WO2020107261A1 - 一种检测概率无声故障的方法和装置 - Google Patents

一种检测概率无声故障的方法和装置 Download PDF

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Publication number
WO2020107261A1
WO2020107261A1 PCT/CN2018/117933 CN2018117933W WO2020107261A1 WO 2020107261 A1 WO2020107261 A1 WO 2020107261A1 CN 2018117933 W CN2018117933 W CN 2018117933W WO 2020107261 A1 WO2020107261 A1 WO 2020107261A1
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Prior art keywords
electronic device
identification code
frequency
correlation coefficient
sound
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PCT/CN2018/117933
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English (en)
French (fr)
Inventor
郭志巍
舒文
张海宏
王硕强
Original Assignee
华为技术有限公司
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Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to CN201880099761.3A priority Critical patent/CN113170268B/zh
Priority to PCT/CN2018/117933 priority patent/WO2020107261A1/zh
Publication of WO2020107261A1 publication Critical patent/WO2020107261A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R29/00—Monitoring arrangements; Testing arrangements

Definitions

  • the present application relates to the field of electronic equipment, and more specifically, to a method and apparatus for detecting probabilistic silent failures.
  • the external speaker and receiver are important devices for music playback and call on the mobile phone.
  • the built-in chip decodes the audio file and passes it to the power amplifier through the audio path.
  • the amplified audio signal is then transmitted to the external speaker for music Play.
  • the lead wire of the mobile phone speaker is connected to the power amplifier through the shrapnel to realize the path.
  • the mobile phone receiver it is similar to the connection of the speaker, and it is usually the shrapnel contact connection. Through such a shrapnel electrical connection structure, the speaker and the receiver can normally receive the music signal and the voice signal of the call and play it during the music playback or the call of the mobile phone.
  • the audio path When the speaker or earpiece's audio path is electrically connected to the shrapnel in poor contact, the audio path will be intermittently interrupted, resulting in a probability or intermittent silent failure of the mobile phone's speaker or earpiece.
  • This probability of silent failure may only occur for a short time during a long time of music playback or call, or a greater probability of intermittent silent when the mobile phone is in motion (such as when the mobile phone falls after a short period of time, when the mobile phone is running) some.
  • any node on the audio hardware path is broken, it will also cause a failure of the earpiece or the speaker being silent.
  • the silent problem of the mobile phone will seriously affect the user's subjective listening experience, so in the mobile phone research and development stage will focus on testing and intercepting this potential problem.
  • a method for detecting probabilistic silent failure is to let the mobile phone play the sound source through the speaker or earpiece.
  • the tester listens to the sound all the time and records whether the probabilistic silence occurs during the entire test time.
  • due to the probabilistic silent detection it takes a long time to play the sound source (a few hours), and the tester needs to participate in the whole process for a long time. Therefore, this manual detection method is inefficient, and may only detect a few mobile phones a day, which is very labor-intensive. .
  • the present application provides a method and device for detecting probabilistic silent failure, which is helpful to realize automatic detection of probabilistic silent.
  • a method for detecting a probabilistic silent failure is provided, which is applied to an electronic device.
  • the electronic device includes a sound player.
  • the method includes: the electronic device determines a utterance frequency corresponding to the electronic device; Frequency to generate audio source data; the electronic device plays the audio source data through the sound player and collects audio data when playing the audio source data; when the processing result of the audio data by the electronic device satisfies preset conditions, the electronic device Determine the probability that the sound player has a silent failure.
  • the electronic device In the method for detecting a probabilistic silent failure in the embodiment of the present application, the electronic device generates sound source data from the determined utterance frequency, and judges whether the electronic device is probabilistically silent by the collected audio data, and can detect artificial subjective listening sound for a long time It becomes an objective detection, which replaces the human ear to judge the probability silent failure of the mobile phone, which is helpful to realize the automatic detection of probability silent of electronic equipment.
  • the electronic device determining the utterance frequency corresponding to the electronic device includes: the electronic device acquiring the utterance frequency. For example, when multiple electronic devices perform a probabilistic silent test, the control device may send the audible frequency (or directly send the sound source data) to each of the multiple electronic devices; or, the electronic device detects the tester After the operation of inputting the utterance frequency, in response to the operation, the utterance frequency corresponding to the electronic device is determined.
  • the sound player is a speaker or a receiver microphone.
  • each electronic device when multiple electronic devices perform probabilistic silent detection, each electronic device can separately determine its own utterance frequency, and generate sound source data from the utterance frequency for playback, because The sound source data played by each electronic device corresponds to a different utterance frequency, which helps to avoid mutual interference between different electronic devices, thereby helping to realize the automatic detection of multiple electronic devices.
  • the electronic device determining the utterance frequency corresponding to the electronic device includes: the electronic device acquiring a first identification code, where the first identification code is corresponding to the electronic device Identification code; the electronic device determines the vocalization frequency according to the first identification code.
  • the electronic device determines the utterance frequency through the identification code, and generates sound source data from the utterance frequency for playback. Since the sound source data played by each electronic device corresponds to a different utterance frequency, Help to avoid mutual interference between different electronic devices, thereby helping to realize the automatic detection of multiple electronic devices.
  • the first identification code is a unique identification code of the electronic device, and determining the sounding frequency according to the first identification code includes: the electronic device The unique identification code is reversely replaced to obtain a second identification code; the electronic device determines the vocalization frequency according to the second identification code.
  • the electronic device may replace the unique identification code of the electronic device according to a predefined rule, and determine the sounding frequency according to the replaced identification code.
  • the unique identification codes may be close to each other, and using the method of reverse replacement helps to further reduce mutual interference between different electronic devices.
  • the second identification code has a linear or nonlinear relationship with the utterance frequency.
  • the second identification code is linearly related to the utterance frequency, where determining the utterance frequency based on the second identification code includes The following formula determines the sound frequency: Where f 0 is the utterance frequency, ID-R is the second identification code, f High is the first utterance frequency threshold, f Low is the second utterance frequency threshold, and ID-R max is the allowed second identification code The maximum value, ID-R min is the minimum value of the allowed second identification code, and the first utterance frequency threshold is greater than the second utterance frequency threshold.
  • the first identification code includes an international mobile user identification IMEI code, a serial number SN code, a user identification SIM code, a wireless local area network WLAN MAC address, a Bluetooth MAC address, or One or more of the pseudo-unique IDs of the pseudo-unique identification code of Android.
  • the method for detecting a probabilistic silent failure determines the corresponding vocalization frequency through the unique identification code of the electronic device, which helps to realize automatic detection of multiple electronic devices.
  • the processing result includes one or more of signal amplitude, correlation coefficient, or energy of the first acoustic signal; wherein, the signal amplitude is in the first frequency range
  • the audio data is obtained after narrowband filtering
  • the correlation coefficient is the correlation coefficient obtained by convolution calculation of the audio data and the sound source data
  • the energy of the first sound signal is the audio data at the utterance frequency.
  • Obtained by Fourier transform (fast Fourier transform, FFT) the first frequency range includes the utterance frequency.
  • the electronic device may adopt one or any of the foregoing dimensions when detecting whether the sound player is probabilistically silent.
  • the narrow-band amplitude near the utterance frequency f 0 after filtering, the correlation coefficient between the collected audio data and the sound source data, and the spectral distribution characteristics near the utterance frequency are used to detect the utterance, which helps to improve the accuracy of the detection degree.
  • the processing result includes the correlation coefficient
  • the electronic device determines that the sound player occurs
  • the probabilistic silent failure includes: when the correlation coefficient is less than or equal to the first value, determining that the sound player has a probabilistic silent failure.
  • the processing result includes the correlation coefficient and the signal amplitude
  • the electronic device determines the The sound player has a probability of silent failure, including: the electronic device determines that the correlation coefficient is greater than or equal to the first value and less than or equal to the second value; and in the case where the signal amplitude is less than or equal to the third value, the electronic device determines The sound player has a probability of silent failure.
  • the two dimensions of the narrowband amplitude near the utterance frequency f 0 after filtering and the correlation coefficient between the collected audio data and the sound source data are used to detect the utterance, which helps to improve the accuracy of the detection.
  • the processing result includes the correlation coefficient and the energy of the first acoustic signal
  • the electronic The device determines that the sound player has a probability of silent failure, including: the electronic device determines that the correlation coefficient is greater than or equal to the first value and less than or equal to the second value; the difference between the energy of the first acoustic signal and the energy of the second acoustic signal When the value is less than or equal to the fourth value, the electronic device determines that the sound player has a probability of silent failure; wherein, the energy of the second sound signal is a sound signal corresponding to other frequencies in the second frequency range except the sounding frequency The average value of energy, the second frequency range includes the utterance frequency.
  • the two dimensions of the correlation coefficient between the audio data collected after filtering and the sound source data and the spectral distribution characteristics near the utterance frequency are used to detect the utterance, which helps to improve the accuracy of the detection.
  • the correlation coefficient and the spectral distribution characteristics near the sound frequency are less affected by the difference of the devices, for different types of electronic equipment, the structure, sound playback device, and audio recording device are different, and it is not necessary to set different for each electronic device. Detection threshold.
  • the method before the electronic device determines that the sound player has a probability of silent failure, the method further includes: the electronic device performing high-pass filtering and windowing on the audio data.
  • the method for detecting a probabilistic silent failure in the embodiment of the present application helps to filter out low-frequency environmental noise by high-pass filtering the collected audio data; by windowing the collected audio data, it helps prevent spectrum leakage .
  • the present technical solution provides an apparatus for detecting a probabilistic silent failure.
  • the apparatus is included in an electronic device, and the apparatus has a function of implementing the above aspect and the possible implementation manners of the above aspect.
  • the function can be realized by hardware, and can also be realized by hardware executing corresponding software.
  • the hardware or software includes one or more modules or units corresponding to the above functions.
  • the present technical solution provides an electronic device, including: a sound player; a sound collector; one or more processors; a memory; multiple application programs; and one or more computer programs.
  • one or more computer programs are stored in the memory, and the one or more computer programs include instructions.
  • the instruction is executed by the electronic device, the electronic device is caused to perform the method for detecting a probabilistic silent failure in any possible implementation of any one of the above aspects.
  • the present technical solution provides an electronic device, including one or more processors and one or more memories.
  • the one or more memories are coupled to one or more processors.
  • the one or more memories are used to store computer program code.
  • the computer program codes include computer instructions.
  • the one or more processors execute the computer instructions, the electronic device is executed.
  • the present technical solution provides a computer storage medium, including computer instructions, which, when the computer instructions run on an electronic device, cause the electronic device to perform any of the possible implementations of any of the above aspects to detect a probability silent failure method.
  • the present technical solution provides a computer program product that, when the computer program product runs on an electronic device, causes the electronic device to perform a method for detecting a probabilistic silent failure in any possible design of any of the above aspects.
  • each electronic device when multiple electronic devices perform probabilistic silent detection, each electronic device can separately determine its own utterance frequency and generate sound source data from the utterance frequency for playback , Change the long-term artificial subjective listening sound detection into objective detection, replace the human ear to judge the mobile phone audio failure, save labor costs. It can also be detected in an environment that cannot be monitored manually (under high temperature, high humidity, salt fog, etc.), expanding the detection range. At the same time, since the sound source data played by each electronic device corresponds to a different utterance frequency, it helps to avoid mutual interference between different electronic devices.
  • FIG. 1 is a schematic structural diagram of a mobile phone provided by an embodiment of the present application.
  • FIG. 2 is another schematic structural diagram of a mobile phone provided by an embodiment of the present application.
  • FIG. 3 is another schematic structural diagram of a mobile phone provided by an embodiment of the present application.
  • FIG. 4 is a schematic flowchart of a method for detecting a probabilistic silent failure provided by an embodiment of the present application.
  • FIG. 5 is another schematic flowchart of a method for detecting a probabilistic silent failure provided by an embodiment of the present application.
  • FIG. 6 is another schematic flowchart of a method for detecting a probabilistic silent failure provided by an embodiment of the present application.
  • FIG. 7 is another schematic flowchart of a method for detecting a probabilistic silent failure provided by an embodiment of the present application.
  • FIG. 8 is a schematic diagram of detecting multiple mobile phones according to an embodiment of the present application.
  • FIG. 9 is a schematic diagram of detection results of multiple mobile phones provided by an embodiment of the present application.
  • FIG. 10 is a schematic block diagram of an apparatus for detecting a probabilistic silent failure provided by an embodiment of the present application.
  • 11 is another schematic block diagram of an apparatus for detecting a probabilistic silent failure provided by an embodiment of the present application.
  • the technical solutions of the embodiments of the present application may be applied to all devices or devices including a sound player and a microphone.
  • the sound player of the electronic device may include a receiver (RCV) or a speaker (SPK).
  • RCV receiver
  • SPK speaker
  • This application does not limit this. That is to say, when it comes to detecting the useless scenario of the sound player's probabilistic silent, no manual detection is required, and the method for detecting the probabilistic silent failure of the embodiment of the present application can be applied.
  • the embodiments of the present application only use terminal devices as examples for description, but do not limit the protection scope of the embodiments of the present application.
  • the technical solutions of the embodiments of the present application may be applied to terminal devices.
  • the terminal devices may be, but not limited to, mobile stations (MS), mobile terminals (mobile terminals), mobile phones (mobile phones), mobile phones (handsets), and portable devices (portable equipment), etc., can communicate with one or more core networks via a wireless access network (eg, radio access network, RAN).
  • a wireless access network eg, radio access network, RAN.
  • the terminal in the embodiments of the present application may refer to a terminal (terminal), user equipment, access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device , User agent or user device.
  • Terminal devices can also be cellular phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (wireless local loop (WLL) stations, personal digital assistants (personal digital assistants, PDAs), wireless communication Functional handheld devices, computing devices or other processing devices connected to wireless modems, in-vehicle devices, wearable devices, terminal devices in future 5G networks or public land mobile communication networks (PLMN) in the future evolution
  • SIP session initiation protocol
  • WLL wireless local loop
  • PDAs personal digital assistants
  • wireless communication Functional handheld devices computing devices or other processing devices connected to wireless modems
  • in-vehicle devices wearable devices
  • terminal devices in future 5G networks or public land mobile communication networks (PLMN) in the future evolution
  • PLMN public land mobile communication networks
  • the terminal device includes a hardware layer, an operating system layer running on the hardware layer, and an application layer running on the operating system layer.
