JP7426071B2 - Bubble detection device, bubble detection method and its program - Google Patents

Description

The present invention relates to technology for detecting and measuring bubbles in liquid.

2. Description of the Related Art Conventionally, an ultrasonic detection device is known as a method for detecting a minute amount of air bubbles in a liquid. The ultrasonic detection device also includes an ultrasonic detection means attached to a conduit through which liquid is passed, and detects or quantifies air bubbles mixed into the conduit. Air bubbles in the conduit are detected or quantified based on the reception level of the ultrasonic waves on the receiving device side (see, for example, Patent Document 1).

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

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

However, the ultrasonic detection device of Patent Document 1 has problems in that it cannot detect air bubbles when the liquid in the conduit is stationary, and it cannot detect air bubbles in droplets on a solid surface. The dispenser device of Patent Document 2 has problems in that it is difficult to accurately measure the displacement of the plunger, and its structure is also complicated.

An object of the present invention is to provide a device, method, and program that can easily detect bubbles contained in a liquid.

According to one aspect of the present invention, there is provided a device for detecting air bubbles contained in a liquid, the device including a microelectromechanical system (MEMS) acoustic sensor that is provided so as to be able to come into 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, the signal analysis unit determining the frequency characteristics of the output signal and analyzing periodic fluctuations. The above-described device is provided, having a detecting section for detecting.

According to the above aspect, the MEMS acoustic sensor detects a sound wave in the liquid, and the frequency characteristic of the output signal from the MEMS acoustic sensor generated in response to the sound wave is determined by the detection unit of the signal analysis unit to determine the period of the output signal. By detecting such fluctuations, it is possible to provide a device that can detect the presence or absence of bubbles in a liquid.

According to another aspect of the invention, there is provided a method for detecting air bubbles contained in a liquid, wherein sound waves in the liquid are detected by a microelectromechanical system (MEMS) acoustic sensor provided in contact with the liquid. a step of analyzing an output signal from the MEMS acoustic sensor generated in response to the detected sound wave, the step of determining a frequency characteristic of the output signal and detecting periodic fluctuations; The above method is provided.

According to the other aspect, the sound waves in the liquid are detected by the MEMS acoustic sensor provided so as to be able to come into contact with the liquid, and the frequency characteristics of the output signal from the MEMS acoustic sensor are determined to detect periodic fluctuations. , it is possible to provide a method capable of detecting the presence or absence of bubbles in a liquid.

According to another aspect of the present invention, a microelectromechanical system (MEMS) acoustic sensor provided in the computer so as to be able to contact the liquid generates an acoustic wave generated in response to a sound wave propagating through the liquid detected by the MEMS acoustic sensor. A program is provided that executes the step of analyzing the output signal, the step of determining the frequency characteristics of the output signal and detecting periodic fluctuations.

According to the above-mentioned other aspects, 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 able to come into contact with the liquid is analyzed to obtain the frequency characteristics of the output signal, and the periodic By detecting fluctuations, it is possible to provide a program that can detect the presence or absence of bubbles in a liquid.

FIG. 3 is an explanatory diagram of the principle of detecting air bubbles in a droplet colliding with the surface of an object according to the present invention. FIG. 1 is a block diagram showing the configuration of a bubble detection device according to a first embodiment of the present invention. FIG. 1 is a perspective view showing a schematic configuration of a MEMS acoustic sensor of a bubble detection device according to a first embodiment of the present invention. FIG. 2 is a cross-sectional view of a MEMS acoustic sensor. FIG. 3 is a diagram showing a circuit configuration of a signal processing section of the bubble detection device according to the first embodiment of the present invention. FIG. 2 is a block diagram showing the hardware configuration of a signal analysis section. 1 is a flowchart of a bubble detection method according to a first embodiment of the present invention. FIG. 2 is a block diagram showing the configuration of a bubble detection device according to a second embodiment of the present invention. FIG. 3 is a waveform diagram of (a) an output signal from a signal processing unit and (b) a photograph of a droplet when a droplet collides in Example 1. FIG. FIG. 4 is a waveform diagram of (a) the output signal of the MEMS acoustic sensor and (b) a photograph of the droplet when the droplet collides in Example 2. FIG. FIG. 3A is a partial enlarged waveform diagram of the output signal from the signal processing section and FIG. 2B is a frequency spectrum subjected to FFT processing by the bubble detection section in Example 2. FIG. FIG. 3 is a diagram showing the relationship between bubble radius and peak frequency.

