JP2021096181A - Air bubble detector, method for detecting air bubble, and program thereof - Google Patents

Abstract

To provide a device and a method for easily detecting an air bubble in a liquid.SOLUTION: The present invention relates to a device 10 for detecting an air bubble in a liquid, and the device includes: a micro electric mechanical system (MEMS) acoustic sensor 12 for detecting a sound wave in the liquid by contacting the liquid; and a signal analysis unit 14 for analyzing an output signal from the MEMS acoustic sensor generated according to the detected sound wave, the signal analysis unit having a detection unit 15 for determining the frequency characteristic of the output signal and detecting a regular change.SELECTED DRAWING: Figure 2

Description

The present invention relates to a technique for detecting and measuring air bubbles in a liquid.

Conventionally, an ultrasonic detection device is known as a method for detecting a minute amount of bubbles in a liquid. The ultrasonic detection device also attaches an ultrasonic detection means to a conduit through which a liquid is passed to detect or quantify air bubbles mixed in the conduit. Bubbles in the conduit are detected or quantified according to the reception level of ultrasonic waves on the receiving device side (see, for example, Patent Document 1).

Further, in a dispenser device, there is known a method of detecting the presence or absence of air bubbles in a liquid filled in a syringe by the position of a plunger that applies pressure to the liquid (see, for example, Patent Document 2).

Japanese Unexamined Patent Publication No. 2004-325350 Japanese Unexamined Patent Publication No. 2013-237019

However, the ultrasonic detection device of Patent Document 1 has a problem that bubbles cannot be detected when the liquid in the conduit is stationary, and bubbles in droplets on the solid surface cannot be detected. With the dispenser device of Patent Document 2, it is difficult to accurately measure the displacement of the plunger, and there is a problem that the structure is complicated.

An object of the present invention is to provide an apparatus, method and program capable of easily detecting air bubbles contained in a liquid.

According to one aspect of the present invention, a device for detecting air bubbles contained in a liquid, which is provided so as to be in contact with the liquid, and is a micro electromechanical system (MEMS) acoustic sensor that detects sound waves in the liquid. A signal analysis unit that analyzes an output signal from the MEMS acoustic sensor generated in response to the detected sound wave is provided, and the signal analysis unit obtains the frequency characteristics of the output signal and performs periodic fluctuations. The above-mentioned device having a detection unit for detecting is provided.

According to the above aspect, the MEMS acoustic sensor detects the sound wave in the liquid, and the detection unit of the signal analysis unit obtains the frequency characteristic of the output signal from the MEMS acoustic sensor generated in response to the sound wave, and the period of the output signal. By detecting the fluctuation, it is possible to provide an apparatus capable of detecting the presence or absence of air bubbles in the liquid.

According to another aspect of the present invention, it is a method of detecting air bubbles contained in a liquid, and the sound waves in the liquid are detected by a micro electromechanical system (MEMS) acoustic sensor provided so as to be in contact with the liquid. And the step of analyzing the output signal from the MEMS acoustic sensor generated in response to the detected sound wave, the step of obtaining the frequency characteristic of the output signal and detecting the periodic fluctuation. The above methods including, are provided.

According to the other aspect described above, the sound wave in the liquid is detected by the MEMS acoustic sensor provided so as to be in contact with the liquid, the frequency characteristic of the output signal from the MEMS acoustic sensor is obtained, and the periodic fluctuation is detected. , A method capable of detecting the presence or absence of air bubbles in a liquid can be provided.

According to another aspect of the present invention, from the MEMS acoustic sensor generated in response to a sound propagating in the liquid, detected by a microelectromechanical system (MEMS) acoustic sensor provided in the computer so as to be in contact with the liquid. A program for executing the step of analyzing the output signal, which obtains the frequency characteristic of the output signal and detects periodic fluctuations, is provided.

According to the other aspect described above, the output signal from the MEMS acoustic sensor corresponding to the sound wave in the liquid detected by the MEMS acoustic sensor provided so as to be in contact with the liquid is analyzed to obtain the frequency characteristic of the output signal and periodically. By detecting fluctuations, it is possible to provide a program that can detect the presence or absence of air bubbles in the liquid.

