CN115009204A - Hydrogenation noise reduction implementation method and device - Google Patents
Hydrogenation noise reduction implementation method and device Download PDFInfo
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- CN115009204A CN115009204A CN202210426289.8A CN202210426289A CN115009204A CN 115009204 A CN115009204 A CN 115009204A CN 202210426289 A CN202210426289 A CN 202210426289A CN 115009204 A CN115009204 A CN 115009204A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
- B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
- B60R16/037—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for occupant comfort, e.g. for automatic adjustment of appliances according to personal settings, e.g. seats, mirrors, steering wheel
- B60R16/0373—Voice control
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/30—Hydrogen technology
- Y02E60/32—Hydrogen storage
Abstract
The invention relates to a hydrogen energy automobile technology, and provides a method, a device and equipment for realizing hydrogenation noise reduction, which respond to a vehicle flameout command and acquire the current positioning information of a vehicle through a vehicle machine; if the current positioning information is the same as the positioning information of the hydrogenation station, generating a noise reduction starting instruction; sending the noise reduction starting instruction to a double-microphone module in the hydrogen energy automobile; and if the sound signal acquired by the double-microphone module is determined to be a noise signal, generating a silencer starting instruction, and sending the silencer starting instruction to the vehicle-mounted silencer to start the vehicle-mounted silencer to absorb noise in the hydrogenation process. When it is determined that the hydrogen energy automobile reaches the hydrogenation station based on the current positioning information, the sound signal acquired by the double-microphone module can be determined to be a noise signal, and a silencer starting instruction is timely triggered to start the vehicle-mounted silencer to absorb noise in the hydrogenation process, so that the environmental noise of the hydrogenation station is effectively reduced.
Description
Technical Field
The invention relates to the technical field of hydrogen energy vehicles, in particular to a method, a device and equipment for realizing hydrogenation and noise reduction.
Background
Currently, hydrogen powered vehicles are used in many cities. The hydrogen energy vehicle, like the conventional gasoline vehicle, diesel vehicle or electric vehicle, needs sufficient energy support to ensure a long distance. When the residual energy of the hydrogen energy source automobile is insufficient, the hydrogen energy source automobile is generally hydrogenated by the hydrogen station, so that the hydrogen energy source supplement is realized. However, the general hydrogenation station is located outdoors and in a noisy environment, which causes drivers and workers of the hydrogenation station to be in a noisy environment with mixed environmental sound and equipment operation sound of the hydrogenation equipment during the hydrogenation process of the hydrogenation station, and thus unavoidable noise pollution is generated.
Disclosure of Invention
The embodiment of the invention provides a method, a device and equipment for realizing hydrogenation noise reduction, and aims to solve the problem that ambient environmental sound and equipment operation sound of hydrogenation equipment cannot be effectively reduced to form much noise in the hydrogenation process of a hydrogen energy source automobile at a hydrogen energy source hydrogenation station in the prior art.
In a first aspect, an embodiment of the present invention provides a method for implementing noise reduction through hydrogenation, which is applied to a hydrogen energy vehicle, and includes:
responding to a vehicle flameout instruction, and acquiring current positioning information of the vehicle through a vehicle machine; the current positioning information corresponds to an initial confidence value;
if the current positioning information is the same as the positioning information of the hydrogenation station, generating a noise reduction starting instruction;
sending the noise reduction starting instruction to a double-microphone module in the hydrogen energy source automobile; and
and if the sound signal acquired by the double-microphone module is determined to be a noise signal, generating a silencer starting instruction, and sending the silencer starting instruction to the vehicle-mounted silencer to start the vehicle-mounted silencer to absorb noise in the hydrogenation process.
In a second aspect, an embodiment of the present invention provides a hydrogenation noise reduction implementation apparatus, which includes:
the positioning information acquisition unit is used for responding to a vehicle flameout instruction and acquiring the current positioning information of the vehicle through the vehicle machine; wherein, the current positioning information corresponds to an initial confidence value;
the first instruction generating unit is used for generating a noise reduction starting instruction if the current positioning information is determined to be the same as the positioning information of the hydrogenation station;
the first instruction sending unit is used for sending the noise reduction starting instruction to a double-microphone module in the hydrogen energy source automobile; and
and the noise reduction starting control unit is used for generating a silencer starting instruction if the sound signal acquired by the double-microphone module is determined to be a noise signal, and sending the silencer starting instruction to the vehicle-mounted silencer to start the vehicle-mounted silencer to absorb noise in the hydrogenation process.
In a third aspect, an embodiment of the present invention further provides a device, which is a hydrogen energy vehicle capable of implementing the method for implementing denoising by hydrogenation according to the first aspect.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and the computer program, when executed by a processor, causes the processor to execute the method for implementing denoising in the first aspect.