  • the hardware layer includes central processing unit (CPU), memory management unit (memory management unit, MMU), and memory (also called main memory) and other hardware.
  • the operating system may be any one or more computer operating systems that implement business processes through processes, for example, a Linux operating system, a Unix operating system, an Android operating system, an iOS operating system, or a windows operating system.
  • the application layer includes browser, address book, word processing software, instant messaging software and other applications.
  • the embodiment of the present application does not specifically limit the specific structure of the execution body of the method provided in the embodiment of the present application, as long as it can run the program that records the code of the method provided by the embodiment of the present application, to provide The method may be used for communication.
  • the execution body of the method provided in the embodiments of the present application may be a terminal device, or a functional module in the terminal device that can call a program and execute the program.
  • the term "article of manufacture” as used in this application encompasses a computer program accessible from any computer-readable device, carrier, or medium.
  • the computer-readable medium may include, but is not limited to: magnetic storage devices (for example, hard disks, floppy disks, or magnetic tapes, etc.), optical disks (for example, compact discs (CDs), digital universal discs (digital discs, DVDs)) Etc.), smart cards and flash memory devices (for example, erasable programmable read-only memory (EPROM), cards, sticks or key drives, etc.).
  • various storage media described herein may represent one or more devices and/or other machine-readable media for storing information.
  • machine-readable medium may include, but is not limited to, wireless channels and various other media capable of storing, containing, and/or carrying instructions and/or data.
  • the RF circuit 110 can be used for receiving and sending signals during receiving and sending information or during a call. In particular, after receiving the downlink information of the base station, it is processed by the processor 130; in addition, the designed uplink data is sent to the base station.
  • RF circuits include but are not limited to antennas, at least one amplifier, transceiver, coupler, low noise amplifier (Low Noise Amplifier, LNA), duplexer, and so on.
  • the RF circuit 110 can also communicate with the network and other devices through wireless communication.
  • the wireless communication may use any communication standard or protocol, including but not limited to a global mobile communication system (global system of mobile communication (GSM), general packet radio service (GPRS), code division multiple access (code division multiple access (CDMA), wideband code division multiple access (wideband code division multiple access (WCDMA), long term evolution (LTE), e-mail, short message service (SMS), etc.).
  • GSM global system of mobile communication
  • GPRS general packet radio service
  • CDMA code division multiple access
  • WCDMA wideband code division multiple access
  • LTE long term evolution
  • SMS short message service
  • the memory 140 may be used to store software programs and modules.
  • the processor 130 executes various functional applications and data processing of the mobile phone 100 by running the software programs and modules stored in the memory 140.
  • the memory 140 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the storage data area may store The data created by using the mobile phone 100 (such as audio data, phone book, etc.) and so on.
  • the memory 140 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.
  • the input unit 150 may be used to receive input numeric or character information, and generate key signal input related to user settings and function control of the mobile phone 100.
  • the input unit 150 may include a touch panel 151 and other input devices 152.
  • the touch panel 151 also known as a touch screen, can collect user's touch operations on or near it (for example, the user uses any suitable objects or accessories such as fingers, stylus, etc. on or near the touch panel 151 Operation), and drive the corresponding connection device according to the preset program.
  • the touch panel 151 may include a touch detection device and a touch controller.
  • the touch detection device detects the user's touch orientation, and detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device and converts it into contact coordinates, and then sends To the processor 130, and can receive the command sent by the processor 130 and execute it.
  • the touch panel 151 may be implemented in various types such as resistive, capacitive, infrared, and surface acoustic waves.
  • the input unit 150 may also include other input devices 152.
  • other input devices 152 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control keys, switch keys, etc.), trackball, mouse, joystick, and so on.
  • the display unit 160 may be used to display information input by the user or information provided to the user and various menus of the mobile phone 100.
  • the display unit 160 may include a display panel 161, and optionally, the display panel 161 may be configured in the form of LCD, OLED, or the like.
  • the touch panel 151 may cover the display panel 161, and when the touch panel 151 detects a touch operation on or near it, it is transmitted to the processor 130 to determine the type of touch event, and then the processor 130 according to the touch event The type provides corresponding visual output on the display panel 161.
  • the touch panel 151 and the display panel 151 are implemented as two independent components to realize the input and input functions of the mobile phone 100, in some embodiments, the touch panel 151 and the display panel 161 may be integrated And realize the input and output functions of the mobile phone 100.
  • the mobile phone 100 may further include at least one sensor 170, such as a light sensor, a motion sensor, and other sensors.
  • the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display panel 161 according to the brightness of the ambient light, and the proximity sensor may close the display panel 161 and the mobile phone 100 when moving to the ear /Or backlight.
  • the accelerometer sensor can detect the magnitude of acceleration in various directions (generally three axes), and can detect the magnitude and direction of gravity when at rest, and can be used to identify mobile phone gesture applications (such as horizontal and vertical screen switching, related Games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tap), etc.
  • other sensors such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc. can be configured here. Repeat again.
  • the audio circuit 180 is used to convert digital audio information into an analog audio signal output, and also used to convert an analog audio input into a digital audio signal.
  • the audio circuit 180 can also be used to encode and decode audio signals.
  • the audio circuit 180 may be disposed in the processor 110, or some functional modules of the audio circuit 180 may be disposed in the processor 110.
  • the speaker 181 also called “speaker”
  • the mobile phone 100 can play music through the speaker 181 or play hands-free call sound.
  • the receiver microphone 182 also known as "handset" is used to convert audio electrical signals into sound signals.
  • the receiver microphone 182 can be used to listen to the voice by approaching the human ear.
  • the microphone 183 also called “microphone”, “microphone”, is used to convert sound signals into electrical signals.
  • the user can make a sound by approaching the microphone 183 through a person's mouth, and input a sound signal to the microphone 183.
  • the mobile phone 100 may be provided with at least one microphone 183.
  • the electronic device may play the sound source data through a speaker or a receiver, and collect audio data through the corresponding microphone 183, and determine by comparing and analyzing the sound source data and the collected audio data Whether the speaker or receiver microphone is silent.
  • FIG. 2 shows another schematic structural diagram of the mobile phone 100, where the positional relationship between the speaker 181 and the microphone 183A in the mobile phone 100 is mainly shown.
  • the speaker 181 and the microphone 183A Adjacent to the left and right sides of the data interface at the bottom of the mobile phone 100, after the mobile phone 100 generates audio source data, the audio source data can be played through the speaker 181, and the audio data when the audio source data is played through the microphone 183A is collected and processed
  • the device 130 may determine whether the speaker 181 of the mobile phone 100 is silent.
  • FIG. 3 shows another schematic structural diagram of the mobile phone 100, where the positional relationship between the receiver microphone 182 and the microphone 183B in the mobile phone 100 is mainly shown.
  • the receiver microphone 182 It is adjacent to the microphone 183B and is located on the upper part of the mobile phone 100.
  • the audio source data can be played through the receiver 182 and the audio data when the audio source data is played through the microphone 183B.
  • the processor 130 can After analyzing the sound source data and audio data, it is determined whether the receiver microphone 182 of the mobile phone 100 is silent.
  • the speaker 181 and the receiver microphone 182 can be separately detected.
  • the sound source data played by the speaker 181 can be detected for the microphone 183A, or the sound source data played by the speaker 181 can be detected by the microphone 183B; for the receiver 182, the sound source data played by the microphone 182 can be detected for the microphone 183B It may be that the microphone 183B detects the sound source data played by the microphone 182; or that the sound source data played by the speaker 181 and the receiver 182 is not detected by the microphone, but is detected by other devices. The embodiments of the present application do not limit this.
  • the microphone 183A may be the main microphone of the mobile phone 100, and the microphone 183B may be the auxiliary microphone of the mobile phone 100.
  • the mobile phone 100 may also be provided with three, four, or more microphones 183 to collect sound signals, reduce noise, identify sound sources, and implement directional recording functions.
  • WiFi is a short-range wireless transmission technology.
  • the mobile phone 100 can help users send and receive emails, browse web pages, and access streaming media through the WiFi module 190. It provides users with wireless broadband Internet access.
  • FIG. 2 shows the WiFi module 190, it can be understood that it is not a necessary component of the mobile phone 100, and can be omitted as needed without changing the scope of the essence of the invention.
  • the processor 130 is the control center of the mobile phone 100, and uses various interfaces and lines to connect various parts of the entire mobile phone, by running or executing software programs and/or modules stored in the memory 140, and calling data stored in the memory 140, Perform various functions and process data of the mobile phone 100, thereby realizing various services based on the mobile phone.
  • the processor 130 may include one or more processing units; preferably, the processor 130 may integrate an application processor and a modem processor, where the application processor mainly processes an operating system, a user interface, and application programs, etc.
  • the modem processor mainly handles wireless communication. It can be understood that, the foregoing modem processor may not be integrated into the processor 130.
  • the embodiments of the present application mainly relate to the built-in physical components of the mobile phone 100 such as the speaker 181, the receiver microphone 182, the microphone 183, and the processor 130.
  • the speaker 181 or the receiver 182 is used to play audio source data
  • the microphone 183 is used to record audio data
  • the processor is used to perform algorithm analysis on the recorded audio data and determine whether the speaker 181 or the receiver microphone 182 has a probabilistic silent failure.
  • the mobile phone 100 further includes a power supply 120 (such as a battery) for powering various components.
  • a power supply 120 (such as a battery) for powering various components.
  • the power supply may be logically connected to the processor 130 through a power management system, so as to realize functions such as charging, discharging, and power consumption management through the power management system.
  • the mobile phone 100 may also include a camera, a Bluetooth module, and the like.
  • FIG. 4 shows a schematic flowchart of a method 200 for detecting a probabilistic silent fault provided by an embodiment of the present application. As shown in FIG. 4, the method 200 includes:
  • the electronic device determines a utterance frequency, and the utterance frequency is the utterance frequency corresponding to the electronic device.
  • the electronic device can determine its own unique utterance frequency itself, or the electronic device can obtain the utterance frequency information from the outside In order to achieve different sound frequencies determined by each electronic device.
  • the electronic device determining the utterance frequency includes:
  • the electronic device determines the vocalization frequency through the information stored locally.
  • the locally stored information includes a first identification code ID of an electronic device, and the electronic device determines the utterance frequency according to the first identification code ID.
  • the electronic device may store information of an ID, and the ID includes but is not limited to:
  • IMEI code including IMEI1 code (ID imei1 ) and IMEI 2 code (ID imei2 );
  • SIM Subscriber identification module
  • ID comb A unique identification code composed of the device's ROM version number (ID rom ), manufacturer name (ID fact ), CPU model (ID cpu ), and other hardware (ID oh ) information; the combination
  • ID comb can be expressed as shown in formula (1):
  • ID comb F 1 (ID rom , ID fact , ID cpu , ID oh ) (1)
  • F 1 is a mapping function, a typical but not limited to this mapping method is shown in formula (2):
  • ID comb c 1 ⁇ ID rom +c 2 ⁇ ID fact +c 3 ⁇ ID cpu +c 4 ⁇ ID oh (2)
  • c 1 , c 2 , c 3 and c 4 are weighting coefficients.
  • the combined unique identification code ID other can be expressed as shown in formula (3):
  • ID other F 2 (ID imei1 , ID imei2 , ID sn , ID sim , ID wlan , ID bt , ID comb ) (3)
  • F 2 is a mapping function, a typical but not limited to this mapping method is shown in formula (4):
  • ID other d 1 ⁇ ID imei1 +d 2 ⁇ ID imei2 +d 3 ⁇ ID sn +d 4 ⁇ ID sim +d 5 ⁇ ID wlan +d 6 ⁇ ID bt +d 7 ⁇ ID comb (4)
  • the utterance frequency may be determined by one or a combination of any of the foregoing several unique identification codes.
  • the electronic device determining the sounding frequency according to the first identification code includes:
  • ID is the first identification code of the electronic device.
  • mapping function F 3 is not specifically limited, as long as the function of the utterance frequency determined by the first identification code should be understood to be within the protection scope of the embodiment of the present application.
  • mapping function for determining the utterance frequency f 0 according to the first identification code (ID) of the electronic device may be as shown in formula (6), namely:
  • ID min is the minimum value of the allowable ID code (generally, all values on each code point are set to 0)
  • ID max is the maximum value of the allowable ID code (generally, all values on each code bit are all set to 9).
  • the electronic device determining the sound frequency according to the first identification code includes:
  • the electronic device reversely replaces the first identification code to obtain a second identification code
  • the electronic device determines the sounding frequency according to the second identification code.
  • the unique identification codes of the same batch of electronic devices are very likely to be close. If the unique identification codes are directly used for frequency mapping, different electronic devices will have a high probability of generating characteristic frequencies with close frequencies, which will cause greater interference and affect Multiple mobile phones are tested at the same time, and the method of reverse replacement can make the identification codes of different electronic devices after replacement have a large difference, which helps ensure that the generated vocalization frequencies differ greatly, thereby helping to reduce mutual interference.
  • the relationship between the second identification code and the utterance frequency is linear or non-linear.
  • the relationship between the second identification code and the utterance frequency is a linear relationship
  • the electronic device obtains the second identification code by reversely replacing the first identification code, and determines the utterance through the second identification code
  • the frequency process is as follows:
  • ID code is reversely replaced, that is, each digit of the ID code from low to high is rearranged into an identification code from high to low, expressed as ID-R.
  • ID-R gfedcba.
  • ID-R min is the minimum value of the allowed ID-R code (generally all the values on each code point are set to 0)
  • ID-R max is the maximum value of the allowed ID-R (generally all the values on each code bit Set to 9).
  • the unique identification code may not be replaced in reverse, but a part of it may be replaced.
  • ID-R may also be abcgfed, abcdgfe, etc. The embodiment does not limit this.
  • the method 200 further includes:
  • the electronic device obtains information on the sound frequency determined by other electronic devices
  • the method further includes:
  • the electronic device raises the utterance frequency by a first frequency threshold or lowers the first frequency threshold.
  • the mapping frequency difference between any two electronic devices should be ensured ⁇ f ⁇ f 0 , where ⁇ f 0 is the frequency resolution threshold.
