Abnormal monitoring method and system for use of accordion

Abstract

The invention relates to an abnormal monitoring method for use of an accordion, which belongs to the technical field of data monitoring and comprises a collision detection device, an abnormal sound detection device, a bottom plate falling detection device, an iron sheet falling detection device, an image recognition detection device and a main control device. And the device is activated as required, is particularly suitable for a portable accordion (battery power supply scene), and reduces idle energy consumption. Logic is reasonable, a troubleshooting sequence is from outside to inside and from simple to complex, and fault diagnosis logic (collision may cause chain problems) is met. Image recognition is used as a final means and is only used when basic detection has no fruit, and waste of high-computing resources is avoided.

Description

Technical Field

[0001] This invention belongs to the field of data monitoring technology, specifically relating to an anomaly monitoring method and system for accordion use. Background Technology

[0002] A common type of keyboard accordion key positioning device includes a soundbox, a key positioning plate, a keyboard box, a U-shaped connecting block, and an electromagnet. A control panel is located on one side of the soundbox, containing a controller with control buttons on one side. The key positioning plate is located at the top inside the soundbox, and the keyboard box contains the black keys, each with a cushioning pad at its bottom. The key positioning plate effectively blocks the height of the black and white keys. The combination of the magnet and the electromagnet allows for adjustment of the key positioning plate's height, improving upon traditional methods of limiting key rise and preventing key scraping against other keys, thus enhancing usability and extending the accordion's lifespan.

[0003] In the above solution, the electromagnet plate plays a crucial role. During our use, we found that if the accordion is accidentally dropped, the internal electromagnet plate may fall off, thus affecting the normal use of the accordion. At present, there is no abnormal monitoring solution for this situation.

[0004] Therefore, at this stage, it is necessary to design an anomaly monitoring method and system for accordion use to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide an abnormal monitoring method and system for accordion use, in order to solve the technical problems existing in the prior art. The role of the electromagnet is extremely critical. During our use, we found that if the accordion is accidentally dropped, its internal electromagnet may fall off, thereby affecting the normal use of the accordion. At present, there is no abnormal monitoring solution for this situation.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows:

[0007] The abnormality monitoring system used in accordions includes a collision detection device, an abnormal noise detection device, a base plate detachment detection device, a metal sheet detachment detection device, an image recognition detection device, and a main control device;

[0008] The main control device is connected to the collision detection device, abnormal noise detection device, bottom plate detachment detection device, iron sheet detachment detection device, and image recognition detection device respectively.

[0009] The collision detection device is used to detect whether the accordion is involved in a collision.

[0010] The abnormal noise detection device is used to detect whether there are abnormal noises inside the accordion;

[0011] The base plate detachment detection device is used to detect whether the base plate of the electromagnet sheet has detached.

[0012] The iron sheet detachment detection device is used to detect whether the electromagnet sheet has detached.

[0013] The image recognition detection device is used to detect the specific conditions of the electromagnet sheet base plate and the electromagnet sheet through image recognition.

[0014] Furthermore, the main control device controls the initial state of the collision detection device to be turned on, and controls the initial state of the abnormal noise detection device, the bottom plate detachment detection device, the iron sheet detachment detection device, and the image recognition detection device to be turned off;

[0015] When the collision detection device detects a collision with the hand, the main control device controls the abnormal noise detection device to be activated;

[0016] When the abnormal noise detection device detects an abnormal noise inside the accordion, the main control device controls the base plate detachment detection device to be activated.

[0017] When the base plate detachment detection device detects that the electromagnet sheet base plate has not detached, the main control device controls the sheet detachment detection device to turn on;

[0018] When the iron sheet detachment detection device detects that the electromagnet sheet has not detached, the main control device controls the image recognition detection device to turn on.

[0019] Furthermore, it also includes an anomaly warning device, which is connected to the main control device;

[0020] The main control device controls the initial state of the abnormal warning device to be off;

[0021] When the base plate detachment detection device detects that the electromagnet plate base plate has detached, or the iron sheet detachment detection device detects that the electromagnet sheet has detached, the main control device controls the abnormality warning device to be activated.

[0022] Furthermore, the collision detection device includes:

[0023] Physical switch / limit switch: When an object touches the switch's lever, roller, or button, the circuit is connected or disconnected, sending a signal.