It is explanatory drawing of the principle of detecting the bubble in the droplet which collided with the surface of the object of this invention. It is a block diagram which shows the structure of the bubble detection apparatus which concerns on 1st Embodiment of this invention. It is a perspective view which shows the schematic structure of the MEMS acoustic sensor of the bubble detection apparatus which concerns on 1st Embodiment of this invention. It is sectional drawing of the MEMS acoustic sensor. It is a figure which shows the circuit structure of the signal processing part of the bubble detection apparatus which concerns on 1st Embodiment of this invention. It is a block diagram which shows the hardware structure of a signal analysis part. It is a flowchart of the bubble detection method which concerns on 1st Embodiment of this invention. It is a block diagram which shows the structure of the bubble detection apparatus which concerns on 2nd Embodiment of this invention. It is (a) the waveform diagram of the output signal from the signal processing unit at the time of a droplet collision of Example 1, and (b) a photograph of a droplet. It is the waveform diagram of the output signal of the (a) MEMS acoustic sensor at the time of the droplet collision of Example 2, and (b) the photograph of the droplet. 2 is a partially enlarged waveform diagram of an output signal from the signal processing unit of Example 2 and a frequency spectrum FFT-processed by the bubble detection unit. It is a figure which shows the relationship between a bubble radius and a peak frequency.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. Elements common to a plurality of drawings are designated by the same reference numerals, and the repetition of detailed description of the elements will be omitted.

FIG. 1 is a diagram for explaining a principle of detecting air bubbles in a droplet colliding with the surface of an object of the present invention. With reference to FIG. 1, when the droplet DR is dropped, it jumps up immediately after colliding with the surface of the object, and at that time, air is entrained due to the properties of the surface of the object and bubbles are generated. Bubbles vibrate in the droplet and propagate in the droplet as sound waves. The frequency of sound waves is known to depend on the size of bubbles (W. Lauterborn, T. Kurz, Rep. Prog. Phys. 73 (2010) 106501 (88pp)).

The inventors of the present application place a microelectromechanical system (MEMS) acoustic sensor on the surface of an object, detect the generation of sound waves by detecting sound waves due to periodic vibration of the sound waves, and further determine the frequency characteristics of the sound waves. It was learned that the size of bubbles, for example, the radius, can be measured based on the frequency of the peak energy. As will be described later, this detection method can also detect bubbles in a liquid by vibrating them by applying a pressure larger than the atmospheric pressure to the liquid.

[First Embodiment]
FIG. 2 is a block diagram showing a configuration of a bubble detection device according to the first embodiment of the present invention. With reference to FIG. 2, the bubble detection device 10 according to the first embodiment includes a microelectromechanical system (MEMS) acoustic sensor 12 arranged on the surface 11a of the object 11, a signal processing unit 13, and a signal analysis unit. It has 14. The object 11 is a solid, for example, paper for inkjet printing. The MEMS acoustic sensor 12 is arranged on the surface 11a of the object 11 and detects the force on which the droplet DR dropped from the droplet generation unit 18 acts. The force exerted by the droplet DR on the MEMS acoustic sensor 12 includes, as described above, due to sound waves based on the vibration of bubbles in the droplet. A mechanical force that pushes the sound wave propagating in the liquid in the propagating direction acts on the MEMS acoustic sensor 12. Therefore, when at least a part of the droplet DR collides with the MEMS acoustic sensor 12, a force due to the collision and rebound of the droplet DR acts on the MEMS acoustic sensor 12, and further, when bubbles are generated in the droplet, if the droplet DR is generated. A force due to sound waves based on the vibration of the bubble DR works.

The signal processing unit 13 converts the change in the electrical resistance value according to the force acting from the droplet DR from the MEMS acoustic sensor 12 and outputs the output signal to the signal analysis unit 14.

The signal analysis unit 14 analyzes the output signal from the signal processing unit 13. The signal analysis unit 14 has a bubble detection unit 15. The bubble detection unit 15 obtains the frequency characteristics of the output signal and detects periodic fluctuations. The bubble detection unit 15 performs, for example, discrete Fourier transform (DFT) processing of the output signal, particularly fast Fourier transform (FFT) processing, and acquires the frequency of the energy peak of the frequency characteristic of the output signal to obtain the period of the output signal. Detect fluctuations. When the bubble detection unit 15 detects periodic fluctuations, it determines that the droplet DR contains bubbles. The bubble detection unit 15 may output the determination result and display it on a display (not shown), for example.

The signal analysis unit 14 may have a bubble size estimation unit 16. The bubble size estimation unit 16 refers to the data relating to the relationship between the frequency of the peak energy of the waveform portion of the periodic fluctuation obtained in advance and the bubble size stored in the bubble size data storage unit 17, and the bubble detection unit 15 Estimate the size of the generated bubbles from the frequency of the peak obtained in. The bubble size data storage unit 17 may have a regression equation of the bubble radius and the peak frequency obtained from the image acquired by the high-speed camera as shown in FIG. 11, and the correspondence between the bubble radius and the peak frequency may be obtained. It may have a table. The bubble size estimation unit 16 may output the size of the bubbles thus obtained and display it on, for example, a display (not shown).