  • each electronic device helps the electronic device adjust the sound frequency in a timely manner when the sound frequencies of the two electronic devices are similar by acquiring the sound frequencies of other electronic devices. This helps prevent audio interference between multiple electronic devices.
  • the electronic device determining the utterance frequency includes:
  • the electronic device receives the information of the utterance frequency sent by the control device.
  • the electronic device can obtain the audible frequency from other devices.
  • multiple electronic devices can communicate with one control device. When detecting whether the multiple electronic devices are silent, the multiple electronic devices can be controlled by the control device.
  • the utterance frequency of each electronic device in the system is sent to the corresponding electronic device, so that each electronic device determines the sound source data according to different utterance frequencies obtained from the control device.
  • each electronic device can obtain the utterance frequency through the control device, and can also store different utterance frequencies and sound source data corresponding to the different utterance frequencies stored at the device.
  • the control device can directly send all the sound source data to the electronic device, or the control device can send both the utterance frequency and the sound source data determined by the utterance frequency to the electronic device.
  • the electronic device determining the utterance frequency includes:
  • the electronic device detects the first operation of the tester to input the sound frequency
  • the utterance frequency is determined.
  • the tester can manually input the corresponding vocalization frequency on each electronic device, and ensure that the audible frequency between any two electronic devices is greater than a certain threshold.
  • the electronic device After detecting the first operation by the tester to input the utterance frequency, the occurrence frequency can be determined.
  • the method for detecting a probabilistic silent failure in the embodiment of the present application can change the long-term artificial subjective listening detection into an objective detection, instead of judging the audio failure of the mobile phone by the human ear, saving labor costs. It can also be detected in an environment that cannot be monitored manually (under high temperature, high humidity, salt fog, etc.), expanding the detection range.
  • the detection method solves the problem of mutual audio crosstalk between multiple mobile phones, so that multiple mobile phones can detect horns or intermittent silent failures of microphones in parallel, improving detection efficiency.
  • the electronic device determines sound source data according to the utterance frequency.
  • the utterance frequency f 0 corresponding to the electronic device is determined according to the method in S410 above, and the electronic device can generate a frame of sound source data (duration T) according to the utterance frequency f 0 , and the sound source data can be a single-frequency sine harmonic Wave signal, the sine wave frequency is f 0 .
  • the electronic device plays the sound source data through a sound player, and collects audio data when playing the sound source data.
  • the mobile phone 100 can play the sound source data through the speaker 181, and collect audio data when playing the sound source data through the microphone 183A.
  • the audio playback device in the electronic device is adjusted by the program control It is output for the speaker 181 and collected using a microphone 183A close to the speaker 181.
  • a frame of audio data is played during each detection period T, and a frame of audio data is collected using a corresponding microphone (microphone, MIC) for subsequent analysis.
  • the mobile phone 100 can play the sound source data through the receiving microphone 182, and collect the audio data when playing the sound source data through the microphone 183B.
  • the program controls the audio playback in the mobile phone
  • the device is adjusted to be output by the receiver 182 and collected using the microphone 183B close to the receiver 182.
  • One frame of audio data is played during each detection period T, and the corresponding MIC is used to collect one frame of data for subsequent analysis.
  • the electronic device determines that the sound player has a probability of silent failure.
  • the electronic device can process the audio data, and when the processing result of the audio data satisfies the preset condition, the electronic device can determine the sound player's utterance probability to be silent.
  • the method further includes:
  • high-pass filtering refers to passing audio data through a designed high-pass filter to filter out low-frequency signals.
  • the environmental noise below the frequency of 500 Hz is relatively large.
  • the signal directly collected by the microphone contains high-frequency low-frequency environmental noise, which can be passed through a high-pass cut-off frequency of 500 Hz. Filtering helps to filter out low-frequency environmental noise.
  • Windowing refers to multiplying a frame of audio data with a window function (such as Hamming window, Haining window, Blackman window, etc.) in the time domain, and then performing subsequent processing to avoid spectral leakage, that is, The sudden truncation of the signal leads to the phenomenon of increasing frequency components in the frequency domain.
  • a window function such as Hamming window, Haining window, Blackman window, etc.
  • the processing result of the audio data by the electronic device includes but is not limited to one or more of the following:
  • the signal amplitude is obtained after the electronic device performs narrow-band filtering on the audio data in the first frequency range.
  • a method of processing audio data to obtain signal amplitude is as follows: determine the passband frequency range and stopband frequency range of the filter according to the utterance frequency f 0 , design the corresponding passband fluctuation and stopband attenuation values, and then obtain the narrowband filter Filter order and filter coefficients. Input the audio data to the filter, obtain the narrow-band filtered data, and calculate the effective value of the filtered data to finally obtain the signal amplitude.
  • the correlation coefficient is obtained by performing convolution calculation on the audio data and the audio source data.
  • a method of processing audio data to obtain a correlation coefficient is as follows: first obtain the audio data s 1 and the sound source data s 0 , and then reversely replace the sound source data s 0 to obtain data s′ 0 , and s 1 and s ‘ 0 performs the convolution operation and normalizes it to finally obtain the correlation coefficient.
  • the energy of the first sound signal is obtained by performing a fast Fourier transform FFT on the audio data at the sounding frequency, and the first frequency range includes the sounding frequency.
  • a method of processing audio data to obtain the energy of the first sound signal is as follows: First, perform FFT transform on the audio data to obtain the frequency spectrum of the audio data. It is then obtained based on the length and the audio data sampling frequency spectrum corresponding to the index of the audible frequency F 0, and finally obtaining the spectral energy at a frequency f 0 of the utterance based on the spectral index, i.e. the first acoustic energy signal.
  • the electronic device determines that the sound player has a probability of silent failure, including:
  • the electronic device determines that the sound player has a probability of silent failure.
  • the electronic device can perform narrow-band filtering around the utterance frequency f 0. After the filtering is completed, the signal amplitude is calculated. When the sound player utters and does not utter, the signal amplitude will be greatly different. When the calculated signal amplitude When it is less than or equal to the first signal amplitude threshold, the electronic device determines that the sound player has a probability of silent failure.
  • the first signal amplitude threshold is -20dB, and when the detected first signal amplitude is less than or equal to -20dB, the electronic device determines that the sound player has a probability of silent failure.
  • the electronic device determines that the sound player has a probability of silent failure, including:
  • the electronic device determines that the sound player has a probability of silent failure.
  • the first value is 0.2, and when the correlation coefficient determined by the electronic device is less than or equal to 0.2, the electronic device determines that the sound player has a probability of silent failure.
  • the electronic device determines that the sound player has a probability of silent failure, including:
  • the electronic device determines that the sound player has a probability of silent failure
  • the energy of the second sound signal is the average value of the energy of the sound signal corresponding to other frequencies in the second frequency range except the sounding frequency, and the second frequency range includes the sounding frequency.
  • the energy threshold of the first acoustic signal is 15-20dB.
  • the electronic device when determining whether the sound player is probabilistically silent, it can be detected by one or more of the above parameters, for example, according to the combination of the signal amplitude and the correlation coefficient To detect, that is, when the detected signal amplitude is less than or equal to the first signal amplitude threshold and the correlation coefficient is less than the first correlation coefficient threshold, the electronic device determines that the sound player has a probability of silent failure.
  • three dimensions such as the narrow band amplitude near the utterance frequency f 0 after filtering, the correlation coefficient between the collected audio data and the sound source data, and the spectral distribution characteristics near the utterance frequency, are used to detect the utterance, which helps to improve the detection Accuracy, and because the correlation coefficient and the spectral distribution characteristics near the sound frequency are less affected by the difference of devices, for different types of electronic equipment, the structure, sound playback device, and audio recording device are different, and there is no need to target each electronic device.
  • Set different detection thresholds are used to detect the utterance, which helps to improve the detection Accuracy, and because the correlation coefficient and the spectral distribution characteristics near the sound frequency are less affected by the difference of devices, for different types of electronic equipment, the structure, sound playback device, and audio recording device are different, and there is no need to target each electronic device.
  • FIG. 5 shows a schematic flowchart of a method 300 for detecting a probabilistic silent failure provided by an embodiment of the present application.
  • the method 300 uses a mobile phone 100 as an example for illustration.
  • the method 300 includes:
  • the unique identification code of the mobile phone may be one or more combinations of the identification codes in S410.
  • the unique identification code may be mapped to f 0 through a preset mapping function, or the unique identification code may be reversely replaced first to obtain the second identification code, and then the preset mapping function may be used to map the unique identification code to f 0 .
  • f 0 is mapped to a second identification code, or may also be obtained by other means f 0.
  • S330 Generate a frame of sound source data according to f 0 .
  • the sound source data played by the speaker 181 can be collected by the microphone 183A, or the sound source data played by the microphone 182 can be collected by the microphone 183B.
  • S383 Perform FFT on the audio data after high-pass filtering and windowing to obtain the energy of the first acoustic signal.
  • S390 Determine whether the preset detection duration is reached. If the preset detection duration is reached, the detection ends; if the preset detection duration is not reached, continue to return to S330 for detection.
  • the preset detection duration of the mobile phone is 8 hours, and the period of silent detection probability of the mobile phone is 0.1s. After the detection of each cycle is completed, the mobile phone will determine whether the detection duration reaches 8 hours. If the detection duration does not reach 8 hours, return S330 continues the next cycle of detection. If the detection duration reaches 8 hours, the detection ends.
  • FIG. 6 shows another schematic flowchart of a method 400 for detecting a probabilistic silent failure provided by an embodiment of the present application.
  • the method 400 describes in detail the judgment process of judging whether a sound player is probabilistically silent.
  • S410 is the same as S381 and S382 in the above method 300, and for the sake of brevity, details are not described here.
  • the second correlation coefficient threshold is greater than the first correlation coefficient threshold.
  • the two dimensions of the narrow band amplitude near the utterance frequency f 0 after filtering and the correlation coefficient between the collected audio data and the sound source data are used to detect the utterance, which helps to improve the accuracy of the detection.
  • the method 500 includes:
  • S510 is the same as S381 and S383 in the above method 300, and for the sake of brevity, details are not described here.
  • the second correlation coefficient threshold is greater than the first correlation coefficient threshold.
  • the energy of the first acoustic signal and the energy of the second acoustic signal are the same as those described in the foregoing embodiment, and for the sake of brevity, they will not be repeated here.
  • three dimensions such as the correlation coefficient of the collected audio data and the sound source data and the spectral distribution characteristics near the utterance frequency, are used to detect the utterance, which helps to improve the accuracy of the detection.
  • FIG. 8 shows a schematic diagram of detecting multiple mobile phones provided by an embodiment of the present application.
  • the test is performed in a thermostat under high temperature and high humidity.
  • Figure 9 shows the detection results of 5 mobile phones such as mobile phones A, B, C, D, and E during the simultaneous detection of 0 to 120 seconds, and mobile phones A, B, C, D, and E are respectively in the 30th to At 33s, 45-48s, 60-63s, 75-78s, 90-93s, it is artificially silent to simulate device sound failure. Check every 0.1s.
  • the test results are as follows, where a test result of 1 indicates normal vocalization, and a test result of 0 indicates vocalization failure.
  • FIG. 10 shows a schematic block diagram of an apparatus 600 for detecting a silent probability failure according to an embodiment of the present application. As shown in FIG. 10, the apparatus 600 includes:
  • the processing module 610 is configured to determine the utterance frequency corresponding to the electronic device
  • the processing module 610 is also used to generate sound source data according to the utterance frequency
  • the sound playing module 620 is used to play the sound source data
  • the sound collection module 630 is used to collect audio data when playing the sound source data
  • the processing module 610 is also used to process the audio data
  • the processing module 610 When the processing result of the processing module 610 on the audio data satisfies the preset condition, the processing module 610 is also used to determine the probability that the sound player has a silent failure.
  • processing module 610 is specifically used to:
  • the first identification code is an identification code corresponding to the electronic device
  • the utterance frequency is determined.
  • the first identification code is a unique identification code of the electronic device
  • the processing module 610 is specifically configured to:
  • the utterance frequency is determined.
  • the second identification code has a linear or non-linear relationship with the utterance frequency.
  • the second identification code has a linear relationship with the utterance frequency
  • the processing module is specifically used to:
  • ID-R is the second identification code
  • f High is the first utterance frequency threshold
  • f Low is the second utterance frequency threshold
  • ID-R max is the allowed second identification code
  • ID-R min is the minimum value of the allowed second identification code
  • the first utterance frequency threshold is greater than the second utterance frequency threshold.
  • the first identification code is selected from one of the International Mobile Subscriber Identity IMEI code, serial number SN code, user identification SIM code, wireless local area network WLAN MAC address, Bluetooth MAC address or Android pseudo-unique identification code Pseudo-unique ID One or more components.
  • the processing result includes one or more of signal amplitude, correlation coefficient, or energy of the first acoustic signal
  • the signal amplitude is obtained by narrow-band filtering the audio data in the first frequency range
  • the correlation coefficient is the correlation coefficient obtained by convolution calculation of the audio data and the sound source data
  • the energy of the first acoustic signal is Obtained by performing fast Fourier transform FFT on the audio data at the utterance frequency
  • the first frequency range includes the utterance frequency.
  • the processing result includes the correlation coefficient
  • the processing module 610 is specifically configured to:
  • the correlation coefficient is less than or equal to the first value, it is determined that the sound player has a probability of silent failure.
  • the processing result includes the correlation coefficient and the signal amplitude
  • the processing module 610 is specifically configured to:
  • the amplitude of the signal is less than or equal to the third value, it is determined that the sound player has a probability of silent failure.
  • the processing result includes the correlation coefficient and the energy of the first acoustic signal
  • the processing module 610 is specifically configured to:
  • the difference between the energy of the first acoustic signal and the energy of the second acoustic signal is less than or equal to the fourth value, it is determined that the sound player has a probability of silent failure
  • the energy of the second sound signal is the average value of the energy of the sound signal corresponding to other frequencies in the second frequency range except the sounding frequency, and the second frequency range includes the sounding frequency.
  • the processing module 610 is also used to perform high-pass filtering and windowing on the audio data before determining that the sound player has a probability of silent failure.