The embodiment of the invention provides a method, a device and equipment for realizing hydrogenation noise reduction, which are characterized in that current positioning information of a vehicle is acquired through a vehicle machine in response to a vehicle flameout command; wherein, the current positioning information corresponds to an initial confidence value; if the current positioning information is the same as the positioning information of the hydrogenation station, generating a noise reduction starting instruction; sending the noise reduction starting instruction to a double-microphone module in the hydrogen energy source automobile; and if the sound signal acquired by the double-microphone module is determined to be a noise signal, generating a silencer starting instruction, and sending the silencer starting instruction to the vehicle-mounted silencer to start the vehicle-mounted silencer to absorb noise in the hydrogenation process. When it is determined that the hydrogen energy automobile reaches the hydrogenation station based on the current positioning information, the sound signal acquired by the double-microphone module can be determined to be a noise signal, and a silencer starting instruction is timely triggered to start the vehicle-mounted silencer to absorb noise in the hydrogenation process, so that the environmental noise of the hydrogenation station is effectively reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
FIG. 1 is a schematic view of an application scenario of a hydrogenation noise reduction implementation method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a hydrogenation noise reduction implementation method provided in an embodiment of the present invention;
FIG. 3 is a schematic block diagram of a hydrogenation noise reduction implementation apparatus provided in an embodiment of the present invention;
FIG. 4 is a schematic block diagram of a computer device provided by an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1 and fig. 2, fig. 1 is a schematic view of an application scenario of a hydrogenation and noise reduction implementation method according to an embodiment of the present invention; fig. 2 is a schematic flow diagram of a hydrogenation noise reduction implementation method provided in an embodiment of the present invention, where the hydrogenation noise reduction implementation method is applied to a hydrogen energy vehicle.
As shown in fig. 2, the method includes steps S101 to S104.
S101, responding to a vehicle flameout instruction, and acquiring current positioning information of the vehicle through a vehicle machine; and the current positioning information corresponds to an initial confidence value.
In this embodiment, a technical solution will be described with a hydrogen energy vehicle as an implementation subject. The hydrogen energy automobile is provided with structural components (such as an automobile body) required by a conventional automobile, a vehicle machine (such as a vehicle-mounted touch screen on a center console is a part of the vehicle machine), a double-microphone module arranged in the vehicle (the double-microphone module is connected with the vehicle machine), a vehicle-mounted silencer arranged in the vehicle and close to a hydrogen energy storage area (the vehicle-mounted silencer is connected with the vehicle machine, the vehicle-mounted silencer can also work under the condition that the automobile is flameout by a self-contained power supply, the vehicle-mounted silencer is an active silencer, sound waves with the same size and the opposite phase as the original sound pressure can be generated, the sound waves cancel the original sound field in a certain range), and a vehicle-mounted camera arranged on the vehicle (such as a camera arranged on a right rearview mirror of the vehicle can be regarded as a vehicle-mounted camera). Therefore, the vehicle-mounted silencer can not only reduce the noise of a hydrogen energy automobile adopting a hydrogen internal combustion engine in the running process of the automobile, but also effectively reduce the noise of the environment of a hydrogen station after reaching the hydrogen station.
In order to more accurately judge whether the driver drives the hydrogen energy vehicle to the hydrogen refueling station, the current positioning information can be acquired based on a positioning module (such as a GPS positioning module, a Beidou positioning module and the like) in the vehicle, and more specifically, the current longitude and latitude corresponding to the current positioning information can be acquired. Moreover, the current positioning information corresponds to an initial confidence value, for example, the initial confidence value is 0.5 to indicate that the positioning accuracy confidence of the current positioning information is 50%. Therefore, the specific position where the hydrogen energy automobile stays at present can be accurately judged based on the acquired current positioning information.
In an embodiment, after step S101, the method further includes:
acquiring a current external environment image through a vehicle-mounted camera;
if the human body exists in the current vehicle exterior environment image is judged through a pre-trained target detection network, acquiring a human body existence area of the current vehicle exterior environment image;
detecting and acquiring a work pattern identification area in the human body existence area through a pre-trained image recognition model, and acquiring a user name corresponding to the work pattern identification area;
if the user name corresponding to the work equipment graphic identification area is determined to be the same as the location type corresponding to the current positioning information, increasing the initial confidence value of the current positioning information by a preset first increase value to obtain a current confidence value;
and if the current confidence value exceeds a preset confidence threshold value, judging that the current positioning information is the same as the positioning information of the hydrogenation station.
In this embodiment, when the vehicle is in a flameout state and a flameout command of the vehicle is generated, the vehicle-mounted camera on the vehicle can acquire the current external environment image of the vehicle in the direction to which the vehicle is aligned, and whether a worker of the hydrogen station is close to the hydrogen energy vehicle to start the hydrogenation operation is judged through the current external environment image. When the vehicle-mounted camera collects the current external environment image, multi-frame images can be collected, then each frame image is judged according to the processing process, whether the current external environment image has a human body existing region or not is judged, if the human body existing region is determined to exist, the work installation graph identification region in the human body existing region is obtained, the user name corresponding to the work installation graph identification region is obtained, and whether the place at the moment is located in the hydrogen adding station or not is judged according to the company name corresponding to the LOGO graph installed publicly by the workers of the hydrogen adding station.
Once it is determined that the username corresponding to the working device graphic identifier region is the same as the location type (e.g., the location type is a hydrogen station) corresponding to the current positioning information or the similarity exceeds a preset similarity threshold, the initial confidence value of the current positioning information may be increased by a preset first increase value to obtain a current confidence value (e.g., the first increase value is set to 0.5), for example, referring to the above example, the initial confidence value is 0.5, and then the initial confidence value is increased by the first increase value of 0.5 to obtain a current confidence value of 1. If the confidence threshold is set to 0.8 in advance, the current confidence value can be judged to be larger than the confidence threshold at this moment, and the current positioning information is the same as the positioning information of the hydrogenation station, so that the fact that the user arrives at the hydrogenation station is further determined. Therefore, whether the hydrogen energy automobile reaches the hydrogen station or not is judged based on the positioning position, and target detection and image recognition can be carried out based on the current environment image outside the automobile collected by the vehicle-mounted camera, so that whether the hydrogen energy automobile reaches the hydrogen station or not is further judged.