FIG. 3 is a perspective view showing a schematic configuration of a MEMS acoustic sensor of the bubble detection device according to the embodiment of the present invention. FIG. 4 is a cross-sectional view taken along the line AA shown in FIG. 3 of the MEMS acoustic sensor. In FIG. 3, the insulating layer 30 shown in FIG. 4 is omitted for convenience of illustration.

With reference to FIGS. 3 and 4, the MEMS acoustic sensor 12 is arranged on the surface 11a of the object 11. The MEMS acoustic sensor 12 is preferably arranged so that the surface 11a of the object 11 and the MEMS acoustic sensor 12 are continuous with each other. In the MEMS acoustic sensor 12, a frame-shaped silicon substrate 20, a silicon oxide layer 21 and a silicon layer 22 are laminated in this order. The MEMS acoustic sensor 12 is provided with a cantilever 23 as an elastic element in the opening 20a. The cantilever 23 has a base portion 23a supported by a laminated body of a frame-shaped silicon substrate 20 and a silicon oxide layer 21, and a tip portion 23b having a free end. The cantilever 23 has a so-called cantilever shape, for example, a length of 100 μm and a width of 80 μm. The cantilever 23 is not particularly limited as long as it is an elastic material. Openings 20s are provided on both sides and the tip of the cantilever 23. The width of the opening 20s is, for example, 1 μm or less.

In the present embodiment, the cantilever 23 is formed with piezoresistive layers 24c and 24d as strain detection layers in the depth direction from the surface of the silicon layer 22. The conductive layer 26 and the electrodes 28 and 29 are formed on a part of the silicon layer 22 and the piezoresistive layers 24c and 24d. The piezoresistive layers 24c and 24d are formed on the two legs 23c and 23d on the base side of the cantilever 23, respectively. Electrodes 28 and 29 are formed on the surface of the laminated body of the frame-shaped silicon substrate 20 and the silicon oxide layer 21. A conductive layer 26 is formed on the surface of the cantilever 23.

An insulating layer 30 is formed on the surfaces of the piezoresistive layers 24c and 24d, the conductive layer 26 and the electrodes 28 and 29 to prevent electrical short circuits when the droplets are conductive. For the insulating layer 30, silicon oxide, parylene (registered trademark), rubber material such as silicone rubber can be used. The insulating layer 30 is preferably a thin film so as not to hinder the vibration of the cantilever 23.

The notch 31 between the leg 23c and the leg 23d adjusts the deflection of the cantilever 23 with respect to the force from the droplet DR to adjust the sensitivity to the force, and the width thereof is appropriately selected.

The electrode 28 is formed in contact with one end of the piezoresistive layer 24c on the base side of the leg 23c, and is electrically connected to the piezoresistive layer 24c. The electrode 29 is formed in contact with one end of the piezoresistive layer 24d on the base side of the leg 23d, and is electrically connected to the piezoresistive layer 24d. The conductive layer 26 is formed in contact with the other end of the piezoresistive layer 24c at the tip of the leg 23c, and is electrically connected to the piezoresistive layer 24c. The conductive layer 26 is further formed at the tip of the leg portion 23d in contact with the other end of the piezoresistive layer 24d, and is electrically connected to the piezoresistive layer 24d. As a result, a series circuit of the electrode 28, the piezoresistive layer 24c, the conductive layer 26, the piezoresistive layer 24d, and the electrode 29 is formed.

The piezoresistive layers 24c and 24d are, for example, regions in which the silicon layer 22 is doped with impurity ions, for example, phosphorus ions, and when stress acts on the piezoresistive layers 24c and 24d, strain occurs, and the electrical resistance value corresponds to the strain. Changes. In the cantilever 23, the legs 23c and 23d are curved by the force received from the droplet DR, and the cantilever 23 vibrates according to the fluctuation of the force. When the legs 23c and 23d are curved, stress acts on the piezoresistive layers 24c and 24d, strain is generated, the electric resistance value changes, and the electric resistance value R between both ends of the piezoresistive layers 24c and 24d changes. To do. The rate of change ΔR / R of the electric resistance value is converted into an output signal by a Wheatstone bridge circuit described later. The MEMS acoustic sensor 12 has a resolution of 0.1 Pa or less.

As an alternative example of the cantilever 23, the MEMS acoustic sensor 12 may have one leg or three or more legs. As a result, the degree of curvature of the leg of the cantilever can be adjusted according to the acting force, and the MEMS acoustic sensor can be selected according to the target pressure range.

In the MEMS acoustic sensor 12, the elastic element may be formed in the shape of a double-sided beam or a diaphragm instead of the cantilever 23.

FIG. 5 is a diagram showing a circuit configuration of a signal processing unit of the bubble detection device according to the embodiment of the present invention, and also shows the electrical resistance of the piezoresistive layer of the MEMS acoustic sensor.