Embodiments of the present invention will be described below based on the drawings. Note that the same reference numerals are given to elements that are common among a plurality of drawings, and repeated detailed explanations of the elements will be omitted.

FIG. 1 is a diagram for explaining the principle of detecting air bubbles in a droplet colliding with the surface of an object according to the present invention. Referring to FIG. 1, when a droplet DR is dropped, it bounces up immediately after colliding with the surface of an object, and at this time, air is drawn in due to the nature of the surface of the object, generating bubbles. The bubbles vibrate within the droplet and propagate through the droplet as sound waves. It is known that the frequency of sound waves depends on the size of the bubble (W. Lauterborn, T. Kurz, Rep. Prog. Phys. 73 (2010) 106501 (88pp)).

The inventors of the present application placed a microelectromechanical system (MEMS) acoustic sensor on the surface of a target object and detected the generation of air bubbles by detecting sound waves caused by periodic vibrations of air bubbles, and further determined the frequency characteristics of the sound waves. It was discovered that the size of a bubble, such as its radius, can be measured based on the frequency of the energy peak. As will be explained later, in this detection method, by applying pressure greater than atmospheric pressure to the liquid, it is also possible to vibrate and detect air bubbles in the liquid.

[First embodiment]
FIG. 2 is a block diagram showing the configuration of the bubble detection device according to the first embodiment of the present invention. Referring to FIG. 2, the bubble detection device 10 according to the first embodiment includes a microelectromechanical system (MEMS) acoustic sensor 12 disposed on the surface 11a of an object 11, a signal processing section 13, and a signal analysis section. 14. The object 11 is a solid body, for example, paper on which inkjet printing is performed. The MEMS acoustic sensor 12 is arranged on the surface 11a of the object 11, and detects the force exerted by the droplet DR dropped from the droplet generating section 18. As described above, the force exerted by the droplet DR on the MEMS acoustic sensor 12 includes the force caused by 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 propagation direction acts on the MEMS acoustic sensor 12 . Therefore, when at least a portion 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 furthermore, if bubbles are generated in the droplet, A force is exerted by a sound wave based on the vibration of the bubble DR.

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

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

The signal analysis section 14 may include a bubble size estimation section 16. The bubble size estimating unit 16 refers to the data stored in the bubble size data storage unit 17 regarding the relationship between the frequency of the energy peak of the waveform portion of periodic fluctuations determined in advance and the bubble size. Estimate the size of the generated bubble from the peak frequency obtained. The bubble size data storage unit 17 may have a regression equation between the bubble radius and the peak frequency obtained from an image acquired by a high-speed camera, as shown in FIG. 11 shown later, and the correspondence between the bubble radius and the peak frequency. It may have a table. The bubble size estimation unit 16 may output the bubble size obtained in this way 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 a bubble detection device according to an 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. Note that in FIG. 3, the insulating layer 30 shown in FIG. 4 is omitted for convenience of illustration.

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

In this embodiment, piezoresistive layers 24c and 24d are formed on the cantilever 23 in the depth direction from the surface of the silicon layer 22 as strain detection layers. A conductive layer 26 and electrodes 28, 29 are formed on silicon layer 22 and portions of piezoresistive layers 24c, 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, 24d, the conductive layer 26, and the electrodes 28, 29 to prevent electrical short circuits when the droplets are conductive. For the insulating layer 30, silicon oxide, Parylene (registered trademark), a rubber material such as silicone rubber, etc. can be used. It is preferable that the insulating layer 30 is a thin film to such an extent that the vibration of the cantilever 23 is not inhibited.

The notch 31 between the leg 23c and the leg 23d is used to adjust the deflection of the cantilever 23 against the force from the droplet DR, thereby adjusting the sensitivity to the force, and its width is appropriately selected.

The electrode 28 is formed on the base side of the leg portion 23c in contact with one end of the piezoresistive layer 24c, and is electrically connected to the piezoresistive layer 24c. The electrode 29 is formed on the base side of the leg portion 23d in contact with one end of the piezoresistive layer 24d, and is electrically connected to the piezoresistive layer 24d. The conductive layer 26 is formed at the tip of the leg portion 23c in contact with the other end of the piezoresistive layer 24c, and is electrically connected to the piezoresistive layer 24c. The conductive layer 26 is further formed at the tip of the leg 23d in contact with the other end of the piezoresistive layer 24d, and is electrically connected to the piezoresistive layer 24d. Thereby, 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, such as phosphorus ions, and when stress acts on the piezoresistive layers 24c and 24d, distortion occurs, and the electrical resistance value changes according to the distortion. changes. The legs 23c and 23d of the cantilever 23 curve due to the force received from the droplet DR, and vibrate in response to changes in the force. When the legs 23c and 23d curve, stress acts on the piezoresistive layers 24c and 24d, causing strain, which changes the electrical resistance value and changes the electrical resistance value R between both ends of the piezoresistive layers 24c and 24d. do. The rate of change ΔR/R of the electrical resistance value is converted into an output signal by a Wheatstone bridge circuit, which will be described later. The MEMS acoustic sensor 12 has a resolution of 0.1 Pa or less.

