CN113170268A

CN113170268A - Method and device for detecting probability silent fault

Info

Publication number: CN113170268A
Application number: CN201880099761.3A
Authority: CN
Inventors: 郭志巍; 舒文; 张海宏; 王硕强
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2018-11-28
Filing date: 2018-11-28
Publication date: 2021-07-23
Anticipated expiration: 2038-11-28
Also published as: CN113170268B; WO2020107261A1

Abstract

The application provides a method and a device for detecting a probability silent fault, wherein the method for detecting the probability silent fault comprises the following steps: the electronic equipment determines the corresponding sound production frequency of the electronic equipment; generating sound source data according to the sound production frequency; playing the sound source data through the sound player, and collecting audio data when the sound source data is played; and when the processing result of the electronic equipment on the audio data meets a preset condition, determining that the probability silent failure occurs to the sound player. The method for detecting the probability silent fault is beneficial to realizing automatic detection of a plurality of electronic devices.

Description

Method and device for detecting probability silent fault

Technical Field

The present application relates to the field of electronic devices, and more particularly, to a method and apparatus for detecting probabilistic silent faults.

Background

The external loudspeaker and the receiver are important devices for playing music and communicating with the mobile phone, when the mobile phone plays music, the built-in chip decodes the audio file and transmits the audio file to the power amplifier through the audio channel, and the amplified audio signal is transmitted to the external loudspeaker for playing music. In general, the lead of the handset speaker is connected to the power amplifier through a spring plate to realize a passage. For a mobile phone receiver, similar to the connection of a loudspeaker, the connection is usually also a spring contact connection. Through the elastic sheet electric connection structure, the loudspeaker and the receiver can normally receive and play music signals and call voice signals in the music playing or call process of the mobile phone.

When the electrical connection elastic sheet on the audio channel of the loudspeaker or the receiver is in poor contact, the audio channel can be interrupted intermittently, so that the probability or intermittent silent fault of the loudspeaker or the receiver of the mobile phone is caused. The probability silent failure may occur only at a short moment during a long music playing or conversation, or may occur in a mobile phone moving state (for example, a short time after the mobile phone is dropped, while the mobile phone is running). In addition, when any node on the audio hardware path has an open circuit fault, the fault that a receiver or a loudspeaker is silent can be generated. The subjective listening feeling of a user can be seriously influenced when the mobile phone has a soundless problem, so that the potential problem can be intensively tested and intercepted in the research and development stage of the mobile phone.

At present, an effective detection means is lacked aiming at the problem of probability silence, and a method for detecting probability silence faults is to enable a mobile phone to play a sound source through a loudspeaker or a receiver, and a tester listens in the whole process and records whether probability silence occurs in the whole test time length. Meanwhile, probability silence detection needs to play a sound source for a long time (several hours), and testers need to participate in the whole process in a long time, so that the manual detection method is low in efficiency, only several mobile phones can be detected in one day, and manpower resources are consumed very much. On the other hand, in order to excite the probability silent fault during the test to facilitate the detection and interception, the mobile phone needs to be tested in an extreme environment, such as real-time detection in a roller, a slight drop, high temperature and high humidity (in an incubator) and a salt fog environment, and at this time, the detection cannot be or is difficult to be performed manually.

Disclosure of Invention

In view of this, the present application provides a method and an apparatus for detecting probabilistic silence fault, which is helpful for realizing automatic detection of probabilistic silence.

In a first aspect, a method for detecting a probabilistic silent failure is provided, which is applied to an electronic device including a sound player, and includes: the electronic equipment determines the corresponding sound production frequency of the electronic equipment; the electronic equipment generates sound source data according to the sound production frequency; the electronic equipment plays the sound source data through the sound player and collects audio data when playing the sound source data; when the processing result of the electronic equipment to the audio data meets the preset condition, the electronic equipment determines that the probability silent failure occurs to the sound player.

According to the method for detecting the probability silent fault, the electronic equipment generates sound source data through the determined sound production frequency, judges whether the electronic equipment is silent in probability through the collected audio data, can change long-time artificial subjective listening detection into objective detection, replaces human ears to judge the probability silent fault of the mobile phone, and is beneficial to realizing automatic detection of the probability silent of the electronic equipment.

In some possible implementations, the determining, by the electronic device, a corresponding sound emission frequency of the electronic device includes: the electronic device obtains the sound frequency. For example, when the plurality of electronic devices perform the probabilistic silence test, the control device may transmit the sound emission frequency (or directly transmit sound source data) to each of the plurality of electronic devices; or after detecting the operation of inputting the sound frequency by the tester, the electronic equipment responds to the operation to determine the sound frequency corresponding to the electronic equipment.

In some possible implementations, the sound player is a speaker or a microphone.

According to the method for detecting the probability silent fault in the embodiment of the application, when a plurality of electronic devices perform probability silent detection, each electronic device can respectively determine the sound production frequency corresponding to the electronic device, and sound source data is generated by the sound production frequency to be played.

With reference to the first aspect, in certain implementations of the first aspect, the determining, by the electronic device, a sound emission frequency corresponding to the electronic device includes: the electronic equipment acquires a first identification code, wherein the first identification code is an identification code corresponding to the electronic equipment; the electronic equipment determines the sounding frequency according to the first identification code.

According to the method for detecting the probability silent fault, the electronic equipment determines the sound production frequency through the identification code, sound source data are generated by the sound production frequency to be played, and due to the fact that the sound production frequency corresponding to the sound source data played by each piece of electronic equipment is different, mutual interference among different pieces of electronic equipment is avoided, and therefore automatic detection of multiple pieces of electronic equipment is facilitated.

With reference to the first aspect, in certain implementations of the first aspect, the determining the sound emission frequency according to the first identification code is a unique identification code of the electronic device, and includes: the electronic equipment reversely replaces the unique identification code to obtain a second identification code; the electronic equipment determines the sounding frequency according to the second identification code.

In some possible implementations, the electronic device may replace the unique identification code of the electronic device according to a predefined rule, and determine the sound emission frequency according to the replaced identification code.

According to the method for detecting the probability silent fault, the unique identification codes are likely to be close to each other for the electronic equipment in the same batch, and the method of reverse replacement is used, so that mutual interference among different electronic equipment is further reduced.

With reference to the first aspect, in certain implementations of the first aspect, the second identification code is in a linear or non-linear relationship with the utterance frequency.

With reference to the first aspect, in certain implementations of the first aspect, the determining the sounding frequency according to the second identification code includes: the electronic device determines the sound emission frequency according to the following formula:

wherein f is₀For the sound frequency, ID-R is the second identification code, f_HighIs a first sound emission frequency threshold, f_LowAs second voicing frequency threshold, ID-R_maxFor the maximum allowed value of the second identification code, ID-R_minThe first utterance frequency threshold is greater than the second utterance frequency threshold for a minimum allowed value of the second identification code.

With reference to the first aspect, in some implementations of the first aspect, the first identification code is composed of one or more of an international mobile subscriber identity IMEI code, a serial number SN code, a subscriber identity module SIM code, a wireless local area network WLAN MAC address, a bluetooth MAC address, or an android Pseudo-unique identification code Pseudo-unique ID.

According to the method for detecting the probability silent fault, the corresponding sounding frequency is determined through the unique identification code of the electronic equipment, and automatic detection of a plurality of pieces of electronic equipment is facilitated.

With reference to the first aspect, in certain implementations of the first aspect, the processing result includes one or more of a signal amplitude, a correlation coefficient, or a first acoustic signal energy; the signal amplitude is obtained by performing narrow-band filtering on the audio data in a first frequency range, the correlation coefficient is obtained by performing convolution calculation on the audio data and the sound source data, the first acoustic signal energy is obtained by performing Fast Fourier Transform (FFT) on the audio data at the sound emission frequency, and the first frequency range includes the sound emission frequency.