With reference to FIG. 5, the signal processing unit 13 differs from the Wheatston bridge circuit 35 including the resistors R of the piezoresistive layers 24c and 24d and the three resistors R1, R2, R3 (each reference also represents a resistance value). It has a dynamic amplifier 36.

In the Wheatstone bridge circuit 35, where the combined resistance value R of the piezoresistive layers 24c and 24d and the change in resistance value due to distortion are ΔR, the output voltage V _PQ between the PQs of the Wheatstone bridge circuit 35 is expressed by the following equation (1). Will be done.
V _PQ = 1/4 x ΔR / R x E ... (1)
However, in order to balance the Wheatstone bridge circuit 35, the resistance values R1, R2, and R3 are set so that R × R2 = R1 × R3. The DC power supply is connected between the ABs of the Wheatstone bridge circuit 35 and has a voltage E (V). For example, when E = 1V (volt) and ΔR / R = 0.001, an _{output of V PQ} = 0.25 mV (millimeter volt) can be obtained.

The output voltage V _PQ is amplified by the differential amplifier 36 connected between the PQs of the Wheatstone bridge circuit 35 and supplied to the signal analysis unit 14.

The signal analysis unit 14 realizes the functions described in FIG. 2 and its description to detect bubbles in the droplet and estimate the size of the bubbles. As the signal analysis unit 14, for example, the personal computer shown in FIG. 6 can be used.

FIG. 6 is a block diagram showing a hardware configuration of the signal analysis unit. Referring to FIG. 6, the signal analysis unit 14 has an input interface 41, a processor 42, a memory 43, and a bus 44 connecting them. The input interface 41 receives an output signal from the signal processing unit 13 and transmits it to the processor 42 or the memory 43 via the bus 44 including an A / D converter (not shown) that converts an analog signal into a digital signal. The processor 42 is a CPU (Central Processing Unit), a GPU (Graphic Processing Unit), or the like, and the bubble detection unit 15 and the bubble size estimation unit 16 described above are subjected to a program stored in the memory 43 or the memory included in the processor 42. Realize the function. The program includes a program for determining the frequency characteristics of the output signal, for example, a program for performing a discrete Fourier transform (DFT) process, particularly a fast Fourier transform (FFT) process. A program or the like for displaying a signal waveform on the display unit 45 may be included.

The memory 43 is a RAM (Random Access Memory), a ROM (Read Only Memory), or the like, and is, for example, a flash memory. The memory 43 may store the above program, the bubble size data storage unit 17 may be provided in a part of the memory 43, or a dedicated memory or a hard disk device (not shown) may be provided.

The signal analysis unit 14 may include a display unit 45 that displays an input signal waveform, a frequency spectrum or the like by FFT processing, or may include a user interface 46 that sets a program or the like. The signal analysis unit 14 may have a wireless communication interface 48 and / and a wired communication interface 59 in order to output the analysis result.

The signal analysis unit 14 may configure the bubble detection unit 15 using an oscilloscope, an FFT (Fast Fourier Transform) analyzer, or the like.

According to the bubble detection device 10 according to the present embodiment, a liquid is dropped or jetted from the droplet generating unit 18 onto the surface 11a of the object 11 provided with the MEMS acoustic sensor 12, and is generated when the droplets collide. The MEMS acoustic sensor 12 detects the sound to be generated, and the bubble detection unit 15 of the signal analysis unit 14 obtains the frequency characteristic of the output signal from the MEMS acoustic sensor 12 generated in response to the sound. For example, the peak of the energy of the frequency characteristic. By detecting the periodic fluctuation of the output signal by acquiring the frequency of, the presence or absence of air bubbles in the droplet can be detected. Further, according to the bubble detection device 10, the bubble size estimation unit 16 determines the peak frequency stored in the bubble size data storage unit 17 from the frequency of the peak of the energy of the frequency characteristic acquired by the bubble detection unit 15. The size of the bubbles in the droplet can be estimated by referring to the relationship between the frequency and the size of the bubbles.

FIG. 7 is a flowchart of a bubble detection method according to an embodiment of the present invention. A bubble detection method will be described with reference to FIG. 7 and FIG.

First, the droplet generation unit 18 drops the droplet DR onto the surface 11a of the object 11 on which the MEMS acoustic sensor 12 is arranged (S100). Specifically, a drop of liquid in the droplet generation unit 18, for example, a syringe, is dropped on the MEMS acoustic sensor 12 arranged on the surface 11a of the object 11. The droplet DR differs in the rebound process, shape, bubble formation, etc. after collision depending on the surface shape, surface roughness, surface wettability, etc. of the object.