As an alternative to the cantilever 23, the MEMS acoustic sensor 12 may have one leg, or may have three or more legs. As a result, the degree of curvature of the cantilever leg can be adjusted according to the applied 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 into a double-sided beam shape or a diaphragm shape instead of the cantilever 23.

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

Referring to FIG. 5, the signal processing unit 13 includes a Wheatstone bridge circuit 35 including a resistance R of piezoresistive layers 24c and 24d and three resistances R1, R2, and R3 (each symbol also represents a resistance value). It has a dynamic amplifier 36.

In the Wheatstone bridge circuit 35, the output voltage V _PQ between PQ of the Wheatstone bridge circuit 35 is expressed by the following formula (1), where R is the combined resistance value of the piezoresistive layers 24c and 24d, and ΔR is the change in resistance value due to strain. 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. A DC power supply is connected between AB of the Wheatstone bridge circuit 35 and has a voltage of E (V). For example, if E=1V (volt) and ΔR/R=0.001, an output of V _PQ =0.25 mV (millivolt) is obtained.

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

The signal analysis unit 14 realizes the functions described in FIG. 2 and its description, and detects air bubbles in a droplet and estimates the size of the air bubbles. For example, the personal computer shown in FIG. 6 can be used as the signal analysis section 14.

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

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

The signal analysis section 14 may include a display section 45 that displays input signal waveforms, frequency spectra through FFT processing, etc., and may also include a user interface 46 that performs program settings and the like. The signal analysis section 14 may have a wireless communication interface 48 and/or a wired communication interface 59 to output analysis results.

The signal analysis section 14 may configure the bubble detection section 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, the liquid is dropped or injected from the droplet generation unit 18 onto the surface 11a of the object 11 on which the MEMS acoustic sensor 12 is provided, and the bubbles are generated when the droplets collide. The MEMS acoustic sensor 12 detects the sound waves generated in response to the sound waves, and the bubble detection unit 15 of the signal analysis unit 14 calculates the frequency characteristics of the output signal from the MEMS acoustic sensor 12 that is generated according to the sound waves. The presence or absence of bubbles in the droplet can be detected by detecting periodic fluctuations in the output signal by acquiring the frequency of the droplet. Further, according to the bubble detection device 10, the bubble size estimating unit 16 calculates a predetermined peak value stored in the bubble size data storage unit 17 from the frequency of the energy peak of the frequency characteristic acquired by the bubble detection unit 15. The size of the bubble in the droplet can be estimated by referring to the relationship between the frequency and the bubble size.

FIG. 7 is a flowchart of a bubble detection method according to an embodiment of the present invention. The bubble detection method will be described with reference to FIG. 7 along with FIG. 2.

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

Next, the MEMS acoustic sensor 12 detects the sound waves propagating in the droplet (S110). Specifically, the dropped droplet DR applies a force due to collision to the MEMS acoustic sensor 12, and further rebounds on the surface 11a, thereby changing the force acting on the MEMS acoustic sensor 12. When a bubble is generated in the collided droplet DR, a sound wave of periodic vibration (that is, a certain frequency) due to the vibration of the bubble acts on the MEMS acoustic sensor 12. MEMS acoustic sensor 12 detects such forces and sound waves.

Next, the output signal from the MEMS acoustic sensor 12 is analyzed to determine the frequency characteristics of the output signal and detect periodic fluctuations (S120). Specifically, the change in the resistance value of the piezoresistive layers 24c and 24d of the MEMS acoustic sensor 12 is converted into an output signal in the signal processing unit 13 and amplified, and the signal analysis unit 14 performs fast Fourier transform processing to detect the peak of the energy spectrum. If detected, it is determined that the droplet contains air bubbles. Multiple peaks may appear along the frequency axis.

