Method for detecting vibration abnormity of Android mobile phone

Abstract

The invention relates to the technical field of mobile phone anomaly detection, in particular to an Android mobile phone vibration anomaly detection method, which comprises the following steps: acquiring data generated when a mobile phone motor vibrates based on a vibration detection sensor attached to the surface of a mobile phone; based on the obtained original data, peak top and peak valley values are separated according to the vibration time period, the vibration acquisition frequency and time period are converted into vibration amplitude through an algorithm, the vibration amplitude is expressed in a sinusoidal waveform, and whether the mobile phone motor vibrates or not and detection data of the vibration strength value are evaluated by comparing the vibration amplitude with the vibration speed, displacement and time curve of the mobile phone motor; and returning a judgment result to the server, and recycling and evaluating. According to the method, the motor evaluation model is established based on the average amplitude, the vibration speed and the vibration displacement, and the state of the motor can be accurately evaluated, so that the data detected by the mobile phone anomaly is more accurate, and better use prospects and commercial values are brought.

Description

Technical Field

[0001] The invention belongs to the technical field of mobile phone abnormality detection, and specifically relates to a method for detecting abnormal vibration of an Android mobile phone. Background Art

[0002] Mobile phone anomaly detection technology plays an important role in modern smartphones. It is mainly used to monitor the health status of the device, protect user data security, improve device performance and extend device life. Smartphones may experience performance degradation during operation, such as system slowdown, application crash, etc. Anomaly detection can monitor the usage of the device's CPU, memory, storage and other resources, and issue warnings when anomalies occur. By monitoring the status of the phone's hardware components, potential hardware failures can be detected in a timely manner to help users perform maintenance or repairs as soon as possible. Anomaly detection can identify potential malware or viruses. These malicious programs may cause abnormal device behavior or data leakage. By monitoring application behavior and network traffic, anomaly detection technology can identify abnormal data access patterns to prevent data leakage and privacy infringement.

[0003] Existing mobile phone anomaly detection technologies are mostly used for virus detection and cannot judge anomalies based specifically on motor vibration and vibration displacement data, resulting in low detection efficiency. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method for detecting abnormal vibration of an Android mobile phone to solve the above technical problems.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for detecting abnormal vibration of an Android mobile phone, the detection method comprising:

[0006] S1: collects data generated by the vibration of the mobile phone motor based on the vibration detection sensor attached to the surface of the mobile phone;

[0007] S2: Based on the acquired raw data, the peak and valley values ​​are separated according to the vibration time period, and the vibration acquisition frequency and time period are converted into amplitude through an algorithm, which is represented by a sine waveform. The vibration speed, displacement and time curve of the mobile phone motor are compared with the amplitude value to evaluate whether the mobile phone motor is vibrating and the detection data of the vibration intensity value;

[0008] S3: Send the judgment result back to the server and recover the estimated price.

[0009] Preferably, the specific steps of S1 are:

[0010] Install the vibration detection sensor on the surface of the mobile phone and set the sampling frequency;

[0011] Record the vibration signal data output by the sensor when the mobile phone motor is running;

[0012] Apply a low-pass filter to remove high-frequency noise and obtain a smooth vibration signal;

[0013] Subtract the DC component of the signal to ensure that the data is centered on the vibration portion.

[0014] Preferably, a peak detection algorithm is used to identify peaks and valleys in the vibration signal;

[0015] Among them, the peak detection algorithm formula is:

[0016] xpeak(t)=armax(x(t)in window)

[0017] Where x(t) represents the vibration signal value at time t, xpeak(t) represents the peak value in the window at time t, and armax is the operator;

[0018] Calculate the average amplitude from the peak and valley values;

[0019] The average amplitude is calculated as:

[0020]

[0021] Where A is the average amplitude, x max is the vibration peak value, x min is the peak-to-valley value;

[0022] Convert the amplitude to a sine wave;

[0023] Among them, the sine waveform conversion formula is:

[0024]

[0025] Where x(t) is the vibration signal, ω is the angular frequency, is the phase, A is the average amplitude;

[0026] Calculate vibration velocity and displacement;

[0027] The vibration velocity is calculated based on the amplitude and frequency, where the vibration velocity calculation formula is:

[0028] v=2πfA

[0029] In the formula, v is the vibration velocity, f is the vibration frequency, π is the circumference of a circle, and A is the average amplitude;

[0030] The vibration velocity is calculated based on the amplitude and frequency, where the vibration displacement is calculated as:

[0031]

[0032] Where d is the vibration displacement, ω is the angular frequency, f is the frequency of vibration, π is the circumference of a circle, and A is the average amplitude.