  • the apparatus 600 may be used to perform the methods of the foregoing method embodiments, such as the methods in FIGS. 4 to 7, and the above and other management operations and/or functions of each module in the apparatus 600
  • the beneficial effects in the foregoing method embodiments can also be achieved. For the sake of brevity, they are not repeated here.
  • each module in the foregoing device 600 may be implemented in the form of software and/or hardware, which is not specifically limited.
  • the device 600 is presented in the form of functional modules.
  • the “module” here may refer to an application-specific integrated circuit ASIC, a circuit, a processor and memory that execute one or more software or firmware programs, an integrated logic circuit, and/or other devices that can provide the above-mentioned functions.
  • the device 600 may adopt the form shown in FIG. 11.
  • the processing module 610 may be implemented by the processor 730 shown in FIG. 11.
  • the processor 730 may also execute the computer program stored in the memory to control the sound player 710 to implement sound playback and control the sound collector 720 to implement sound collection.
  • the functions and/or implementation processes of the transceiver involved in the device 600 may also be implemented through pins or interface circuits.
  • the memory is a storage unit in the chip, such as a register, a cache, etc.
  • the storage unit may also be a storage unit located outside the chip in the computer device, as shown in FIG. 11 740.
  • FIG. 11 shows a schematic structural diagram of an apparatus 700 for detecting a probability silent failure according to an embodiment of the present application.
  • the apparatus 700 includes a sound player 710, a sound collector 720, a memory 730, and a processor 740 Where one or more computer programs are stored in the memory 730, and the one or more computer programs include instructions.
  • the apparatus 700 is caused to perform the following operations:
  • the apparatus 700 specifically executes the following steps:
  • the first identification code is an identification code corresponding to the electronic device
  • the utterance frequency is determined.
  • the first identification code is a unique identification code of the electronic device, and when the instruction is executed by the processor 730, the apparatus 700 specifically executes the following steps:
  • the utterance frequency is determined.
  • the second identification code has a linear or non-linear relationship with the utterance frequency.
  • the second identification code has a linear relationship with the utterance frequency, where when the instruction is executed by the processor 730, the device 700 specifically executes the following steps:
  • ID-R is the second identification code
  • f High is the first utterance frequency threshold
  • f Low is the second utterance frequency threshold
  • ID-R max is the allowed second identification code
  • ID-R min is the minimum value of the allowed second identification code
  • the first utterance frequency threshold is greater than the second utterance frequency threshold.
  • the first identification code is selected from one of the International Mobile Subscriber Identity IMEI code, serial number SN code, user identification SIM code, wireless local area network WLAN MAC address, Bluetooth MAC address or Android pseudo-unique identification code Pseudo-unique ID One or more components.
  • the processing result includes one or more of signal amplitude, correlation coefficient, or energy of the first acoustic signal
  • the signal amplitude is obtained by narrow-band filtering the audio data in the first frequency range
  • the correlation coefficient is the correlation coefficient obtained by convolution calculation of the audio data and the sound source data
  • the energy of the first acoustic signal is Obtained by performing fast Fourier transform FFT on the audio data at the utterance frequency
  • the first frequency range includes the utterance frequency.
  • the processing result includes the correlation coefficient.
  • the apparatus 700 specifically executes the following steps:
  • the correlation coefficient is less than or equal to the first value, it is determined that the sound player has a probability of silent failure.
  • the processing result includes the correlation coefficient and the signal amplitude.
  • the device 700 specifically executes the following steps:
  • the amplitude of the signal is less than or equal to the third value, it is determined that the sound player has a probability of silent failure.
  • the processing result includes the correlation coefficient and the energy of the first acoustic signal.
  • the device 700 specifically executes the following steps:
  • the difference between the energy of the first acoustic signal and the energy of the second acoustic signal is less than or equal to the fourth value, it is determined that the sound player has a probability of silent failure
  • the energy of the second sound signal is the average value of the energy of the sound signal corresponding to other frequencies in the second frequency range except the sounding frequency, and the second frequency range includes the sounding frequency.
  • the apparatus 700 specifically executes the following steps:
  • the foregoing apparatus 600 or apparatus 700 may be a terminal device.
  • the device 700 may correspond to the mobile phone 100 in FIG. 1
  • the processor 730 may correspond to the processor 130 in FIG. 1
  • the memory 140 may correspond to the memory 140 in FIG. 1
  • the sound player 710 may correspond to FIG.
  • the sound collector may correspond to the microphone 183 in FIG.
  • the processor may be an integrated circuit chip with signal processing capabilities.
  • each step of the foregoing method embodiment may be completed by an integrated logic circuit of hardware in a processor or instructions in the form of software.
  • the aforementioned processor may be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), an existing programmable gate array (FPGA), or other available Programming logic devices, discrete gates or transistor logic devices, discrete hardware components.
  • DSP digital signal processor
  • ASIC application specific integrated circuit
  • FPGA existing programmable gate array
  • the general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
  • the steps of the method disclosed in conjunction with the embodiments of the present application may be directly embodied and executed by a hardware decoding processor, or may be executed and completed by a combination of hardware and software modules in the decoding processor.
  • the software module may be located in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, and registers.
  • the storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.
  • the memory in the embodiments of the present application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.
  • the non-volatile memory can be read-only memory (read-only memory, ROM), programmable read-only memory (programmable ROM, PROM), erasable programmable read-only memory (erasable PROM, EPROM), electronically Erasable programmable read-only memory (electrically EPROM, EEPROM) or flash memory.
  • the volatile memory may be a random access memory (random access memory, RAM), which is used as an external cache.
  • RAM random access memory
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • synchronous RAM synchronous dynamic random access memory
