Acoustic transducers, methods of designing acoustic transducers, and methods of forming acoustic transducers

Patent metadata

Field	Value
Publication number	US-12101594-B2
Application number	US-202117196780-A
Country	US
Kind code	B2
Filing date	Mar 9, 2021
Priority date	Mar 9, 2021
Publication date	Sep 24, 2024
Grant date	Sep 24, 2024

Abstract

A method of designing and forming at least one element of an acoustic transducer. The method includes receiving one or more required operating parameters of the at least one element of the acoustic transducer for an application, iteratively modeling and simulating performance of one or more materials to utilize within the at least one element of the acoustic transducer, iteratively modeling and simulating performance of one or more structures to utilize within the at least one element of the acoustic transducer, identifying at least one material and at least one structure that exhibit predicted performance that at least achieves the one or more required operating parameters of the at least one element of the acoustic transducer for the application, outputting a design of the at least one element of the acoustic transducer, and forming the at least one element of the acoustic transducer via one or more additive manufacturing processes.

First claim

What is claimed is:

1. A method of designing at least one element of an acoustic transducer, the method comprising:
receiving two or more required operating parameters of the at least one element of the acoustic transducer for an application, the at least one element chosen from an impedance matching layer, a ceramic crystal, and a backing material, and the two or more required operating parameters chosen from two or more of excitation levels, attenuation of back reflection, phase linearity, sensitivity, pulse-length, and pulse width;
iteratively modeling and simulating performance of one or more materials relative to the two or more required operating parameters to utilize within the at least one element of the acoustic transducer;
iteratively modeling and simulating performance of one or more structures relative to the two or more required operating parameters to utilize within the at least one element of the acoustic transducer; and
identifying at least one material and at least one structure that exhibit predicted performance that at least substantially achieves the two or more required operating parameters of the at least one element of the acoustic transducer for the application, the at least one material comprises one or more of a high temperature resin, polyetherimide, a nickel-chromium alloy, a stainless steel, nickel, silicon bronze, MONEL, or any alloys of foregoing materials.

2. The method of claim 1 , further comprising outputting a design of the at least one element of the acoustic transducer based at least partially on the identified at least one material and the identified at least one structure.

3. The method of claim 2 , further comprising forming the at least one element of the acoustic transducer via one or more additive manufacturing processes.

4. The method of claim 3 , wherein the one or more additive manufacturing processes comprises one or more of binder jetting, stereolithography (SLA), sol-gel or liquid dispense methods, inkjet 3D printing, direct metal deposition, micro-plasma powder deposition, direct laser sintering, selective laser sintering, electron beam melting, or electron beam freeform fabrication.

5. The method of claim 1 , wherein identifying the at least one material comprises identifying each of a lead zirconium titanate and a polymer binder.

6. The method of claim 1 , wherein iteratively modeling and simulating performance of the one or more materials and structures comprises utilizing one or more machine learning techniques to iteratively model and simulate the performance of the one or more materials and the one or more structures.

7. The method of claim 6 , wherein the one or more machine learning techniques comprise one or more of quadratic regression analysis, logistic regression analysis, support vector machines, Gaussian process regression, ensemble models, decision tree learning, regression trees, boosted trees, gradient boosted trees, multilayer perceptron, one-vs-rest, Naïve Bayes, k-nearest neighbor, association rule learning, neural networks, deep learning, or pattern recognition.

8. The method of claim 1 , wherein receiving the two or more required operating parameters comprises receiving requirements regarding a footprint requirement for the acoustic transducer.

9. The method of claim 1 , wherein the at least one element comprises at least a backing layer of the acoustic transducer.

10. The method of claim 1 , wherein the at least one element comprises at least a matching layer of the acoustic transducer.

11. The method of claim 1 , wherein the at least one element comprises at least a piezoelectric ceramic crystal of the acoustic transducer.