Next, the MEMS acoustic sensor 12 detects the sound wave propagating in the droplet (S110). Specifically, the dropped droplet DR gives a force due to collision to the MEMS acoustic sensor 12, and further rebounds on the surface 11a to change the force acting on the MEMS acoustic sensor 12. When bubbles are generated in the collision droplet DR, sound waves of periodic vibration (that is, a certain frequency) due to the vibration of the bubbles act on the MEMS acoustic sensor 12. The MEMS acoustic sensor 12 detects such forces and sound waves.

Next, the output signal from the MEMS acoustic sensor 12 is analyzed to obtain the frequency characteristics of the output signal, and periodic fluctuations are detected (S120). Specifically, the signal processing unit 13 converts the resistance value changes of the piezo resistance layers 24c and 24d of the MEMS acoustic sensor 12 into an output signal and amplifies the signal, and the signal analysis unit 14 performs a fast Fourier transform process to peak the energy spectrum. Is detected, it is determined that the droplet contains air bubbles. Multiple peaks may appear with respect to the frequency axis.

Next, the bubble size estimation unit 16 refers to the relationship between the frequency of the peak energy of the waveform portion of the periodic fluctuation of the output signal stored in the bubble size data storage unit 17 and the size of the bubble. The size of bubbles in the droplet is estimated from the frequency of the peak acquired by the bubble detection unit 15 (S130).

According to the bubble detection method according to the present embodiment, the droplet generation unit 18 drops the droplet DR onto the surface 11a of the object 11 on which the MEMS acoustic sensor 12 is arranged, and the output signal from the MEMS acoustic sensor 12 is output. The presence or absence of air bubbles in the droplet can be detected by obtaining the frequency characteristic and detecting the periodic fluctuation. Further, from the frequency of the peak of the energy of the frequency characteristic, the size of the bubble in the droplet is determined by referring to the relationship between the frequency of the peak obtained in advance and the size of the bubble stored in the bubble size data storage unit 17. Can be estimated.

[Second Embodiment]
FIG. 8 is a block diagram showing a configuration of a bubble detection device according to a second embodiment of the present invention.
With reference to FIG. 8, the bubble detection device 100 according to the second embodiment includes a syringe 111, a MEMS acoustic sensor 12 arranged on the inner wall thereof, a signal processing unit 13, a signal analysis unit 14, and a pressure application unit. It has 113 and a tube 114.

A liquid LQ is housed in the syringe 111, and a pressure applying unit 113 applies a predetermined incremental pressure to the liquid LQ in the syringe 111 via the tube 114 in a short time to hold the liquid LQ. For example, when the pressure of the gas in the syringe 111 is 0.1 MPa (1 atm), an incremental pressure of 0.5 MPa or less is applied so as to reach in a short time (for example, 100 ms (milliseconds)). As a result, when there are air bubbles in the liquid, the air bubbles in the liquid vibrate by applying pressure to the liquid LQ and propagate in the liquid as sound waves, and the MEMS acoustic sensor 12 detects the sound waves.

The signal processing unit 13 and the signal analysis unit 14 perform the same operations as in the first embodiment. The bubble detection unit 15 of the signal analysis unit 14 obtains the frequency characteristics of the output signal and detects periodic fluctuations. The bubble detection unit 15 performs FFT processing to acquire the frequency of the energy peak of the frequency characteristic of the output signal. The bubble size estimation unit 16 of the signal analysis unit 14 refers to the relationship between the frequency of the peak energy of the energy peak of the periodic fluctuation waveform portion of the output signal stored in the bubble size data storage unit 17 and the bubble size. Then, the size of bubbles in the liquid LQ is estimated from the frequency of the peak acquired by the bubble detection unit 15.

When a plurality of bubbles having different sizes are present in the liquid LQ, the bubble detection unit 15 detects a plurality of peaks having different frequencies. The bubble size estimation unit 16 estimates the bubble size for each peak frequency acquired by the bubble detection unit 15.

As a result, in the bubble detection device 100, the bubble detection unit 15 can detect the presence or absence of bubbles, and when there are bubbles in the liquid LQ, the bubble size estimation unit 16 can estimate the size of each bubble. is there.

The bubble detection device 100 is applicable to a dispenser that discharges a liquid agent. The dispenser provided with the bubble detection device 100 can detect the presence or absence of bubbles in the liquid. If there are air bubbles, an alarm can be set to prevent the discharge amount from fluctuating due to the adverse effects of air bubbles.

The bubble detection method according to the second embodiment of the present invention is almost the same as the bubble detection method of the first embodiment shown in FIG. 7, and thus the illustration is omitted. In the bubble detection method according to the second embodiment, instead of S100 in FIG. 7, a step of applying a predetermined pressure to the liquid LQ in the syringe is performed by the pressure application unit 113, and then each step of S110 to S130 is performed. Do. Thereby, the presence or absence of bubbles can be detected, and further, when there are bubbles in the liquid LQ, the size of each bubble can be estimated.