  • SDRAM double data rate synchronous dynamic random access memory
  • double data SDRAM double data SDRAM
  • DDR SDRAM enhanced synchronous dynamic random access memory
  • ESDRAM synchronous connection dynamic random access memory
  • direct RAMbus RAM direct RAMbus RAM
  • system and “network” are often used interchangeably herein.
  • the term “and/or” in this article is just an association relationship that describes an associated object, indicating that there can be three relationships, for example, A and/or B, which can mean: A exists alone, A and B exist at the same time, exist alone B these three cases.
  • the character "/" in this article generally indicates that the related objects before and after are in an "or” relationship.
  • B corresponding to A means that B is associated with A, and B can be determined according to A.
  • determining B based on A does not mean determining B based on A alone, and B may also be determined based on A and/or other information.
  • the computer program product may include one or more computer instructions.
  • the computer may be a general-purpose computer, a dedicated computer, a computer network, or other programmable devices.
  • the computer instructions may be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be from a website site, computer, server or data center Transmission to another website, computer, server or data center via wired (such as coaxial cable, optical fiber, digital subscriber (DSL)) or wireless (such as infrared, wireless, microwave, etc.).
  • the computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device including a server, a data center, and the like integrated with one or more available media.
  • the usable medium may be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic disk), an optical medium (for example, a DVD), or a semiconductor medium (for example, solid state disk (SSD)) or the like.
  • the disclosed system, device, and method may be implemented in other ways.
  • the device embodiments described above are only schematic.
  • the division of the units is only a division of logical functions.
  • there may be other divisions for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.
  • the technical solution of the present application essentially or part of the contribution to the existing technology or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to enable a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (random access memory, RAM), magnetic disk or optical disk and other media that can store program codes .

Abstract

本申请提供了一种检测概率无声故障的方法和装置，其中，该检测概率无声故障的方法包括：电子设备确定该电子设备对应的发声频率；根据该发声频率，生成音源数据；通过该声音播放器播放该音源数据，并采集播放该音源数据时的音频数据；当该电子设备对该音频数据的处理结果满足预设条件时，确定该声音播放器发生概率无声故障。本申请实施例的检测概率无声故障的方法，有助于实现多台电子设备的自动化检测。

Description

一种检测概率无声故障的方法和装置 技术领域
本申请涉及电子设备领域，并且更具体地，涉及一种检测概率无声故障的方法和装置。
背景技术
外放喇叭和受话器是手机进行音乐播放和通话的重要器件，在手机播放音乐时内置芯片对音频文件进行解码并通过音频通路传递给功率放大器，放大后的音频信号再传输到外放喇叭进行音乐播放。通常情况下，手机喇叭的引线通过弹片连接到功率放大器上实现通路。对于手机受话器来说，与喇叭的连接类似，通常情况下也为弹片接触连接。通过这样的弹片电连接结构，可以实现手机音乐播放或通话过程中喇叭与受话器正常接收到音乐信号与通话语音信号并进行播放。
当喇叭或听筒的音频通路上电连接弹片接触不良时，音频通路会间歇性中断，导致手机喇叭或听筒概率或间歇无声故障。该概率无声故障有可能在很长时间的音乐播放或通话过程中才出现短暂的时刻，或者在手机运动状态下(例如手机跌落后短时间内、手持手机跑步时)出现的间歇无声概率更大一些。另外，当音频硬件通路上任何一个节点出现断路故障时也都会产生听筒或喇叭无声的故障。手机出现无声问题会严重影响用户主观听音感受，因此在手机研发阶段会针对该潜在问题进行重点测试与拦截。
目前针对概率无声的问题缺乏有效的检测手段，一种检测概率无声故障的方法是让手机通过喇叭或听筒播放音源，测试人员全程听音并记录整个测试时间长度内是否出现概率无声。同时由于概率无声检测需要播放很长时间音源(几小时)，在很长时间内均需要测试人员全程参与，因此该种人工检测方法效率低，一天可能只能检测几台手机，非常耗费人力资源。另一方面，在测试时为了激发概率无声故障以方便检测与拦截，手机需要在极端环境下进行测试，例如在滚筒、微跌、高温高湿(温箱内)以及盐雾环境下进行实时检测，此时人工将无法或很难检测。
发明内容
有鉴于此，本申请提供一种检测概率无声故障的方法和装置，有助于实现自动化检测概率无声。
第一方面，提供了一种检测概率无声故障的方法，应用于电子设备，该电子设备包括声音播放器，该方法包括：该电子设备确定该电子设备对应的发声频率；该电子设备根据该发声频率，生成音源数据；该电子设备通过该声音播放器播放该音源数据，并采集播放该音源数据时的音频数据；当该电子设备对该音频数据的处理结果满足预设条件时，该电子设备确定该声音播放器发生概率无声故障。
本申请实施例中的检测概率无声故障的方法，电子设备通过确定的发声频率生成音源数据，并通过采集到的音频数据来判断该电子设备是否概率无声，可将长时间的人工主观 听音检测变为客观检测，代替人耳判断手机概率无声故障，有助于实现电子设备自动化检测概率无声。
在一些可能的实现方式中，该电子设备确定该电子设备对应的发声频率，包括：该电子设备获取该发声频率。例如，当多台电子设备进行概率无声测试时，可以由控制设备向多台电子设备中每台电子设备发送该发声频率(或者，直接发送音源数据)；或者，该电子设备在检测到测试人员输入发声频率的操作后，响应于该操作，确定该电子设备对应的发声频率。
在一些可能的实现方式中，该声音播放器为喇叭或者受话筒。
本申请实施例中的检测概率无声故障的方法，在多台电子设备进行概率无声检测时，每台电子设备可以分别确定对应于自己的发声频率，并由该发声频率生成音源数据进行播放，由于每台电子设备播放的音源数据所对应的发声频率不同，有助于避免不同电子设备之间的相互干扰，从而有助于实现多台电子设备的自动化检测。
结合第一方面，在第一方面的某些实现方式中，该电子设备确定该电子设备对应的发声频率，包括：该电子设备获取第一标识码，该第一标识码为该电子设备对应的标识码；该电子设备根据该第一标识码，确定该发声频率。
本申请实施例中的检测概率无声故障的方法，电子设备通过标识码来确定发声频率，并由该发声频率生成音源数据进行播放，由于每台电子设备播放的音源数据所对应的发声频率不同，有助于避免不同电子设备之间的相互干扰，从而有助于实现多台电子设备的自动化检测。
结合第一方面，在第一方面的某些实现方式中，该第一标识码为该电子设备的唯一标识码，该根据该第一标识码，确定该发声频率，包括：该电子设备将该唯一标识码反向置换，得到第二标识码；该电子设备根据该第二标识码，确定该发声频率。
在一些可能的实现方式中，该电子设备可以将该电子设备的唯一标识码按照预定义规则置换，并根据置换后的标识码确定该发声频率。
本申请实施例的检测概率无声故障的方法，对于同一批次的电子设备而言，唯一标识码有可能很接近，使用反向置换的方法有助于进一步降低不同电子设备之间的相互干扰。
结合第一方面，在第一方面的某些实现方式中，该第二标识码与该发声频率为线性或者非线性关系。
结合第一方面，在第一方面的某些实现方式中，该第二标识码与该发声频率为线性关系，其中，该根据该第二标识码，确定该发声频率，包括：该电子设备根据以下公式确定该发声频率：
Figure PCTCN2018117933-appb-000001
其中，f 0为该发声频率，ID-R为该第二标识码，f High为第一发声频率阈值，f Low为第二发声频率阈值，ID-R max为允许的该第二标识码的最大值，ID-R min为允许的该第二标识码的最小值，该第一发声频率阈值大于该第二发声频率阈值。
结合第一方面，在第一方面的某些实现方式中，该第一标识码由国际移动用户标识IMEI码、序列号SN码、用户身份识别SIM码、无线局域网WLAN MAC地址、蓝牙MAC地址或者安卓伪唯一标识码Pseudo-unique ID中的一种或者多种组成。
本申请实施例的检测概率无声故障的方法，通过电子设备的唯一标识码确定对应的发 声频率，有助于实现多台电子设备的自动化检测。
结合第一方面，在第一方面的某些实现方式中，该处理结果包括信号幅度、相关系数或者第一声信号能量中的一种或者多种；其中，该信号幅度为在第一频率范围内对该音频数据进行窄带滤波后获得，该相关系数为该音频数据和该音源数据进行卷积计算而获得的相关系数，该第一声信号能量为在该发声频率处对该音频数据进行快速傅里叶变换(fast Fourier transform，FFT)获得的，该第一频率范围包括该发声频率。
在一些可能的实现方式中，该电子设备在检测声音播放器是否概率无声时可以采用上述几种维度中的一种或者任几种。
本申请实施例中，采用滤波后发声频率f 0附近窄带幅度、采集到的音频数据与音源数据的相关系数、发声频率附近频谱分布特性等维度对发声情况进行检测，有助于提高检测的准确度。
结合第一方面，在第一方面的某些实现方式中，该处理结果包括该相关系数，该当该电子设备对该音频数据的处理结果满足预设条件时，该电子设备确定该声音播放器发生概率无声故障，包括：在该相关系数小于或者等于第一数值的情况下，确定该声音播放器发生概率无声故障。
结合第一方面，在第一方面的某些实现方式中，该处理结果包括该相关系数和该信号幅度，该当该电子设备对该音频数据的处理结果满足预设条件时，该电子设备确定该声音播放器发生概率无声故障，包括：该电子设备确定该相关系数大于或者等于第一数值，并且小于或者等于第二数值；在该信号幅度小于或者等于第三数值的情况下，该电子设备确定该声音播放器发生概率无声故障。
本申请实施例中，采用滤波后发声频率f 0附近窄带幅度、采集到的音频数据与音源数据的相关系数这两个维度对发声情况进行检测，有助于提高检测的准确度。
结合第一方面，在第一方面的某些实现方式中，该处理结果包括该相关系数和该第一声信号能量，该当该电子设备对该音频数据的处理结果满足预设条件时，该电子设备确定该声音播放器发生概率无声故障，包括：该电子设备确定该相关系数大于或者等于第一数值，并且小于或者等于第二数值；在该第一声信号能量与第二声信号能量的差值小于或者等于第四数值的情况下，该电子设备确定该声音播放器发生概率无声故障；其中，该第二声信号能量为第二频率范围内除该发声频率以外的其他频率对应的声信号能量的平均值，该第二频率范围包括该发声频率。
本申请实施例中，采用滤波后采集到的音频数据与音源数据的相关系数、发声频率附近频谱分布特性这两个维度对发声情况进行检测，有助于提高检测的准确度。
同时，由于相关系数与发声频率附近频谱分布特性受器件差异影响较小，因此对于不同型号电子设备，其结构形式、声音播放器件、音频录制器件不同，不需要针对每台电子设备设定不同的检测门限。
结合第一方面，在第一方面的某些实现方式中，该电子设备确定该声音播放器发生概率无声故障之前，该方法还包括：该电子设备对该音频数据进行高通滤波和加窗。
本申请实施例的检测概率无声故障的方法，通过对采集到的音频数据进行高通滤波，有助于滤除低频环境噪声；通过对采集到的音频数据进行加窗处理，有助于防止频谱泄露。
第二方面，本技术方案提供了一种检测概率无声故障的装置，该装置包含在电子设备 中，该装置具有实现上述方面及上述方面的可能实现方式中电子设备行为的功能。功能可以通过硬件实现，也可以通过硬件执行相应的软件实现。硬件或软件包括一个或多个与上述功能相对应的模块或单元。
第三方面，本技术方案提供了一种电子设备，包括：声音播放器；声音采集器；一个或多个处理器；存储器；多个应用程序；以及一个或多个计算机程序。其中，一个或多个计算机程序被存储在存储器中，一个或多个计算机程序包括指令。当指令被电子设备执行时，使得电子设备执行上述任一方面任一项可能的实现中的检测概率无声故障的方法。
第四方面，本技术方案提供了一种电子设备，包括一个或多个处理器和一个或多个存储器。该一个或多个存储器与一个或多个处理器耦合，一个或多个存储器用于存储计算机程序代码，计算机程序代码包括计算机指令，当一个或多个处理器执行计算机指令时，使得电子设备执行上述任一方面任一项可能的实现中的检测概率无声故障的方法。
第五方面，本技术方案提供了一种计算机存储介质，包括计算机指令，当计算机指令在电子设备上运行时，使得电子设备执行上述任一方面任一项可能的实现中的检测概率无声故障的方法。
第六方面，本技术方案提供了一种计算机程序产品，当计算机程序产品在电子设备上运行时，使得电子设备执行上述任一方面任一项可能的设计中的检测概率无声故障的方法。
本申请实施例中的检测概率无声故障的方法和装置，在多台电子设备进行概率无声检测时，每台电子设备可以分别确定对应于自己的发声频率，并由该发声频率生成音源数据进行播放，将长时间的人工主观听音检测变为客观检测，代替人耳判断手机音频故障，节省劳动力成本。在人工无法监听的环境下(高温高湿、盐雾等环境下)也可以实现检测，扩展了检测范围。同时，由于每台电子设备播放的音源数据所对应的发声频率不同，有助于避免不同电子设备之间的相互干扰。
附图说明
图1是本申请实施例提供的手机的示意性结构图。
图2是本申请实施例提供的手机的另一示意性结构图。
图3是本申请实施例提供的手机的另一示意性结构图。
图4是本申请实施例提供的检测概率无声故障的方法的示意性流程图。
图5是本申请实施例提供的检测概率无声故障的方法的另一示意性流程图。
图6是本申请实施例提供的检测概率无声故障的方法的另一示意性流程图。
图7是本申请实施例提供的检测概率无声故障的方法的另一示意性流程图。
图8是本申请实施例提供的对多台手机进行检测的示意图。
图9是本申请实施例提供的对多台手机的检测结果的示意图。
图10是本申请实施例提供的检测概率无声故障的装置的示意性框图。
图11是本申请实施例提供的检测概率无声故障的装置的另一示意性框图。
具体实施方式
下面将结合附图，对本申请中的技术方案进行描述。
