Live-line worker upper limb exoskeleton bioelectricity sensing method, device, equipment and medium

Abstract

The invention relates to the technical field of physical and electrical detection, in particular to a method, a device, equipment and a medium for sensing bioelectricity of an upper limb exoskeleton of a hot-line worker. The method comprises the following steps: firstly, setting a bio-electricity signal expression, carrying out N-point sampling aiming at electric upper limb hot-line operation, carrying out discrete Fourier transform on a sequence obtained after sampling and adding four cosine windows, sampling a discrete Fourier transform result to obtain a digital frequency representation form, correcting a spectral analysis result according to an interpolation coefficient, and finally obtaining a digital frequency representation form. On the basis of a spectral analysis result correction result, an intensity characteristic sequence of the bio-electricity signal can be obtained through full-wave rectification and low-pass filtering. Due to the fact that the bio-electricity signals have large randomness and individual difference, but the motion condition of the upper limb exoskeleton of the live working personnel is relatively determined through comparison, the method conducts frequency spectrum result correction through a double-spectral-line interpolation correction algorithm, the intensity characteristics of the bio-electricity signals are effectively determined, and the exoskeleton response speed is increased.

Description

Technical Field

[0001] The present invention relates to the field of physical electricity detection, and in particular to a method, device, equipment and medium for bioelectric sensing of an upper limb exoskeleton for workers working with electricity. Background Art

[0002] The main methods of traditional live distribution network operations are insulated pole operation and insulated glove operation. The use of insulated tools such as insulated gloves, insulated clothing, and insulated poles effectively protects the personal safety of distribution network operators and promotes the widespread development of distribution network non-stop operations. The insulated pole operation method, also known as the indirect operation method, refers to the method in which the operator maintains a specified safety distance from the live object, wears insulating protective equipment, and operates through the insulating pole. The insulated pole operation method can be used in pole climbing operations, or in the working bucket of a boom truck or other ground-insulated working platforms. The insulated glove operation method, also known as the direct operation method, refers to the method in which the operator uses insulated carrying tools such as boom trucks, insulated ladders, and insulated platforms to maintain a specified safety distance from the ground, wears insulating protective equipment, and maintains insulation isolation from surrounding objects, and directly operates on the live object through insulating gloves.

[0003] For example, the Chinese patent with publication number CN110289574A discloses a multifunctional wire clamp for 10kV live-line working on insulating poles. Although the operator of the insulating pole working method does not directly contact the live body, which effectively reduces the risk of electric shock, the effective insulation length of the existing insulating operating pole is required to be no less than 0.7m when in use, and 1.5m or even longer is required on site. The working time of simple projects using the insulating pole method is about 1-2 hours, and the working time of complex projects is about 2-3 hours. Long-term lifting and operation are required during the operation, which does not meet the characteristics of ergonomics, has low working efficiency and consumes a lot of physical energy. Workers who work with live poles for a long time generally have symptoms of joint and muscle strain such as hand joint pain, shoulder joint pain, lumbar pain, and cervical pain. Long-term work may lead to chronic occupational injuries such as musculoskeletal injuries, endangering the occupational safety and health of personnel. At the same time, electric exoskeletons are important auxiliary equipment to help the power construction industry. The emergence of electric exoskeletons can effectively reduce the labor intensity of workers, reduce work intensity, and protect the health of workers. However, the existing electric exoskeletons have large errors in obtaining the bioelectric signals of operators during use, and the control is not precise enough. Therefore, how to improve the response speed of the exoskeleton is an urgent problem that needs to be solved. Summary of the invention

[0004] The technical problem to be solved by the present invention is: to overcome the shortcomings of the prior art and provide a bioelectric sensing method, device, equipment and medium for the upper limb exoskeleton of personnel working with live wires, which can improve the response speed of the upper limb exoskeleton and ensure the safety of live wire working.