[Example]
Using the bubble detection device 10 according to the first embodiment shown in FIG. 2, water droplets were dropped on the MEMS acoustic sensor 12 arranged on the surface of the silicon substrate to detect and analyze the output signal at the time of collision. At the same time, water droplets were photographed using a high-speed camera (Photron model FASTCAM SA-Z, photographing speed 50,000 frames / sec).

FIG. 9 is a waveform diagram of (a) an output signal from the signal processing unit at the time of droplet collision of Example 1 and (b) a photograph of the droplet. In (a), the horizontal axis represents time, and the vertical axis represents the output converted into the rate of change ΔR / R of the electric resistance value R between both ends of the piezoresistive layer. (B) is a photograph taken from the side of the droplet at the time when 2 msec, 7 msec, 8 msec, and 14 msec have passed from the start of drip.

In the first embodiment, a water droplet having a diameter of 2.2 mm is dropped on the surface of the silicon substrate to set the speed at the time of collision to 0.64 m / s. With reference to FIGS. 9A and 9B, a peak appears in the output signal from the signal processing unit 13 due to the impact when the droplet collides with the surface (2 ms), and the droplet separates from the surface. At the hour (14 ms), the output signal becomes 0. No periodic fluctuations appeared during the period. With reference to FIG. 9B, it can be seen that no bubbles appear in all of the images of the four droplets.

FIG. 10 is a waveform diagram of the output signal of the MEMS acoustic sensor at the time of the droplet collision of the second embodiment and (b) a photograph of the droplet. The second embodiment is a case where a water droplet having a diameter of 2.2 mm is dropped on the surface of the silicon substrate and the speed at the time of collision is set to 0.50 m / s. With reference to FIGS. 10A and 10B, a peak appears in the output signal from the signal processing unit 13 due to the impact when the droplet collides with the surface (2 ms), and the droplet separates from the surface. At the hour (14 ms), the output signal becomes 0. In the meantime, it can be seen that periodic fluctuations appear from 7.2 msec to 9.7 msec. As shown in FIG. 9B, it can be seen that bubbles appear in the droplets of the image at 8 msec.

FIG. 11 is a partially enlarged waveform diagram of (a) the output signal from the signal processing unit of Example 2 and (b) a frequency spectrum FFT-processed by the bubble detection unit.

With reference to FIG. 11A, since the output signal from the signal processing unit of the second embodiment clearly contains periodic fluctuations, it can be seen by the bubble detection unit 15 that bubbles are present. With reference to FIG. 11B, it can be seen that the frequency spectrum acquired by the FFT process by the bubble detection unit 15 has an energy spectrum peak at 12 kHz.

FIG. 12 is a diagram showing the relationship between the bubble radius and the peak frequency. With reference to FIG. 12, the bubble size estimation unit 16 uses a regression equation (f _B (kHz) = 5 × 10) _{showing the relationship between the bubble radius r B} stored in the bubble size data storage unit 17 and the peak frequency f _B. ^With reference to 6 r _B (μm) ^-1.02 ), the bubble size is estimated from the frequency of the peak of the energy spectrum acquired by the bubble detection unit 15. According to FIG. 11B, since the peak frequency is 12 kHz, the bubble size can be estimated to be 370 μm. This regression equation is obtained by the method of least squares.

Although the preferred embodiment of the present invention has been described in detail above, the present invention is not limited to the specific embodiment, and various modifications and changes can be made within the scope of the present invention described in the claims. It is possible. Instead of the piezoresistive layers 24c and 24d of the MEMS acoustic sensor 12, a piezo piezoelectric layer may be adopted. When the piezo piezoelectric layer is used, the Wheatstone bridge circuit 35 of the signal processing unit 13 shown in FIG. 5 is omitted.