In some possible implementations, the electronic device may employ one or any of the above dimensions in detecting whether the sound player is probabilistically unvoiced.

In the embodiment of the application, the sound frequency f after filtering is adopted₀The sounding condition is detected by dimensions such as the correlation coefficient of the collected audio data and the sound source data and the frequency spectrum distribution characteristic near the sounding frequency, and the detection accuracy is improved.

With reference to the first aspect, in certain implementations of the first aspect, the processing result includes the correlation coefficient, and when the processing result of the electronic device on the audio data satisfies a preset condition, the determining, by the electronic device, that the sound player has a probability of silent failure includes: in the case where 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.

With reference to the first aspect, in certain implementations of the first aspect, the processing result includes the correlation coefficient and the signal amplitude, and when the processing result of the electronic device on the audio data satisfies a preset condition, the electronic device determines that a probabilistic silent failure occurs in the sound player, including: the electronic device determines that the correlation coefficient is greater than or equal to a first value and less than or equal to a second value; in the case where the signal amplitude is less than or equal to the third value, the electronic device determines that a probabilistic silent failure of the sound player has occurred.

In the embodiment of the application, the sound frequency f after filtering is adopted₀The sounding condition is detected by two dimensions of the near narrow-band amplitude and the correlation coefficient of the collected audio data and the sound source data, and the detection accuracy is improved.

With reference to the first aspect, in certain implementations of the first aspect, the processing result includes the correlation coefficient and the first acoustic signal energy, and when the processing result of the electronic device on the audio data satisfies a preset condition, the electronic device determines that the sound player has a probabilistic silent failure, including: the electronic device determines that the correlation coefficient is greater than or equal to a first value and less than or equal to a second value; in the case that the difference value between the first sound signal energy and the second sound signal energy is smaller than or equal to a fourth value, the electronic equipment determines that the sound player has a probability silent fault; the second sound signal energy is an average value of sound signal energy corresponding to other frequencies in a second frequency range except the sounding frequency, and the second frequency range includes the sounding frequency.

In the embodiment of the application, the two dimensions of the correlation coefficient of the audio data and the sound source data acquired after filtering and the spectral distribution characteristic near the sounding frequency are adopted to detect the sounding condition, so that the accuracy of detection is improved.

Meanwhile, the correlation coefficient and the frequency spectrum distribution characteristic near the sounding frequency are less influenced by the difference of the devices, so that different types of electronic equipment are different in structural form, sound playing devices and audio recording devices, and different detection thresholds do not need to be set for each piece of electronic equipment.

With reference to the first aspect, in certain implementations of the first aspect, before the electronic device determines that the sound player has a probabilistic silent failure, the method further includes: the electronic device high-pass filters and windows the audio data.

According to the method for detecting the probability silent fault, the collected audio data is subjected to high-pass filtering, so that low-frequency environment noise is filtered; by windowing the collected audio data, it is helpful to prevent the spectrum leakage.

In a second aspect, the present disclosure provides an apparatus for detecting a probabilistic silent failure, the apparatus being included in an electronic device, and the apparatus having functionality for implementing the above aspects and possible implementations of the above aspects. The functions may be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more modules or units corresponding to the above-described functions.

In a third aspect, the present technical solution provides an electronic device, including: a sound player; a sound collector; one or more processors; a memory; a plurality of application programs; and one or more computer programs. Wherein the one or more computer programs are stored in the memory, the one or more computer programs comprising instructions. The instructions, when executed by the electronic device, cause the electronic device to perform a method of detecting a probabilistic silent failure in any of the possible implementations of any of the above aspects.

In a fourth aspect, the present disclosure provides an electronic device comprising one or more processors and one or more memories. The one or more memories are coupled to the one or more processors for storing computer program code comprising computer instructions that, when executed by the one or more processors, cause the electronic device to perform a method of detecting probabilistic silent faults in any of the possible implementations of the above aspects.

In a fifth aspect, the present disclosure provides a computer storage medium comprising computer instructions that, when executed on an electronic device, cause the electronic device to perform a method for detecting probabilistic silent faults in any one of the possible implementations of the above aspects.

In a sixth aspect, the present disclosure provides a computer program product, which when run on an electronic device, causes the electronic device to perform a method for detecting probabilistic silent faults in any one of the possible designs.

According to the method and the device for detecting the probability silent faults, when a plurality of electronic devices perform probability silent detection, each electronic device can respectively determine the sound production frequency corresponding to the electronic device, sound source data is generated by the sound production frequency to be played, long-time artificial subjective listening detection is changed into objective detection, the mobile phone audio faults are judged by replacing human ears, and labor cost is saved. The detection can be realized in the environment which can not be monitored manually (high temperature, high humidity, salt fog and other environments), and the detection range is expanded. Meanwhile, because the sound source data played by each electronic device have different sound production frequencies, the electronic device is beneficial to avoiding mutual interference among different electronic devices.

Drawings

Fig. 1 is a schematic structural diagram of a mobile phone provided in an embodiment of the present application.

Fig. 2 is another schematic structural diagram of a mobile phone provided in an embodiment of the present application.

Fig. 3 is another schematic structural diagram of a mobile phone provided in an embodiment of the present application.

Fig. 4 is a schematic flow chart of a method for detecting a probabilistic silent fault according to an embodiment of the present application.

Fig. 5 is another schematic flow chart of a method for detecting a probabilistic silent fault provided by an embodiment of the present application.

Fig. 6 is another schematic flow chart of a method for detecting a probabilistic silent fault provided by an embodiment of the present application.

Fig. 7 is another schematic flow chart of a method for detecting a probabilistic silent fault 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 according to an embodiment of the present application.

Fig. 10 is a schematic block diagram of an apparatus for detecting a probabilistic silent fault according to an embodiment of the present application.

Fig. 11 is another schematic block diagram of an apparatus for detecting a probabilistic silent fault provided by an embodiment of the present application.

Detailed Description

The technical solution in the present application will be described below with reference to the accompanying drawings.

The technical solution of the embodiment of the present application may be applied to all apparatuses or devices including a sound player and a microphone, for example, the sound player of the electronic device may include a microphone (RCV) or a Speaker (SPK), and the embodiment of the present application is not limited thereto. That is to say, the method for detecting the probability silence fault according to the embodiment of the present application can be applied to the use scene of detecting the probability silence of the sound player without manual detection. For convenience of description, the embodiments of the present application are described by taking a terminal device as an example, but the scope of protection of the embodiments of the present application is not limited.

The technical solution of the embodiment of the present application may be applied to a terminal device, where the terminal device may be, but is not limited to, a Mobile Station (MS), a mobile terminal (mobile terminal), a mobile phone (mobile phone), a mobile phone (handset), a portable device (portable equipment), and the like, and may communicate with one or more core networks through a radio access network (RAN, for example). A terminal in the embodiments of the present application may refer to a terminal (terminal), user equipment, access terminal, subscriber unit, subscriber station, mobile station, remote terminal, mobile device, user terminal, wireless communication device, user agent, or user equipment. The terminal device may also be a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA), a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a wearable device, a terminal device in a future 5G network or a terminal device in a future evolved Public Land Mobile Network (PLMN), and the like, which are not limited in this embodiment.

In the embodiment of the application, the terminal device comprises 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 hardware such as a Central Processing Unit (CPU), a Memory Management Unit (MMU), and a memory (also referred to as a main memory). The operating system may be any one or more computer operating systems that implement business processing through processes (processes), such as a Linux operating system, a Unix operating system, an Android operating system, an iOS operating system, or a windows operating system. The application layer comprises applications such as a browser, an address list, word processing software, instant messaging software and the like. Furthermore, the embodiment of the present application does not particularly limit the specific structure of the execution main body of the method provided by the embodiment of the present application, as long as the communication can be performed according to the method provided by the embodiment of the present application by running the program recorded with the code of the method provided by the embodiment of the present application, for example, the execution main body of the method provided by the embodiment of the present application may be a terminal device, or a functional module capable of calling a program and executing the program in the terminal device.