In one embodiment, the target detection network is a single-lens multi-box detector model.
The Single-lens multi-box Detector model is an SSD model, which is called a Single Shot multi box Detector, and is a target detection model, and can effectively identify each target in a current picture to obtain an identification frame of each target, and each identification frame is a known classification result (such as a classification result of a human body, a hydrogenation device, and the like) and a classification probability value corresponding to the classification result. Through the single-lens multi-box detector model, whether a human body exists in the current vehicle exterior environment image can be detected quickly and accurately.
In an embodiment, before obtaining the human body existence region of the current vehicle exterior environment image, if it is determined that the human body exists in the current vehicle exterior environment image through a pre-trained target detection network, the method further includes:
inputting the current vehicle exterior environment image into the single-lens multi-box detector model for target detection to obtain a plurality of detection identification frames; each detection identification frame corresponds to one identification classification name;
and if the classification corresponding to the detection identification frame is determined to be a human body, judging that the human body exists in the current vehicle exterior environment image.
In this embodiment, for example, whether a human body exists in a frame of current vehicle exterior environment image is detected based on a single-lens multi-box detector model, normalization processing needs to be performed on the current vehicle exterior environment image to obtain a normalized picture, and then the normalized picture is input to the single-lens multi-box detector model to perform target detection to obtain a plurality of detection identification frames; the method comprises the steps of identifying a region where a person exists in a current vehicle exterior environment image based on a single-lens multi-box detector model, and giving an identification classification name and a probability value corresponding to the identification classification name aiming at the region where the person exists. Therefore, through the single-lens multi-box detector model, the detection of the plurality of detection identification frames in the current vehicle exterior environment image can be quickly and accurately carried out, so that whether a human body exists or not is further judged based on the identification classification names of the detection identification frames.
In one embodiment, the image recognition model is a Yolov3 model; the obtaining of the user name corresponding to the work clothing graphic identification area includes:
acquiring current image characteristics corresponding to the work clothing graphic identification area;
sending the current image features to a cloud server;
and acquiring an identification result corresponding to the current image feature sent by the cloud server, and taking the identification result as a user name.
In this embodiment, whether a work pattern identification area exists in the human body existence area may be detected based on the YOLOv3 detection model; and YOLOv3 is a v3 version of the YOLO, an object detection algorithm. Because the workers at the hydrogen adding station generally wear the work clothes, the user name (such as XXX hydrogen energy) of the operation company corresponding to the hydrogen adding station or the trademark image (generally comprising images and/or characters) of the operation company corresponding to the hydrogen adding station is arranged at the left chest or the back of the work clothes, at this time, the current vehicle exterior environment image can be acquired by the vehicle-mounted camera and sent to the vehicle machine, and the image identification model stored in the vehicle machine can detect and extract the work clothes image identification area in the current vehicle exterior environment image. Once the acquisition of the work load pattern identification area is detected, the work load pattern identification area is acquired by considering the situation of insufficient vehicle computing power, the current image characteristics corresponding to the work pattern-loading identification area (generally, current image characteristics corresponding to the work pattern-loading identification area can be obtained after the work pattern-loading identification area is processed on the basis of a convolutional layer, a pooling layer and a full connection layer of a convolutional neural network stored in the vehicle), which are obtained by the vehicle, are sent to the cloud server, the similarity is calculated between the image characteristics of a large number of company trademark images stored in the cloud server and the current image characteristics, the trademark image corresponding to the image characteristics having the maximum similarity with the current image characteristics is selected as the target trademark image, and acquiring a corresponding recognition result (generally, the recognition result is represented by a user company name) in a cloud server based on the target trademark image; the image characteristics of the trademark images stored in the cloud server and the identification results corresponding to the image characteristics are bound in a one-to-one correspondence mode. And finally, after the recognition result corresponding to the current image feature is obtained in the cloud server, the recognition result is sent to the vehicle machine by the cloud server. Therefore, the image classification can be effectively participated by means of the calculation force of the cloud server in this way, and the data processing pressure of the vehicle machine is effectively reduced.
And S102, if the current positioning information is determined to be the same as the positioning information of the hydrogenation station, generating a noise reduction starting instruction.
In this embodiment, generally, offline navigation data (such as offline GIS electronic map data) is stored in the in-vehicle device, the offline navigation data stores positioning information of a plurality of hydrogen stations, and once the current longitude and latitude corresponding to the current positioning information is the same as the longitude and latitude of one of the hydrogen station positioning information of the offline navigation data or the longitude and latitude difference value between the two does not exceed a preset difference threshold value, it indicates that the current positioning information is the same as the hydrogen station positioning information, and at this time, the in-vehicle device may generate a noise reduction start instruction to start the in-vehicle noise reduction function.
S103, sending the noise reduction starting instruction to a double-microphone module in the hydrogen energy automobile.