[0024] Pressure / force sensor: detects changes in the magnitude of pressure or force generated when an object comes into contact with another object;

[0025] Deformation sensor: detects minute deformations caused by collisions.

[0026] Furthermore, the abnormal noise detection device includes a sensor unit, a signal conditioning circuit, a data acquisition system, a signal processing and analysis unit, a decision and output unit, and a human-computer interaction unit.

[0027] Furthermore, it also includes a wireless communication device and a remote data center, with the main control device connected to the wireless communication device and the remote data center network respectively.

[0028] The anomaly monitoring method for accordions uses the anomaly monitoring system described above.

[0029] A storage medium storing a computer program, which, when run, executes an anomaly monitoring method for an accordion as described above.

[0030] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0031] High efficiency and energy saving: The device is activated on demand, making it especially suitable for portable accordions (battery-powered scenarios) and reducing idle energy consumption.

[0032] Logically sound: The troubleshooting order, from the outside to the inside and from simple to complex, conforms to the logic of fault diagnosis (collisions may trigger a chain of problems).

[0033] Redundancy reduction: Image recognition is used as a last resort, only when basic detection fails, to avoid wasting high computing resources. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of the system structure of an embodiment of this solution.

[0035] Figure 2 This is a schematic diagram illustrating the system operation principle of an embodiment of this solution. Detailed Implementation

[0036] like Figure 1 As shown, the abnormal monitoring system used in the accordion includes a collision detection device, an abnormal noise detection device, a base plate detachment detection device, a metal sheet detachment detection device, an image recognition detection device, and a main control device.

[0037] The main control device is connected to the collision detection device, abnormal noise detection device, bottom plate detachment detection device, iron sheet detachment detection device, and image recognition detection device respectively.

[0038] The collision detection device is used to detect whether the accordion is involved in a collision.

[0039] The abnormal noise detection device is used to detect whether there are abnormal noises inside the accordion;

[0040] The base plate detachment detection device is used to detect whether the base plate of the electromagnet sheet has detached.

[0041] The iron sheet detachment detection device is used to detect whether the electromagnet sheet has detached.

[0042] The image recognition detection device is used to detect the specific conditions of the electromagnet sheet base plate and the electromagnet sheet through image recognition.

[0043] Furthermore, such as Figure 2 As shown, the main control device controls the initial state of the collision detection device to be turned on, and controls the initial state of the abnormal noise detection device, the bottom plate detachment detection device, the iron sheet detachment detection device, and the image recognition detection device to be turned off.

[0044] When the collision detection device detects a collision with the hand, the main control device controls the abnormal noise detection device to be activated;

[0045] When the abnormal noise detection device detects an abnormal noise inside the accordion, the main control device controls the base plate detachment detection device to be activated.

[0046] When the base plate detachment detection device detects that the electromagnet sheet base plate has not detached, the main control device controls the sheet detachment detection device to turn on;

[0047] When the iron sheet detachment detection device detects that the electromagnet sheet has not detached, the main control device controls the image recognition detection device to turn on.

[0048] System Composition

[0049] Collision detection device: Initially activated to detect whether the accordion has been involved in a collision.

[0050] Abnormal noise detection device: initially closed, detects for abnormal noises inside the accordion.

[0051] Base plate detachment detection device: initially closed, detects whether the electromagnet plate base plate has detached.

[0052] Iron sheet detachment detection device: initially closed, it detects whether the electromagnet sheet has detached.

[0053] Image recognition detection device: initially off, it analyzes the specific conditions of the electromagnet base plate and iron sheet (such as positional deviation, minor damage, etc.) through image recognition.

[0054] Main control unit: Connects all detection devices, controls their on / off status, and triggers the next operation based on the detection results.

[0055] Workflow (Condition-Triggered)

[0056] In the initial system state, only the collision detection device is activated, while other devices are deactivated to reduce energy consumption. The process is as follows:

[0057] Collision detection triggers abnormal noise detection:

[0058] When the collision detection device detects a collision, the main control device activates the abnormal noise detection device.

[0059] If no collision is detected, the system remains in its initial state (collision detection only).

[0060] Abnormal noise detection triggers base plate detachment detection:

[0061] When the abnormal noise detection device detects an internal abnormal noise, the main control device activates the base plate detachment detection device.

[0062] If no abnormal noise is detected, the main control unit will not activate subsequent devices (possibly assuming that the collision did not cause internal problems).