Additionally, various aspects or features of the present application may be presented as an off-the-shelf method, apparatus, or article of manufacture using standard programming and/or engineering techniques. The term "article of manufacture" as used herein is intended to encompass a computer program accessible from any computer-readable device, carrier, or media. For example, computer-readable media can include but are not limited to magnetic storage devices (e.g., hard disk, floppy disk, magnetic strips, etc.), optical disks (e.g., Compact Disk (CD), Digital Versatile Disk (DVD), etc.), smart cards, and flash memory devices (e.g., erasable programmable read-only memory (EPROM), card, stick, or key drive, etc.). In addition, various storage media described herein can represent one or more devices and/or other machine-readable media for storing information. The term "machine-readable medium" can include, without being limited to, wireless channels and various other media capable of storing, containing, and/or carrying instruction(s) and/or data.

The following describes the components of the mobile phone 100 in detail with reference to fig. 1:

the RF circuit 110 may be used for receiving and transmitting signals during information transmission and reception or during a call, and in particular, receives downlink information of a base station and then sends the received downlink information to the processor 130; in addition, the data for designing uplink is transmitted to the base station. Typically, the RF circuitry includes, but is not limited to, an antenna, at least one Amplifier, a transceiver, a coupler, a Low Noise Amplifier (LNA), a duplexer, and the like. In addition, the RF circuitry 110 may also communicate with networks and other devices via wireless communications. The wireless communication may use any communication standard or protocol, including but not limited to global system for mobile communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, Short Message Service (SMS), etc.

The memory 140 may be used to store software programs and modules, and the processor 130 executes various functional applications and data processing of the mobile phone 100 by operating the software programs and modules stored in the memory 140. The memory 140 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone 100, and the like. Further, the memory 140 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The input unit 150 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the cellular phone 100. Specifically, the input unit 150 may include a touch panel 151 and other input devices 152. The touch panel 151, also referred to as a touch screen, may collect a touch operation performed by a user on or near the touch panel 151 (e.g., an operation performed by the user on or near the touch panel 151 using any suitable object or accessory such as a finger or a stylus), and drive a corresponding connection device according to a preset program. Alternatively, the touch panel 151 may include two parts of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 130, and can receive and execute commands sent by the processor 130. In addition, the touch panel 151 may be implemented in various types, such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. The input unit 150 may include other input devices 152 in addition to the touch panel 151. In particular, 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.), a trackball, a mouse, a joystick, and the like.

The display unit 160 may be used to display information input by or provided to the user and various menus of the cellular 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 an LCD, an OLED, or the like. Further, the touch panel 151 may cover the display panel 161, and when the touch panel 151 detects a touch operation thereon or nearby, the touch panel is transmitted to the processor 130 to determine the type of the touch event, and then the processor 130 provides a corresponding visual output on the display panel 161 according to the type of the touch event. Although the touch panel 151 and the display panel 151 are shown in fig. 2 as two separate components to implement the input and output functions of the mobile phone 100, in some embodiments, the touch panel 151 and the display panel 161 may be integrated to implement the input and output functions of the mobile phone 100.

The handset 100 may also include at least one sensor 170, such as a light sensor, motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor that adjusts the brightness of the display panel 161 according to the brightness of ambient light, and a proximity sensor that turns off the display panel 161 and/or the backlight when the mobile phone 100 is moved to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally, three axes), can detect the magnitude and direction of gravity when stationary, and can be used for applications of recognizing the posture of a mobile phone (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer and tapping), and the like; as for other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which can be configured on the mobile phone 100, further description is omitted here.

The audio circuit 180 is used to convert digital audio information into an analog audio signal output and also to convert an analog audio input into a digital audio signal. The audio circuit 180 may also be used to encode and decode audio signals. In some embodiments, the audio circuit 180 may be disposed in the processor 110, or some functional blocks of the audio circuit 180 may be disposed in the processor 110.

The speaker 181, also called "speaker", is used to convert an audio electrical signal into a sound signal. The cellular phone 100 can perform music playback or hands-free call sound playback through the speaker 181.

A receiver 182, also referred to as an "earpiece," is used to convert the electrical audio signals into acoustic signals. When the cellular phone 100 receives a call or voice information, it is possible to receive voice by placing the receiving microphone 182 close to the ear of the person.

The microphone 183, also called "microphone", is used to convert sound signals into electrical signals. When making a call or transmitting voice information, the user can input a voice signal to the microphone 183 by making a sound near the microphone 183 through the mouth. The handset 100 may be provided with at least one microphone 183.

In the embodiment of the application, after the electronic device generates the sound source data, the sound source data can be played through a loudspeaker or a microphone, the audio data is collected through the corresponding microphone 183, and whether the probability of the loudspeaker or the microphone is silent is determined by comparing and analyzing the sound source data and the collected audio data.

Fig. 2 shows another schematic structural diagram of the mobile phone 100, wherein the positional relationship between the speaker 181 and the microphone 183A in the mobile phone 100 is mainly shown, as shown in fig. 2, the speaker 181 and the microphone 183A are adjacent to each other and located on the left side and the right side of the data interface at the bottom of the mobile phone 100, respectively, after the mobile phone 100 generates sound source data, the sound source data can be played through the speaker 181, and audio data during playing of the sound source data is collected through the microphone 183A, and the processor 130 can analyze the sound source data and the audio data to determine whether the speaker 181 of the mobile phone 100 has silence probability.

Another possible implementation manner is that fig. 3 shows another schematic structural diagram of the mobile phone 100, where the schematic structural diagram mainly shows a positional relationship between the microphone 182 and the microphone 183B in the mobile phone 100, as shown in fig. 3, the microphone 182 and the microphone 183B are adjacent to each other and are respectively located at the upper portion of the mobile phone 100, when the mobile phone 100 generates sound source data, the sound source data can be played through the microphone 182, and audio data during playing of the sound source data is collected through the microphone 183B, and the processor 130 can analyze the sound source data and the audio data to determine whether the microphone 182 of the mobile phone 100 is silent in probability.

It should be understood that the detection may be performed separately for the speaker 181 and the receiver 182.

It should also be understood that for the speaker 181, the sound source data played by the speaker 181 may be detected by the microphone 183A, and the sound source data played by the speaker 181 may also be detected by the microphone 183B; for the microphone 182, sound source data played by the microphone 182 may be detected by the microphone 183B, or sound source data played by the microphone 182 may be detected by the microphone 183B; it is also possible that the sound source data played by the speaker 181 and the microphone 182 are not detected by the microphone but detected by other devices. The examples of the present application are not limited in this respect.

It is also understood that microphone 183A may be the primary microphone of handset 100 and microphone 183B may be the secondary microphone of handset 100.

It should also be understood that in other embodiments, the handset 100 may further include three, four or more microphones 183 for collecting sound signals, reducing noise, identifying sound sources, performing directional recording functions, etc.

WiFi belongs to short-distance wireless transmission technology, and the mobile phone 100 can help the user send and receive e-mails, browse web pages, access streaming media, etc. through the WiFi module 190, which provides wireless broadband internet access for the user. Although fig. 2 shows the WiFi module 190, it is understood that it does not belong to the essential constitution of the handset 100, and may be omitted entirely as needed within the scope not changing the essence of the invention.