In this embodiment, since the car machine cannot participate in the collection of external environmental sounds, it is possible to determine whether the external sounds of the hydrogen filling station are noises more accurately, and at this time, the car machine may be configured to generate the noise reduction start command to be sent to the dual microphone module in the hydrogen energy vehicle.
In an embodiment, after sending the noise reduction start command to the dual-microphone module in the hydrogen energy automobile, before determining that the sound signal collected by the dual-microphone module is a noise signal, the method further includes:
acquiring a first sound signal acquired by one microphone and a second sound signal acquired by the other microphone in the dual-microphone module;
acquiring a first sound phase of the first sound signal and a second sound phase of the second sound signal;
and if the phase difference between the first sound phase and the second sound phase is smaller than a preset phase difference threshold value, determining that the sound signal collected by the double-microphone module is a noise signal.
In this embodiment, two microphones can be used for noise detection, i.e. the phase and amplitude difference of the same sound signal reaching two microphones are used to determine the position of the sound source of the sound signal relative to the two microphones. Specifically, if the phase difference between the two microphones in the two-microphone module reached by one sound signal is small, the sound source position of the sound signal is considered to be far away from the microphones, and the sound signal can be determined as noise. Therefore, noise in the surrounding environment can be detected more accurately based on the double-microphone module.
In one embodiment, the obtaining a first sound phase of the first sound signal and a second sound phase of the second sound signal includes:
and acquiring a first sinusoidal sound wave function of the first sound signal and a second sinusoidal sound wave function of the second sound signal, acquiring a first sound phase of the first sound signal through the first sinusoidal sound wave function, and acquiring a second sound phase of the second sound signal through the second sinusoidal sound wave function.
In this embodiment, the sound is essentially represented by a sine wave function, so that the first sine wave function of the first sound signal is represented by a function such as S1 ═ A1sin (θ 1), and the second sine wave function of the second sound signal is represented by a function such as S2 ═ A2sin (θ 2), and then the difference between the first sound phase θ 1 and the second sound phase θ 2 is calculated to obtain the phase difference between the first sound phase and the second sound phase. Therefore, whether the phase difference determined based on the sine wave representation form of the sound exceeds the phase difference threshold value or not can be determined more accurately whether the sound signal collected by the double-microphone module is a noise signal or not.
And S104, if the sound signal acquired by the double-microphone module is determined to be a noise signal, generating a silencer starting instruction, and sending the silencer starting instruction to the vehicle-mounted silencer to start the vehicle-mounted silencer to absorb noise in the hydrogenation process.
In this embodiment, when confirming the sound signal that the dual microphone module was gathered is the noise signal, shows to have the car machine to produce silencer start-up command this moment, will silencer start-up command sends to on-vehicle silencer and carries out hydrogenation in-process noise absorption with starting on-vehicle silencer, carries out partial effective elimination through this active silencer of on-vehicle silencer to noise and ambient environment noise in the hydrogenation process for driver and hydrogenation station staff's hearing under this noisy environment in the hydrogenation station has obtained the protection.
According to the method, when the hydrogen energy automobile is determined to reach the hydrogenation station based on the current positioning information, the collected sound signal is determined to be the noise signal by the double-microphone module, a silencer starting instruction is timely triggered to be generated to start the vehicle-mounted silencer to absorb the noise in the hydrogenation process, and therefore the environmental noise of the hydrogenation station is effectively reduced.
The embodiment of the invention also provides a hydrogenation noise reduction implementation device, which is used for executing any embodiment of the hydrogenation noise reduction implementation method. Specifically, referring to fig. 3, fig. 3 is a schematic block diagram of a hydrogenation noise reduction implementation apparatus 100 according to an embodiment of the present invention.
As shown in fig. 3, the hydrogenation and noise reduction implementation apparatus 100 includes a positioning information obtaining unit 101, a first instruction generating unit 102, a first instruction sending unit 103, and a noise reduction start control unit 104.
The positioning information obtaining unit 101 is used for describing a technical scheme by using a hydrogen energy vehicle as an execution subject. The hydrogen energy automobile is provided with structural components (such as an automobile body) required by a conventional automobile, a vehicle machine (such as a vehicle-mounted touch screen on a center console is a part of the vehicle machine), a double-microphone module arranged in the vehicle (the double-microphone module is connected with the vehicle machine), a vehicle-mounted silencer arranged in the vehicle and close to a hydrogen energy storage area (the vehicle-mounted silencer is connected with the vehicle machine, the vehicle-mounted silencer can also work under the condition that the automobile is flameout by a self-contained power supply, the vehicle-mounted silencer is an active silencer, sound waves with the same size and the opposite phase as the original sound pressure can be generated, the sound waves cancel the original sound field in a certain range), and a vehicle-mounted camera arranged on the vehicle (such as a camera arranged on a right rearview mirror of the vehicle can be regarded as a vehicle-mounted camera). Therefore, the vehicle-mounted silencer can not only reduce the noise of a hydrogen energy automobile adopting a hydrogen internal combustion engine in the running process of the automobile, but also effectively reduce the noise of the environment of a hydrogen station after reaching the hydrogen station.