Next, the bubble size estimating unit 16 refers to the relationship between the frequency of the energy peak of the waveform portion of the periodic fluctuation of the output signal and the size of the bubble, which is stored in the bubble size data storage unit 17 and is determined in advance. The size of the bubble in the droplet is estimated from the peak frequency 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 detected. By determining the frequency characteristics and detecting periodic fluctuations, it is possible to detect the presence or absence of air bubbles in the droplet. Furthermore, from the frequency of the energy peak of the frequency characteristic, the size of the bubble in the droplet is determined by referring to the relationship between the peak frequency and bubble size determined in advance, which is stored in the bubble size data storage unit 17. It can be estimated.

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

The syringe 111 contains the liquid LQ, and the pressure applying unit 113 applies and maintains a predetermined increment of pressure to the liquid LQ in the syringe 111 via the tube 114 in a short period of time. For example, when the pressure of the gas in the syringe 111 is 0.1 MPa (1 atm), the pressure is applied in increments of 0.5 MPa or less so as to be reached in a short time (for example, 100 ms (milliseconds)). As a result, if there are bubbles in the liquid, the bubbles in the liquid vibrate due to the pressure applied 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 section 13 and the signal analysis section 14 perform operations similar to those in the first embodiment. The bubble detection section 15 of the signal analysis section 14 determines the frequency characteristics of the output signal and detects periodic fluctuations. The bubble detection unit 15 performs FFT processing to obtain 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 energy peak of the waveform portion of the periodic fluctuation of the output signal and the bubble size, which is stored in the bubble size data storage unit 17 and which has been determined in advance. Then, the size of the 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 of different sizes are present in the liquid LQ, the bubble detection unit 15 detects a plurality of peaks of different frequencies. The bubble size estimation unit 16 estimates the size of the bubble for each peak frequency acquired by the bubble detection unit 15.

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

The bubble detection device 100 can be applied to a dispenser that discharges a liquid agent. A dispenser equipped with the bubble detection device 100 is capable of detecting the presence or absence of bubbles in a liquid agent. By setting an alarm if there are air bubbles, it is possible to avoid variations in the discharge amount 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 according to the first embodiment shown in FIG. 7, so illustration thereof 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 by the pressure application unit 113 is performed, and then each step of S110 to S130 is performed. conduct. Thereby, it is possible to detect the presence or absence of bubbles, and furthermore, when there are bubbles in the liquid LQ, it is possible to estimate the size of each bubble.

[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 placed on the surface of a silicon substrate, and output signals upon collision were detected and analyzed. At the same time, the water droplets were photographed using a high-speed camera (model FASTCAM SA-Z manufactured by Photron, photographing speed 50,000 frames/sec).

FIG. 9 shows (a) a waveform diagram of the output signal from the signal processing unit and (b) a photograph of the droplet when the droplet collides in Example 1. In (a), the horizontal axis represents time, and the vertical axis represents the output converted to the rate of change ΔR/R of the electrical resistance value R between both ends of the piezoresistive layer. (b) is a photograph taken from the side of the droplet at 2 msec, 7 msec, 8 msec, and 14 msec after the start of dropping.

In Example 1, a water droplet with a diameter of 2.2 mm is dropped onto the surface of a silicon substrate, and the speed at the time of collision is set to 0.64 m/s. Referring to FIGS. 9(a) and 9(b), 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. The output signal becomes 0 at (14 msec). During the period in between, no periodic fluctuations appear. Referring to FIG. 9(b), it can be seen that no bubbles appear in any of the four droplet images.

FIG. 10 shows (a) a waveform diagram of the output signal of the MEMS acoustic sensor and (b) a photograph of the droplet when the droplet collides in Example 2. Example 2 is a case in which a water droplet with a diameter of 2.2 mm is dropped onto the surface of a silicon substrate, and the speed at the time of collision is set to 0.50 m/s. Referring to FIGS. 10(a) and (b), 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. The output signal becomes 0 at (14 msec). It can be seen that periodic fluctuations appear in the period between 7.2 msec and 9.7 msec. As shown in FIG. 9(b), it can be seen that bubbles appear in the droplet in the image taken at 8 msec.

FIG. 11 shows (a) a partial enlarged waveform diagram of the output signal from the signal processing unit and (b) a frequency spectrum subjected to FFT processing by the bubble detection unit in the second embodiment.

Referring to FIG. 11(a), since the output signal from the signal processing section of the second embodiment clearly includes periodic fluctuations, the bubble detection section 15 indicates the presence of bubbles. Referring to FIG. 11(b), it can be seen that the frequency spectrum acquired by the bubble detection unit 15 through FFT processing has an energy spectrum peak at 12 kHz.

