Anti-interference system for micro-vibration detection

Abstract

The invention provides an anti-interference system for micro-vibration detection. The system comprises a signal acquisition assembly and an anti-interference assembly connected with the output end of the signal acquisition assembly, and the anti-interference assembly comprises a hardware configurable filter network, an interference feature library and a control logic unit. The hardware configurable filter network receives an original vibration signal collected by the signal collection assembly as an input signal, and the control logic unit monitors the amplitude and / or frequency characteristics of the input signal in real time. And querying the interference feature library in which the mapping relationship between the interference source features and the filter configuration parameters is stored according to the monitored amplitude and / or frequency features of the input signal, so as to generate a control instruction corresponding to a query result based on the query result, thereby enabling the hardware configurable filter network to dynamically configure a filtering strategy. And filtering the environmental interference signal in the analog signal domain based on the configured filtering strategy.

Description

Technical Field

[0001] This disclosure relates to the field of biosignal detection technology, and more specifically, to an anti-interference system capable of eliminating interference signals at the front end of vibration signal detection and processing. Background Technology

[0002] With the development of sensing technology, non-contact vital sign monitoring devices based on high-sensitivity micro-vibration (seismic wave) sensing technology are becoming increasingly common. These sensors are typically installed under the mattress or bed frame, continuously collecting weak vibration signals generated by heartbeat, respiration, and blood flow while the user is lying down, and then calculating physiological parameters such as heart rate, respiratory rate, and even blood pressure. During the detection of various minute vibrations or wave signals, interference from environmental vibrations or wave signals is common. To obtain a pure target wave signal or vibration, it is usually necessary to filter out or reduce environmental interference waves or vibrations.

[0003] However, the core challenge of this technology lies in the fact that its extremely high sensitivity is a double-edged sword. It can not only collect weak physiological signals from the target, but also inevitably collect various environmental interference vibrations, such as vibrations transmitted from the ground due to people walking, which are transmitted to the sensor through bed legs and supports; shock waves transmitted through the building structure caused by closing doors and impacts; and periodic vibrations generated by electrical appliances, such as air conditioners and refrigerators.

[0004] The amplitude of these interference signals is often much larger than that of weak physiological signals (such as heartbeat vibrations), causing signal saturation or a sharp drop in the signal-to-noise ratio (SNR), making it impossible for the back-end algorithm to effectively extract useful physiological information, which seriously affects the accuracy and reliability of the measurement.

[0005] Currently, the industry mostly uses software algorithms (such as adaptive filtering, wavelet transform, machine learning, etc.) for noise reduction in the digital signal processing (DSP) stage. However, software processing has a lag, and when the interference is too strong, causing the front-end acquisition circuit to saturate or become distorted, the software algorithm will be unable to recover a valid signal, i.e., the problem of "garbage in, garbage out".

[0006] Therefore, there is an urgent need for a technology that performs pre-filtering at the hardware physical layer (i.e., analog signal domain) of signal acquisition to suppress strong interference signals to the greatest extent possible from the source, ensuring that the signal input to the analog-to-digital converter (ADC) is an uncontaminated and valid signal, thus laying a high-quality data foundation for back-end software processing.

[0007] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0008] In view of the above, this disclosure provides an anti-interference system for micro-vibration detection to eliminate the problems in the prior art, comprising: a signal acquisition component and an anti-interference component connected to the output terminal of the signal acquisition component, wherein the anti-interference component includes a hardware configurable filter network, an interference feature library, and a control logic unit. The hardware configurable filter network receives the original vibration signal acquired by the signal acquisition component as an input signal. The control logic unit monitors the amplitude and / or frequency characteristics of the input signal in real time, and queries the interference feature library storing the mapping relationship between interference source characteristics and filter configuration parameters according to the monitored amplitude and / or frequency characteristics of the input signal. Based on the query result, a control command corresponding to the query result is generated, thereby enabling the hardware configurable filter network to dynamically configure a filtering strategy so as to filter out environmental interference signals in the analog signal domain based on the configured filtering strategy.

[0009] According to the anti-interference system for micro-vibration detection disclosed herein, the hardware configurable filter network is a reconfigurable RLC cascade filter network including resistors (R), inductors (L), and capacitors (C), and the control command is a configuration code corresponding to the mapping relationship, which contains instruction signals corresponding to the on / off switching of specific resistors (R), inductors (L), and capacitors (C) in the reconfigurable RLC cascade filter network, thereby forming an environmental interference signal that can filter out the monitored amplitude and / or frequency characteristics.