[0005] The technical solution of the present invention is:

[0006] A bioelectric sensing method for upper limb exoskeleton of live working personnel, comprising the following steps:

[0007] When the exoskeleton is worn by the operator, the sampling frequency f s The bioelectric signals of N points of the operators are sampled to obtain a bioelectric signal sequence, and a 4-term cosine window is added to the bioelectric signal sequence for discrete Fourier transform to obtain a discrete Fourier transform result, and the discrete Fourier transform result is sampled to obtain a digital frequency. According to the digital frequency, the spectral line amplitude ratio of two adjacent frequency points is calculated, and spectrum analysis is performed based on the spectral line amplitude ratio of two adjacent frequency points. The spectrum analysis results are corrected by using interpolation coefficients, and the intensity characteristic sequence of the bioelectric signal is obtained by full-wave rectification and low-pass filtering of the corrected spectrum analysis results.

[0008] As a further solution of the present invention, a bioelectric signal having M frequency components is expressed as:

[0009]

[0010] Where: A m 、f m , are the amplitude, frequency and phase of the mth bioelectric signal respectively.

[0011] As a further solution of the present invention, the discrete Fourier transform result is: Where: A m is the amplitude of the bioelectric signal in the frequency domain, ω-ω m is the frequency offset, ω m is the initial frequency, W4(ω-ω m ) is a 4-term rectangular window spectrum function expressed in digital frequency.

[0012] As a further solution of the present invention, the discrete Fourier transform result X(e jw ) is sampled, the digital frequency representation is:

[0013]

[0014] Where: λ=Nω / 2π, λ m =Nω m / 2π=Nf m / f s , is the rectangular window spectrum function expressed in digital frequency, a m is the coefficient of the spectrum function.

[0015] As a further solution of the present invention, let the frequency f mThe corresponding digital frequency position is: λ m =k m +δ m

[0016] Where: k m is a positive integer sampling point, δ m is the interpolation coefficient and δ m ∈[0,1); in the case of asynchronous sampling, δ m ≠0, k m The amplitude spectrum X(k m ) and the true frequency f m There is a bias;

[0017] As a further solution of the present invention, let the amplitude ratio of the spectrum lines of two adjacent frequency points near the frequency point be β m , the β m The expression is:

[0018]

[0019] Where: b i and c 2i are the spectral function coefficients a m The polynomial function of the 4-term 5th-order Nuttall window has a spectral line amplitude ratio of β m b i and c 2i Both are 0.

[0020] As a further solution of the present invention, according to the interpolation coefficient δ m Correct the spectrum analysis result, the δ m The expression is:

[0021]

[0022] An upper limb exoskeleton bioelectric sensing device for live-line workers, the device comprising:

[0023] Bioelectric signal acquisition module: used to sample bioelectric signals at multiple key points of the upper limbs of live workers according to a preset sampling frequency after the workers wearing the upper limb exoskeleton.

[0024] Signal processing module: Perform discrete Fourier transform on the collected bioelectric signal sequence and sample the transformation result to obtain digital frequency;

[0025] Spectrum correction module: according to the calculated spectrum line amplitude ratio of two adjacent frequency points, the spectrum analysis results are corrected using the interpolation coefficient;

[0026] Feature extraction module: Full-wave rectification and low-pass filtering are performed on the corrected spectrum analysis results to obtain the intensity characteristic sequence of the bioelectric signal;

[0027] Display and feedback module: used to display the processed bioelectric signal characteristics and provide operation status feedback or safety warnings based on the signal characteristics.

[0028] A bioelectric sensing computer device for upper limb exoskeleton of workers working with live lines, the computer device comprising at least one processor and a memory, the processor and the memory being connected by a bus, the memory storing at least one program to implement the bioelectric sensing method for upper limb exoskeleton of workers working with live lines as described in any one of claims 1 to 7.