In order to more accurately judge whether the driver drives the hydrogen energy vehicle to the hydrogen refueling station, the current positioning information can be acquired based on a positioning module (such as a GPS positioning module, a Beidou positioning module and the like) in the vehicle, and more specifically, the current longitude and latitude corresponding to the current positioning information can be acquired. Moreover, the current positioning information corresponds to an initial confidence value, for example, the initial confidence value is 0.5 to indicate that the positioning accuracy confidence of the current positioning information is 50%. Therefore, the specific position where the hydrogen energy automobile stays at present can be accurately judged based on the acquired current positioning information.
In an embodiment, the hydrogenation noise reduction implementation apparatus 100 further includes:
the image acquisition control unit is used for acquiring the current environment image outside the vehicle through the vehicle-mounted camera;
the first detection unit is used for acquiring a human body existence area of the current vehicle exterior environment image if the existence of the human body in the current vehicle exterior environment image is judged through a pre-trained target detection network;
the second detection unit is used for detecting and acquiring a work pattern identification area in the human body existence area through a pre-trained image recognition model and acquiring a user name corresponding to the work pattern identification area;
the confidence value updating unit is used for increasing the initial confidence value of the current positioning information by a preset first increase value to obtain the current confidence value if the user name corresponding to the work equipment graphic identification area is determined to be the same as the location type corresponding to the current positioning information;
and the first judgment unit is used for judging that the current positioning information is the same as the positioning information of the hydrogenation station if the current confidence value exceeds a preset confidence threshold value.
In this embodiment, when the vehicle is in a flameout state and a flameout command of the vehicle is generated, the vehicle-mounted camera on the vehicle can acquire the current external environment image of the vehicle in the direction to which the vehicle is aligned, and whether a worker of the hydrogen station is close to the hydrogen energy vehicle to start the hydrogenation operation is judged through the current external environment image. When the vehicle-mounted camera collects the current external environment image, multi-frame images can be collected, then each frame image is judged according to the processing process, whether the current external environment image has a human body existing region or not is judged, if the human body existing region is determined to exist, the work installation graph identification region in the human body existing region is obtained, the user name corresponding to the work installation graph identification region is obtained, and whether the place at the moment is located in the hydrogen adding station or not is judged according to the company name corresponding to the LOGO graph installed publicly by the workers of the hydrogen adding station.
Once it is determined that the username corresponding to the working device graphic identifier region is the same as the location type (e.g., the location type is a hydrogen station) corresponding to the current positioning information or the similarity exceeds a preset similarity threshold, the initial confidence value of the current positioning information may be increased by a preset first increase value to obtain a current confidence value (e.g., the first increase value is set to 0.5), for example, referring to the above example, the initial confidence value is 0.5, and then the initial confidence value is increased by the first increase value of 0.5 to obtain a current confidence value of 1. If the confidence threshold is set to 0.8 in advance, the current confidence value can be judged to be larger than the confidence threshold at the moment, the current positioning information is the same as the positioning information of the hydrogen refueling station, and therefore it is further determined that the user arrives at the hydrogen refueling station. Therefore, whether the hydrogen energy automobile reaches the hydrogen station or not is judged based on the positioning position, and target detection and image recognition can be carried out based on the current environment image outside the automobile collected by the vehicle-mounted camera, so that whether the hydrogen energy automobile reaches the hydrogen station or not is further judged.
In one embodiment, the object detection network is a single lens multi-box detector model.
The Single-lens multi-box Detector model is an SSD model, which is called a Single Shot multi box Detector, and is a target detection model, and can effectively identify each target in a current picture to obtain an identification frame of each target, and each identification frame is a known classification result (such as a classification result of a human body, a hydrogenation device, and the like) and a classification probability value corresponding to the classification result. Through the single-lens multi-box detector model, whether a human body exists in the current vehicle exterior environment image can be detected quickly and accurately.
In an embodiment, the apparatus 100 for reducing noise further includes:
the third detection unit is used for inputting the current vehicle exterior environment image into the single-lens multi-box detector model for target detection to obtain a plurality of detection identification frames; each detection identification frame corresponds to one identification classification name;
and the second judgment unit is used for judging that the human body exists in the current vehicle exterior environment image if the classification corresponding to the detection identification frame is determined as the human body.
In this embodiment, for example, whether a human body exists in a frame of current vehicle exterior environment image is detected based on a single-lens multi-box detector model, normalization processing needs to be performed on the current vehicle exterior environment image to obtain a normalized picture, and then the normalized picture is input to the single-lens multi-box detector model to perform target detection to obtain a plurality of detection identification frames; the method comprises the steps that the area where a person exists in a current vehicle exterior environment image can be identified based on a single-lens multi-box detector model, and an identification classification name and a probability value corresponding to the identification classification name are given according to the area where the person exists. Therefore, through the single-lens multi-box detector model, the detection of the plurality of detection identification frames in the current vehicle exterior environment image can be quickly and accurately carried out, so that whether a human body exists or not is further judged based on the identification classification names of the detection identification frames.
In one embodiment, the image recognition model is a Yolov3 model; the second detection unit is specifically configured to:
acquiring current image characteristics corresponding to the work clothing graphic identification area;
sending the current image features to a cloud server;
and acquiring an identification result corresponding to the current image feature sent by the cloud server, and taking the identification result as a user name.