FIG. 12 is a diagram showing the relationship between bubble radius and peak frequency. Referring to FIG _{. 12, the bubble size estimating unit 16 calculates a regression equation (f B ( kHz} ) = 5×10 ⁶ r _B (μm) ^-1.02 ), the size of the bubble is estimated from the frequency of the peak of the energy spectrum acquired by the bubble detection unit 15. According to FIG. 11(b), since the peak frequency is 12 kHz, the bubble size can be estimated to be 370 μm. Note that this regression equation was determined by the least squares method.

Although the preferred embodiments of the present invention have been described in detail above, the present invention is not limited to such specific embodiments, and various modifications and changes can be made within the scope of the present invention as set forth in the claims. It is possible. A piezoelectric layer may be used instead of the piezoresistive layers 24c and 24d of the MEMS acoustic sensor 12. When using a piezoelectric layer, the Wheatstone bridge circuit 35 of the signal processing section 13 shown in FIG. 5 is omitted.

In addition, regarding the above description, the following additional notes will be disclosed as further embodiments.
(Additional Note 1) A device for detecting air bubbles contained in a liquid, comprising:
a microelectromechanical system (MEMS) acoustic sensor that is provided so as to be able to come into contact with the liquid and detect 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;
The above-mentioned device, wherein the signal analysis section includes a detection section that obtains frequency characteristics of the output signal and detects periodic fluctuations.
(Additional Note 2) The device according to Additional Note 1, wherein the detection unit determines that the liquid contains bubbles when detecting the periodic fluctuation.
(Additional Note 3) The detection unit detects periodic fluctuations in the output signal by acquiring the frequency of the energy peak of the frequency characteristic of the output signal,
The signal analysis section refers to the relationship between the frequency of the energy peak of the waveform portion of the periodic fluctuation of the output signal obtained in advance and the size of the bubble, and calculates the frequency of the peak obtained by the detection section. The device according to supplementary note 1 or 2, further comprising an estimating section that estimates the size of bubbles in the liquid.
(Additional Note 4) When the detection unit acquires the frequencies of multiple peaks of energy in the frequency characteristic of the output signal, the estimation unit estimates the bubble size according to each of the frequencies of the multiple peaks. Possible device as described in Appendix 3.
(Additional Note 5) Further comprising a droplet generation unit that generates droplets by dropping or spraying the liquid onto the surface of the object,
The device according to any one of appendices 1 to 4, wherein the MEMS acoustic sensor detects a sound wave generated when the droplet collides with a surface of the object on which the MEMS acoustic sensor is provided.
(Additional Note 6) The apparatus according to Additional Note 5, wherein the detection unit detects the periodic fluctuation in the output signal after the first peak when the droplet collides with the surface of the object.
(Supplementary note 7) The apparatus according to supplementary note 5 or 6, wherein the surface of the object is a printing surface of inkjet printing.
(Additional Note 8) Further comprising a pressure applying section that applies pressure to the liquid,
5. The device according to any one of appendices 1 to 4, wherein the pressure applying unit applies pressure to the liquid, so that the MEMS acoustic sensor detects sound waves caused by vibrations of bubbles contained in the liquid.
(Additional Note 9) Further comprising a syringe containing the liquid,
The device according to appendix 8, wherein the MEMS acoustic sensor is arranged on an inner wall surface of the syringe.
(Additional Note 10) The MEMS acoustic sensor has an elastic element that covers at least a portion of the opening that comes into contact with the liquid or droplet, and the elastic element curves in response to sound waves generated by the bubbles, and in response to the curvature. 10. The device according to any one of appendices 1 to 9, wherein a strain detection layer is formed to detect strain caused by the strain.