[0029] A bioelectric sensing medium for an upper limb exoskeleton of a worker working with live lines. The medium stores an execution program. When the execution program is executed, a bioelectric sensing method for an upper limb exoskeleton of a worker working with live lines is implemented.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. Using the dual-line interpolation correction algorithm to correct the spectrum results can effectively determine the intensity characteristics of the bioelectric signal and improve the response speed of the exoskeleton;

[0032] 2. The 4-term 5th-order Nuttall window has excellent performance, which helps to reduce spectrum leakage and interference and improve the accuracy of spectrum analysis;

[0033] 3. Full-wave rectification can eliminate the negative part of the signal, making the signal easier to analyze and process; while low-pass filtering can filter out high-frequency noise and retain useful low-frequency information. By combining these two technologies, we can obtain a clearer and more accurate bioelectric signal intensity feature sequence, providing strong support for subsequent decision-making and optimization. By obtaining the bioelectric signal, the final bioelectric signal can be finally determined, which is convenient for determining the current status of the operator based on the final bioelectric signal, so as to detect danger in time. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in combination with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0035] Example

[0036] A bioelectric sensing method for upper limb exoskeleton of live working personnel, comprising the following steps:

[0037] When the exoskeleton is worn by the operator, the sampling frequency f s The bioelectric signals of N points of the operators are sampled, and the sequence obtained after sampling is added with a 4-term cosine window for discrete Fourier transform. The result of discrete Fourier transform is sampled to obtain the digital frequency. According to the digital frequency, the spectral line amplitude ratio of two adjacent frequency points is calculated, and the spectrum analysis result is used for correction. Based on the correction result of the spectrum analysis result, the intensity characteristic sequence of the bioelectric signal can be obtained through full-wave rectification and low-pass filtering.

[0038] Preferably, a bioelectric signal having M frequency components is expressed as:

[0039] Where: A m 、f m , are the amplitude, frequency and phase of the mth signal component respectively.

[0040] Preferably, the sampling frequency f s Perform N-point sampling, and the discrete Fourier transform result of the obtained sequence after sampling plus a 4-term cosine window is:

[0041] Preferably, X(e jw ) is sampled, the digital frequency representation is:

[0042]

[0043] Where: λ=Nω / 2π, λ m =Nω m / 2π=Nf m / f s , W R (λ)=sin(λπ) / sin(λπ / N) is a rectangular window spectrum function expressed in digital frequency.

[0044] Preferably, let the frequency f m The corresponding digital frequency position is: λ m =k m +δ m

[0045] Where: k m is a positive integer sampling point, δ m is the interpolation coefficient and δ m ∈[0,1); in the case of asynchronous sampling, δ m ≠0, k mThe amplitude spectrum X(k m ) and the true frequency f m There is a deviation.

[0046] Preferably, the amplitude ratio of two adjacent spectral lines near the frequency point is β m , the β m The expression is:

[0047]

[0048] Where: b i and c 2i are the spectral function coefficients a m Polynomial function of .

[0049] Preferably, according to the δ m Correct the spectrum analysis result, the δ m The expression is:

[0050]

[0051] Let the spectral line amplitude ratio of the 4-term 5th-order Nuttall window be m b i and c 2i (i≠0) are all 0, and the interpolation coefficient δ is obtained m About the amplitude ratio β m Display expressions that are easier to implement in engineering.

[0052] The time domain expression of the 4-term 5th-order Nuttall window is The sidelobe peak is -61dB, the main lobe width is 16π / N, the spectrum function coefficients a0 are 0.3125, a1 are 0.46875, a2 are 0.1875, and a3 are 0.03125.

[0053] In a certain embodiment, since the movement of the upper limb exoskeleton of the live working personnel is relatively certain, the moving artifact noise can be considered as a fixed value, and the parameter table of the bioelectric signal (including 12 frequency components) with an M value of 12 is as follows:

[0054] Table 1 Parameters of bioelectric signals with M value of 12

[0055]

[0056]

[0057] The amplitude of bioelectric signals is between 0.01-10mV, and the energy is concentrated between 0-1000Hz. Spectrum results need to be corrected to stabilize the useful frequency range between 20-500Hz. At the same time, the frequency error must be less than one ten-thousandth, and the amplitude and phase errors must be less than two percent.

[0058] The sampling signal spectrum analysis time window is set to 10 fundamental wave cycles, that is, the number of sampling points N is 1280. At the same time, due to the low amplitude of the bioelectric signal, the signal component is easily affected by background noise. The measurement results are averaged after 10 measurements to ensure the reliability of the correction results.