The processor 130 is a control center of the mobile phone 100, connects various parts of the entire mobile phone by using various interfaces and lines, and performs various functions of the mobile phone 100 and processes data by operating or executing software programs and/or modules stored in the memory 140 and calling data stored in the memory 140, thereby implementing various services based on the mobile phone. Alternatively, processor 130 may include one or more processing units; preferably, the processor 130 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 130.

The embodiment of the present application mainly relates to the built-in physical components of the mobile phone 100, such as the speaker 181, the receiver 182, the microphone 183, and the processor 130. The speaker 181 or the microphone 182 plays audio data, the microphone 183 records audio data, and the processor performs algorithmic analysis on the recorded audio data and determines whether a probability silence fault occurs in the speaker 181 or the microphone 182.

The handset 100 also includes a power supply 120 (e.g., a battery) for powering the various components, which may preferably be logically connected to the processor 130 via a power management system, such that the power management system may manage charging, discharging, and power consumption functions.

Although not shown, the handset 100 may also include a camera, a bluetooth module, and the like.

Fig. 4 shows a schematic flow chart of a method 200 for detecting a probabilistic silent fault according to an embodiment of the present application, where, as shown in fig. 4, the method 200 includes:

s210, the electronic device determines the sound production frequency, wherein the sound production frequency is the sound production frequency corresponding to the electronic device.

Specifically, when a plurality of electronic devices need to perform probabilistic silence detection, for each electronic device, the electronic device may determine its own unique sound frequency, or the electronic device may acquire information of the sound frequency from the outside, thereby realizing that the sound frequencies determined by each electronic device are different.

Optionally, the electronic device determines a sound emission frequency, comprising:

the electronic equipment determines the sound production frequency through the locally stored information.

Optionally, the locally stored information includes a first identification code ID of the electronic device, and the electronic device determines the sound emission frequency according to the first identification code ID.

Alternatively, the electronic device may hold information of IDs including, but not limited to:

(1) international mobile subscriber identity (IMEI) code, including IMEI1 code (ID)_imei1) With IMEI 2 code (ID)_imei2)；

(2) Serial Number (SN) code (ID)_sn)；

(3) Subscriber Identity Module (SIM) card number (ID)_sim)；

(4) WLAN MAC Address (ID)_wlan)；

(5) Bluetooth MAC Address (ID)_bt)；

(6) By ROM version number (ID) of the device_rom) Manufacturer name (ID)_fact) CPU model (ID)_cpu) And other hardware (ID)_oh) Unique identification code (ID) combined by information_comb) (ii) a The combined unique identification code ID_combCan be expressed as shown in equation (1):

ID _comb＝F ₁(ID _rom,ID _fact,ID _cpu,ID _oh) (1)

wherein, F₁For mapping functions, a typical mapping method, but not limited thereto, is shown in equation (2):

ID _comb＝c ₁×ID _rom+c ₂×ID _fact+c ₃×ID _cpu+c ₄×ID _oh (2)

wherein, c₁、c ₂、c ₃And c₄Are weighting coefficients.

(7) The unique identification code ID formed by randomly combining the 6 types_other。

The combined unique identification code ID_otherCan be expressed as shown in equation (3):

ID _other＝F ₂(ID _imei1,ID _imei2,ID _sn,ID _sim,ID _wlan,ID _bt,ID _comb) (3)

wherein, F₂For mapping functions, a typical mapping method, but not limited thereto, is shown in equation (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)

wherein d is_i(i ═ 1, 2.., 7) is a weighting coefficient.

In the embodiment of the present application, the sound emission frequency may be determined by one or a combination of any of the above unique identification codes.

Optionally, the determining, by the electronic device, the sound emission frequency according to the first identification code includes:

the voicing frequency is determined according to the following equation:

f ₀＝F ₃(ID) (5)

wherein, ID is the first identification code of the electronic equipment, and after the first identification code (ID) of the electronic equipment is determined, the sound frequency f is generated according to the unique identification code₀＝F ₃(ID) in which F₃To map ID to f₀The mapping function of (2).

It should be understood that, in the embodiment of the present application, the mapping function F₃Without being limited in particular, it is understood to be within the scope of the embodiments of the present application as long as the function of the sound emission frequency determined by the first identification code is determined.

For example, in one possible implementation, the frequency f of sound emission is determined from a first identification code (ID) of the electronic device₀The mapping function of (c) can be as shown in equation (6), i.e.:

wherein, ID_minThe ID code is set to the minimum allowable value (generally, all values in each code bit are set to 0)_maxThe maximum allowable value of the ID code (generally, all values in the code bits are set to 9). Optionally, the electronic device determines the sound emission frequency according to the first identification code, including:

the electronic equipment reversely replaces the first identification code to obtain a second identification code;

the electronic equipment determines the sounding frequency according to the second identification code.

Generally, the electronic equipment in the same batch has very close probability unique identification codes, if the unique identification codes are directly adopted for frequency mapping, different electronic equipment generates characteristic frequencies with close frequencies, the interference is large, the simultaneous detection of a plurality of mobile phones is influenced, and the identification codes replaced by different electronic equipment have large difference by using a reverse replacement method, so that the generated sound frequency difference is large, and the mutual interference is reduced.

Optionally, the relationship between the second identification code and the sound emission frequency is linear or non-linear.

In a possible implementation manner, the relationship between the second identification code and the sound emission frequency is a linear relationship, and the electronic device obtains the second identification code by reversely replacing the first identification code, and determines the sound emission frequency through the second identification code as follows:

(1) and (4) carrying out reverse replacement on the ID code, namely rearranging each digit of the ID code from low order to high order into an identification code from high order to low order, which is represented as ID-R.

For example, if ID is abcdefg, ID-R is gfedcba.

(2) Setting a lower limit f of a characteristic frequency of sound emission according to an operating noise environment of an electronic device_LowAnd upper limit f_HighThen the sound frequency f of the electronic device₀The calculation can be made according to equation (7), i.e.:

wherein, ID-R_minFor the minimum allowable value of the ID-R code (generally, all values at each code bit are set to 0), the ID-R code_maxThe maximum allowable value of ID-R (generally, all values in code bits are set to 9).

It should be understood that, in the embodiment of the present application, the unique identification code may not be reversely replaced, but may be replaced by a part of the unique identification code, for example, when the ID is abcdefg, the ID-R may also be abcgfed, abcdgfe, and the like, which is not limited in this embodiment of the present application.

Optionally, the method 200 further comprises:

the electronic equipment acquires the information of the sounding frequency determined by other electronic equipment;

if the absolute value of the sounding frequency difference value determined by the electronic device and the sounding frequency difference value determined by any one of the other electronic devices is less than or equal to the first frequency threshold, the method further includes:

the electronic device adjusts the sound emission frequency up to a first frequency threshold or down to the first frequency threshold.

For example, if the predetermined detection period is T, the spectral resolution of the audio data in the frequency domain is 1/T. For securing a plurality of electronic devicesWhen the device is detected simultaneously, no large mutual interference is generated, and the mapping frequency difference delta f between any two electronic devices is ensured to be more than or equal to delta f₀Wherein, Δ f₀Is the frequency resolution threshold.

Alternatively, the frequency resolution threshold may be Δ f₀3 × 1/T. If the sound frequency of the two electronic devices after mapping is relatively close, the frequency difference is smaller than the threshold value delta f₀Then, the frequency of one of the electronic devices can be adjusted slightly, and the sound frequency of the electronic device with smaller frequency is shifted down by Δ f₀Or the upward shift frequency Δ f of the electronic device with a large frequency₀。

According to the method for detecting the probability silent fault, each electronic device is beneficial to timely adjusting the sound production frequency of the electronic device by acquiring the sound production frequency of other electronic devices under the condition that the sound production frequencies of the two electronic devices are close to each other, so that the audio interference among a plurality of electronic devices is prevented.

in the case where a plurality of electronic devices communicate with a control device, the electronic devices receive information of sound emission frequencies transmitted from the control device.