[0010] According to the anti-interference system for micro-vibration detection disclosed herein, the hardware-configurable filter network changes the on / off state of its analog switches based on a received configuration code, thereby dynamically switching the filter type, cutoff frequency, or center frequency to form a low-pass filter, band-stop filter, high-pass filter, or notch filter. According to the anti-interference system for micro-vibration detection disclosed herein, the hardware configurable filter network, after dynamic configuration, forms a notch filter for power frequency 50 / 60Hz interference, a low-pass filter for slow ambient noise with a cutoff frequency in the range of 0.1Hz to 5Hz, a band-stop filter for periodic electrical interference, or a high-pass filter for extremely low frequency drift interference with a cutoff frequency in the range of 0.5Hz to 2Hz.

[0011] According to the anti-interference system for micro-vibration detection disclosed herein, the notch filter is for normal mode interference at power frequency of 50 / 60Hz, the low-pass filter is for low-frequency walking interference for slow ambient noise with a cutoff frequency in the range of 0.1Hz to 5Hz, and the band-stop filter is for periodic electrical noise interference of about 30Hz.

[0012] According to the anti-interference system for micro-vibration detection disclosed herein, the control logic unit employs an amplitude detection circuit within it to monitor whether the intensity of the input signal exceeds a preset threshold, and / or employs a frequency detection circuit within it to identify the dominant frequency of the input signal. According to the anti-interference system for micro-vibration detection disclosed herein, the mapping relationship between the interference source features stored in the interference feature library and the filter configuration parameters is established in advance through the collection and analysis of a large amount of environmental data, and a set of optimal filter configuration codes is pre-calculated for each type in the mapping relationship. The configuration codes are then sent as command signals to the analog switch array for control, thereby reconstructing the on / off state of specific resistor (R), inductor (L), and capacitor (C) elements in the RLC cascaded filter network.

[0013] According to the anti-interference system for micro-vibration detection disclosed herein, the control logic unit is a microprocessor unit (MCU) or a dedicated state machine circuit including a zero-crossing detection counter, a peak detector, and a comparator.

[0014] According to the anti-interference system for micro-vibration detection disclosed herein, the microprocessor unit (MCU) continuously monitors the amplitude of the input signal through an auxiliary ADC channel and analyzes the spectral characteristics of the signal using its internal software algorithm. According to the anti-interference system for micro-vibration detection disclosed herein, the software algorithm is a fast Fourier transform or bandpass filtering algorithm, used to analyze the dominant frequency component when strong interference is detected.

[0015] The anti-interference system for micro-vibration detection according to this disclosure filters the input signal at its source through pre-filtering in the analog domain, effectively preventing strong interference signals from saturating the amplifier and fully utilizing the dynamic range of the ADC, thereby protecting the front end. Furthermore, due to the use of hardware filters, its response speed is much faster than software algorithms, making it particularly suitable for suppressing sudden transient interference, thus resulting in rapid response. By using front-end filtering on the input signal, a cleaner, higher signal-to-noise ratio original signal is provided for the back-end software algorithm, significantly reducing the complexity and power consumption of digital signal processing, thereby reducing the pressure on the back end. In particular, through configurable hardware and simple control logic, it can intelligently cope with various environmental interference scenarios, improving the robustness of the device in different user environments and exhibiting strong adaptability. Moreover, based on MCU control, no additional expensive chips are required, resulting in minimal cost increase but significant improvement, thus demonstrating high practicality.

[0016] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this disclosure. Attached Figure Description

[0017] The above and other objects, features, and advantages of this disclosure will become more apparent from the detailed description of exemplary embodiments with reference to the accompanying drawings. The drawings described below are merely some embodiments of this disclosure, and those skilled in the art will be able to obtain other drawings based on these drawings without any inventive effort.

[0018] Figure 1 This is a schematic diagram of an anti-interference system for micro-vibration detection, according to an exemplary embodiment.

[0019] Figure 2 This is a schematic diagram of a reconfigurable RLC cascaded filter network according to an exemplary embodiment. Detailed Implementation

[0020] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted.

[0021] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, systems, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0022] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0023] It should be understood that while the terms first, second, third, etc., may be used herein to describe various components, these components should not be limited by these terms. These terms are used to distinguish one component from another. Therefore, the first component discussed below may be referred to as the second component without departing from the teachings of this disclosure. As used herein, the term "and / or" includes all combinations of any and more of the associated listed items.

[0024] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of exemplary embodiments, and the modules or processes in the drawings are not necessarily necessary for implementing this disclosure, and therefore cannot be used to limit the scope of protection of this disclosure.

