of mismatch between the positions reached by the magnetic particles (1) under the influence of a magnetic field and the target region (TR). The evaluation results can be used to validate and/or correct the measurements obtained in the target region (TR).

Disclosed herein are detection methods that use magnetic nanoparticles (MNPs) to allow molecules to be identified. Embodiments of this disclosure include methods of using magnetic sensors (e.g., magnetoresistive sensors) to detect temperature-dependent magnetic fields (or changes in magnetic fields) emitted by MNPs, and, specifically to distinguish between the presence and absence of magnetic fields emitted, or not emitted, by MNPs at different temperatures selected to take advantage of knowledge of how the MNPs' magnetic properties change with temperature. Embodiments disclosed herein may be used for nucleic acid sequencing, such as deoxyribonucleic acid (DNA) sequencing.

An oil state detection apparatus detects the amount of degradation substances contained in oil. The oil state detection apparatus includes a first oscillation circuit including a coil 1 and a capacitor 2, and a first detection device. Either one of the coil 1 or the capacitor 2 is configured to be immersed in oil. The first detection device is configured to detect the oscillatory frequency of the oscillation circuit.

An oil state detection apparatus detects the amount of degradation substances contained in oil. The oil state detection apparatus includes a first oscillation circuit including a coil 1 and a capacitor 2, and a first detection device. Either one of the coil 1 or the capacitor 2 is configured to be immersed in oil. The first detection device is configured to detect the oscillatory frequency of the oscillation circuit.

A measuring device includes a sensor generating a sensor signal in dependence upon a detected measured variable, a compensating facility generating a compensation signal in response to detected shocks, and an evaluating facility generating a measurement result from a difference between the sensor signal and the compensation signal. The compensating facility includes a multi-axis MEMS inertial measuring unit having an acceleration sensor alone or together with a gyroscope and generating a plurality of movement signals in correspondence to a number of axes, and a computer including a computational model trained to model an unwanted signal portion of the sensor signal in response to the shocks caused by the movement signals, and to output the unwanted signal portion as a compensation signal. The computational mod& is trained such that absent a measured variable, the difference between the sensor signal and the compensation signal is zero or is below a predetermined threshold.

A measuring device includes a sensor generating a sensor signal in dependence upon a detected measured variable, a compensating facility generating a compensation signal in response to detected shocks, and an evaluating facility generating a measurement result from a difference between the sensor signal and the compensation signal. The compensating facility includes a multi-axis MEMS inertial measuring unit having an acceleration sensor alone or together with a gyroscope and generating a plurality of movement signals in correspondence to a number of axes, and a computer including a computational model trained to model an unwanted signal portion of the sensor signal in response to the shocks caused by the movement signals, and to output the unwanted signal portion as a compensation signal. The computational mod& is trained such that absent a measured variable, the difference between the sensor signal and the compensation signal is zero or is below a predetermined threshold.