本申请实施例的技术方案可以应用于所有包括声音播放器和麦克风的装置或设备，例如，该电子设备的声音播放器可以包括受话筒(receiver，RCV)或者喇叭(speaker，SPK)，本申请实施例对此不作限定。也就是说，涉及到检测声音播放器概率无声的使用场景，无需人工进行检测，均可以应用本申请实施例的检测概率无声故障的方法。为了便于描述，本申请实施例仅以终端设备为例进行描述，但并不对本申请实施例的保护范围构成限定。
本申请实施例的技术方案可以应用于终端设备，终端设备可以是但不限于移动台(mobile station，MS)、移动终端(mobile terminal)、移动电话(mobile telephone)、手机(handset)及便携设备(portable equipment)等，可以经无线接入网(例如，radio access network，RAN)与一个或多个核心网进行通信。本申请实施例中的终端可以指终端(terminal)、用户设备、接入终端、用户单元、用户站、移动站、移动台、远方站、远程终端、移动设备、用户终端、终端、无线通信设备、用户代理或用户装置。终端设备还可以是蜂窝电话、无绳电话、会话启动协议(session initiation protocol，SIP)电话、无线本地环路(wireless local loop，WLL)站、个人数字助理(personal digital assistant，PDA)、具有无线通信功能的手持设备、计算设备或连接到无线调制解调器的其它处理设备、车载设备、可穿戴设备，未来5G网络中的终端设备或者未来演进的公用陆地移动通信网络(public land mobile network，PLMN)中的终端设备等，本申请实施例对此并不限定。
在本申请实施例中，终端设备包括硬件层、运行在硬件层之上的操作系统层，以及运行在操作系统层上的应用层。该硬件层包括中央处理器(central processing unit，CPU)、内存管理单元(memory management unit，MMU)和内存(也称为主存)等硬件。该操作系统可以是任意一种或多种通过进程(process)实现业务处理的计算机操作系统，例如，Linux操作系统、Unix操作系统、Android操作系统、iOS操作系统或windows操作系统等。该应用层包含浏览器、通讯录、文字处理软件、即时通信软件等应用。并且，本申请实施例并未对本申请实施例提供的方法的执行主体的具体结构特别限定，只要能够通过运行记录有本申请实施例的提供的方法的代码的程序，以根据本申请实施例提供的方法进行通信即可，例如，本申请实施例提供的方法的执行主体可以是终端设备，或者，是终端设备中能够调用程序并执行程序的功能模块。
另外，本申请的各个方面或特征可以是现成方法、装置或使用标准编程和/或工程技术的制品。本申请中使用的术语“制品”涵盖可从任何计算机可读器件、载体或介质访问的计算机程序。例如，计算机可读介质可以包括，但不限于:磁存储器件(例如，硬盘、软盘或磁带等)，光盘(例如，压缩盘(compact disc，CD)、数字通用盘(digital versatile disc，DVD)等)，智能卡和闪存器件(例如，可擦写可编程只读存储器(erasable programmable read-only memory，EPROM)、卡、棒或钥匙驱动器等)。另外，本文描述的各种存储介质可代表用于存储信息的一个或多个设备和/或其它机器可读介质。术语“机器可读介质”可包括但不限于，无线信道和能够存储、包含和/或承载指令和/或数据的各种其它介质。
下面结合图1对手机100的各个构成部件进行具体的介绍：
RF电路110可用于收发信息或通话过程中，信号的接收和发送，特别地，将基站的下行信息接收后，给处理器130处理；另外，将设计上行的数据发送给基站。通常，RF电路包括但不限于天线、至少一个放大器、收发信机、耦合器、低噪声放大器(Low Noise Amplifier，LNA)、双工器等。此外，RF电路110还可以通过无线通信与网络和其他设 备通信。所述无线通信可以使用任一通信标准或协议，包括但不限于全球移动通讯系统(global system of mobile communication，GSM)、通用分组无线服务(general packet radio service，GPRS)、码分多址(code division multiple access，CDMA)、宽带码分多址(wideband code division multiple access，WCDMA)、长期演进(long term evolution，LTE)、电子邮件、短消息服务(short messaging service，SMS)等。
存储器140可用于存储软件程序以及模块，处理器130通过运行存储在存储器140的软件程序以及模块，从而执行手机100的各种功能应用以及数据处理。存储器140可主要包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的应用程序(比如声音播放功能、图像播放功能等)等；存储数据区可存储根据手机100的使用所创建的数据(比如音频数据、电话本等)等。此外，存储器140可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他易失性固态存储器件。
输入单元150可用于接收输入的数字或字符信息，以及产生与手机100的用户设置以及功能控制有关的键信号输入。具体地，输入单元150可包括触控面板151以及其他输入设备152。触控面板151，也称为触摸屏，可收集用户在其上或附近的触摸操作(比如用户使用手指、触笔等任何适合的物体或附件在触控面板151上或在触控面板151附近的操作)，并根据预先设定的程式驱动相应的连接装置。可选地，触控面板151可包括触摸检测装置和触摸控制器两个部分。其中，触摸检测装置检测用户的触摸方位，并检测触摸操作带来的信号，将信号传送给触摸控制器；触摸控制器从触摸检测装置上接收触摸信息，并将它转换成触点坐标，再送给处理器130，并能接收处理器130发来的命令并加以执行。此外，可以采用电阻式、电容式、红外线以及表面声波等多种类型实现触控面板151。除了触控面板151，输入单元150还可以包括其他输入设备152。具体地，其他输入设备152可以包括但不限于物理键盘、功能键(比如音量控制按键、开关按键等)、轨迹球、鼠标、操作杆等中的一种或多种。
显示单元160可用于显示由用户输入的信息或提供给用户的信息以及手机100的各种菜单。显示单元160可包括显示面板161，可选地，可以采用LCD、OLED等形式来配置显示面板161。进一步地，触控面板151可覆盖显示面板161，当触控面板151检测到在其上或附近的触摸操作后，传送给处理器130以确定触摸事件的类型，随后处理器130根据触摸事件的类型在显示面板161上提供相应的视觉输出。虽然在图2中，触控面板151与显示面板151是作为两个独立的部件来实现手机100的输入和输入功能，但是在某些实施例中，可以将触控面板151与显示面板161集成而实现手机100的输入和输出功能。
手机100还可包括至少一种传感器170，比如光传感器、运动传感器以及其他传感器。具体地，光传感器可包括环境光传感器及接近传感器，其中，环境光传感器可根据环境光线的明暗来调节显示面板161的亮度，接近传感器可在手机100移动到耳边时，关闭显示面板161和/或背光。作为运动传感器的一种，加速计传感器可检测各个方向上(一般为三轴)加速度的大小，静止时可检测出重力的大小及方向，可用于识别手机姿态的应用(比如横竖屏切换、相关游戏、磁力计姿态校准)、振动识别相关功能(比如计步器、敲击)等；至于手机100还可配置的陀螺仪、气压计、湿度计、温度计、红外线传感器等其他传感器，在此不再赘述。
音频电路180用于将数字音频信息转换成模拟音频信号输出，也用于将模拟音频输入转换为数字音频信号。音频电路180还可以用于对音频信号编码和解码。在一些实施例中，音频电路180可以设置于处理器110中，或将音频电路180的部分功能模块设置于处理器110中。
喇叭181，也称“扬声器”，用于将音频电信号转换为声音信号。手机100可以通过扬声器181进行音乐播放，或进行免提通话声音播放。
受话筒182，也称“听筒”，用于将音频电信号转换成声音信号。当手机100接听电话或语音信息时，可以通过将受话筒182靠近人耳接听语音。
麦克风183，也称“话筒”，“传声器”，用于将声音信号转换为电信号。当拨打电话或发送语音信息时，用户可以通过人嘴靠近麦克风183发声，将声音信号输入到麦克风183。手机100可以设置至少一个麦克风183。
本申请实施例中，电子设备在生成音源数据后，可以通过喇叭或者受话筒播放该音源数据，并通过相应的麦克风183来采集音频数据，通过对比分析音源数据和采集到的音频数据，来确定喇叭或者受话筒是否概率无声。
一种可能的实现方式是，图2示出了手机100的另一结构示意图，其中，主要示出了手机100中喇叭181和麦克风183A的位置关系，如图2所示，喇叭181和麦克风183A相邻，分别为位于手机100底部数据接口的左侧和右侧，当手机100生成音源数据后，可以通过喇叭181播放该音源数据，并通过麦克风183A采集播放该音源数据时的音频数据，处理器130可以对音源数据和音频数据进行分析后，确定该手机100的喇叭181是否概率无声。
另一种可能的实现方式是，图3示出了手机100的另一结构示意图，其中，主要示出了手机100中受话筒182和麦克风183B的位置关系，如图3所示，受话筒182和麦克风183B相邻，分别为位于手机100的上部，当手机100生成音源数据后，可以通过受话筒182播放该音源数据，并通过麦克风183B采集播放该音源数据时的音频数据，处理器130可以对音源数据和音频数据进行分析后，确定该手机100的受话筒182是否概率无声。
应理解，对于喇叭181和受话筒182可以分开进行检测。
还应理解，对于喇叭181，可以为麦克风183A检测喇叭181播放的音源数据，也可以是麦克风183B检测喇叭181播放的音源数据；对于受话筒182，可以为麦克风183B检测受话筒182播放的音源数据，也可以是麦克风183B检测受话筒182播放的音源数据；还可以是，喇叭181和受话筒182所播放的音源数据不由麦克风检测，而是由其他设备进行检测。本申请实施例对此并不作任何限定。
还应理解，麦克风183A可以为手机100的主麦克风，麦克风183B可以为手机100的辅麦克风。
还应理解，在另一些实施例中，手机100还可以设置三个，四个或更多麦克风183，实现采集声音信号，降噪，还可以识别声音来源，实现定向录音功能等。
WiFi属于短距离无线传输技术，手机100通过WiFi模块190可以帮助用户收发电子邮件、浏览网页和访问流式媒体等，它为用户提供了无线的宽带互联网访问。虽然图2示出了WiFi模块190，但是可以理解的是，其并不属于手机100的必须构成，完全可以根据需要在不改变发明的本质的范围内而省略。
处理器130是手机100的控制中心，利用各种接口和线路连接整个手机的各个部分，通过运行或执行存储在存储器140内的软件程序和/或模块，以及调用存储在存储器140内的数据，执行手机100的各种功能和处理数据，从而实现基于手机的多种业务。可选地，处理器130可包括一个或多个处理单元；优选的，处理器130可集成应用处理器和调制解调处理器，其中，应用处理器主要处理操作系统、用户界面和应用程序等，调制解调处理器主要处理无线通信。可以理解的是，上述调制解调处理器也可以不集成到处理器130中。
本申请实施例中主要涉及喇叭181、受话筒182、麦克风183、处理器130等手机100内置物理元器件。其中喇叭181或者受话筒182用以音源数据的播放，麦克风183用以录制音频数据，处理器用以对录制的音频数据进行算法分析并判定喇叭181或者受话筒182是否发生概率无声故障。
手机100还包括给各个部件供电的电源120(比如电池)，优选的，电源可以通过电源管理系统与处理器130逻辑相连，从而通过电源管理系统实现管理充电、放电、以及功耗等功能。
尽管未示出，手机100还可以包括摄像头、蓝牙模块等。
图4示出了本申请实施例提供的检测概率无声故障的方法200的示意性流程图，如图4所示，该方法200包括：
S210，电子设备确定发声频率，该发声频率为该电子设备对应的发声频率。
具体而言，当有多台电子设备需要进行概率无声检测时，针对每一台电子设备，可以由该电子设备自己确定自己唯一的发声频率，也可以由电子设备从外部获取到发声频率的信息，从而实现每台电子设备所确定的发声频率不同。
可选地，该电子设备确定发声频率，包括：
该电子设备通过本地保存的信息，确定发声频率。
可选地，该本地保存的信息包括电子设备的第一标识码ID，该电子设备根据该第一标识码ID，确定该发声频率。
可选地，电子设备可以保存有ID的信息，该ID包括但不限于：
(1)国际移动用户标识(international mobile equipment identity，IMEI)码，包括IMEI1码(ID imei1)与IMEI 2码(ID imei2)；
(2)序列号(serial number，SN)码(ID sn)；
(3)用户身份识别(subscriber identification module，SIM)卡卡号(ID sim)；
(4)WLAN MAC地址(ID wlan)；
(5)蓝牙MAC地址(ID bt)；
(6)由设备的ROM版本号(ID rom)、厂商名(ID fact)、CPU型号(ID cpu)和其他硬件(ID oh)信息来组合而成的唯一标识码(ID comb)；该组合唯一识别码ID comb可以表示为公式(1)所示：
ID comb＝F 1(ID rom,ID fact,ID cpu,ID oh)            (1)
其中，F 1为映射函数，一种典型的但不仅限于此的映射方法如公式(2)所示：
ID comb＝c 1×ID rom+c 2×ID fact+c 3×ID cpu+c 4×ID oh          (2)
其中、c 1、c 2、c 3与c 4为加权系数。
(7)由以上6种任意组合而成的唯一标识码ID other。
该组合唯一识别码ID other可以表示为公式(3)所示：
ID other＝F 2(ID imei1,ID imei2,ID sn,ID sim,ID wlan,ID bt,ID comb)         (3)
其中，F 2为映射函数，一种典型的但不仅限于此的映射方法如公式(4)所示：
ID other＝d 1×ID imei1+d 2×ID imei2+d 3×ID sn+d 4×ID sim+d 5×ID wlan+d 6×ID bt+d 7×ID comb   (4)
其中，d i(i＝1,2,...,7)为加权系数。
本申请实施例中，可以通过上述几种唯一标识码的一种或者任几种的组合来确定该发声频率。
可选地，该电子设备根据该第一标识码，确定该发声频率，包括：
根据以下公式确定该发声频率：
f 0＝F 3(ID)              (5)
其中，ID为该电子设备的第一标识码，电子设备的第一标识码(ID)确定后，根据该唯一标识码生成发声频率f 0＝F 3(ID)，其中F 3为将ID映射为f 0的映射函数。
应理解，本申请实施例中，对映射函数F 3并不作具体限定，只要是通过第一标识码确定的发声频率的函数都应理解为在本申请实施例的保护范围之内。
例如，一个可能的实现方式中，根据电子设备第一标识码(ID)确定发声频率f 0的映射函数可以如公式(6)所示，即：
Figure PCTCN2018117933-appb-000002
其中，ID min为允许的ID码最小值(一般各码位上的值全部设为0)，ID max为允许的ID码最大值(一般各码位上的值全部设为9)。可选地，该电子设备根据第一标识码，确定发声频率，包括：
该电子设备将该第一标识码反向置换，得到第二标识码；
该电子设备根据该第二标识码，确定该发声频率。
一般来说，同一批次的电子设备很大概率唯一标识码很接近，如果直接采用唯一标识码进行频率映射的话，不同的电子设备将大概率产生频率接近的特征频率，则干扰较大，影响多台手机进行同时检测，使用反向置换的方法，可以使得不同的电子设备置换后的标识码相差较大，有助于保证生成的发声频率相差较大，从而有助于降低相互干扰。
可选地，该第二标识码与该发声频率的关系为线性或者非线性。
在一种可能的实现方式中，该第二标识码和该发声频率的关系为线性关系，该电子设备通过将第一标识码反向置换得到第二标识码，并通过第二标识码确定发声频率的过程如下：
(1)将ID码进行反向置换，即将ID码由低位到高位的每一位数字重新排列成由高位到低位的标识码，表示为ID-R。
例如，若ID＝abcdefg，则ID-R＝gfedcba。
(2)根据电子设备的工作噪声环境，设定发声特征频率的下限f Low及上限f High，则电子设备的发声频率f 0可以按公式(7)进行计算，即：
Figure PCTCN2018117933-appb-000003
其中，ID-R min为允许的ID-R码最小值(一般各码位上的值全部设为0)，ID-R max为允许的ID-R最大值(一般各码位上的值全部设为9)。
应理解，本申请实施例中，对于唯一标识码也可以不进行反向置换，而是选择置换其中的部分，例如，ID＝abcdefg时，ID-R还可以为abcgfed、abcdgfe等等，本申请实施例对此不作任何限定。
可选地，该方法200还包括：
该电子设备获取其他电子设备确定的发声频率的信息；
其中，若该电子设备确定的发声频率与其他电子设备中任意一台电子设备确定的发声频率差值的绝对值小于或者等于第一频率阈值，该方法还包括：
该电子设备将该发声频率上调第一频率阈值或者下调第一频率阈值。
例如，预设的检测周期为T，则音频数据频域内频谱分辨率为1/T。为保证多台电子设备同时检测时不产生较大的相互干扰，应保证任意两台电子设备之间的映射频率差Δf≥Δf 0，其中，Δf 0为频率分辨阈值。