[0059] The spectrum analysis measurement results and relative errors are shown in the following table:

[0060] Table 2 Spectrum analysis measurement results and relative error table

[0061]

[0062]

[0063] The accuracy stability between 20-500 Hz in the spectrum analysis measurement of this embodiment meets the requirements.

[0064] Finally, based on the spectrum analysis correction results, the intensity characteristic sequence of the bioelectric signal can be obtained through full-wave rectification and low-pass filtering.

[0065] Example 2

[0066] A bioelectric sensing virtual device for upper limb exoskeleton of live working personnel, the virtual device comprising:

[0067] Bioelectric signal acquisition module: used to sample bioelectric signals at multiple key points of the upper limbs of live workers according to a preset sampling frequency after the workers wearing the upper limb exoskeleton.

[0068] Signal processing module: add a 4-term cosine window to the collected bioelectric signal sequence for discrete Fourier transform, and sample the transformation result to obtain the digital frequency;

[0069] Spectrum correction module: Based on the calculated spectrum line amplitude ratio between two adjacent frequency points, the spectrum analysis results are corrected using interpolation coefficients to reduce the deviation caused by asynchronous sampling;

[0070] Feature extraction module: Full-wave rectification and low-pass filtering are performed on the corrected spectrum analysis results to obtain the intensity characteristic sequence of the bioelectric signal;

[0071] Display and feedback module: used to display the processed bioelectric signal characteristics and provide operation status feedback or safety warnings based on the signal characteristics.

[0072] When this embodiment is applied, the operator first puts on the special upper limb exoskeleton equipment and ensures that the bioelectric signal acquisition module is tightly fitted with multiple key points of the upper limbs to ensure the accurate acquisition of bioelectric signals. The bioelectric signal acquisition module immediately samples the bioelectric signals of the operator's upper limbs continuously and uninterruptedly according to the preset high-precision sampling frequency. The collected bioelectric signals are preliminarily processed by the signal processing module. In order to eliminate the spectrum deviation that may be caused by asynchronous sampling, the spectrum correction module uses advanced interpolation algorithms based on the amplitude ratio of the spectrum lines of two adjacent frequency points to make fine corrections to the spectrum analysis results. The corrected spectrum data enters the feature extraction module, and through full-wave rectification and low-pass filtering, the high-frequency noise is filtered out and the low-frequency feature sequence reflecting the strength of the bioelectric signal is retained. Finally, the processed bioelectric signal characteristics are intuitively displayed to the operator and monitoring personnel through the display and feedback module.

[0073] Example 3

[0074] A bioelectric sensing computer device for upper limb exoskeleton of workers working with live lines, the computer device comprising at least one processor and a memory, the processor and the memory being connected by a bus, the memory storing at least one program to implement the above-mentioned bioelectric sensing method for upper limb exoskeleton of workers working with live lines.

[0075] When this embodiment is applied, the processor and the memory are connected through an efficient bus system, thereby achieving high-speed data transmission and fast execution of instructions.

[0076] Example 4

[0077] A bioelectric sensing medium for an upper limb exoskeleton for workers working with live lines, wherein the medium stores an execution program, and when the execution program is executed, the above-mentioned bioelectric sensing method for an upper limb exoskeleton for workers working with live lines is implemented.

[0078] Although the present invention has been described in detail by way of preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person of ordinary skill in the art may easily think of changes or substitutions within the technical scope disclosed by the present invention, and these shall be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A bioelectric sensing method for upper limb exoskeleton of live working personnel, characterized in that: The following steps are involved: When the exoskeleton is worn by the operator, the sampling frequency f s The bioelectric signals of N points of the operators are sampled to obtain a bioelectric signal sequence, and a 4-term cosine window is added to the bioelectric signal sequence for discrete Fourier transform to obtain a discrete Fourier transform result, and the discrete Fourier transform result is sampled to obtain a digital frequency. According to the digital frequency, the spectral line amplitude ratio of two adjacent frequency points is calculated, and spectrum analysis is performed based on the spectral line amplitude ratio of two adjacent frequency points. The spectrum analysis results are corrected by using interpolation coefficients, and the intensity characteristic sequence of the bioelectric signal is obtained by full-wave rectification and low-pass filtering of the corrected spectrum analysis results.