In this embodiment, whether a work pattern identification area exists in a human body existence area may be detected based on the YOLOv3 detection model; and YOLOv3 is a v3 version of the YOLO, an object detection algorithm. Because the workers at the hydrogen adding station generally wear the work clothes, the user name (such as XXX hydrogen energy) of the operation company corresponding to the hydrogen adding station or the trademark image (generally comprising images and/or characters) of the operation company corresponding to the hydrogen adding station is arranged at the left chest or the back of the work clothes, at this time, the current vehicle exterior environment image can be acquired by the vehicle-mounted camera and sent to the vehicle machine, and the image identification model stored in the vehicle machine can detect and extract the work clothes image identification area in the current vehicle exterior environment image. Once the acquisition of the work load pattern identification area is detected, the work load pattern identification area is acquired by considering the situation of insufficient vehicle computing power, the current image characteristics corresponding to the work pattern-loading identification area (generally, current image characteristics corresponding to the work pattern-loading identification area can be obtained after the work pattern-loading identification area is processed on the basis of a convolutional layer, a pooling layer and a full connection layer of a convolutional neural network stored in the vehicle), which are obtained by the vehicle, are sent to the cloud server, the similarity is calculated between the image characteristics of a large number of company trademark images stored in the cloud server and the current image characteristics, the trademark image corresponding to the image characteristics having the maximum similarity with the current image characteristics is selected as the target trademark image, and acquiring a corresponding recognition result (generally, the recognition result is represented by a user company name) in a cloud server based on the target trademark image; the image characteristics of each trademark image stored in the cloud server and the identification result corresponding to each image characteristic are bound in a one-to-one correspondence manner. And finally, after the recognition result corresponding to the current image feature is obtained in the cloud server, the recognition result is sent to the vehicle machine by the cloud server. Therefore, the image classification can be effectively participated by means of the calculation force of the cloud server in this way, and the data processing pressure of the vehicle machine is effectively reduced.
The first instruction generating unit 102 is configured to generate a noise reduction start instruction if it is determined that the current positioning information is the same as the hydrogen refueling station positioning information.
In this embodiment, generally, offline navigation data (such as offline GIS electronic map data) is stored in the in-vehicle device, the offline navigation data stores positioning information of a plurality of hydrogen stations, and once the current longitude and latitude corresponding to the current positioning information is the same as the longitude and latitude of one of the hydrogen station positioning information of the offline navigation data or the longitude and latitude difference value between the two does not exceed a preset difference threshold value, it indicates that the current positioning information is the same as the hydrogen station positioning information, and at this time, the in-vehicle device may generate a noise reduction start instruction to start the in-vehicle noise reduction function.
And a first instruction sending unit 103, configured to send the noise reduction start instruction to a dual microphone module in the hydrogen energy vehicle.
In this embodiment, since the car machine cannot participate in the collection of external environmental sounds, it is possible to determine whether the external sounds of the hydrogen filling station are noises more accurately, and at this time, the car machine may be configured to generate the noise reduction start command to be sent to the dual microphone module in the hydrogen energy vehicle.
In an embodiment, the apparatus 100 for reducing noise further includes:
the first acquisition unit is used for acquiring a first sound signal acquired by one microphone and a second sound signal acquired by the other microphone in the dual-microphone module;
a second obtaining unit configured to obtain a first sound phase of the first sound signal and a second sound phase of the second sound signal;
and the phase difference calculating unit is used for determining that the sound signal acquired by the dual-microphone module is a noise signal if the phase difference between the first sound phase and the second sound phase is smaller than a preset phase difference threshold value.
In this embodiment, two microphones can be used for noise detection, i.e. the phase and amplitude difference of the same sound signal reaching two microphones are used to determine the position of the sound source of the sound signal relative to the two microphones. Specifically, if the phase difference between the two microphones in the two-microphone module reached by one sound signal is small, the sound source position of the sound signal is considered to be far away from the microphones, and the sound signal can be determined as noise. Therefore, noise in the surrounding environment can be detected more accurately based on the double-microphone module.
In an embodiment, the second obtaining unit is specifically configured to:
and acquiring a first sinusoidal sound wave function of the first sound signal and a second sinusoidal sound wave function of the second sound signal, acquiring a first sound phase of the first sound signal through the first sinusoidal sound wave function, and acquiring a second sound phase of the second sound signal through the second sinusoidal sound wave function.
In this embodiment, the sound is essentially represented by a sine wave function, so that the first sine wave function of the first sound signal is represented by a function such as S1 ═ A1sin (θ 1), and the second sine wave function of the second sound signal is represented by a function such as S2 ═ A2sin (θ 2), and then the difference between the first sound phase θ 1 and the second sound phase θ 2 is calculated to obtain the phase difference between the first sound phase and the second sound phase. Therefore, whether the phase difference determined based on the sine wave representation form of the sound exceeds the phase difference threshold value or not can be determined more accurately whether the sound signal collected by the double-microphone module is a noise signal or not.
And the noise reduction starting control unit 104 is used for generating a silencer starting instruction if the sound signal acquired by the double-microphone module is determined to be a noise signal, and sending the silencer starting instruction to the vehicle-mounted silencer to start the vehicle-mounted silencer to absorb noise in the hydrogenation process.