(Supplementary note 11) The device according to supplementary note 10, wherein the elastic element is formed in the shape of a cantilever beam, a double-sided beam shape, or a diaphragm shape.
(Additional Note 12) The device according to Additional Note 10 or 11, wherein the strain detection layer is a piezoresistive layer or a piezoelectric layer.
(Additional Note 13) A method for detecting air bubbles contained in a liquid, the method comprising:
Detecting sound waves propagating in the liquid with a microelectromechanical system (MEMS) acoustic sensor provided so as to be able to come into 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 determining the frequency characteristics of the output signal and detecting periodic fluctuations; Method.
(Supplementary note 14) The method according to supplementary note 13, wherein in the analyzing step, if the periodic fluctuation is detected, it is determined that the liquid contains bubbles.
(Additional Note 15) In the step of analyzing, detecting periodic fluctuations in the output signal by acquiring the frequency of the energy peak of the frequency characteristic of the output signal,
Estimate the size of the bubble in the liquid from the frequency of the peak obtained by referring to the relationship between the frequency of the energy peak of the waveform portion of the periodic fluctuation of the output signal obtained in advance and the size of the bubble. 15. The method according to appendix 13 or 14, further comprising the step of:
(Additional Note 16) If the frequencies of multiple peaks of the energy of the frequency characteristic of the output signal are obtained in the above analyzing step, the bubble size is determined in accordance with the frequency of each of the multiple peaks in the above estimating step. The method according to appendix 15 for estimating .
(Additional Note 17) Before the detecting step, further comprising a step of dropping or spraying the liquid onto the surface of the object to generate droplets,
The method according to any one of appendices 13 to 16, wherein the MEMS acoustic sensor detects a sound wave generated when the droplet collides with a surface of the object on which the MEMS acoustic sensor is provided.
(Additional Note 18) Before the detecting step, the step further includes applying pressure to the liquid using a pressure applying section,
17. The method according to any one of appendices 13 to 16, wherein the MEMS acoustic sensor detects sound waves caused by vibrations of bubbles contained in the liquid by applying pressure to the liquid.
(Additional note 19) On the computer,
A step of analyzing an output signal from the MEMS acoustic sensor generated in response to a sound wave propagating through the liquid detected by a microelectromechanical system (MEMS) acoustic sensor provided so as to be able to come into contact with the liquid, the output signal A program that executes the above steps to find the frequency characteristics of and detect periodic fluctuations.
(Supplementary note 20) The program according to supplementary note 19, wherein in the analyzing step, if the periodic fluctuation is detected, it is determined that the liquid contains bubbles.
(Additional Note 21) In the step of analyzing, detecting periodic fluctuations in the output signal by acquiring the frequency of the energy peak of the frequency characteristic of the output signal,
Estimate the size of the bubble in the liquid from the frequency of the peak obtained by referring to the relationship between the frequency of the energy peak of the waveform portion of the periodic fluctuation of the output signal obtained in advance and the size of the bubble. The program according to appendix 19 or 20, further comprising the step of:
(Additional Note 22) If the frequencies of multiple peaks of the energy of the frequency characteristic of the output signal are obtained in the above analyzing step, the bubble size is determined in accordance with each of the frequencies of the multiple peaks in the above estimating step. The program according to appendix 21, which estimates .