2. The bioelectric sensing method for upper limb exoskeleton of live working personnel as claimed in claim 1, characterized in that: The expression of a bioelectric signal containing M frequency components is: Where: A m 、f m , are the amplitude, frequency and phase of the mth bioelectric signal respectively.

3. A bioelectric sensing method for upper limb exoskeleton of live working personnel as claimed in claim 2, characterized in that: The discrete Fourier transform result is: Where: A m is the amplitude of the bioelectric signal in the frequency domain, ω-ω m is the frequency offset, ω m is the initial frequency, W4(ω-ω m ) is a 4-term rectangular window spectrum function expressed in digital frequency.

4. A bioelectric sensing method for upper limb exoskeleton of live working personnel as claimed in claim 3, characterized in that: The discrete Fourier transform result X(e) is analyzed at intervals of 2π / N. jw ) is sampled, the digital frequency representation is: Where: λ=Nω / 2π, λ m =Nω m / 2π=Nf m / f s , is the rectangular window spectrum function expressed in digital frequency, a m is the coefficient of the spectrum function.

5. The bioelectric sensing method for upper limb exoskeleton of live working personnel as claimed in claim 4, characterized in that: Let frequency f m The corresponding digital frequency position is: λ m =k m +δ m Where: k m is a positive integer sampling point, δ m is the interpolation coefficient and δ m ∈[0,1); in the case of asynchronous sampling, δ m ≠0, k m The amplitude spectrum X(k m ) and the true frequency f m There is a deviation.

6. A bioelectric sensing method for upper limb exoskeleton of live working personnel as claimed in claim 5, characterized in that: Let the amplitude ratio of the spectrum lines of two adjacent frequency points near the frequency point be β m , the β m The expression is: Where: b i and c 2i are the spectral function coefficients a m The polynomial function of the 4-term 5th-order Nuttall window has a spectral line amplitude ratio of β m b i and c 2i Both are 0.

7. A bioelectric sensing method for upper limb exoskeleton of live working personnel as claimed in claim 6, characterized in that: According to the interpolation coefficient δ m Correct the spectrum analysis result, the δ m The expression is:

8. A bioelectric sensing device for upper limb exoskeleton of live-line workers, using any of the bioelectric sensing methods for upper limb exoskeleton of live-line workers described in claims 1-7, characterized in that: The device comprises: Bioelectric signal acquisition module: used to sample bioelectric signals at multiple key points of the upper limbs of live workers according to a preset sampling frequency after the workers wearing the upper limb exoskeleton. Signal processing module: Perform discrete Fourier transform on the collected bioelectric signal sequence and sample the transformation result to obtain digital frequency; Spectrum correction module: according to the calculated spectrum line amplitude ratio of two adjacent frequency points, the spectrum analysis results are corrected using the interpolation coefficient; Feature extraction module: Full-wave rectification and low-pass filtering are performed on the corrected spectrum analysis results to obtain the intensity characteristic sequence of the bioelectric signal; Display and feedback module: used to display the processed bioelectric signal characteristics and provide operation status feedback or safety warnings based on the signal characteristics.

9. A bioelectric sensing computer device for upper limb exoskeleton of live working personnel, characterized in that: The computer device includes at least one processor and a memory, the processor and the memory are connected by a bus, and the memory stores at least one program to implement the bioelectric sensing method of the upper limb exoskeleton of a live working personnel as described in any one of claims 1-7.

10. A bioelectric sensing medium for upper limb exoskeleton of live working personnel, characterized in that: The medium stores an execution program, and when the execution program is executed, the bioelectric sensing method of the upper limb exoskeleton of a live working personnel as described in any one of claims 1-7 is implemented.

Images