# US 12,180,430 B2 · Control device and control method

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- Number: US 12,180,430 B2
- Document ID: US12180430B2
- Status: Granted
- Kind: B2
- Application number: 17/251,437
- Filed: 2019-06-24
- Published: 2021-08-26
- Granted: 2024-12-31
- Earliest claimed: 2018-07-25
- Assignees: Sekisui Chemical Co., Ltd.
- Applicants: Sekisui Chemical Co., Ltd.
- Inventors: Kanetomo Sato; Kazuto Natsuyama; Kokoro Hamachi
- Web page: https://patentgrep.com/patent/US12180430B2

## CPC

- C10J 3/723: {Controlling or regulating the gasification process}
- F23G 5/50: Control or safety arrangements
- G05B 15/02: electric
- G06F 18/217: {Validation; Performance evaluation; Active pattern learning techniques}
- G06N 3/006: based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
- G06N 3/0464: Convolutional networks [CNN, ConvNet]
- G06N 3/08: Learning methods
- G06N 3/088: Non-supervised learning, e.g. competitive learning
- G06N 3/092: Reinforcement learning
- C10J 2300/1665: to alcohols, e.g. methanol or ethanol
- G06N 3/045: Combinations of networks
- G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks
- G06N 20/00: Machine learning
- Y02E 50/30: Fuel from waste, e.g. synthetic alcohol or diesel
- C10J: PRODUCTION OF PRODUCER GAS, WATER-GAS, SYNTHESIS GAS FROM SOLID CARBONACEOUS MATERIAL, OR MIXTURES CONTAINING THESE GASES (synthesis gas from liquid or gaseous hydrocarbons C01B; underground gasification of minerals E21B43/295); CARBURETTING AIR OR OTHER GASES
- F23G: CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
- G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- Y02E: REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION

## Abstract

The object is to provide a control device, an operation control device, a server, a management server, a recording medium, a neural network system model, a control method and an operation control method that enable reuse of combustible waste as industrial raw materials with high efficiency. A control device comprises a gas information acquisition unit that acquires gas information on gas converted by a gasifying furnace for converting collected waste to gas; a control information acquisition unit that acquires control information controlling the gas purification device for purifying gas converted by the gasifying furnace; a feature information acquisition unit that acquires feature information including information on purified gas purified by the gas purification device; and a creation unit that creates a learning model by machine learning based on the gas information, the control information and the feature information.

## Claims

### Claim 1

A control device controlling a gas purification device, comprising:
a gas information acquisition unit that acquires gas information on gas converted by a gasifying furnace for converting collected waste to gas;
a control information acquisition unit that acquires control information controlling the gas purification device for purifying gas converted by the gasifying furnace;
a feature information acquisition unit that acquires feature information including information on purified gas purified by the gas purification device;
a creation unit that creates a learning model by machine learning based on the gas information, the control information and the feature information;
a use history acquisition unit that acquires a use history of an adsorber provided in the gas purification device;
a transmission unit that transmits a use history acquired by the use history acquisition unit to a management server; and
a degradation level acquisition unit that acquires a degradation level of an adsorber provided in the gas purification device, wherein
the transmission unit transmits a degradation level acquired by the degradation level acquisition unit to the management server.

### Claim 2

A control device controlling a gas purification device, comprising:
a gas information acquisition unit that acquires gas information on gas converted by a gasifying furnace for converting collected waste to gas;
a control information acquisition unit that acquires control information controlling the gas purification device for purifying gas converted by the gasifying furnace;
a feature information acquisition unit that acquires feature information including information on purified gas purified by the gas purification device;
a creation unit that creates a learning model by machine learning based on the gas information, the control information and the feature information;
a use history acquisition unit that acquires a use history of an adsorber provided in the gas purification device;
a transmission unit that transmits a use history acquired by the use history acquisition unit to a management server; and
an installation and removal operation acquisition unit that acquires a presence or absence of installation and removal operation of an adsorber provided in the gas purification device, wherein
the transmission unit transmits, if presence of installation and removal operation is acquired by the installation and removal operation acquisition unit, the presence of the installation and removal operation to the management server.

### Claim 3

A control device controlling a gas purification device, comprising:
a gas information acquisition unit that acquires gas information on gas converted by a gasifying furnace for converting collected waste to gas;
a control information acquisition unit that acquires control information controlling the gas purification device for purifying gas converted by the gasifying furnace;
a feature information acquisition unit that acquires feature information including information on purified gas purified by the gas purification device;
a creation unit that creates a learning model by machine learning based on the gas information, the control information and the feature information; and
a determination unit that determines, based on a state of microorganisms for generating ethanol from carbon monoxide gas and hydrogen gas purified by the gas purification device, an activity degree of the microorganisms.