[0033] Preferably, a motor evaluation model is established based on average amplitude, vibration velocity and vibration displacement;

[0034] Based on the motor evaluation formula, evaluate whether the mobile phone motor is vibrating;

[0035] Evaluate the vibration intensity value based on the motor evaluation formula.

[0036] Preferably, based on the average amplitude, vibration velocity and vibration displacement, a motor evaluation formula is established, which specifically includes:

[0037] Obtain average amplitude, vibration velocity and vibration displacement data;

[0038] Calculate the weights of average amplitude, vibration velocity and vibration displacement data;

[0039] The weight calculation formula is:

[0040] W=(X T X) -1 X T Y

[0041] Where W is the vector of weight coefficients, X is the matrix containing independent variables, and Y is the vector of target variables;

[0042] Establish a comprehensive scoring model for motor assessment;

[0043] Among them, the motor evaluation comprehensive scoring model formula is:

[0044] S=W1·A+W2·v+W3·d

[0045] Among them, S is the total score, W1W2W3 are the weight coefficients of average amplitude, vibration velocity and vibration displacement respectively, A is the average amplitude, v is the vibration velocity, and d is the vibration position.

[0046] Preferably, based on the motor evaluation formula, evaluating whether the mobile phone motor is vibrating specifically includes:

[0047] Set the threshold of S;

[0048] Determine whether the intensity and range of the vibration generated by the phone are within the expected threshold. If the S value is outside the normal range, it indicates that the risk of a problem is high and exception handling is required.

[0049] Preferably, based on the motor evaluation formula, evaluating the vibration intensity value specifically includes:

[0050] According to the vibration intensity value and spectrum analysis results, fault diagnosis is performed, including imbalance, misalignment and bearing failure;

[0051] Develop a maintenance and repair schedule to reduce vibration and increase motor operating efficiency and life.

[0052] Preferably, the judgment result is transmitted back to the server, and the recycling valuation specifically includes:

[0053] Generate a report containing vibration intensity values, analysis conclusions and suggestions based on data analysis results;

[0054] Encapsulate the assessment report and related data into a data package, ensuring that the data package contains all necessary information, including timestamp, device ID and assessment results;

[0055] Encrypt and compress data to ensure data security and transmission efficiency;

[0056] Use the API interface to send data packets to the server through the network;

[0057] The server receives the transmitted data packet;

[0058] Decrypt and decompress the received data packets and extract the evaluation results;

[0059] The evaluation results are stored in a database.

[0060] Preferably, an evaluation process is performed based on the received data to assess the status of the equipment and possible maintenance needs.

[0061] Generate Recycling Valuation Report: Generate a detailed report based on the valuation results, including recommended maintenance measures and budget.

[0062] The recycling valuation results are returned to the client through the corresponding protocol.

[0063] Preferably, the assessment results and recycling valuation report are sent to the user via email, SMS and application notification;

[0064] Allow users to provide feedback on the report and ask further questions;

[0065] Regularly monitor the performance of data transmission and processing systems and update the systems based on demand and technological advances.

[0066] Compared with the prior art, the present invention has the following beneficial effects:

[0067] This application establishes a motor evaluation model based on average amplitude, vibration velocity and vibration displacement, which can accurately evaluate the status of the motor, thereby making the data detected by the mobile phone abnormality more accurate, bringing better usage prospects and commercial value. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is a step flow framework diagram of the present invention. DETAILED DESCRIPTION

[0069] In order to better understand the present application, a more detailed description will be made of various aspects of the present application with reference to the accompanying drawings. It should be understood that these detailed descriptions are only descriptions of exemplary embodiments of the present application, and are not intended to limit the scope of the present application in any way. Throughout the specification, the same reference numerals refer to the same elements. The expression "and / or" includes any and all combinations of one or more of the associated listed items.

[0070] In the accompanying drawings, the size, dimensions and shapes of the elements have been slightly adjusted for ease of illustration. The drawings are for illustration only and are not strictly drawn to scale. As used herein, the terms "substantially", "approximately" and similar terms are used as terms of approximation, not as terms of degree, and are intended to illustrate the inherent deviations in measurements or calculations that would be recognized by a person of ordinary skill in the art. In addition, in this application, the order in which the processing of each step is described does not necessarily represent the order in which these processes occur in actual operation, unless otherwise specified or can be derived from the context.

[0071] It should also be understood that expressions such as "include", "including", "have", "contain" and / or "comprising" are open rather than closed expressions in this specification, which indicate the presence of the stated features, elements and / or components, but do not exclude the presence of one or more other features, elements, components and / or combinations thereof. In addition, when expressions such as "at least one of..." appear after a list of listed features, they modify the entire list of features rather than just the individual elements in the list. In addition, when describing embodiments of the present application, "may" is used to mean "one or more embodiments of the present application". And, the term "exemplary" is intended to refer to an example or illustration.