In this embodiment, when confirming the sound signal that the dual microphone module was gathered is the noise signal, shows that there can be the car this moment to produce silencer start-up command, will silencer start-up command sends to on-vehicle silencer and carries out hydrogenation in-process noise absorption with starting on-vehicle silencer, carries out partial effective elimination through this active silencer of on-vehicle silencer to noise and ambient environment noise in the hydrogenation process for be in this noisy environment of hydrogenation station under driver and the hydrogenation station staff's hearing has obtained the protection.
The device has realized when confirming that hydrogen energy automobile has arrived the hydrogenation station based on current locating information, can be when the sound signal that two microphone module confirm to gather is the noise signal, timely trigger produces silencer start-up instruction and carries out hydrogenation in-process noise absorption in order to start on-vehicle silencer to effectively fall the noise to the ambient noise at hydrogenation station.
The above-mentioned hydrogenation noise reduction implementation apparatus may be implemented in the form of a computer program in a vehicle of a hydrogen energy vehicle, and the computer program may be run on a computer device as shown in fig. 4.
Referring to fig. 4, fig. 4 is a schematic block diagram of a computer device according to an embodiment of the present invention. The computer device 500 is a vehicle-mounted device on a hydrogen energy vehicle, and the vehicle-mounted device can be understood as a vehicle-mounted intelligent terminal.
Referring to fig. 4, the computer apparatus 500 includes a processor 502, a memory, which may include a storage medium 503 and an internal memory 504, and a network interface 505 connected by a device bus 501.
The storage medium 503 may store an operating device 5031 and a computer program 5032. The computer program 5032, when executed, may cause the processor 502 to perform a method of implementing hydro-denoising.
The processor 502 is used to provide computing and control capabilities that support the operation of the overall computer device 500.
The internal memory 504 provides an environment for the computer program 5032 in the storage medium 503 to run, and when the computer program 5032 is executed by the processor 502, the processor 502 can be enabled to execute the hydrogenation and noise reduction implementation method.
The network interface 505 is used for network communication, such as providing transmission of data information. Those skilled in the art will appreciate that the configuration shown in fig. 4 is a block diagram of only a portion of the configuration associated with aspects of the present invention and is not intended to limit the computing device 500 to which aspects of the present invention may be applied, and that a particular computing device 500 may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
The processor 502 is configured to run the computer program 5032 stored in the memory to implement the hydrogenation and noise reduction implementation method disclosed in the embodiment of the present invention.
Those skilled in the art will appreciate that the embodiment of a computer device illustrated in fig. 4 does not constitute a limitation on the specific construction of the computer device, and that in other embodiments a computer device may include more or fewer components than those illustrated, or some components may be combined, or a different arrangement of components. For example, in some embodiments, the computer device may only include a memory and a processor, and in such embodiments, the structures and functions of the memory and the processor are consistent with those of the embodiment shown in fig. 4, which are not described herein again.
It should be understood that, in the embodiment of the present invention, the Processor 502 may be a Central Processing Unit (CPU), and the Processor 502 may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In another embodiment of the invention, a computer-readable storage medium is provided. The computer-readable storage medium may be a nonvolatile computer-readable storage medium or a volatile computer-readable storage medium. The computer readable storage medium stores a computer program, wherein the computer program is executed by a processor to implement the hydrogenation and noise reduction implementation method disclosed by the embodiment of the invention.
It can be clearly understood by those skilled in the art that, for convenience and simplicity of description, the specific working processes of the above-described devices, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the technical solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided by the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the units is only a logical division, and there may be another division in actual implementation, and units having the same function may be grouped into one unit, for example, multiple units or components may be combined or may be integrated into another device, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electric, mechanical or other form of connection.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a background server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A hydrogenation noise reduction implementation method is applied to a hydrogen energy automobile and is characterized by comprising the following steps:
responding to a vehicle flameout instruction, and acquiring current positioning information of the vehicle through a vehicle machine; the current positioning information corresponds to an initial confidence value;
if the current positioning information is the same as the positioning information of the hydrogenation station, generating a noise reduction starting instruction;
sending the noise reduction starting instruction to a double-microphone module in the hydrogen energy source automobile; and
and if the sound signal acquired by the double-microphone module is determined to be a noise signal, generating a silencer starting instruction, and sending the silencer starting instruction to the vehicle-mounted silencer to start the vehicle-mounted silencer to absorb noise in the hydrogenation process.
2. The method for achieving hydrogenation noise reduction according to claim 1, wherein after the obtaining of the current positioning information of the vehicle by the vehicle machine, the method further comprises:
acquiring a current external environment image through a vehicle-mounted camera;
if the human body exists in the current vehicle exterior environment image is judged through a pre-trained target detection network, acquiring a human body existence area of the current vehicle exterior environment image;
detecting and acquiring a work pattern identification area in the human body existing area through a pre-trained image recognition model, and acquiring a user name corresponding to the work pattern identification area;
if the user name corresponding to the work equipment graphic identification area is the same as the place type corresponding to the current positioning information, increasing the initial confidence value of the current positioning information by a preset first increase value to obtain a current confidence value;
and if the current confidence value exceeds a preset confidence threshold value, judging that the current positioning information is the same as the positioning information of the hydrogenation station.
3. The method of claim 1, wherein after the sending the noise reduction start command to a dual-microphone module in the hydrogen energy vehicle, before determining that the sound signal collected by the dual-microphone module is a noise signal, the method further comprises:
acquiring a first sound signal acquired by one microphone and a second sound signal acquired by the other microphone in the dual-microphone module;
acquiring a first sound phase of the first sound signal and a second sound phase of the second sound signal;
and if the phase difference between the first sound phase and the second sound phase is smaller than a preset phase difference threshold value, determining that the sound signal collected by the double-microphone module is a noise signal.