[0025] Figure 1 This is a schematic diagram of an anti-interference system for micro-vibration detection, according to an exemplary embodiment.

[0026] like Figure 1 As shown, an anti-interference system 100 for micro-vibration detection according to this disclosure includes: a signal acquisition component 110 and an anti-interference component 120 connected to the output terminal of the signal acquisition component. The anti-interference component 120 includes a hardware configurable filter network 121, an interference feature library 122, and a control logic unit 123. The hardware configurable filter network 121 receives the original vibration signal acquired by the signal acquisition component 110 as an input signal. The control logic unit 123 monitors the amplitude and / or frequency characteristics of the input signal in real time, and queries the interference feature library storing the mapping relationship between interference source characteristics and filter configuration parameters according to the monitored amplitude and / or frequency characteristics of the input signal. Based on the query result, a control command corresponding to the query result is generated, thereby enabling the hardware configurable filter network to dynamically configure a filtering strategy so as to filter out environmental interference signals in the analog signal domain based on the configured filtering strategy.

[0027] like Figure 1 As shown, the hardware-configurable filter network 121 is a reconfigurable RLC cascade filter network 1212 including resistors (R), inductors (L), and capacitors (C), also referred to as RLC network 1212. It also includes an analog switch array 1211. The analog switch array 1211 generates switching signals based on the received command signals, controlling the on / off states of specific resistors (R), inductors (L), and capacitors (C) in the corresponding reconfigurable RLC cascade filter network 1212. This configures the reconfigurable RLC cascade filter network 1212 into a filter circuit mapped to the corresponding command signal; that is, it configures and reconfigures the RLC cascade filter network 1212 according to the filtering strategy corresponding to the command signal, forming the corresponding filter circuit.

[0028] The control commands are configuration codes corresponding to the mapping relationship. These codes contain instruction signals corresponding to the on / off states of specific resistors (R), inductors (L), and capacitors (C) in the reconfigurable RLC cascaded filter network, thereby generating environmental interference signals that can filter out the monitored amplitude and / or frequency characteristics. Based on the received configuration codes, the hardware-configurable filter network 121 changes the on / off state of its analog switches 1211, thereby dynamically switching the filter type, cutoff frequency, or center frequency to form a low-pass filter, band-stop filter, high-pass filter, or notch filter. Traditional fixed-parameter filters cannot cope with diverse interference. Therefore, as described above, the reconfigurable RLC cascaded filter network 1212 of this disclosure is a reconfigurable RLC filter network controlled by the analog switch array 1211 of this disclosure, such as a MOSFET array or a dedicated analog switch IC. The basic structure of the RLC network 1212 consists of multiple cascaded filter units with different center frequencies, different Q values, and different types (low-pass, band-stop). This structure is a common result of filter networks and will not be described in detail. The analog switch array 1211 dynamically changes the transfer function (frequency response) of the entire filter network by switching the analog switches on and off, i.e., connecting or bypassing different resistors (R), inductors (L), and capacitors (C), thereby achieving configurability.

[0029] The following table shows examples of filter types formed by the specific configuration of RLC network 1212: Filter type Examples of interference sources to be filtered out Examples of configurable parameters 50 / 60Hz Notch Filter Power frequency interference Center frequency (50 / 60Hz switching), bandwidth Low-pass filter (LPF) Slowly changing environmental noise Cutoff frequency (e.g., adjustable from 0.1Hz to 5Hz) Band-stop filter Periodic electrical interference (such as air conditioner compressor, ~30Hz) Center frequency, bandwidth High-pass filter (HPF) Extremely low frequency drift (such as temperature changes) Cutoff frequency (e.g., adjustable from 0.5Hz to 2Hz) Figure 2 This is a schematic diagram illustrating a reconfigurable RLC cascaded filter network according to an exemplary embodiment. Figure 2 As shown, the analog switch array 1211, i.e. the MCU in the figure, is used to turn the analog switches on and off, i.e. to connect or bypass different resistors (R), inductors (L), and capacitors (C), thereby dynamically changing the transfer function (frequency response) of the entire filter network 1212, thus achieving configurability.

[0030] The hardware-configurable filtering network 121, after dynamic configuration, forms a notch filter for interference at the power frequency of 50 / 60Hz, a low-pass filter for slow ambient noise with a cutoff frequency in the range of 0.1Hz to 5Hz, a band-stop filter for periodic electrical interference, or a high-pass filter for extremely low-frequency drift interference with a cutoff frequency in the range of 0.5Hz to 2Hz. In other words, different filtering strategies are formed for different interference signals. For example, the notch filter targets normal mode interference at the power frequency of 50 / 60Hz, the low-pass filter targets low-frequency walking interference with slow ambient noise in the range of 0.1Hz to 5Hz, and the band-stop filter targets electrical noise interference around 30Hz.