可选地，频率分辨阈值可以为Δf 0＝3×1/T。若两台电子设备映射后发声频率较接近，其频率差小于阈值Δf 0，则可以对其中一台电子设备进行频率微调整，频率偏小的电子设备的发声频率下移Δf 0或频率偏大的电子设备上移频率Δf 0。
本申请实施例提供的检测概率无声故障的方法，每台电子设备通过获取其他电子设备的发声频率，在两台电子设备的发声频率相近的情况下，有助于电子设备及时调整发声频率，，从而有助于防止多个电子设备之间的音频干扰。
可选地，该电子设备确定发声频率，包括：
在多个电子设备都与控制设备通信的情况下，电子设备接收该控制设备发送的发声频率的信息。
例如，该电子设备可以从其他设备处获取该发声频率，例如，多台电子设备可以和一个控制设备通信，在检测该多台电子设备是否概率无声时，可以通过控制设备将该多个电子设备中每一台电子设备的发声频率发送给对应的电子设备，从而使得每一台电子设备根据从控制设备处获得的不同的发声频率，确定音源数据。
应理解，本申请实施例中，每台电子设备可以通过控制设备获取发声频率，还可以控制设备处保存有不同的发声频率以及不同发声频率所对应的音源数据，当多台电子设备需要进行检测概率无声故障时，控制设备可以直接将音源数据都发送给电子设备，或者，控制设备可以将发声频率和由该发声频率确定的音源数据都发送给电子设备。
可选地，该电子设备确定发声频率，包括：
该电子设备检测到测试人员输入发声频率的第一操作；
响应于该第一操作，确定该发声频率。
例如，多台电子设备在测试概率无声之前，可以由测试人员手动在每一台电子设备上输入对应的发声频率，并保证任意两台电子设备之间的发声频率大于一定的阈值，该电子设备在检测到测试人员输入发声频率的第一操作后，可以确定该发生频率。
本申请实施例的检测概率无声故障的方法，可将长时间的人工主观听音检测变为客观检测，代替人耳判断手机音频故障，节省劳动力成本。在人工无法监听的环境下(高温高湿、盐雾等环境下)也可以实现检测，扩展了检测范围。该检测方法解决了多台手机间的相互音频串扰问题，使得多台手机可并行检测喇叭或者受话筒间歇无声故障，提升检测效率。
S220，该电子设备根据该发声频率，确定音源数据。
具体而言，根据以上S410中方法确定了电子设备对应的发声频率f 0，该电子设备可以根据该发声频率f 0生成一帧音源数据(时长为T)，该音源数据可以为单频正弦谐波信号，正弦波频率为f 0。
应理解，电子设备可以根据发声频率f 0生成一帧音源数据的过程可以通过现有的方式实现，为了简洁，在此不再赘述。
S230，该电子设备通过声音播放器播放该音源数据，并采集播放该音源数据时的音频数据。
例如，如图2所示，手机100可以通过喇叭181播放该音源数据，并通过麦克风183A采集播放该音源数据时的音频数据，在检测喇叭181时由程序控制将电子设备中的音频播放设备调整为喇叭181输出，并使用与喇叭181接近的麦克风183A采集，每个检测周期T时间内播放一帧音频数据，并使用相应麦克风(microphone，MIC)采集一帧音频数据，用于后续分析。
又例如，如图3所示，手机100可以通过受话筒182播放该音源数据，并通过麦克风183B采集播放该音源数据时的音频数据，在检测受话筒182时由程序控制将手机中的音频播放设备调整为受话筒182输出，并使用与受话筒182接近的麦克风183B采集，每个检测周期T时间内播放一帧音频数据，并使用相应MIC采集一帧数据，用于后续分析。
S240，当该电子设备对该音频数据的处理结果满足预设条件时，该电子设备确定该声音播放器发生概率无声故障。
具体而言，在采集到该音频数据后，该电子设备可以对该音频数据进行处理，通过对该音频数据的处理结果满足预设条件时，该电子设备可以确定声音播放器发声概率无声故障。
可选地，该电子设备对该音频数据处理之前，该方法还包括：
对该音频数据进行高通滤波和加窗处理。
其中，高通滤波指的是将音频数据通过设计好的高通滤波器，以滤除低频信号。
例如，在高温高湿环境下的温箱内进行检测时，500Hz频率以下环境噪声较大，此时由麦克风直接采集到的信号含有较高能量的低频环境噪声，可以通过截止频率为500Hz的高通滤波器进行滤波，有助于滤除低频环境噪声。
加窗处理指的是对一帧音频数据在时域上与一个窗函数(例如汉明窗、海宁窗以及布莱克曼窗等)进行相乘操作，然后再进行后续处理，以避免频谱泄漏，即信号突然截断导致在频域增加频率分量的现象。
可选地，该电子设备对该音频数据的处理结果包括但不限于以下中的一种或者多种：
(1)信号幅度
该信号幅度为该电子设备在第一频率范围内对该音频数据进行窄带滤波后获得。
例如，一种对音频数据进行处理获得信号幅度的方式如下：根据发声频率f 0确定滤波器通带频率范围与阻带频率范围，设计相应通带波动与阻带衰减值，进而获得该窄带滤波器的滤波器阶数及滤波系数。将该音频数据对滤波器进行输入，获取窄带后滤波数据，并对滤波数据进行有效值计算，最终获得该信号幅度。
(2)相关系数
该相关系数为该音频数据和该音源数据进行卷积计算而获得的。
例如，一种对音频数据进行处理获得相关系数的方式如下：首先获取该音频数据s 1及音源数据s 0，然后对音源数据s 0进行反向置换获得数据s′ 0，对s 1与s′ 0进行卷积运算并归一化处理后最终获得相关系数。
(3)第一声信号能量
该第一声信号能量为在该发声频率处对该音频数据进行快速傅里叶变换FFT获得的，该第一频率范围包括该发声频率。
例如，一种对音频数据进行处理获得第一声信号能量的方式如下：首先对该音频数据进行FFT变换，获得该音频数据的频谱。然后根据该音频数据的时长及采样频率获得发声频率f 0处对应的频谱索引，最后根据该频谱索引获取该发声频率f 0处的频谱能量，即为第一声信号能量。
可选地，当该电子设备对该音频数据的处理结果满足预设条件时，该电子设备确定该声音播放器发生概率无声故障，包括：
当确定该信号幅度小于或者等于第一信号幅度阈值后，该电子设备确定该声音播放器发生概率无声故障。
具体而言，该电子设备可以在在发声频率f 0附近进行窄带滤波，滤波完成后计算信号幅度，声音播放器发声与不发声时该信号幅度会有较大差异，当该计算得到的信号幅度小于或者等于第一信号幅度阈值时，该电子设备确定该声音播放器发生概率无声故障。
例如，该第一信号幅度阈值为-20dB，当检测得到的第一信号幅度小于或者等于-20dB时，该电子设备确定声音播放器发生概率无声故障。
可选地，当该电子设备对该音频数据的处理结果满足预设条件时，该电子设备确定该声音播放器发生概率无声故障，包括：
当该相关系数小于第一相关系数阈值时，该电子设备确定该声音播放器发生概率无声故障。
例如，该第一数值为0.2，当该电子设备确定的相关系数小于或者等于0.2时，该电子设备确定该声音播放器发生概率无声故障。
可选地，该电子设备对该音频数据的处理结果满足预设条件时，该电子设备确定该声音播放器发生概率无声故障，包括：
在该第一声信号能量与第二声信号能量的差值小于或者等于第一声信号能量阈值的情况下，该电子设备确定该声音播放器发生概率无声故障；
其中，该第二声信号能量为第二频率范围内除该发声频率以外的其他频率对应的声信号能量的平均值，该第二频率范围包括该发声频率。
可选地，该第一声信号能量阈值为15-20dB。
应理解，本申请实施例中，在确定声音播放器是否发生概率无声时，可以通过以上几种参数中的一种或者多种结合方式来检测，例如，可以根据信号幅度和相关系数相结合方式来检测，即当检测得到的信号幅度小于或者等于第一信号幅度阈值，且相关系数小于第一相关系数阈值时，该电子设备判断该声音播放器发生概率无声故障。
本申请实施例中，采用滤波后发声频率f 0附近窄带幅度、采集到的音频数据与音源数据的相关系数、发声频率附近频谱分布特性等三个维度对发声情况进行检测，有助于提高检测的准确度，同时，由于相关系数与发声频率附近频谱分布特性受器件差异影响较小， 因此对于不同型号电子设备，其结构形式、声音播放器件、音频录制器件不同，不需要针对每台电子设备设定不同的检测门限。
图5示出了本申请实施例提供的检测概率无声故障的方法300的示意性流程图，如图5所示，该方法300中以手机100为例进行说明，该方法300的执行主体可以为手机100，该方法300包括：
S310，获取手机100的唯一标识码。
可选地，该手机的唯一标识码可以为S410中的标识码中的一种或者多种组合。
S320，将该唯一标识码映射为发声频率f 0。
这里，可以通过预设的映射函数将该唯一标识码映射为f 0，或者，也可以是先将该唯一标识码进行反向置换后获得第二标识码，再通过预设的映射函数将该第二标识码映射为f 0，或者，还可以是通过其他方式得到f 0。
S330，根据f 0，生成一帧音源数据。
应理解，通过f 0确定音源数据的过程可以和现有的做法相同，为了简洁，在此不再赘述。
S340，通过喇叭181或者受话筒182，播放该音源数据；
S350，通过麦克风183采集播放该音源数据时的音频数据。
具体而言，可以通过麦克风183A采集喇叭181播放的音源数据，或者，通过麦克风183B采集受话筒182播放的音源数据。
S360，对该音频数据进行高通滤波；
S370，对该音频数据进行加窗处理。
应理解，S360和S370之间并没有实际的先后顺序。
S381，对高通滤波和加窗处理后的音频数据在f 0附近进行窄带滤波，得到信号幅度；
S382，对高通滤波和加窗处理后的音频数据和该音源数据进行卷积计算，得到相关系数；
S383，对高通滤波和加窗处理后的音频数据进行FFT，获得第一声信号能量。
S384，根据声信号幅度、相关系数或者第一声信号能量中的一种或者任几种，判断该声音播放器是否发生概率无声。
应理解，S384中通过声信号幅度、相关系数或者第一声信号能量中的一种或者任几种，判断该声音播放器是否发生概率无声的过程与S240中的过程相同，为了简洁，在此不再赘述。
S390，判断是否达到预设的检测时长，若达到预设的检测时长，则检测结束；若没有达到预设的检测时长，则继续返回至S330进行检测。
例如，手机预设的检测时长为8小时，手机检测概率无声的周期为0.1s，在每个周期检测完成后，手机会判断检测时长是否达到8小时，如果检测时长没有达到8小时，则返回S330继续进行下一个周期的检测，如果检测时长达到8小时，则检测结束。
图6示出了本申请实施例提供的检测概率无声故障的方法400的另一示意性流程图，方法400中对判声音播放器是否概率无声的判断过程进行了详细描述，该方法400包括：
S410，对音频数据处理得到相关系数和信号幅度。
应理解，S410与上述方法300中的S381和S382相同，为了简洁，在此不再赘述。
S420，判断相关系数是否小于或者等于第一相关系数阈值；
S421，在相关系数小于或者等于第一相关系数阈值的情况下，确定声音播放器发生概率无声故障；
S422，在相关系数大于第一相关系数阈值的情况下，判断该相关系数是否大于第二相关系数阈值。
应理解，该第二相关系数阈值大于该第一相关系数阈值。
S423，在该相关系数大于该第二相关系数阈值的关系的情况下，确定声音播放器有声；
S424，在该相关系数小于该第二相关系数阈值的关系的情况下，判断信号幅度是否小于或者等于第一信号幅度阈值的关系；
S425，在该信号幅度小于或者等于第一信号阈值的情况下，确定声音播放器发生概率无声故障；
S426，在该信号幅度大于第一信号阈值的情况下，确定声音播放器有声。
本申请实施例中，采用滤波后发声频率f 0附近窄带幅度、采集到的音频数据与音源数据的相关系数这二个维度对发声情况进行检测，有助于提高检测的准确度。
图7示出了本申请实施例提供的检测概率无声故障的方法500的另一示意性流程图，方法500中对判声音播放器是否概率无声的另一判断过程进行了详细描述，该方法500包括：
S510，对音频数据处理得到相关系数和第一声信号能量。
应理解，S510与上述方法300中的S381和S383相同，为了简洁，在此不再赘述。
S520，判断相关系数是否小于或者等于第一相关系数阈值；
S521，在相关系数小于或者等于第一相关系数阈值的情况下，确定声音播放器发生概率无声故障；
S522，在相关系数大于第一相关系数阈值的情况下，判断该相关系数是否大于第二相关系数阈值。
应理解，该第二相关系数阈值大于该第一相关系数阈值。
S523，在该相关系数大于该第二相关系数阈值的关系的情况下，确定声音播放器有声；
S524，在该相关系数小于该第二相关系数阈值的关系的情况下，判断第一声信号能量与第二声信号能量的差值是否小于或者等于声信号能量阈值。
应理解，该第一声信号能量与该第二声信号能量与上述实施例中的描述相同，为了简洁，在此不再赘述。
S525，在该差值小于或者等于声信号能量阈值的情况下，确定声音播放器发生概率无声故障；
S526，在该差值大于声信号能量阈值的情况下，确定声音播放器有声。
本申请实施例中，采用采集到的音频数据与音源数据的相关系数和发声频率附近频谱分布特性等三个维度对发声情况进行检测，有助于提高检测的准确度。
图8示出了本申请实施例提供的对多台手机进行检测的示意图。该检测是在高温高湿环境下的温箱内进行检测。首先将检测程序分别置入5台手机(手机A、B、C、D和E)，检测前在常温常湿环境下将5台手机放入温箱内。以恒定速率对温箱进行升温与加湿操作，待温箱内温度与湿度达到指定温度与湿度指标时，保持温箱内湿度与温度不变，此时 5台手机分别启动检测。
图9示出了手机A、B、C、D、E等5台手机同时发声并行检测时在0～120s时长内的检测结果，其中手机A、B、C、D、E分别在第30～33s、45～48s、60～63s、75～78s、90～93s时人为静音以模拟器件发声故障。每隔0.1s检测一次。检测结果如下，其中检测结果为1代表发声正常，检测结果为0代表发声故障。
由实施效果图可见，在人为中断的时刻，通过本申请实施例的检测概率无声故障的方法检测到了该中断。
以上结合图1至图9，详细地描述了本申请实施例的检测概率无声故障的方法，下面结合附图描述本申请实施例的检测概率无声故障的装置。应理解，方法实施例所描述的技术特征同样适用于以下装置实施例。
图10示出了本申请实施例的检测概率无声故障的装置600的示意性框图，如图10所示，该装置600包括：
处理模块610，用于确定该电子设备对应的发声频率；
处理模块610，还用于根据该发声频率，生成音源数据；
声音播放模块620，用于播放该音源数据；
声音采集模块630，用于采集播放该音源数据时的音频数据；
处理模块610，还用于对该音频数据进行处理；
当该处理模块610对该音频数据的处理结果满足预设条件时，该处理模块610，还用于确定该声音播放器发生概率无声故障。
可选地，该处理模块610具体用于：
获取第一标识码，该第一标识码为该电子设备对应的标识码；
根据该第一标识码，确定该发声频率。
可选地，该第一标识码为该电子设备的唯一标识码，该处理模块610具体用于：
将该唯一标识码反向置换，得到第二标识码；
根据该第二标识码，确定该发声频率。
可选地，该第二标识码与该发声频率为线性或者非线性关系。
可选地，该第二标识码与该发声频率为线性关系，其中，该处理模块具体用于：
根据以下公式确定该发声频率：
Figure PCTCN2018117933-appb-000004
其中，f 0为该发声频率，ID-R为该第二标识码，f High为第一发声频率阈值，f Low为第二发声频率阈值，ID-R max为允许的该第二标识码的最大值，ID-R min为允许的该第二标识码的最小值，该第一发声频率阈值大于该第二发声频率阈值。
可选地，该第一标识码由国际移动用户标识IMEI码、序列号SN码、用户身份识别SIM码、无线局域网WLAN MAC地址、蓝牙MAC地址或者安卓伪唯一标识码Pseudo-unique ID中的一种或者多种组成。
可选地，该处理结果包括信号幅度、相关系数或者第一声信号能量中的一种或者多种；
其中，该信号幅度为在第一频率范围内对该音频数据进行窄带滤波后获得，该相关系数为该音频数据和该音源数据进行卷积计算而获得的相关系数，该第一声信号能量为在该 发声频率处对该音频数据进行快速傅里叶变换FFT获得的，该第一频率范围包括该发声频率。
可选地，该处理结果包括该相关系数，处理模块610具体用于：
在该相关系数小于或者等于第一数值的情况下，确定该声音播放器发生概率无声故障。
可选地，该处理结果包括该相关系数和该信号幅度，处理模块610具体用于：
确定该相关系数大于或者等于第一数值，并且小于或者等于第二数值；
在该信号幅度小于或者等于第三数值的情况下，确定该声音播放器发生概率无声故障。
可选地，该处理结果包括该相关系数和该第一声信号能量，处理模块610具体用于：
确定该相关系数大于或者等于第一数值，并且小于或者等于第二数值；
在该第一声信号能量与第二声信号能量的差值小于或者等于第四数值的情况下，确定该声音播放器发生概率无声故障；
其中，该第二声信号能量为第二频率范围内除该发声频率以外的其他频率对应的声信号能量的平均值，该第二频率范围包括该发声频率。
可选地，该处理模块610，还用于在确定该声音播放器发生概率无声故障之前，对该音频数据进行高通滤波和加窗。
应理解，根据本申请实施例的装置600可用于执行前述方法实施例的方法，比如，图4至图7中的方法，并且装置600中的各个模块的上述和其它管理操作和/或功能分别为了实现前述方法实施例的方法的相应步骤，因此也可以实现前述方法实施例中的有益效果，为了简洁，这里不作赘述。
还应理解，上述装置600中的各个模块可以通过软件和/或硬件形式实现，对此不作具体限定。换言之，装置600是以功能模块的形式来呈现。这里的“模块”可以指特定应用集成电路ASIC、电路、执行一个或多个软件或固件程序的处理器和存储器、集成逻辑电路，和/或其他可以提供上述功能的器件。
可选地，在一个简单的实施例中，本领域的技术人员可以想到装置600可以采用图11所示的形式。处理模块610可以通过图11所示的处理器730实现。处理器730还可以通过执行存储器中存储的计算机程序来控制声音播放器710来实现声音播放以及控制声音采集器720来实现声音采集。可选地，当所述装置600是芯片时，那么装置600中涉及的收发的功能和/或实现过程还可以通过管脚或接口电路等来实现。可选地，所述存储器为所述芯片内的存储单元，比如寄存器、缓存等，所述存储单元还可以是所述计算机设备内的位于所述芯片外部的存储单元，如图11所的存储器740。