For example, the electronic device may obtain the sound emission frequency from another device, for example, a plurality of electronic devices may communicate with a control device, and when detecting whether the plurality of electronic devices are silent, the control device may transmit the sound emission frequency of each of the plurality of electronic devices to the corresponding electronic device, so that each electronic device determines sound source data according to the different sound emission frequencies obtained from the control device.

It should be understood that, in this embodiment of the application, each electronic device may obtain the sound emission frequency through the control device, and the control device may also store different sound emission frequencies and sound source data corresponding to different sound emission frequencies, and when multiple electronic devices need to detect a silent failure in probability, the control device may directly send the sound source data to the electronic device, or the control device may send the sound emission frequency and the sound source data determined by the sound emission frequency to the electronic device.

the electronic equipment detects a first operation of inputting the sound production frequency by a tester;

in response to the first operation, the voicing frequency is determined.

For example, before the test probability of the plurality of electronic devices is silent, a tester can manually input the corresponding sound production frequency on each electronic device, and ensure that the sound production frequency between any two electronic devices is greater than a certain threshold value, and the electronic device can determine the sound production frequency after detecting the first operation of inputting the sound production frequency by the tester.

According to the method for detecting the probability silent fault, long-time artificial subjective listening detection can be changed into objective detection, the audio fault of the mobile phone can be judged by replacing human ears, and labor cost is saved. The detection can be realized in the environment which can not be monitored manually (high temperature, high humidity, salt fog and other environments), and the detection range is expanded. The detection method solves the problem of mutual audio crosstalk among a plurality of mobile phones, so that the plurality of mobile phones can detect the loudspeaker or the intermittent silent fault of the microphone in parallel, and the detection efficiency is improved.

And S220, the electronic equipment determines sound source data according to the sound production frequency.

Specifically, the sound emission frequency f corresponding to the electronic device is determined according to the method in S410 above₀The electronic device can generate the sound according to the sound frequency f₀Generating a frame of sound source data (duration T), wherein the sound source data can be a single-frequency sine harmonic signal and the frequency of the sine wave is f₀。

It should be understood that the electronic device may be based on the frequency of sound production f₀The process of generating a frame of sound source data can be implemented in the existing manner, and is not described herein for brevity.

And S230, the electronic equipment plays the sound source data through the sound player and collects audio data when the sound source data is played.

For example, as shown in fig. 2, the mobile phone 100 may play the sound source data through the speaker 181, and acquire audio data through the microphone 183A when playing the sound source data, and adjust the audio playing device in the electronic device to output through the speaker 181 under program control when detecting the speaker 181, and acquire the audio data using the microphone 183A close to the speaker 181, play one frame of audio data in each detection period T, and acquire one frame of audio data using a corresponding Microphone (MIC) for subsequent analysis.

For another example, as shown in fig. 3, the mobile phone 100 may play the sound source data through the microphone 182, and acquire audio data through the microphone 183B when playing the sound source data, and adjust the audio playing device in the mobile phone to be output by the microphone 182 under the control of a program when detecting the microphone 182, and acquire the audio data using the microphone 183B close to the microphone 182, and play one frame of audio data in each detection period T, and acquire one frame of data using a corresponding MIC for subsequent analysis.

And S240, when the processing result of the electronic equipment to the audio data meets a preset condition, the electronic equipment determines that the sound player has a probability silent failure.

Specifically, after the audio data is collected, the electronic device may process the audio data, and when a processing result of the audio data satisfies a preset condition, the electronic device may determine that the sound player has a silent failure.

Optionally, before the electronic device processes the audio data, the method further includes:

the audio data is high-pass filtered and windowed.

The high-pass filtering refers to passing the audio data through a designed high-pass filter to filter out low-frequency signals.

For example, when the environment noise below 500Hz is large when the detection is performed in a warm box under a high-temperature and high-humidity environment, the signal directly acquired by the microphone contains high-energy low-frequency environment noise, and the low-frequency environment noise can be filtered by a high-pass filter with the cut-off frequency of 500Hz, which is beneficial to filtering the low-frequency environment noise.

The windowing process refers to a multiplication operation of a frame of audio data with a window function (such as a hamming window, a haining window, and a blackman window) in the time domain, and then a subsequent process is performed to avoid a spectrum leakage, i.e., a phenomenon that a signal is suddenly truncated to increase frequency components in the frequency domain.

Optionally, the processing result of the electronic device on the audio data includes, but is not limited to, one or more of the following:

(1) amplitude of signal

The signal amplitude is obtained by narrowband filtering the audio data by the electronic device in a first frequency range.

For example, one way to process audio data to obtain signal amplitude is as follows: according to the frequency of sound production f₀Determining the pass band frequency range and the stop band frequency range of the filter, designing corresponding pass band fluctuation and stop band attenuation values, and further obtaining the filter order and the filter coefficient of the narrow-band filter. And inputting the audio data to a filter to obtain narrow-band post-filtering data, and performing effective value calculation on the filtering data to finally obtain the signal amplitude.

(2) Correlation coefficient

The correlation coefficient is obtained by performing convolution calculation on the audio data and the sound source data.

For example, one way to process audio data to obtain correlation coefficients is as follows: first, the audio data s is acquired₁And sound source data s₀Then, for sound source data s₀Reverse substitution is carried out to obtain data s'₀To s to₁And s'₀And performing convolution operation and normalization processing to finally obtain a correlation coefficient.

(3) Energy of the first acoustic signal

The first acoustic signal energy is obtained by fast fourier transforming, FFT, of the audio data at the voicing frequency, the first frequency range including the voicing frequency.

For example, a method for processing audio data to obtain a first audio signalEnergy mode is as follows: first, FFT transformation is performed on the audio data to obtain a spectrum of the audio data. Then, the sounding frequency f is obtained according to the duration and the sampling frequency of the audio data₀Corresponding frequency spectrum index is processed, and finally the sound production frequency f is obtained according to the frequency spectrum index₀The spectral energy of (b) is the energy of the first acoustic signal.

Optionally, when the processing result of the electronic device on the audio data satisfies a preset condition, the determining, by the electronic device, that a probabilistic silent failure occurs in the sound player includes:

upon determining that the signal amplitude is less than or equal to the first signal amplitude threshold, the electronic device determines that a probabilistic silent failure of the sound player has occurred.

In particular, the electronic device may be operated at a sound emission frequency f₀And carrying out narrow-band filtering nearby, calculating the signal amplitude after filtering is finished, wherein the signal amplitude has larger difference when the sound player sounds and does not sound, and when the calculated signal amplitude is smaller than or equal to a first signal amplitude threshold value, the electronic equipment determines that the sound player has a probability silent fault.

For example, the first signal amplitude threshold is-20 dB, and the electronic device determines that a probabilistic silent failure of the sound player occurs when the detected first signal amplitude is less than or equal to-20 dB.

when the correlation coefficient is less than a first correlation coefficient threshold, the electronic device determines that a probabilistic silent failure of the sound player has occurred.

For example, the first value is 0.2, and the electronic device determines that the sound player has a probabilistic silent failure when the correlation coefficient determined by the electronic device is less than or equal to 0.2.

Optionally, when the processing result of the electronic device on the audio data meets a preset condition, the determining, by the electronic device, that the sound player has a probability silent failure includes:

in the case that the difference between the first acoustic signal energy and the second acoustic signal energy is less than or equal to a first acoustic signal energy threshold, the electronic device determines that a probabilistic silent failure has occurred in the sound player;

the second sound signal energy is an average value of sound signal energy corresponding to other frequencies in a second frequency range except the sounding frequency, and the second frequency range includes the sounding frequency.