[0031] The interference feature library 122 disclosed herein does not store interference in digital form, but rather maps the frequency characteristics of typical interference sources to corresponding hardware filter configuration parameters. Through prior collection and analysis of a large amount of environmental data, the frequency domain characteristics of common interferences are summarized. For example, people walking: energy is mainly concentrated in the low-frequency band of 1Hz to 20Hz. Door closing / impact: a wideband transient pulse signal. Air conditioner compressor: a stable single-frequency vibration of ~30-40Hz. For each identified typical interference mode, this disclosure pre-calculates a set of optimal filter configuration codes. This configuration code is a digital quantity used to control the analog switch array. The mapping relationship between the interference source characteristics and filter configuration parameters stored in the interference feature library 122 is established through prior collection and analysis of a large amount of environmental data, and a set of optimal filter configuration codes is pre-calculated for each type in the mapping relationship. These configuration codes are then sent as command signals to the analog switch array for control, thereby reconstructing the on / off state of specific resistors (R), inductors (L), and capacitors (C) in the RLC cascaded filter network. A specific mapping method between the common interference patterns and configuration codes stored in the interference feature library 122 is shown in Table 2: Interference mode Characteristic frequency Hardware configuration code (example) Filtering actions taken Normal mode No strong interference 0x01 Enable only Qualcomm (0.7Hz) and 50Hz notch filter. Walking interference 1-20Hz 0x02 Add a 15Hz low-pass filter Electrical interference 30Hz 0x03 Add a 30Hz bandstop filter with a higher Q value. Pulse interference Full-band 0x04 Enable transient suppression circuitry (such as a fast limiter). like Figure 1 As shown, the control logic unit 123 uses its internal amplitude detection circuit to monitor whether the strength of the input signal exceeds a preset threshold, and / or uses its internal frequency detection circuit to identify the main frequency of the input signal. The control logic unit 123 can be a microprocessor unit (MCU) or a dedicated state machine circuit containing a zero-crossing counter, a peak detector, and a comparator. The MCU continuously monitors the amplitude of the input signal through an auxiliary ADC channel and analyzes the spectral characteristics of the signal through its internal software algorithm. The software algorithm is a fast Fourier transform or a bandpass filter algorithm, used to analyze the main frequency component when strong interference is detected.

[0032] Specifically, the control logic unit 123 of this disclosure can be a lightweight adaptive control circuit for automatically identifying interference and switching filter configurations. It can be the system's main MCU, continuously monitoring the analog signal strength before ADC acquisition, for example, by reading the signal amplitude through an additional low-precision ADC channel. When the signal amplitude continuously exceeds a set threshold, the MCU determines that strong interference has occurred and then, according to a preset mapping table, outputs the corresponding hardware configuration code to the analog switch array via I / O ports to switch the filtering mode. Alternatively, the control logic unit 123 of this disclosure can be a dedicated state machine circuit. This circuit includes a frequency detection module (such as a zero-crossing counter) and an amplitude detection module (such as a peak detector and comparator). The hardware circuit monitors the amplitude-frequency characteristics of the input signal in real time. When the detected signal characteristics (e.g., frequency falling around 30Hz and amplitude extremely high) match preset interference characteristics, it automatically generates a control signal to switch the filtering network. This solution has an extremely fast response speed and requires no MCU intervention. When the control logic unit 123 finds that the input signal contains multiple interference signals, it performs filtering processing on the input signal one by one according to the hardware filter configuration parameters (configuration codes) corresponding to the frequency characteristics of the interference sources in the interference feature library 122. That is, after filtering the original input signal based on the first configuration code, the first output signal is fed back to the input terminal of the hardware configurable filter network 121 as the input signal, and the first output signal, which is the input signal, is subjected to a second filtering processing based on the second configuration code. This process is repeated until all the retrieved configuration codes have been configured for the hardware configurable filter network 121 and filtered one by one, forming the final output signal to eliminate all interference signals.