[0063] Base plate detachment detection triggers iron sheet detachment detection:

[0064] When the base plate detachment detection device detects that the electromagnet base plate has not detached, the main control device activates the base plate detachment detection device.

[0065] If the base plate is detected to be detached, the main control device will not activate the metal sheet detachment detection (it may directly handle or report the base plate problem).

[0066] Iron sheet detachment detection triggers image recognition detection:

[0067] When the iron sheet detachment detection device detects that the electromagnet sheet has not detached, the main control device activates the image recognition detection device.

[0068] If a piece of iron is detected to have detached, the main control device will not activate image recognition detection (it may directly process or report the iron problem).

[0069] Image recognition and detection execution:

[0070] When the image recognition detection device is turned on, it provides detailed analysis (such as identifying minute defects or displacements in the base plate or sheet metal through a camera) to diagnose problems that were not detected in previous steps.

[0071] System Logic Core

[0072] Energy-saving design: Initially, only collision detection is activated, and other devices are activated as needed to avoid unnecessary power consumption.

[0073] Troubleshooting sequence: The system prioritizes handling external events (collisions), then gradually delves into internal issues (abnormal noises → base plate → metal sheet → image details), which is suitable for the structural characteristics of an accordion (the electromagnet system is susceptible to collisions).

[0074] Conditional triggering: Each step is triggered only when the previous detection result meets the condition, for example:

[0075] Image recognition is activated only when there is "no base plate detachment and no iron sheet detachment" to diagnose more hidden faults (such as material fatigue or micro-cracks).

[0076] If any detection device detects a problem (such as a detached base plate), the system may stop subsequent detection (because the problem has been located), but your description does not specify the main control device's response (such as alarm or logging).

[0077] High efficiency and energy saving: The device is activated on demand, making it especially suitable for portable accordions (battery-powered scenarios) and reducing idle energy consumption.

[0078] Logically sound: The troubleshooting order, from the outside to the inside and from simple to complex, conforms to the logic of fault diagnosis (collisions may trigger a chain of problems).

[0079] Redundancy reduction: Image recognition is used as a last resort, only when basic detection fails, to avoid wasting high computing resources.

[0080] Furthermore, it also includes an anomaly warning device, which is connected to the main control device;

[0081] The main control device controls the initial state of the abnormal warning device to be off;

[0082] When the base plate detachment detection device detects that the electromagnet plate base plate has detached, or the iron sheet detachment detection device detects that the electromagnet sheet has detached, the main control device controls the abnormality warning device to be activated.

[0083] Furthermore, the collision detection device includes:

[0084] Physical switch / limit switch: When an object touches the switch's lever, roller, or button, the circuit is connected or disconnected, sending a signal.

[0085] Pressure / force sensor: detects changes in the magnitude of pressure or force generated when an object comes into contact with another object;

[0086] Deformation sensor: detects minute deformations caused by collisions.

[0087] Key considerations when selecting a sensor for specific applications:

[0088] Detection range and accuracy: What area needs to be covered? What level of detection accuracy is required?

[0089] Response time: The time from detecting a collision to triggering an action must be extremely short, especially in high-speed scenarios.

[0090] Reliability: Must be highly reliable to avoid false alarms (false triggers) and missed alarms (no collision detected).

[0091] Robustness: It can work stably under various environmental conditions (temperature, humidity, light, dust, electromagnetic interference).

[0092] Cost: The cost varies greatly depending on the technology.

[0093] Installation and maintenance: Is it easy to install, debug and maintain?

[0094] Furthermore, the abnormal noise detection device includes a sensor unit, a signal conditioning circuit, a data acquisition system, a signal processing and analysis unit, a decision and output unit, and a human-computer interaction unit.

[0095] Sensor unit:

[0096] Microphone: The most common type, used to capture sound signals in the air. Various types are available.

[0097] Condenser microphones: high precision, wide frequency response, commonly used in laboratories or precision testing.

[0098] Electret microphones: low cost, small size, and high integration, widely used in consumer electronics and industrial embedded systems.

[0099] Piezoelectric microphone: Resistant to harsh environments (high temperature, high humidity).

[0100] Microphone array: Composed of multiple microphones arranged in a specific geometry, used for sound source localization and amplification of sound from a specific direction, while suppressing background noise.