Regarding the above description, the following additional notes will be further disclosed as an embodiment.
(Appendix 1) A device that detects air bubbles contained in a liquid.
A microelectromechanical system (MEMS) acoustic sensor that is provided in contact with the liquid and detects sound waves in the liquid.
A signal analysis unit that analyzes an output signal from the MEMS acoustic sensor generated in response to the detected sound wave is provided.
The signal analysis unit includes a detection unit that obtains a frequency characteristic of the output signal and detects periodic fluctuations.
(Appendix 2) The apparatus according to Appendix 1, wherein when the detection unit detects the periodic fluctuation, it determines that the liquid contains air bubbles.
(Appendix 3) The detection unit detects periodic fluctuations in the output signal by acquiring the frequency of the peak energy of the frequency characteristics of the output signal.
The signal analysis unit refers to the relationship between the frequency of the peak energy of the waveform portion of the periodic fluctuation of the output signal obtained in advance and the size of the bubble, and obtains the frequency of the peak obtained by the detection unit. The device according to Appendix 1 or 2, further comprising an estimation unit for estimating the size of bubbles in a liquid.
(Appendix 4) When the detection unit acquires the frequencies of a plurality of peaks of the energy of the frequency characteristics of the output signal, the estimation unit estimates the size of bubbles corresponding to the frequencies of the plurality of peaks. Possible device according to Appendix 3.
(Appendix 5) Further provided with a droplet generation unit for generating droplets by dropping or injecting the above liquid onto the surface of an object.
The apparatus according to any one of Supplementary note 1 to 4, wherein the MEMS acoustic sensor detects a sound wave generated when the droplet collides with the surface of the object provided with the MEMS acoustic sensor.
(Appendix 6) The apparatus according to Appendix 5, wherein the detection unit detects the periodic fluctuation after the first peak in which the droplet collides with the surface of the object in the output signal.
(Appendix 7) The apparatus according to Appendix 5 or 6, wherein the surface of the object is a printing surface for inkjet printing.
(Appendix 8) Further provided with a pressure applying portion for applying pressure to the liquid is provided.
The device according to any one of Supplementary note 1 to 4, wherein the MEMS acoustic sensor detects a sound wave due to vibration of bubbles contained in the liquid by applying pressure to the liquid by the pressure applying unit.
(Appendix 9) Further provided with a syringe for accommodating the above liquid,
The device according to Appendix 8, wherein the MEMS acoustic sensor is arranged on the inner wall surface of the syringe.
(Appendix 10) The MEMS acoustic sensor has an elastic element that covers at least a part of an opening that comes into contact with the liquid or a droplet, and the elastic element is curved in response to a sound wave generated by the bubble, and in response to the curvature. The apparatus according to any one of Supplementary note 1 to 9, wherein a strain detection layer for detecting the strain is formed.
(Appendix 11) The device according to Appendix 10, wherein the elastic element is formed in a cantilever shape, a double beam shape, or a diaphragm shape.
(Appendix 12) The apparatus according to Appendix 10 or 11, wherein the strain detection layer is a piezoresistive layer or a piezoelectric piezoelectric layer.
(Appendix 13) A method for detecting air bubbles contained in a liquid.
A step of detecting a sound wave propagating in the liquid by a microelectromechanical system (MEMS) acoustic sensor provided so as to be in contact with the liquid, and a step of detecting the sound wave propagating in the liquid.
The step of analyzing the output signal from the MEMS acoustic sensor generated in response to the detected sound wave, which includes the step of obtaining the frequency characteristic of the output signal and detecting the periodic fluctuation. Method.
(Appendix 14) The method according to Appendix 13, wherein when the periodic fluctuation is detected in the analysis step, it is determined that the liquid contains air bubbles.
(Appendix 15) In the step of the analysis, the periodic fluctuation of the output signal is detected by acquiring the frequency of the energy peak of the frequency characteristic of the output signal.
The size of bubbles in the liquid is estimated from the frequency of the obtained peak with reference to the relationship between the peak frequency of energy and the size of bubbles in the waveform portion of the periodic fluctuation of the output signal obtained in advance. The method according to Appendix 13 or 14, further comprising the steps to be performed.
(Appendix 16) When the frequencies of a plurality of peaks of the energy of the frequency characteristics of the output signal are acquired in the step of the analysis, the size of the bubbles corresponding to the frequencies of the plurality of peaks is obtained in the step of the estimation. 15. The method according to Appendix 15.
(Appendix 17) Prior to the detection step, the step of dropping or injecting the liquid onto the surface of the object to generate droplets is further included.
The method according to any one of Supplementary note 13 to 16, wherein the MEMS acoustic sensor detects a sound wave generated when the droplet collides with the surface of the object provided with the MEMS acoustic sensor.
(Appendix 18) Prior to the detection step, a step of applying pressure to the liquid by the pressure applying unit is further included.
The method according to any one of Supplementary note 13 to 16, wherein the MEMS acoustic sensor detects a sound wave due to vibration of bubbles contained in the liquid by applying pressure to the liquid.
(Appendix 19) To the computer
It is a step of analyzing the output signal from the MEMS acoustic sensor generated in response to the sound wave propagating in the liquid detected by the microelectromechanical system (MEMS) acoustic sensor provided so as to be in contact with the liquid. A program that executes the above steps to detect periodic fluctuations by finding the frequency characteristics of.
(Appendix 20) The program according to Appendix 19, which determines that the liquid contains air bubbles when the periodic fluctuation is detected in the analysis step.
(Appendix 21) In the step of the analysis, the periodic fluctuation of the output signal is detected by acquiring the frequency of the energy peak of the frequency characteristic of the output signal.
The size of bubbles in the liquid is estimated from the frequency of the obtained peak with reference to the relationship between the peak frequency of energy and the size of bubbles in the waveform portion of the periodic fluctuation of the output signal obtained in advance. The program according to Appendix 19 or 20, further comprising the steps to be performed.
(Appendix 22) When the frequencies of a plurality of peaks of the energy of the frequency characteristics of the output signal are acquired in the step of the analysis, the size of the bubbles corresponding to the frequencies of the plurality of peaks is obtained in the step of the estimation. 21. The program according to Appendix 21.