[0072] Unless otherwise defined, all words (including engineering terms and scientific and technological terms) used in this article have the same meaning as commonly understood by ordinary technical citizens in the field to which this application belongs. It should also be understood that, unless explicitly stated in this application, words defined in commonly used dictionaries should be interpreted as having the same meaning as their meaning in the context of the relevant technology, and should not be interpreted in an idealized or overly formal sense.

[0073] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0074] The present invention provides a technical solution: a method for detecting abnormal vibration of an Android mobile phone, the detection method comprising:

[0075] S1: collects data generated by the vibration of the mobile phone motor based on the vibration detection sensor attached to the surface of the mobile phone;

[0076] S2: Based on the acquired raw data, the peak and valley values ​​are separated according to the vibration time period, and the vibration acquisition frequency and time period are converted into amplitude through an algorithm, which is represented by a sine waveform. The vibration speed, displacement and time curve of the mobile phone motor are compared with the amplitude value to evaluate whether the mobile phone motor is vibrating and the detection data of the vibration intensity value;

[0077] S3: Send the judgment result back to the server and recover the estimated price.

[0078] Furthermore, the specific steps of S1 are:

[0079] Install the vibration detection sensor on the surface of the mobile phone and set the sampling frequency;

[0080] Record the vibration signal data output by the sensor when the mobile phone motor is running;

[0081] Apply a low-pass filter to remove high-frequency noise and obtain a smooth vibration signal;

[0082] Subtract the DC component of the signal to ensure that the data is centered on the vibration portion.

[0083] Furthermore, a peak detection algorithm is used to identify peaks and valleys in the vibration signal;

[0084] Among them, the peak detection algorithm formula is:

[0085] xpeak(t)=armax)x(t)in window)

[0086] Where x(t) represents the vibration signal value at time t, xpeak(t) represents the peak value in the window at time t, and armax is the operator;

[0087] Calculate the average amplitude from the peak and valley values;

[0088] The average amplitude is calculated as:

[0089]

[0090] Where A is the average amplitude, x max is the vibration peak value, x min is the peak-to-valley value;

[0091] Convert the amplitude to a sine wave;

[0092] Among them, the sine waveform conversion formula is:

[0093]

[0094] Where x(t) is the vibration signal, ω is the angular frequency, is the phase, A is the average amplitude;

[0095] Calculate vibration velocity and displacement;

[0096] The vibration velocity is calculated based on the amplitude and frequency, where the vibration velocity calculation formula is:

[0097] v=2πfA

[0098] In the formula, v is the vibration velocity, f is the vibration frequency, π is the circumference of a circle, and A is the average amplitude;

[0099] The vibration velocity is calculated based on the amplitude and frequency, where the vibration displacement is calculated as:

[0100]

[0101] Where d is the vibration displacement, ω is the angular frequency, f is the frequency of vibration, π is the circumference of a circle, and A is the average amplitude.

[0102] Furthermore, a motor evaluation model is established based on the average amplitude, vibration velocity and vibration displacement;

[0103] Based on the motor evaluation formula, evaluate whether the mobile phone motor is vibrating;

[0104] Evaluate the vibration intensity value based on the motor evaluation formula.

[0105] Furthermore, based on the average amplitude, vibration velocity and vibration displacement, a motor evaluation formula is established, including:

[0106] Obtain average amplitude, vibration velocity and vibration displacement data;

[0107] Calculate the weights of average amplitude, vibration velocity and vibration displacement data;

[0108] The weight calculation formula is:

[0109] W=(X T X) -1 X T Y

[0110] Where W is the vector of weight coefficients, X is the matrix containing independent variables, and Y is the vector of target variables;

[0111] Establish a comprehensive scoring model for motor assessment;

[0112] Among them, the motor evaluation comprehensive scoring model formula is:

[0113] S=W1·A+W2·v+W3·d

[0114] Among them, S is the total score, W1W2W3 are the weight coefficients of average amplitude, vibration velocity and vibration displacement respectively, A is the average amplitude, v is the vibration velocity, and d is the vibration position.

[0115] Furthermore, based on the motor evaluation formula, the evaluation of whether the mobile phone motor is vibrating specifically includes:

[0116] Set the threshold of S;

[0117] Determine whether the intensity and range of the vibration generated by the phone are within the expected threshold. If the S value is outside the normal range, it indicates that the risk of a problem is high and exception handling is required.