[0101] Accelerometer: Used to detect solid-borne sound (structural noise) generated by structural vibration. Particularly suitable for rotating machinery (bearings, gearboxes), engines, etc.

[0102] Acoustic emission sensors detect high-frequency stress waves (such as crack propagation and friction) generated by the rapid release of energy within materials. The frequency range is usually much higher than that of audible sound.

[0103] Ultrasonic sensors: specially designed to detect ultrasonic waves (>20kHz) that are inaudible to the human ear, used to detect gas leaks, electrical discharges (corona), certain bearing failures, etc.

[0104] Selection criteria: sound source characteristics (frequency range, sound pressure level), propagation medium (air, solid), environmental conditions (temperature, humidity, electromagnetic interference), cost, and size.

[0105] Signal conditioning circuit:

[0106] Amplification: Amplifying weak sensor signals to a level suitable for acquisition.

[0107] Filtering:

[0108] Bandpass filtering: retains only the target frequency range (such as a specific abnormal noise band) and removes irrelevant high and low frequency noise.

[0109] Anti-aliasing filtering: Before analog-to-digital conversion, filter out frequency components that are higher than half the sampling frequency.

[0110] Impedance matching: Optimize the connection between the sensor and subsequent circuitry.

[0111] Noise reduction / interference suppression: Suppresses power supply noise, electromagnetic interference, etc.

[0112] Data acquisition system:

[0113] Analog-to-digital converter: Converts analog sound / vibration signals into digital signals. Sampling rate and resolution are key parameters (the sampling rate should be at least twice the highest target frequency).

[0114] Data transmission: Transmitting digital signals to the processing unit (wired: USB, Ethernet; wireless: WiFi, Bluetooth, LoRa, NB-IoT).

[0115] Signal Processing and Analysis Unit:

[0116] Hardware platforms: microcontrollers, DSPs, FPGAs, embedded computers (such as Raspberry Pi), industrial PCs, or cloud servers.

[0117] Core Algorithm:

[0118] Preprocessing: noise reduction (wavelet transform, adaptive filtering), framing, windowing.

[0119] Time-domain analysis: Calculates statistical characteristics such as RMS value, peak value, kurtosis, and impulse factor. Kurtosis is sensitive to impact-related abnormal noises.

[0120] Frequency domain analysis:

[0121] Fast Fourier Transform (FFT): Converts a time-domain signal to the frequency domain to analyze its spectral characteristics (peak frequency, sidebands, harmonics). It is the most basic and commonly used.

[0122] Power spectral density: Analyzes the distribution of signal power across frequencies.

[0123] Cepstral analysis: used to separate excitation source and transmission path information, and is effective for fault diagnosis of gears and bearings.

[0124] Envelope analysis: It is particularly suitable for extracting periodic impact signals (such as bearing failures) that are submerged in strong background noise.

[0125] Time-frequency domain analysis:

[0126] Short-time Fourier transform: Analyzes the changes in frequency components over time.

[0127] Wavelet transform: multi-resolution analysis, suitable for non-stationary signals and transient impact detection.

[0128] Hilbert-Huang Transform: Adaptive processing of nonlinear and non-stationary signals.

[0129] Feature extraction: Extract key feature vectors that can characterize abnormal noises from the above analysis (such as MFCC-Mel frequency cepstral coefficients, which are often used for sound recognition, spectral centroid, frequency band energy, time domain statistics, etc.).

[0130] Pattern recognition / machine learning:

[0131] Threshold method: Set a threshold for the feature value, and trigger an alarm if the threshold is exceeded. It is simple and direct, but has poor adaptability.

[0132] Supervised learning: requires a large number of labeled "normal" and "abnormal" samples to train the model.

[0133] Classification algorithms such as SVM, KNN, decision trees, and random forests are used to distinguish between normal and abnormal noises or to identify the type of abnormal noise.

[0134] Deep learning: 1D-CNN (directly processes waveforms), 2D-CNN (processes spectrograms), and RNN / LSTM (processes temporal characteristics) are effective in complex sound recognition, but require a large amount of data and computing resources.

[0135] Unsupervised learning / anomaly detection:

[0136] Clustering: Cluster the sound samples, and those far from the normal clusters are considered abnormal.

[0137] Autoencoders: The network is trained to reconstruct normal sound, and samples with large reconstruction errors are considered abnormal sounds. They do not require abnormal sound samples and are suitable for scenarios where it is difficult to obtain such samples.