10,100 Bubble detection device 12 Microelectromechanical system (MEMS) Acoustic sensor 13 Signal processing unit 14 Signal analysis unit 15 Bubble detection unit 16 Bubble size estimation unit 17 Bubble size data storage unit 18 Droplet generation unit 113 Pressure application unit

Claims (15)

A device that detects air bubbles contained in a liquid.
A microelectromechanical system (MEMS) acoustic sensor that is provided in contact with the liquid and detects sound waves in the liquid.
A signal analysis unit that analyzes an output signal from the MEMS acoustic sensor generated in response to the detected sound wave is provided.
The signal analysis unit includes a detection unit that obtains a frequency characteristic of the output signal and detects periodic fluctuations. The device according to claim 1, wherein the detection unit determines that the liquid contains air bubbles when the periodic fluctuation is detected. The detection unit detects periodic fluctuations in the output signal by acquiring the frequency of the peak energy of the frequency characteristics of the output signal.
The signal analysis unit refers to the relationship between the frequency of the peak energy of the waveform portion of the periodic fluctuation of the output signal and the size of the bubble obtained in advance, and obtains the frequency of the peak obtained by the detection unit. The device according to claim 1 or 2, further comprising an estimation unit for estimating the size of bubbles in a liquid. Further provided with a droplet generating section for generating droplets by dropping or injecting the liquid onto the surface of an object.
The device according to any one of claims 1 to 3, wherein the MEMS acoustic sensor detects a sound wave generated when the droplet collides with the surface of the object provided with the MEMS acoustic sensor. The apparatus according to claim 4, wherein the detection unit detects the periodic fluctuation after the first peak in which the droplet collides with the surface of the object in the output signal. Further provided with a pressure applying portion for applying pressure to the liquid,
The device according to any one of claims 1 to 3, wherein the MEMS acoustic sensor detects a sound wave due to vibration of bubbles contained in the liquid by applying pressure to the liquid by the pressure applying unit. Further provided with a syringe for accommodating the liquid
The apparatus according to claim 6, wherein the MEMS acoustic sensor is arranged on an inner wall surface of the syringe. The MEMS acoustic sensor has an elastic element that covers at least a part of an opening that comes into contact with the liquid or a droplet, and the elastic element is curved in response to a sound wave generated by the bubble, and a strain corresponding to the curvature is detected. The apparatus according to any one of claims 1 to 7, wherein a strain detection layer is formed. The device according to claim 8, wherein the strain detection layer is a piezoresistive layer or a piezoelectric piezoelectric layer. It is a method of detecting air bubbles contained in a liquid.
A step of detecting sound waves propagating in the liquid by a microelectromechanical system (MEMS) acoustic sensor provided so as to be in contact with the liquid.
The step of analyzing an output signal from the MEMS acoustic sensor generated in response to the detected sound wave, the step of obtaining a frequency characteristic of the output signal and detecting periodic fluctuations, and the above-mentioned step. Method. The method according to claim 10, wherein when the periodic fluctuation is detected in the analysis step, it is determined that the liquid contains air bubbles. In the step of the analysis, the periodic fluctuation of the output signal is detected by acquiring the frequency of the peak energy of the frequency characteristic of the output signal.
The size of bubbles in the liquid is estimated from the frequency of the obtained peak with reference to the relationship between the peak frequency of energy and the size of bubbles in the waveform portion of the periodic fluctuation of the output signal obtained in advance. 10. The method of claim 10 or 11, further comprising the steps of Prior to the detection step, the step of dropping or jetting the liquid onto the surface of the object to generate droplets is further included.
The method according to any one of claims 10 to 12, wherein the MEMS acoustic sensor detects a sound wave generated when the droplet collides with the surface of the object provided with the MEMS acoustic sensor. Prior to the detection step, a step of applying pressure to the liquid by a pressure applying unit is further included.
The method according to any one of claims 10 to 12, wherein the MEMS acoustic sensor detects a sound wave due to vibration of bubbles contained in the liquid by applying pressure to the liquid. On the computer
It is a step of analyzing an output signal from the MEMS acoustic sensor generated in response to a sound wave propagating in the liquid detected by a microelectromechanical system (MEMS) acoustic sensor provided so as to be in contact with the liquid. A program that executes the step of detecting periodic fluctuations by obtaining the frequency characteristics of the sound wave.

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