[0118] Furthermore, based on the motor evaluation formula, the vibration intensity values ​​evaluated specifically include:

[0119] According to the vibration intensity value and spectrum analysis results, fault diagnosis is performed, including imbalance, misalignment and bearing failure;

[0120] Develop a maintenance and repair schedule to reduce vibration and increase motor operating efficiency and life.

[0121] Furthermore, the judgment result is sent back to the server, and the recycling valuation specifically includes:

[0122] Generate a report containing vibration intensity values, analysis conclusions and suggestions based on data analysis results;

[0123] Encapsulate the assessment report and related data into a data package, ensuring that the data package contains all necessary information, including timestamp, device ID and assessment results;

[0124] Encrypt and compress data to ensure data security and transmission efficiency;

[0125] Use the API interface to send data packets to the server through the network;

[0126] The server receives the transmitted data packet;

[0127] Decrypt and decompress the received data packets and extract the evaluation results;

[0128] The evaluation results are stored in a database.

[0129] Furthermore, an evaluation process is performed based on the received data to assess the status of the equipment and possible maintenance needs.

[0130] Generate Recycling Valuation Report: Generate a detailed report based on the valuation results, including recommended maintenance measures and budget.

[0131] The recycling valuation results are returned to the client through the corresponding protocol.

[0132] Furthermore, the assessment results and recycling valuation report are sent to the user via email, SMS and app notifications;

[0133] Allow users to provide feedback on the report and ask further questions;

[0134] Regularly monitor the performance of data transmission and processing systems and update the systems based on demand and technological advances.

[0135] The use steps of the present invention are:

[0136] Step 1: Install the vibration detection sensor on the surface of the mobile phone and set the sampling frequency;

[0137] Step 2: Record the vibration signal data output by the sensor when the mobile phone motor is running;

[0138] Step 3: Apply a low-pass filter to remove high-frequency noise and obtain a smooth vibration signal;

[0139] Step 4: Apply a low-pass filter to remove high-frequency noise and obtain a smooth vibration signal;

[0140] Step 5: Subtract the DC component of the signal to ensure that the data is concentrated in the vibration part;

[0141] Step 6: Use peak detection algorithm to identify peaks and valleys in the vibration signal;

[0142] Step 7: Calculate the average amplitude from the peak and valley values;

[0143] Step 8: Calculate vibration velocity and displacement;

[0144] Step 9: Establish a motor evaluation model based on the average amplitude, vibration velocity and vibration displacement;

[0145] Step 10: Based on the motor evaluation formula, evaluate whether the mobile phone motor is vibrating;

[0146] Step 11: Evaluate the vibration intensity value based on the motor evaluation formula;

[0147] Step 12: Send the judgment result back to the server and recover the estimated price;

[0148] Step 13: Perform valuation processing based on the received data to assess the equipment status and possible maintenance needs;

[0149] Step 14: Generate a recycling valuation report, and generate a detailed report based on the valuation results, including recommended maintenance measures and budget;

[0150] Step 15: Return the recycling valuation result to the client through the corresponding protocol;

[0151] Step 16: Send the assessment results and recycling valuation report to the user via email, SMS and app notification;

[0152] Step 17: Regularly monitor the performance of data transmission and processing systems and update the systems based on demand and technological advances.

[0153] According to the above steps, the advantages of the present invention are as follows:

[0154] This application uses a peak detection algorithm to identify the peaks and valleys in the vibration signal, then calculates the average amplitude from the peak and valley values, calculates the vibration velocity and displacement, and finally establishes a motor evaluation model based on the average amplitude, vibration velocity and vibration displacement. This can accurately evaluate the state of the motor, thereby making the data detected by the mobile phone abnormality more accurate, bringing better usage prospects and commercial value.

[0155] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0156] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for detecting abnormal vibration of an Android mobile phone, characterized in that: Detection methods include: S1: collects data generated by the vibration of the mobile phone motor based on the vibration detection sensor attached to the surface of the mobile phone; S2: Based on the acquired raw data, the peak and valley values ​​are separated according to the vibration time period, and the vibration acquisition frequency and time period are converted into amplitude through an algorithm, which is represented by a sine waveform. The vibration speed, displacement and time curve of the mobile phone motor are compared with the amplitude value to evaluate whether the mobile phone motor is vibrating and the detection data of the vibration intensity value; S3: Send the judgment result back to the server and recover the estimated price.

2. The method for detecting abnormal vibration of an Android mobile phone according to claim 1, characterized in that: The specific steps of S1 are: Install the vibration detection sensor on the surface of the mobile phone and set the sampling frequency; Record the vibration signal data output by the sensor when the mobile phone motor is running; Apply a low-pass filter to remove high-frequency noise and obtain a smooth vibration signal; Subtract the DC component of the signal to ensure that the data is centered on the vibration portion.