Optionally, the first acoustic signal energy threshold is 15-20 dB.

It should be understood that, in the embodiment of the present application, when determining whether the probability silence occurs in the sound player, the detection may be performed by one or more combinations of the above parameters, for example, the detection may be performed by a combination of a signal amplitude and a correlation coefficient, that is, when the detected signal amplitude is less than or equal to a first signal amplitude threshold and the correlation coefficient is less than a first correlation coefficient threshold, the electronic device determines that the probability silence occurs in the sound player.

In the embodiment of the application, the sound frequency f after filtering is adopted₀The sounding condition is detected by three dimensions, namely the correlation coefficient of the collected audio data and the sound source data, the frequency spectrum distribution characteristic near the sounding frequency and the like, so that the detection accuracy is improved, and meanwhile, the correlation coefficient and the frequency spectrum distribution characteristic near the sounding frequency are less influenced by device difference, so that different types of electronic equipment are different in structural form, sound playing devices and audio recording devices, and different detection thresholds do not need to be set for each piece of electronic equipment.

Fig. 5 shows a schematic flowchart of a method 300 for detecting a probabilistic silent fault according to an embodiment of the present application, as shown in fig. 5, the method 300 is described by taking a mobile phone 100 as an example, an execution subject of the method 300 may be the mobile phone 100, and the method 300 includes:

s310, the unique identification code of the mobile phone 100 is obtained.

Alternatively, the unique identification code of the mobile phone may be one or more combinations of the identification codes in S410.

S320, mapping the unique identification code into sound frequency f₀。

Here, the unique identification code may be mapped to f by a preset mapping function₀Or, the unique identification code may be reversely replaced to obtain a second identification code, and the second identification code is mapped to f through a preset mapping function₀Alternatively, f can also be obtained by other means₀。

S330, according to f₀And generating a frame of sound source data.

It is understood that by f₀The process of determining the audio source data may be the same as the conventional method, and for brevity, will not be described herein again.

S340, playing the sound source data through the speaker 181 or the receiving microphone 182;

s350, the microphone 183 acquires the audio data when playing the sound source data.

Specifically, the sound source data played by the speaker 181 may be collected by the microphone 183A, or the sound source data played by the microphone 182 may be collected by the microphone 183B.

S360, carrying out high-pass filtering on the audio data;

s370, the audio data is subjected to windowing processing.

It should be understood that there is no actual order between S360 and S370.

S381, high-pass filtering and windowing the audio data at f₀Carrying out narrow-band filtering nearby to obtain signal amplitude;

s382, performing convolution calculation on the audio data subjected to the high-pass filtering and windowing and the sound source data to obtain a correlation coefficient;

and S383, carrying out FFT (fast Fourier transform) on the audio data subjected to the high-pass filtering and windowing processing to obtain first sound signal energy.

And S384, judging whether the probability silence occurs in the sound player according to one or more of the amplitude of the sound signal, the correlation coefficient or the energy of the first sound signal.

It should be understood that, in S384, the process of determining whether the probability silence occurs in the sound player according to one or more of the amplitude of the sound signal, the correlation coefficient, or the energy of the first sound signal is the same as that in S240, and for brevity, the description is omitted here.

S390, judging whether a preset detection time length is reached, and if the preset detection time length is reached, finishing the detection; if the preset detection time length is not reached, the process continues to return to S330 for detection.

For example, the preset detection duration of the mobile phone is 8 hours, the period of the silence of the detection probability of the mobile phone is 0.1S, after the detection of each period is completed, the mobile phone will determine whether the detection duration reaches 8 hours, if the detection duration does not reach 8 hours, the mobile phone returns to S330 to continue the detection of the next period, and if the detection duration reaches 8 hours, the detection is finished.

Fig. 6 shows another schematic flow chart of a method 400 for detecting a probabilistic silence fault according to an embodiment of the present application, where a process for determining whether a sound player is probabilistic silent is described in detail in the method 400, and the method 400 includes:

and S410, processing the audio data to obtain a correlation coefficient and a signal amplitude.

It should be understood that S410 is the same as S381 and S382 in the method 300 described above, and therefore, for brevity, will not be described again here.

S420, judging whether the correlation coefficient is smaller than or equal to a first correlation coefficient threshold value;

s421, under the condition that the correlation coefficient is less than or equal to the first correlation coefficient threshold value, determining that the probability silent failure occurs to the sound player;

s422, when the correlation coefficient is greater than the first correlation coefficient threshold, determine whether the correlation coefficient is greater than the second correlation coefficient threshold.

It is to be understood that the second correlation coefficient threshold is greater than the first correlation coefficient threshold.

S423, determining that the audio player is voiced if the correlation coefficient is greater than the second correlation coefficient threshold;

s424, determining whether the signal amplitude is less than or equal to the first signal amplitude threshold value when the correlation coefficient is less than the second correlation coefficient threshold value;

s425, in case the signal amplitude is less than or equal to the first signal threshold, determining that a probability silent failure of the sound player occurs;

s426, in case the signal amplitude is greater than the first signal threshold, determining that the sound player is voiced.

Fig. 7 shows another schematic flow chart of a method 500 for detecting a probabilistic silence fault according to an embodiment of the present application, where another determination process for determining whether a sound player is probabilistic silent is described in detail in the method 500, and the method 500 includes:

and S510, processing the audio data to obtain a correlation coefficient and first acoustic signal energy.

It should be understood that S510 is the same as S381 and S383 in the above-described method 300, and therefore, for brevity, will not be described again.

S520, judging whether the correlation coefficient is smaller than or equal to a first correlation coefficient threshold value;

s521, determining that the probability of silent failure of the sound player is generated under the condition that the correlation coefficient is less than or equal to the first correlation coefficient threshold;

s522, if the correlation coefficient is greater than the first correlation coefficient threshold, it is determined whether the correlation coefficient is greater than the second correlation coefficient threshold.

S523, determining that the sound player is voiced when the correlation coefficient is greater than the relationship of the second correlation coefficient threshold;

s524, determining whether the difference between the first acoustic signal energy and the second acoustic signal energy is less than or equal to the acoustic signal energy threshold when the correlation coefficient is less than the second correlation coefficient threshold.

It should be understood that the first and second acoustic signal energies are the same as those described in the above embodiments, and therefore, for brevity, are not described again.

S525, under the condition that the difference value is less than or equal to the energy threshold value of the sound signal, determining that the probability of the soundless fault of the sound player occurs;

s526, in case that the difference is greater than the acoustic signal energy threshold, it is determined that the sound player is voiced.

In the embodiment of the application, the sounding condition is detected by adopting the collected correlation coefficient of the audio data and the sound source data and three dimensions such as the spectral distribution characteristic near the sounding frequency, and the accuracy of detection is improved.

Fig. 8 shows a schematic diagram of detecting multiple mobile phones according to an embodiment of the present application. The detection is carried out in an incubator in a high-temperature and high-humidity environment. Firstly, the detection programs are respectively put into 5 mobile phones (mobile phones A, B, C, D and E), and the 5 mobile phones are put into an incubator in a normal-temperature and normal-humidity environment before detection. The constant-speed temperature rise and humidification operation is carried out on the incubator, when the temperature and the humidity in the incubator reach the specified temperature and humidity indexes, the humidity and the temperature in the incubator are kept unchanged, and at the moment, 5 mobile phones are respectively started for detection.

FIG. 9 shows the detection results of 5 mobile phones such as A, B, C, D, E in the time duration of 0-120 s when they are simultaneously sounding and detecting, wherein the mobile phone A, B, C, D, E is artificially muted to simulate the sounding failure of the device at 30-33 s, 45-48 s, 60-63 s, 75-78 s, and 90-93 s, respectively. Detection was performed every 0.1 s. The detection results are as follows, wherein a detection result of 1 represents normal sounding, and a detection result of 0 represents sounding failure.