12. A method of forming a plurality of elements of an acoustic transducer, the method comprising:
receiving a three-dimensional model design of the plurality of elements of the acoustic transducer;
forming the plurality of elements of the acoustic transducer via one or more additive manufacturing processes; and
forming at least one element of the plurality of elements of the acoustic transducer with one or more of a high temperature resin, a nickel-chromium alloy, a stainless steel, nickel, silicon bronze, MONEL, or any alloys of foregoing materials.

13. The method of claim 12 , wherein the one or more additive manufacturing processes comprise one or more of binder jetting, stereolithography (SLA), sol-gel or liquid dispense methods, inkjet 3D printing, direct metal deposition, micro-plasma powder deposition, direct laser sintering, selective laser sintering, electron beam melting, or electron beam freeform fabrication.

14. The method of claim 12 , wherein forming the plurality of elements of the acoustic transducer via the one or more additive manufacturing processes comprises forming each of a piezoelectric ceramic crystal, a matching layer, and a backing layer via the one or more additive manufacturing processes.

15. The method of claim 12 , wherein forming the plurality of elements of the acoustic transducer via the one or more additive manufacturing processes comprises forming only one of a piezoelectric ceramic crystal, a matching layer, and a backing layer via the one or more additive manufacturing processes.

16. The method of claim 12 , wherein forming the plurality of elements of the acoustic transducer via the one or more additive manufacturing processes comprises:
forming a first element of the acoustic transducer via a first additive manufacturing process;
forming a second element of the acoustic transducer via a second additive manufacturing process; and
assembling the first and second elements of the acoustic transducer.

17. The method of claim 12 , wherein forming the plurality of elements of the acoustic transducer via the one or more additive manufacturing processes comprises forming at least one element of the plurality of elements with a nickel chromium alloy.

18. The method of claim 12 , wherein forming the plurality of elements of the acoustic transducer via the one or more additive manufacturing processes comprises forming at least one element of the plurality of elements with each of a lead zirconium titanate and a polymer binder.

19. A method of forming an acoustic transducer, the method comprising:
receiving two or more required operating parameters of each of a piezoelectric ceramic crystal, a matching layer, and a backing layer of the acoustic transducer for an application, the one or more required operating parameters chosen from excitation levels, attenuation of back reflection, phase linearity, sensitivity, pulse-length, and pulse width;
iteratively modeling and simulating performance of one or more materials relative to the two or more required operating parameters to utilize within the piezoelectric ceramic crystal, the matching layer, and the backing layer of the acoustic transducer;
iteratively modeling and simulating performance of one or more structures relative to the two or more required operating parameters to utilize within the piezoelectric ceramic crystal, the matching layer, and the backing layer of the acoustic transducer;
identifying at least one material and at least one structure that exhibit predicted performance that at least substantially achieves the two or more required operating parameters of each of the piezoelectric ceramic crystal, the matching layer, and the backing layer of the acoustic transducer for the application, the at least one material comprises one or more of a high temperature resin, polyetherimide, a nickel-chromium alloy, a stainless steel, nickel, silicon bronze, MONEL, or a

Assignees

• Baker Hughes Oilfield Operations Llc

Inventors

• Avagliano Aaron
• Sakthivel Navin
• Yates Chad
• Wieneke Brian Steven
• Steinsiek Roger
• Ganesan Baskaran
• Wise Peter Leonard
• Hoemske Benjamin
• Austerman Sarah Elizabeth

Classifications

• B22F10/25

  Direct deposition of metal particles, e.g. direct metal deposition [DMD] or laser engineered net shaping [LENS] · CPC title

• H04R1/02

  Casings; Cabinets {; Supports therefor;} Mountings therein (H04R1/28 takes precedence {; attachments for microphones H04R1/08; mounting of transducers in earpieces H04R1/1075}) · CPC title

• B22F10/85

  for controlling or regulating additive manufacturing processes · CPC title

• H04R9/06

  Loudspeakers · CPC title

• B22F10/28

  Powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM] · CPC title