4. The method of claim 3, wherein obtaining the first acoustic phase of the first acoustic signal and the second acoustic phase of the second acoustic signal comprises:
and acquiring a first sinusoidal sound wave function of the first sound signal and a second sinusoidal sound wave function of the second sound signal, acquiring a first sound phase of the first sound signal through the first sinusoidal sound wave function, and acquiring a second sound phase of the second sound signal through the second sinusoidal sound wave function.
5. The method of claim 2, wherein the target detection network is a single-lens multi-box detector model.
6. The method for achieving hydrogenation and noise reduction according to claim 5, wherein if it is determined that a human body exists in the current vehicle exterior environment image through a pre-trained target detection network, before the obtaining of the human body existence region of the current vehicle exterior environment image, the method further comprises:
inputting the current vehicle exterior environment image into the single-lens multi-box detector model for target detection to obtain a plurality of detection identification frames; each detection identification frame corresponds to one identification classification name;
and if the classification corresponding to the detection and identification frame is determined to be a human body, judging that the human body exists in the current vehicle exterior environment image.
7. The method for achieving hydrogenation noise reduction according to claim 2, wherein the image recognition model is a Yolov3 model;
the obtaining of the user name corresponding to the work clothing graphic identification area includes:
acquiring current image characteristics corresponding to the work clothing graphic identification area;
sending the current image features to a cloud server;
and acquiring an identification result corresponding to the current image feature sent by the cloud server, and taking the identification result as a user name.
8. A hydrogenation noise reduction implementation device is characterized by comprising:
the positioning information acquisition unit is used for responding to a vehicle flameout instruction and acquiring the current positioning information of the vehicle through the vehicle machine; wherein, the current positioning information corresponds to an initial confidence value;
the first instruction generating unit is used for generating a noise reduction starting instruction if the current positioning information is determined to be the same as the positioning information of the hydrogenation station;
the first instruction sending unit is used for sending the noise reduction starting instruction to a double-microphone module in the hydrogen energy source automobile; and
and the noise reduction starting control unit is used for generating a silencer starting instruction if the sound signal acquired by the double-microphone module is determined to be a noise signal, and sending the silencer starting instruction to the vehicle-mounted silencer to start the vehicle-mounted silencer to absorb noise in the hydrogenation process.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, causes the processor to perform the method of any of claims 1 to 7.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011152820A (en) * | 2010-01-26 | 2011-08-11 | Denso Corp | Noise cancel device for vehicle and noise cancel system for vehicle |
| CN108174321A (en) * | 2018-02-11 | 2018-06-15 | 歌尔股份有限公司 | The method, apparatus and earphone of earphone noise reduction process |
| CN109086745A (en) * | 2018-08-31 | 2018-12-25 | 广东工业大学 | A kind of localization method, device, equipment and computer readable storage medium |
| CN110310618A (en) * | 2019-06-05 | 2019-10-08 | 广州小鹏汽车科技有限公司 | Processing method, processing unit and the vehicle of vehicle running environment sound |
| CN111461101A (en) * | 2020-04-20 | 2020-07-28 | 上海东普信息科技有限公司 | Method, device and equipment for identifying work clothes mark and storage medium |
| CN112443435A (en) * | 2019-09-05 | 2021-03-05 | 北汽福田汽车股份有限公司 | Noise control system, method and device and automobile |
| CN112944115A (en) * | 2021-03-15 | 2021-06-11 | 北京伯肯节能科技股份有限公司 | Hydrogenation station |
| CN113239913A (en) * | 2021-07-13 | 2021-08-10 | 深圳市图元科技有限公司 | Noise source positioning method, device and system based on sound and image |
-
2022
- 2022-04-21 CN CN202210426289.8A patent/CN115009204A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011152820A (en) * | 2010-01-26 | 2011-08-11 | Denso Corp | Noise cancel device for vehicle and noise cancel system for vehicle |
| CN108174321A (en) * | 2018-02-11 | 2018-06-15 | 歌尔股份有限公司 | The method, apparatus and earphone of earphone noise reduction process |
| CN109086745A (en) * | 2018-08-31 | 2018-12-25 | 广东工业大学 | A kind of localization method, device, equipment and computer readable storage medium |
| CN110310618A (en) * | 2019-06-05 | 2019-10-08 | 广州小鹏汽车科技有限公司 | Processing method, processing unit and the vehicle of vehicle running environment sound |
| CN112443435A (en) * | 2019-09-05 | 2021-03-05 | 北汽福田汽车股份有限公司 | Noise control system, method and device and automobile |
| CN111461101A (en) * | 2020-04-20 | 2020-07-28 | 上海东普信息科技有限公司 | Method, device and equipment for identifying work clothes mark and storage medium |
| CN112944115A (en) * | 2021-03-15 | 2021-06-11 | 北京伯肯节能科技股份有限公司 | Hydrogenation station |
| CN113239913A (en) * | 2021-07-13 | 2021-08-10 | 深圳市图元科技有限公司 | Noise source positioning method, device and system based on sound and image |
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