[0138] Sound source localization algorithm: Based on microphone array, it uses techniques such as time difference of arrival, beamforming, and acoustic holography to calculate the location of the sound source.

[0139] Decision-making and output:

[0140] Based on the analysis results, determine whether there are any abnormal noises, their type, and their location.

[0141] Alarm: Triggers lights, buzzers, relay outputs, and sends alarm information (SMS, email, platform message).

[0142] Data shows that the spectrum, time-domain waveform, location results, alarm status, and historical records are displayed on the local screen or remote monitoring platform.

[0143] Data storage: Stores raw data, feature data, analysis results, and alarm logs for traceability and analysis.

[0144] Human-computer interaction:

[0145] Local buttons and displays.

[0146] PC software.

[0147] Mobile app.

[0148] Webpage monitoring platform.

[0149] Furthermore, it also includes a wireless communication device and a remote data center, with the main control device connected to the wireless communication device and the remote data center network respectively.

[0150] The anomaly monitoring method for accordions uses the anomaly monitoring system described above.

[0151] A storage medium storing a computer program, which, when run, executes an anomaly monitoring method for an accordion as described above.

Claims

1. An anomaly monitoring system for accordions, characterized in that, It includes a collision detection device, an abnormal noise detection device, a base plate detachment detection device, a metal sheet detachment detection device, an image recognition detection device, and a main control device; The main control device is connected to the collision detection device, abnormal noise detection device, bottom plate detachment detection device, iron sheet detachment detection device, and image recognition detection device respectively. The collision detection device is used to detect whether the accordion is involved in a collision. The abnormal noise detection device is used to detect whether there are abnormal noises inside the accordion; The base plate detachment detection device is used to detect whether the base plate of the electromagnet sheet has detached. The iron sheet detachment detection device is used to detect whether the electromagnet sheet has detached. The image recognition detection device is used to detect the specific conditions of the electromagnet sheet base plate and the electromagnet sheet through image recognition.

2. The anomaly monitoring system for the accordion according to claim 1, characterized in that, The main control device controls the initial state of the collision detection device to be turned on, and controls the initial state of the abnormal noise detection device, the bottom plate detachment detection device, the iron sheet detachment detection device, and the image recognition detection device to be turned off. When the collision detection device detects a collision with the hand, the main control device controls the abnormal noise detection device to be activated; When the abnormal noise detection device detects an abnormal noise inside the accordion, the main control device controls the base plate detachment detection device to be activated. When the base plate detachment detection device detects that the electromagnet sheet base plate has not detached, the main control device controls the sheet detachment detection device to turn on; When the iron sheet detachment detection device detects that the electromagnet sheet has not detached, the main control device controls the image recognition detection device to turn on.

3. The anomaly monitoring system used in the accordion according to claim 2, characterized in that, It also includes an anomaly warning device, which is connected to the main control device; The main control device controls the initial state of the abnormal warning device to be off; When the base plate detachment detection device detects that the electromagnet plate base plate has detached, or the iron sheet detachment detection device detects that the electromagnet sheet has detached, the main control device controls the abnormality warning device to be activated.

4. The anomaly monitoring system for the accordion according to claim 1, characterized in that, The collision detection device includes: Physical switch / limit switch: When an object touches the switch's lever, roller, or button, the circuit is connected or disconnected, sending a signal. Pressure / force sensor: detects changes in the magnitude of pressure or force generated when an object comes into contact with another object; Deformation sensor: detects minute deformations caused by collisions.

5. The anomaly monitoring system for the accordion according to claim 1, characterized in that, The abnormal noise detection device includes a sensor unit, a signal conditioning circuit, a data acquisition system, a signal processing and analysis unit, a decision and output unit, and a human-computer interaction unit.

6. The anomaly monitoring system for the accordion according to claim 1, characterized in that, It also includes a wireless communication device and a remote data center, with the main control device connected to the wireless communication device and the remote data center network respectively.

7. An abnormality monitoring method for accordions, characterized in that, Anomaly monitoring is performed using the anomaly monitoring system described in any one of claims 1-6 for accordion use.

8. A storage medium, characterized in that, The storage medium stores a computer program, which, when run, executes the anomaly monitoring method for the accordion as described in claim 7.

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