图11示出了根据本申请实施例的检测概率无声故障的装置700的示意性结构图，如图11所示，该装置700包括声音播放器710、声音采集器720、存储器730和处理器740，其中，一个或多个计算机程序被存储在存储器730中，一个或多个计算机程序包括指令。当指令被处理器730执行时，使得装置700执行以下操作：
确定该电子设备对应的发声频率；
根据该发声频率，生成音源数据；
通过该声音播放器播放该音源数据，并采集播放该音源数据时的音频数据；
当对该音频数据的处理结果满足预设条件时，确定该声音播放器发生概率无声故障。
可选地，当所述指令被处理器730执行时，使得所述装置700具体执行以下步骤：
获取第一标识码，该第一标识码为该电子设备对应的标识码；
根据该第一标识码，确定该发声频率。
可选地，该第一标识码为该电子设备的唯一标识码，当所述指令被处理器730执行时，使得所述装置700具体执行以下步骤：
将该唯一标识码反向置换，得到第二标识码；
根据该第二标识码，确定该发声频率。
可选地，该第二标识码与该发声频率为线性或者非线性关系。
可选地，该第二标识码与该发声频率为线性关系，其中，当所述指令被处理器730执行时，使得所述装置700具体执行以下步骤：
根据以下公式确定该发声频率：
Figure PCTCN2018117933-appb-000005
其中，f 0为该发声频率，ID-R为该第二标识码，f High为第一发声频率阈值，f Low为第二发声频率阈值，ID-R max为允许的该第二标识码的最大值，ID-R min为允许的该第二标识码的最小值，该第一发声频率阈值大于该第二发声频率阈值。
可选地，该第一标识码由国际移动用户标识IMEI码、序列号SN码、用户身份识别SIM码、无线局域网WLAN MAC地址、蓝牙MAC地址或者安卓伪唯一标识码Pseudo-unique ID中的一种或者多种组成。
可选地，该处理结果包括信号幅度、相关系数或者第一声信号能量中的一种或者多种；
其中，该信号幅度为在第一频率范围内对该音频数据进行窄带滤波后获得，该相关系数为该音频数据和该音源数据进行卷积计算而获得的相关系数，该第一声信号能量为在该发声频率处对该音频数据进行快速傅里叶变换FFT获得的，该第一频率范围包括该发声频率。
可选地，该处理结果包括该相关系数，当所述指令被处理器730执行时，使得所述装置700具体执行以下步骤：
在该相关系数小于或者等于第一数值的情况下，确定该声音播放器发生概率无声故障。
可选地，该处理结果包括该相关系数和该信号幅度，当所述指令被处理器730执行时，使得所述装置700具体执行以下步骤：
确定该相关系数大于或者等于第一数值，并且小于或者等于第二数值；
在该信号幅度小于或者等于第三数值的情况下，确定该声音播放器发生概率无声故障。
可选地，该处理结果包括该相关系数和该第一声信号能量，当所述指令被处理器730执行时，使得所述装置700具体执行以下步骤：
确定该相关系数大于或者等于第一数值，并且小于或者等于第二数值；
在该第一声信号能量与第二声信号能量的差值小于或者等于第四数值的情况下，确定该声音播放器发生概率无声故障；
其中，该第二声信号能量为第二频率范围内除该发声频率以外的其他频率对应的声信号能量的平均值，该第二频率范围包括该发声频率。
可选地，当所述指令被处理器730执行时，使得所述装置700具体执行以下步骤：
对该音频数据进行高通滤波和加窗。
可选地，在一种可能的实现方式中，上述装置600或装置700可以是终端设备。
例如，该装置700可以对应于图1中的手机100，处理器730可以对应于图1中的处理器130，存储器140可以对应于图1中的存储器140，声音播放器710可以对应于图1中的喇叭181或者受话筒182，声音采集器可以对应于图1中的麦克风183。
在本申请实施例中，应注意，本申请实施例上述的方法实施例可以应用于处理器中，或者由处理器实现。处理器可能是一种集成电路芯片，具有信号的处理能力。在实现过程中，上述方法实施例的各步骤可以通过处理器中的硬件的集成逻辑电路或者软件形式的指令完成。上述的处理器可以是通用处理器、数字信号处理器(digital signal processor，DSP)、专用集成电路(application specific integrated circuit，ASIC)、现成可编程门阵列(field programmable gate array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。可以实现或者执行本申请实施例中的公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。结合本申请实施例所公开的方法的步骤可以直接体现为硬件译码处理器执行完成，或者用译码处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器，处理器读取存储器中的信息，结合其硬件完成上述方法的步骤。
可以理解，本申请实施例中的存储器可以是易失性存储器或非易失性存储器，或可包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(read-only memory，ROM)、可编程只读存储器(programmable ROM，PROM)、可擦除可编程只读存储器(erasable PROM，EPROM)、电可擦除可编程只读存储器(electrically EPROM，EEPROM)或闪存。易失性存储器可以是随机存取存储器(random access memory，RAM)，其用作外部高速缓存。通过示例性但不是限制性说明，许多形式的RAM可用，例如静态随机存取存储器(static RAM，SRAM)、动态随机存取存储器(dynamic RAM，DRAM)、同步动态随机存取存储器(synchronous DRAM，SDRAM)、双倍数据速率同步动态随机存取存储器(double data rate SDRAM，DDR SDRAM)、增强型同步动态随机存取存储器(enhanced SDRAM，ESDRAM)、同步连接动态随机存取存储器(synchlink DRAM，SLDRAM)和直接内存总线随机存取存储器(direct rambus RAM，DR RAM)。应注意，本文描述的系统和方法的存储器旨在包括但不限于这些和任意其它适合类型的存储器。
应理解，说明书通篇中提到的“一个实施例”或“一实施例”意味着与实施例有关的特定特征、结构或特性包括在本申请的一个或多个实施例中。因此，在整个说明书各处出现的“在一个实施例中”或“在一实施例中”未必一定指相同的实施例。此外，这些特定的特征、结构或特性可以任意适合的方式结合在一个或多个实施例中。应理解，在本申请的各种实施例中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
另外，本文中术语“系统”和“网络”在本文中常被可互换使用。本文中术语“和/或”，仅 仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系。
应理解，在本申请实施例中，“与A相应的B”表示B与A相关联，根据A可以确定B。但还应理解，根据A确定B并不意味着仅仅根据A确定B，还可以根据A和/或其它信息确定B。
上述实施例中，可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件实现时，可以全部或部分地以计算机程序产品的形式实现。所述计算机程序产品可以包括一个或多个计算机指令。在计算机上加载和执行所述计算机程序指令时，全部或部分地产生按照本申请实施例所述的流程或功能。所述计算机可以是通用计算机、专用计算机、计算机网络或者其他可编程装置。所述计算机指令可以存储在计算机可读存储介质中，或者从一个计算机可读存储介质向另一个计算机可读存储介质传输，例如，所述计算机指令可以从一个网站站点、计算机、服务器或数据中心通过有线(例如同轴电缆、光纤、数字用户(DSL))或无线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。所述计算机可读存储介质可以是计算机能够存取的任何可用介质或者是包含一个或多个可用介质集成的服务器、数据中心等数据存储设备。所述可用介质可以是磁性介质(例如，软盘、硬盘、磁盘)、光介质(例如，DVD)、或者半导体介质(例如固态硬盘solid state disk(SSD))等。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统、装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机 软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(read-only memory，ROM)、随机存取存储器(random access memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以所述权利要求的保护范围为准。

Claims (24)

  1. 一种检测概率无声故障的方法，应用于电子设备，所述电子设备包括声音播放器，其特征在于，包括：
    所述电子设备确定所述电子设备对应的发声频率；
    所述电子设备根据所述发声频率，生成音源数据；
    所述电子设备通过所述声音播放器播放所述音源数据，并采集播放所述音源数据时的音频数据；
    当所述电子设备对所述音频数据的处理结果满足预设条件时，所述电子设备确定所述声音播放器发生概率无声故障。
  2. 根据权利要求1所述的方法，其特征在于，所述电子设备确定所述电子设备对应的发声频率，包括：
    所述电子设备获取第一标识码，所述第一标识码为所述电子设备对应的标识码；
    所述电子设备根据所述第一标识码，确定所述发声频率。
  3. 根据权利要求2所述的方法，其特征在于，所述第一标识码为所述电子设备的唯一标识码，所述根据所述第一标识码，确定所述发声频率，包括：
    所述电子设备将所述唯一标识码反向置换，得到第二标识码；
    所述电子设备根据所述第二标识码，确定所述发声频率。
  4. 根据权利要求3所述的方法，其特征在于，所述第二标识码与所述发声频率为线性或者非线性关系。
  5. 根据权利要求3或4所述的方法，其特征在于，所述第二标识码与所述发声频率为线性关系，其中，所述根据所述第二标识码，确定所述发声频率，包括：
    所述电子设备根据以下公式确定所述发声频率：
    Figure PCTCN2018117933-appb-100001
    其中，f 0为所述发声频率，ID-R为所述第二标识码，f High为第一发声频率阈值，f Low为第二发声频率阈值，ID-R max为允许的所述第二标识码的最大值，ID-R min为允许的所述第二标识码的最小值，所述第一发声频率阈值大于所述第二发声频率阈值。
  6. 根据权利要求2至5中任一项所述的方法，其特征在于，所述第一标识码由国际移动用户标识IMEI码、序列号SN码、用户身份识别SIM码、无线局域网WLAN MAC地址、蓝牙MAC地址或者安卓伪唯一标识码Pseudo-unique ID中的一种或者多种组成。
  7. 根据权利要求1至6中任一项所述的方法，其特征在于，所述处理结果包括信号幅度、相关系数或者第一声信号能量中的一种或者多种；
    其中，所述信号幅度为在第一频率范围内对所述音频数据进行窄带滤波后获得，所述相关系数为所述音频数据和所述音源数据进行卷积计算而获得的相关系数，所述第一声信号能量为在所述发声频率处对所述音频数据进行快速傅里叶变换FFT获得的，所述第一频率范围包括所述发声频率。
  8. 根据权利要求7所述的方法，其特征在于，所述处理结果包括所述相关系数，所述当所述电子设备对所述音频数据的处理结果满足预设条件时，所述电子设备确定所述声 音播放器发生概率无声故障，包括：
    在所述相关系数小于或者等于第一数值的情况下，所述电子设备确定所述声音播放器发生概率无声故障。
  9. 根据权利要求7所述的方法，其特征在于，所述处理结果包括所述相关系数和所述信号幅度，所述当所述电子设备对所述音频数据的处理结果满足预设条件时，所述电子设备确定所述声音播放器发生概率无声故障，包括：
    所述电子设备确定所述相关系数大于或者等于第一数值，并且小于或者等于第二数值；
    在所述信号幅度小于或者等于第三数值的情况下，所述电子设备确定所述声音播放器发生概率无声故障。
  10. 根据权利要求7所述的方法，其特征在于，所述处理结果包括所述相关系数和所述第一声信号能量，所述当所述电子设备对所述音频数据的处理结果满足预设条件时，所述电子设备确定所述声音播放器发生概率无声故障，包括：
    所述电子设备确定所述相关系数大于或者等于第一数值，并且小于或者等于第二数值；
    在所述第一声信号能量与第二声信号能量的差值小于或者等于第四数值的情况下，所述电子设备确定所述声音播放器发生概率无声故障；
    其中，所述第二声信号能量为第二频率范围内除所述发声频率以外的其他频率对应的声信号能量的平均值，所述第二频率范围包括所述发声频率。
  11. 根据权利要求1至10中任一项所述的方法，其特征在于，所述电子设备确定所述声音播放器发生概率无声故障之前，所述方法还包括：
    所述电子设备对所述音频数据进行高通滤波和加窗。
  12. 一种检测概率无声故障的装置，其特征在于，该装置包括处理器、声音播放器、声音采集器，其中，
    所述处理器，用于确定所述装置对应的发声频率；
    所述处理器，还用于根据所述发声频率，生成音源数据；
    所述声音播放器，用于播放所述音源数据；
    所述声音采集器，用于采集播放所述音源数据时的音频数据；
    当所述处理器对所述音频数据的处理结果满足预设条件时，所述处理器，还用于确定所述声音播放器发生概率无声故障。
  13. 根据权利要求12所述的装置，其特征在于，所述处理器具体用于：
    获取第一标识码，所述第一标识码为所述装置对应的标识码；
    根据所述第一标识码，确定所述发声频率。
  14. 根据权利要求13所述的装置，其特征在于，所述第一标识码为所述装置的唯一标识码，所述处理器具体用于：
    将所述唯一标识码反向置换，得到第二标识码；
    根据所述第二标识码，确定所述发声频率。
  15. 根据权利要求14所述的装置，其特征在于，所述第二标识码与所述发声频率为线性或者非线性关系。
  16. 根据权利要求14或15所述的装置，其特征在于，所述第二标识码与所述发声频率为线性关系，其中，所述处理器具体用于：
    根据以下公式确定所述发声频率：
    Figure PCTCN2018117933-appb-100002
    其中，f 0为所述发声频率，ID-R为所述第二标识码，f High为第一发声频率阈值，f Low为第二发声频率阈值，ID-R max为允许的所述第二标识码的最大值，ID-R min为允许的所述第二标识码的最小值，所述第一发声频率阈值大于所述第二发声频率阈值。
  17. 根据权利要求13至16中任一项所述的装置，其特征在于，所述第一标识码由国际移动用户标识IMEI码、序列号SN码、用户身份识别SIM码、无线局域网WLAN MAC地址、蓝牙MAC地址或者安卓伪唯一标识码Pseudo-unique ID中的一种或者多种组成。
  18. 根据权利要求12至17中任一项所述的装置，其特征在于，所述处理结果包括信号幅度、相关系数或者第一声信号能量中的一种或者多种；
    其中，所述信号幅度为在第一频率范围内对所述音频数据进行窄带滤波后获得，所述相关系数为所述音频数据和所述音源数据进行卷积计算而获得的相关系数，所述第一声信号能量为在所述发声频率处对所述音频数据进行快速傅里叶变换FFT获得的，所述第一频率范围包括所述发声频率。
  19. 根据权利要求18所述的装置，其特征在于，所述处理结果包括所述相关系数，所述处理器具体用于：
    在所述相关系数小于或者等于第一数值的情况下，确定所述声音播放器发生概率无声故障。
  20. 根据权利要求18所述的装置，其特征在于，所述处理结果包括所述相关系数和所述信号幅度，所述处理器具体用于：
    确定所述相关系数大于或者等于第一数值，并且小于或者等于第二数值；
    在所述信号幅度小于或者等于第三数值的情况下，确定所述声音播放器发生概率无声故障。
  21. 根据权利要求18所述的装置，其特征在于，所述处理结果包括所述相关系数和所述第一声信号能量，所述处理器具体用于：
    确定所述相关系数大于或者等于第一数值，并且小于或者等于第二数值；
    在所述第一声信号能量与第二声信号能量的差值小于或者等于第四数值的情况下，确定所述声音播放器发生概率无声故障；
    其中，所述第二声信号能量为第二频率范围内除所述发声频率以外的其他频率对应的声信号能量的平均值，所述第二频率范围包括所述发声频率。
  22. 根据权利要求12至21中任一项所述的方法，其特征在于，所述处理器，还用于在确定所述声音播放器发生概率无声之前，对所述音频数据进行高通滤波和加窗。
  23. 一种计算机可读存储介质，包括指令，当其在计算机上运行时，使得计算机执行上述权利要求1-11中任一项所述的方法。
  24. 一种计算机程序产品，当其在计算机上运行时，使得计算机执行上述权利要求1-11中任一项所述的方法。
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