[0033] The anti-interference system for micro-vibration detection according to this disclosure filters the input signal at its source through pre-filtering in the analog domain, effectively preventing strong interference signals from saturating the amplifier and fully utilizing the dynamic range of the ADC, thereby protecting the front end. Furthermore, due to the use of hardware filters, its response speed is much faster than software algorithms, making it particularly suitable for suppressing sudden transient interference, thus resulting in rapid response. By using front-end filtering on the input signal, a cleaner, higher signal-to-noise ratio original signal is provided for the back-end software algorithm, significantly reducing the complexity and power consumption of digital signal processing, thereby reducing the pressure on the back end. In particular, through configurable hardware and simple control logic, it can intelligently cope with various environmental interference scenarios, improving the robustness of the device in different user environments and exhibiting strong adaptability. Moreover, based on MCU control, no additional expensive chips are required, resulting in minimal cost increase but significant improvement, thus demonstrating high practicality.

[0034] Through the description of the above embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the operation process of the technical solution according to the embodiments of this disclosure can be embodied in the form of a software product. This software product can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, and includes several instructions to cause a computing device (such as a personal computer, server, mobile terminal, or network device, etc.) to execute the method according to the embodiments of this disclosure.

[0035] Exemplary embodiments of this disclosure have been specifically shown and described above. It should be understood that this disclosure is not limited to the detailed structures, arrangements, or implementations described herein; rather, this disclosure is intended to cover various modifications and equivalent arrangements contained within the spirit and scope of the appended claims.

Claims

1. An anti-interference system for micro-vibration detection, comprising: The signal acquisition component and an anti-interference component connected to the output end of the signal acquisition component, wherein the anti-interference component includes a hardware configurable filter network, an interference feature library and a control logic unit, the hardware configurable filter network receives the original vibration signal collected by the signal acquisition component as an input signal, the control logic unit monitors the amplitude and / or frequency characteristics of the input signal in real time, and queries the interference feature library storing the mapping relationship between the interference source characteristics and the filter configuration parameters according to the monitored amplitude and / or frequency characteristics of the input signal, thereby generating a control instruction corresponding to the query result based on the query result, so that the hardware configurable filter network dynamically configures the filtering strategy, so as to filter out the environmental interference signal in the analog signal domain based on the configured filtering strategy.

2. The system of claim 1, wherein, The hardware configurable filter network is a reconfigurable RLC cascade filter network including resistance (R), inductance (L) and capacitance (C) elements, and the control instruction is a configuration code corresponding to the mapping relationship, which contains instruction signals corresponding to the on-off of specific resistance (R), inductance (L) and capacitance (C) elements in the reconfigurable RLC cascade filter network, thereby forming an environmental interference signal capable of filtering out the monitored amplitude and / or frequency characteristics.

3. The system of claim 2, wherein, The hardware configurable filter network changes the on-off state of its analog switch based on the received configuration code, thereby dynamically switching the type, cutoff frequency or center frequency of the filter to form a low-pass filter, a band-stop filter, a high-pass filter or a notch filter.

4. The system of claim 3, wherein, The notch filter formed by the dynamically configured hardware configurable filter network is for power frequency 50 / 60Hz interference, the low-pass filter is for slow environmental noise with a cutoff frequency in the range of 0.1Hz to 5Hz, the band-stop filter is for periodic electrical interference, or the high-pass filter is for extremely low frequency drift interference with a cutoff frequency in the range of 0.5Hz to 2Hz.

5. The system of claim 4, wherein, The notch filter for power frequency 50 / 60Hz interference is normal mode interference, the low-pass filter for slow environmental noise with a cutoff frequency in the range of 0.1Hz to 5Hz is low frequency walking interference, and the band-stop filter for periodic electrical interference is electrical noise interference around 30Hz.

6. The system of claim 1, wherein, The control logic unit uses the amplitude detection circuit therein to monitor whether the intensity of the input signal exceeds a preset threshold, and / or uses the frequency detection circuit therein to identify the main frequency of the input signal.

7. The system of claim 2, wherein, The mapping relationship between the interference source characteristics and the filter configuration parameters stored in the interference feature library is established by pre-collecting and analyzing a large amount of environmental data, and a set of optimal filter configuration codes is pre-calculated for each of the mapping relationships, so that the configuration codes are sent to the analog switch array as instruction signals to control the reconfiguration of the on-off of specific resistance (R), inductance (L) and capacitance (C) elements in the RLC cascade filter network.

8. The system of claim 1, wherein, The control logic unit is a micro processing unit (MCU) or a dedicated state machine circuit including a zero-crossing detection counter, a peak detector and a comparator.

9. The system of claim 8, wherein, The micro processing unit MCU continuously monitors the amplitude of the input signal through the auxiliary ADC channel and analyzes the spectral characteristics of the signal through a software algorithm within it.

10. The system of claim 9, wherein, The software algorithm is a fast Fourier transform or a band pass filtering algorithm for analyzing the main frequency component when strong interference is detected.

Images