As can be seen from the implementation effect diagram, at the moment of artificial interruption, the interruption is detected by the method for detecting the probability silent fault of the embodiment of the application.

The method for detecting a probabilistic silent fault according to the embodiment of the present application is described in detail above with reference to fig. 1 to 9, and the apparatus for detecting a probabilistic silent fault according to the embodiment of the present application is described below with reference to the accompanying drawings. It should be understood that the technical features described in the method embodiments are equally applicable to the following apparatus embodiments.

Fig. 10 shows a schematic block diagram of an apparatus 600 for detecting a probabilistic silent fault according to an embodiment of the present application, and as shown in fig. 10, the apparatus 600 includes:

the processing module 610 is configured to determine a sound emission frequency corresponding to the electronic device;

the processing module 610 is further configured to generate sound source data according to the sound emission frequency;

a sound playing module 620, configured to play the sound source data;

a sound collection module 630, configured to collect audio data when the sound source data is played;

the processing module 610 is further configured to process the audio data;

when the processing result of the processing module 610 for the audio data meets the preset condition, the processing module 610 is further configured to determine that a probability silent failure occurs in the sound player.

Optionally, the processing module 610 is specifically configured to:

acquiring a first identification code, wherein the first identification code is an identification code corresponding to the electronic equipment;

and determining the sounding frequency according to the first identification code.

Optionally, the first identification code is a unique identification code of the electronic device, and the processing module 610 is specifically configured to:

reversely replacing the unique identification code to obtain a second identification code;

and determining the sounding frequency according to the second identification code.

Optionally, the second identification code is in a linear or non-linear relationship with the sound emission frequency.

Optionally, the second identification code and the sound frequency are in a linear relationship, wherein the processing module is specifically configured to:

the voicing frequency is determined according to the following equation:

Optionally, the first identification code is composed of one or more of an international mobile subscriber identity IMEI code, a serial number SN code, a subscriber identity SIM code, a wireless local area network WLAN MAC address, a bluetooth MAC address, or an android Pseudo-unique identification code Pseudo-unique ID.

Optionally, the processing result comprises one or more of signal amplitude, correlation coefficient or first acoustic signal energy;

the signal amplitude is obtained by performing narrow-band filtering on the audio data in a first frequency range, the correlation coefficient is obtained by performing convolution calculation on the audio data and the sound source data, the first acoustic signal energy is obtained by performing Fast Fourier Transform (FFT) on the audio data at the sounding frequency, and the first frequency range includes the sounding frequency.

Optionally, the processing result includes the correlation coefficient, and the processing module 610 is specifically configured to:

in the case where 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.

Optionally, the processing result includes the correlation coefficient and the signal amplitude, and the processing module 610 is specifically configured to:

determining that the correlation coefficient is greater than or equal to a first value and less than or equal to a second value;

in the case where the signal amplitude is less than or equal to the third value, it is determined that the sound player has a probability of silent failure.

Optionally, the processing result includes the correlation coefficient and the first acoustic signal energy, and the processing module 610 is specifically configured to:

determining that the sound player has a probability of silent failure if the difference between the first sound signal energy and the second sound signal energy is less than or equal to a fourth value;

Optionally, the processing module 610 is further configured to high-pass filter and window the audio data before determining that the probability silence failure occurs in the sound player.

It should be understood that the apparatus 600 according to the embodiment of the present application may be configured to perform the method of the foregoing method embodiment, for example, the method in fig. 4 to fig. 7, and the above and other management operations and/or functions of the respective modules in the apparatus 600 are respectively for implementing the corresponding steps of the method of the foregoing method embodiment, so that the beneficial effects in the foregoing method embodiment may also be achieved, and for brevity, no repeated description is provided here.

It should be further understood that the modules in the apparatus 600 may be implemented in software and/or hardware, and are not particularly limited thereto. In other words, the apparatus 600 is presented in the form of a functional module. As used herein, a "module" may refer to an Application Specific Integrated Circuit (ASIC), an electronic circuit, a processor and memory that execute one or more software or firmware programs, an integrated logic circuit, and/or other devices that may provide the described functionality.

Alternatively, in a simple embodiment, those skilled in the art will appreciate that the apparatus 600 may take 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 control the sound player 710 to implement sound playing and the sound collector 720 to implement sound collection by executing computer programs stored in the memory. Alternatively, when the apparatus 600 is a chip, then the functions and/or implementation procedures of transceiving involved in the apparatus 600 may also be implemented by pins or interface circuits, etc. Optionally, the memory is a storage unit in the chip, such as a register, a cache, and the like, and the storage unit may also be a storage unit located outside the chip in the computer device, such as the memory 740 in fig. 11.

Fig. 11 shows a schematic block diagram of an apparatus 700 for detecting a probabilistic silent fault according to an embodiment of the present application, and as shown in fig. 11, the apparatus 700 includes a sound player 710, a sound collector 720, a memory 730, and a processor 740, wherein one or more computer programs are stored in the memory 730, and the one or more computer programs include instructions. The instructions, when executed by the processor 730, cause the apparatus 700 to:

determining the corresponding sound production frequency of the electronic equipment;

generating sound source data according to the sound production frequency;

playing the sound source data through the sound player, and collecting audio data when the sound source data is played;

and when the processing result of the audio data meets a preset condition, determining that the probability of silent failure of the sound player occurs.

Optionally, when executed by the processor 730, the instructions cause the apparatus 700 to specifically perform the following steps:

Optionally, the first identification code is a unique identification code of the electronic device, and when executed by the processor 730, the apparatus 700 specifically performs the following steps:

Optionally, the second identification code is linear with the sound frequency, wherein the instructions, when executed by the processor 730, cause the apparatus 700 to specifically perform the following steps:

the voicing frequency is determined according to the following equation:

Optionally, the processing result includes the correlation coefficient, and when executed by the processor 730, the instructions cause the apparatus 700 to specifically perform the following steps:

Optionally, the processing result includes the correlation coefficient and the signal amplitude, and when executed by the processor 730, the instructions cause the apparatus 700 to specifically perform the following steps:

Optionally, the processing result includes the correlation coefficient and the first acoustic signal energy, and when executed by the processor 730, the instructions cause the apparatus 700 to specifically perform the following steps:

the audio data is high-pass filtered and windowed.

Alternatively, in a possible implementation manner, the apparatus 600 or the apparatus 700 may be a terminal device.

For example, the apparatus 700 may correspond to the mobile phone 100 of fig. 1, the processor 730 may correspond to the processor 130 of fig. 1, the memory 140 may correspond to the memory 140 of fig. 1, the sound player 710 may correspond to the speaker 181 or the microphone 182 of fig. 1, and the sound collector may correspond to the microphone 183 of fig. 1.

In the embodiment of the present application, it should be noted that the above method embodiments of the embodiment of the present application may be applied to a processor, or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method embodiments may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The processor may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A 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 connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.

It will be appreciated that the memory in the embodiments of the subject application can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable EPROM (EEPROM), or a flash memory. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), double data rate SDRAM, enhanced SDRAM, SLDRAM, Synchronous Link DRAM (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.

It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. It should be understood that, in the various embodiments of the present application, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

Additionally, the terms "system" and "network" are often used interchangeably herein. The term "and/or" herein is only one kind of association relationship describing the associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

It should be understood that in the embodiment of the present application, "B corresponding to a" means that B is associated with a, from which B can be determined. It should also be understood that determining B from a does not mean determining B from a alone, but may be determined from a and/or other information.