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

Claims (16)

A device for detecting air bubbles contained in a liquid or droplets, the device comprising:
A microelectromechanical system (MEMS) acoustic sensor that is provided in contact with the liquid or droplet and detects sound waves in the liquid or droplet, the sensor comprising: at least a portion of the opening that contacts the liquid or droplet; The MEMS acoustic sensor has an elastic element covering the MEMS acoustic sensor, the elastic element is curved in response to the sound waves generated by the bubble, and a strain detection layer is formed to detect strain in accordance with the curvature.
a signal analysis unit that analyzes an output signal from the MEMS acoustic sensor generated in response to the detected sound wave;
The signal analysis unit includes a detection unit that determines the frequency characteristics of the output signal and detects periodic fluctuations,
In the device, the detection unit determines that the liquid or droplets contain bubbles when detecting the periodic fluctuation. A device for detecting air bubbles contained in a liquid or droplets, the device comprising:
A microelectromechanical system (MEMS) acoustic sensor that is provided in contact with the liquid or droplet and detects sound waves in the liquid or droplet, the sensor comprising: at least a portion of the opening that contacts the liquid or droplet; The MEMS acoustic sensor has an elastic element covering the MEMS acoustic sensor, the elastic element is curved in response to the sound waves generated by the bubble, and a strain detection layer is formed to detect strain in accordance with the curvature.
a signal analysis unit that analyzes an output signal from the MEMS acoustic sensor generated in response to the detected sound wave;
The signal analysis unit includes a detection unit that determines the frequency characteristics of the output signal and detects periodic fluctuations,
The detection unit detects periodic fluctuations in the output signal by acquiring a frequency of an energy peak of a frequency characteristic of the output signal,
The signal analysis section refers to the relationship between the frequency of the energy peak of the waveform portion of the periodic fluctuation of the output signal obtained in advance and the size of the bubble, and calculates the frequency of the peak obtained by the detection section. The device further comprises an estimator that estimates the size of the bubble. A device for detecting air bubbles contained in a liquid or droplets, the device comprising:
A microelectromechanical system (MEMS) acoustic sensor that is provided in contact with the liquid or droplet and detects sound waves in the liquid or droplet, the sensor comprising: at least a portion of the opening that contacts the liquid or droplet; The MEMS acoustic sensor has an elastic element covering the MEMS acoustic sensor, the elastic element is curved in response to the sound waves generated by the bubble, and a strain detection layer is formed to detect strain in accordance with the curvature.
a signal analysis unit that analyzes an output signal from the MEMS acoustic sensor generated in response to the detected sound wave;
a droplet generation unit that generates droplets by dropping or jetting the liquid onto the surface of a target object,
The signal analysis unit includes a detection unit that determines the frequency characteristics of the output signal and detects periodic fluctuations, and the MEMS acoustic sensor detects the droplet on the surface of the object on which the MEMS acoustic sensor is provided The device detects sound waves generated when two collide. 4. The apparatus according to claim 3, wherein the detection unit detects the periodic fluctuation in the output signal after an initial peak when the droplet impinges on the surface of the object. A device for detecting air bubbles contained in a liquid or droplets, the device comprising:
A microelectromechanical system (MEMS) acoustic sensor that is provided in contact with the liquid or droplet and detects sound waves in the liquid or droplet, the sensor comprising: at least a portion of the opening that contacts the liquid or droplet; The MEMS acoustic sensor has an elastic element covering the MEMS acoustic sensor, the elastic element is curved in response to the sound waves generated by the bubble, and a strain detection layer is formed to detect strain in accordance with the curvature.
a signal analysis unit that analyzes an output signal from the MEMS acoustic sensor generated in response to the detected sound wave;
a pressure application unit that applies pressure to the liquid;
Equipped with
The signal analysis unit includes a detection unit that determines the frequency characteristics of the output signal and detects periodic fluctuations,
The device, wherein the pressure application unit applies pressure to the liquid, so that the MEMS acoustic sensor detects sound waves caused by vibrations of bubbles contained in the liquid. further comprising a syringe containing the liquid,
6. The device according to claim 5, wherein the MEMS acoustic sensor is arranged on an inner wall surface of the syringe. The apparatus according to any one of claims 2 and 3 to 6, wherein the detection unit determines that the liquid or droplets contain bubbles when detecting the periodic fluctuation. The detection unit detects periodic fluctuations in the output signal by acquiring a frequency of an energy peak of a frequency characteristic of the output signal,
The signal analysis section refers to the relationship between the frequency of the energy peak of the waveform portion of the periodic fluctuation of the output signal obtained in advance and the size of the bubble, and calculates the frequency of the peak obtained by the detection section. The device according to any one of claims 1 and 3 to 6, further comprising an estimator for estimating the size of the bubble. A method for detecting air bubbles contained in a liquid or droplet, the method comprising:
A microelectromechanical system (MEMS) acoustic sensor provided to be able to contact the liquid or droplet, the elastic element comprising an elastic element covering at least a portion of an opening that contacts the liquid or droplet, the elastic element comprising: Detecting sound waves propagating in the liquid using the MEMS acoustic sensor, which is formed with a strain detection layer that curves in response to sound waves caused by the bubbles and detects distortion in accordance with the curvature;
Analyzing an output signal from the MEMS acoustic sensor generated in response to the detected sound wave, the step of determining the frequency characteristics of the output signal to detect periodic fluctuations, and detecting the periodic fluctuations. If so, determining that the liquid or droplet contains bubbles. A method for detecting air bubbles contained in a liquid or droplet, the method comprising:
A microelectromechanical system (MEMS) acoustic sensor provided to be able to contact the liquid or droplet, the elastic element comprising an elastic element covering at least a portion of an opening that contacts the liquid or droplet, the elastic element comprising: Detecting sound waves propagating in the liquid using the MEMS acoustic sensor, which is formed with a strain detection layer that curves in response to sound waves caused by the bubbles and detects distortion in accordance with the curvature;
a step of analyzing an output signal from the MEMS acoustic sensor generated in response to the detected sound wave, the step comprising: determining a frequency characteristic of the output signal and detecting periodic fluctuations;
In the step of analyzing, detecting periodic fluctuations in the output signal by obtaining a frequency of an energy peak of a frequency characteristic of the output signal,
The size of the bubble in the liquid or droplet is determined from the frequency of the peak obtained by referring to the relationship between the frequency of the energy peak of the waveform portion of the periodic fluctuation of the output signal obtained in advance and the size of the bubble. The method further comprises the step of estimating the A method for detecting air bubbles contained in a liquid or droplet, the method comprising:
Dropping or spraying the liquid onto the surface of an object to generate droplets;
A microelectromechanical system (MEMS) acoustic sensor provided to be able to contact the liquid or droplet, the elastic element comprising an elastic element covering at least a portion of an opening that contacts the liquid or droplet, the elastic element comprising: Detecting sound waves propagating in the liquid using the MEMS acoustic sensor, which is formed with a strain detection layer that curves in response to sound waves caused by the bubbles and detects distortion in accordance with the curvature;
a step of analyzing an output signal from the MEMS acoustic sensor generated in response to the detected sound wave, the step comprising: determining a frequency characteristic of the output signal and detecting periodic fluctuations;
In the method, the MEMS acoustic sensor detects sound waves generated when the droplet collides with the surface of the object on which the MEMS acoustic sensor is provided. A method for detecting air bubbles contained in a liquid or droplet, the method comprising:
applying pressure to the liquid by a pressure application unit;
A microelectromechanical system (MEMS) acoustic sensor provided to be able to contact the liquid or droplet, the elastic element comprising an elastic element covering at least a portion of an opening that contacts the liquid or droplet, the elastic element comprising: Detecting sound waves propagating in the liquid using the MEMS acoustic sensor, which is formed with a strain detection layer that curves in response to sound waves caused by the bubbles and detects distortion in accordance with the curvature;
a step of analyzing an output signal from the MEMS acoustic sensor generated in response to the detected sound wave, the step comprising: determining a frequency characteristic of the output signal and detecting periodic fluctuations;
The method, wherein the MEMS acoustic sensor detects sound waves caused by vibrations of bubbles contained in the liquid by applying pressure to the liquid. to the computer,
A microelectromechanical system (MEMS) acoustic sensor configured to be able to contact a liquid or droplet, the elastic element having an elastic element covering at least a portion of an opening that contacts the liquid or droplet, the elastic element being able to contact the liquid or droplet. Alternatively, a sound wave propagating through the liquid or droplet, detected by the MEMS acoustic sensor, is formed with a distortion detection layer that curves in response to sound waves caused by air bubbles contained in the droplet and detects distortion in accordance with the curvature. A step of analyzing an output signal from the MEMS acoustic sensor generated according to A program that executes the step of determining that the liquid or droplets contain bubbles. to the computer,
A microelectromechanical system (MEMS) acoustic sensor configured to be able to contact a liquid or droplet, the elastic element having an elastic element covering at least a portion of an opening that contacts the liquid or droplet, the elastic element being able to contact the liquid or droplet. Alternatively, a sound wave propagating through the liquid or droplet, detected by the MEMS acoustic sensor, is formed with a distortion detection layer that curves in response to sound waves caused by air bubbles contained in the droplet and detects distortion in accordance with the curvature. analyzing an output signal from the MEMS acoustic sensor generated according to the output signal, determining the frequency characteristics of the output signal, and detecting periodic fluctuations, the step of detecting periodic fluctuations of the frequency characteristics of the output signal, detecting periodic fluctuations in the output signal by acquiring the frequency;
The size of the bubble in the liquid or droplet is determined from the frequency of the peak obtained by referring to the relationship between the frequency of the energy peak of the waveform portion of the periodic fluctuation of the output signal obtained in advance and the size of the bubble. Steps to estimate and a program to execute. to the computer,
A microelectromechanical system (MEMS) acoustic sensor configured to be able to contact a liquid or droplet, the elastic element having an elastic element covering at least a portion of an opening that contacts the liquid or droplet, the elastic element being able to contact the liquid or droplet. Alternatively, a droplet is formed by forming a distortion detection layer that curves in response to sound waves generated by air bubbles contained in the droplet and detects distortion according to the curvature, and the droplet is generated by dropping or jetting the liquid onto the surface of an object. analyzing an output signal from the MEMS acoustic sensor generated in response to a sound wave propagating through the MEMS acoustic sensor, determining frequency characteristics of the output signal, and detecting periodic fluctuations; A program for executing the step of detecting a sound wave generated when the droplet collides with a surface of the object provided with a MEMS acoustic sensor. to the computer
A microelectromechanical system (MEMS) acoustic sensor configured to be able to contact a liquid or a droplet, the elastic element having an elastic element covering at least a portion of an opening in contact with the liquid or droplet, the elastic element being able to contact a gas bubble. A strain detection layer is formed that curves in response to sound waves generated by the liquid and detects distortion corresponding to the curvature, and is generated in response to sound waves caused by vibrations of bubbles contained in the liquid to which pressure is applied by the pressure application unit. A program for executing a step of analyzing an output signal from the MEMS acoustic sensor, the step of determining frequency characteristics of the output signal and detecting periodic fluctuations.

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