3. The method for detecting abnormal vibration of an Android mobile phone according to claim 1, characterized in that: The specific steps of S2 are: Use peak detection algorithms to identify peaks and valleys in vibration signals; Among them, the peak detection algorithm formula is: xpeak(t)=armax(x(t)in window) Where x(t) represents the vibration signal value at time t, xpeak(t) represents the peak value in the window at time t, and armax is the operator; Calculate the average amplitude from the peak and valley values; The average amplitude is calculated as: Where A is the average amplitude, x max is the vibration peak value, x min is the peak-to-valley value; Convert the amplitude to a sine wave; Among them, the sine waveform conversion formula is: Where x(t) is the vibration signal, ω is the angular frequency, is the phase, A is the average amplitude; Calculate vibration velocity and displacement; The vibration velocity is calculated based on the amplitude and frequency, where the vibration velocity calculation formula is: v=2πfA In the formula, v is the vibration velocity, f is the vibration frequency, π is the circumference of a circle, and A is the average amplitude; The vibration velocity is calculated based on the amplitude and frequency, where the vibration displacement is calculated as: Where d is the vibration displacement, ω is the angular frequency, f is the frequency of vibration, π is the circumference of a circle, and A is the average amplitude.

4. The method for detecting abnormal vibration of an Android mobile phone according to claim 3, characterized in that: A motor evaluation model is established based on average amplitude, vibration velocity and vibration displacement; Based on the motor evaluation formula, evaluate whether the mobile phone motor is vibrating; Evaluate the vibration intensity value based on the motor evaluation formula.

5. The method for detecting abnormal vibration of an Android mobile phone according to claim 4, characterized in that: Based on the average amplitude, vibration velocity and vibration displacement, the motor evaluation formula is established, including: Obtain average amplitude, vibration velocity and vibration displacement data; Calculate the weights of average amplitude, vibration velocity and vibration displacement data; The weight calculation formula is: W=(X T X) -1 X T Y Where W is the vector of weight coefficients, X is the matrix containing independent variables, and Y is the vector of target variables; Establish a comprehensive scoring model for motor assessment; Among them, the motor evaluation comprehensive scoring model formula is: S=W1·A+W2·v+W3·d Among them, S is the total score, W1W2W3 are the weight coefficients of average amplitude, vibration velocity and vibration displacement respectively, A is the average amplitude, v is the vibration velocity, and d is the vibration displacement.

6. The method for detecting abnormal vibration of an Android mobile phone according to claim 5, characterized in that: Based on the motor evaluation formula, the evaluation of whether the mobile phone motor is vibrating specifically includes: Set the threshold of S; Determine whether the intensity and range of the vibration generated by the phone are within the expected threshold. If the S value is outside the normal range, it indicates that the risk of a problem is high and exception handling is required.

7. The method for detecting abnormal vibration of an Android mobile phone according to claim 6, characterized in that: Based on the motor evaluation formula, the vibration intensity values ​​evaluated include: According to the vibration intensity value and spectrum analysis results, fault diagnosis is performed, including imbalance, misalignment and bearing failure; Develop a maintenance and repair schedule to reduce vibration and increase motor operating efficiency and life.

8. The method for detecting abnormal vibration of an Android mobile phone according to claim 7, characterized in that: The judgment result is sent back to the server, and the recycling valuation specifically includes: Generate a report containing vibration intensity values, analysis conclusions and suggestions based on data analysis results; Encapsulate the assessment report and related data into a data package, ensuring that the data package contains all necessary information, including timestamp, device ID and assessment results; Encrypt and compress data to ensure data security and transmission efficiency; Use the API interface to send data packets to the server through the network; The server receives the transmitted data packet; Decrypt and decompress the received data packets and extract the evaluation results; The evaluation results are stored in a database.

9. The method for detecting abnormal vibration of an Android mobile phone according to claim 8, characterized in that: The received data is then used to perform an evaluation to assess the equipment's condition and possible maintenance needs. Generate Recycling Valuation Report: Generate a detailed report based on the valuation results, including recommended maintenance measures and budget. The recycling valuation results are returned to the client through the corresponding protocol.

10. The method for detecting abnormal vibration of an Android mobile phone according to claim 9, characterized in that: Send the assessment results and recycling valuation report to users via email, SMS and app notifications; Allow users to provide feedback on the report and ask further questions; Regularly monitor the performance of data transmission and processing systems and update the systems based on demand and technological advances.

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