The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product may include one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic disk), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

A method for detecting a probabilistic silent failure, applied to an electronic device including a sound player, comprising:

the electronic equipment determines the corresponding sound production frequency of the electronic equipment;

the electronic equipment generates sound source data according to the sound production frequency;

the electronic equipment plays the sound source data through the sound player and collects audio data when playing the sound source data;

and when the processing result of the electronic equipment on the audio data meets a preset condition, the electronic equipment determines that the probability silent fault occurs to the sound player.
The method of claim 1, wherein the electronic device determines a corresponding sound emission frequency of the electronic device, comprising:

the electronic equipment acquires a first identification code, wherein the first identification code is an identification code corresponding to the electronic equipment;

and the electronic equipment determines the sound production frequency according to the first identification code.
The method of claim 2, wherein the first identification code is a unique identification code of the electronic device, and wherein determining the frequency of the spoken utterance from the first identification code comprises:

the electronic equipment reversely replaces the unique identification code to obtain a second identification code;

and the electronic equipment determines the sounding frequency according to the second identification code.
The method of claim 3, wherein the second identification code is linearly or non-linearly related to the frequency of the spoken utterance.
The method according to claim 3 or 4, wherein the second identification code is linear with the sound emission frequency, wherein the determining the sound emission frequency according to the second identification code comprises:

the electronic device determines the sound emission frequency according to the following formula:

wherein f is₀For the sound emission frequency, ID-R is the second identification code, f_HighIs a first sound emission frequency threshold, f_LowAs second voicing frequency threshold, ID-R_maxFor maximum allowable of said second identification code, ID-R_minThe first utterance frequency threshold is greater than the second utterance frequency threshold for a minimum allowed value of the second identification code.
The method according to any of the claims 2 to 5, characterized in that the first identification code consists of one or more of an international mobile subscriber identity, IMEI code, a serial number, SN, a subscriber identity, SIM, a wireless local area network, WLAN, MAC, Bluetooth, MAC address or an android Pseudo-unique identification code, Pseudo-unique ID.
The method of any one of claims 1 to 6, wherein the processing result comprises one or more of a signal amplitude, a correlation coefficient, or a first acoustic signal energy;

the signal amplitude is obtained by performing narrow-band filtering on the audio data in a first frequency range, the correlation coefficient is obtained by performing convolution calculation on the audio data and the sound source data, the first acoustic signal energy is obtained by performing Fast Fourier Transform (FFT) on the audio data at the sounding frequency, and the first frequency range includes the sounding frequency.
The method according to claim 7, wherein the processing result comprises the correlation coefficient, and the determining, by the electronic device, that the sound player has a probability of silent failure when the processing result of the electronic device on the audio data satisfies a preset condition comprises:

in the case where the correlation coefficient is less than or equal to a first value, the electronic device determines that a probability silent failure has occurred in the sound player.
The method of claim 7, wherein the processing result comprises the correlation coefficient and the signal amplitude, and wherein the determining, by the electronic device, that the sound player has a probabilistic silent failure when the processing result of the electronic device on the audio data satisfies a preset condition comprises:

the electronic device determines that the correlation coefficient is greater than or equal to a first value and less than or equal to a second value;

in the case where the signal amplitude is less than or equal to a third value, the electronic device determines that a probabilistic silent failure has occurred with the sound player.
The method of claim 7, wherein the processing result comprises the correlation coefficient and the first sound signal energy, and wherein the determining, by the electronic device, that the sound player has a probabilistic silent failure when the processing result of the electronic device on the audio data satisfies a preset condition comprises:

the electronic device determines that the correlation coefficient is greater than or equal to a first value and less than or equal to a second value;

in the case that the difference value between the first sound signal energy and the second sound signal energy is smaller than or equal to a fourth numerical value, the electronic equipment determines that the sound player has a probability silent fault;

the second sound signal energy is an average value of sound signal energy corresponding to other frequencies in a second frequency range except the sound production frequency, and the second frequency range comprises the sound production frequency.
The method of any of claims 1-10, wherein before the electronic device determines that the sound player has a probabilistic silent failure, the method further comprises:

the electronic device high-pass filters and windows the audio data.
A device for detecting probability silent failure is characterized in that the device comprises a processor, a sound player and a sound collector, wherein,

the processor is used for determining the corresponding sound production frequency of the device;

the processor is further used for generating sound source data according to the sound production frequency;

the sound player is used for playing the sound source data;

the sound collector is used for collecting audio data when the sound source data are played;

and when the processing result of the processor on the audio data meets a preset condition, the processor is also used for determining that the probability silent fault occurs to the sound player.
The apparatus of claim 12, wherein the processor is specifically configured to:

acquiring a first identification code, wherein the first identification code is an identification code corresponding to the device;

and determining the sound production frequency according to the first identification code.
The apparatus of claim 13, wherein the first identification code is a unique identification code of the apparatus, and wherein the processor is configured to:

reversely replacing the unique identification code to obtain a second identification code;

and determining the sounding frequency according to the second identification code.
The device of claim 14, wherein the second identification code is linearly or non-linearly related to the frequency of the spoken utterance.
The device according to claim 14 or 15, wherein the second identification code is linearly related to the sound emission frequency, and wherein the processor is specifically configured to:

determining the voicing frequency according to the following formula:

wherein f is₀For the sound emission frequency, ID-R is the second identification code, f_HighIs a first sound emission frequency threshold, f_LowAs second voicing frequency threshold, ID-R_maxFor maximum allowable of said second identification code, ID-R_minThe first utterance frequency threshold is greater than the second utterance frequency threshold for a minimum allowed value of the second identification code.
The apparatus according to any of the claims 13 to 16, wherein the first identification code consists of one or more of an international mobile subscriber identity, IMEI, code, serial number, SN, subscriber identity, SIM, wireless local area network, WLAN, MAC, address, bluetooth, or Pseudo-unique identification code, pseudounique-unique ID.
The apparatus of any one of claims 12 to 17, wherein the processing result comprises one or more of a signal amplitude, a correlation coefficient, or a first acoustic signal energy;

the signal amplitude is obtained by performing narrow-band filtering on the audio data in a first frequency range, the correlation coefficient is obtained by performing convolution calculation on the audio data and the sound source data, the first acoustic signal energy is obtained by performing Fast Fourier Transform (FFT) on the audio data at the sounding frequency, and the first frequency range includes the sounding frequency.
The apparatus as claimed in claim 18, wherein the processing result comprises the correlation coefficient, and the processor is specifically configured to:

and determining that the probability of silent failure of the sound player is generated under the condition that the correlation coefficient is less than or equal to a first numerical value.
The apparatus of claim 18, wherein the processing result comprises the correlation coefficient and the signal amplitude, and wherein the processor is specifically configured to:

determining that the correlation coefficient is greater than or equal to a first value and less than or equal to a second value;

determining that the sound player has a probabilistic silent failure if the signal amplitude is less than or equal to a third value.
The apparatus of claim 18, wherein the processing result comprises the correlation coefficient and the first acoustic signal energy, and wherein the processor is specifically configured to:

determining that the correlation coefficient is greater than or equal to a first value and less than or equal to a second value;

determining that the sound player has a probabilistic silent failure if the difference between the first and second acoustic signal energies is less than or equal to a fourth value;

the second sound signal energy is an average value of sound signal energy corresponding to other frequencies in a second frequency range except the sound production frequency, and the second frequency range comprises the sound production frequency.
The method of any of claims 12 to 21, wherein the processor is further configured to high pass filter and window the audio data prior to determining that the sound player is likely to be silent.
A computer-readable storage medium comprising instructions which, when executed on a computer, cause the computer to perform the method of any of claims 1-11.
A computer program product which, when run on a computer, causes the computer to perform the method of any one of the preceding claims 1-11.