Signal processing method and system for pedestrian sensing revolving door

Abstract

The present invention provides a signal processing method and system for a pedestrian sensing revolving door, which relates to the field of signal processing. The method includes: obtaining a first sensing signal, a second sensing signal and volume information between adjacent revolving door leaves; filtering the first sensing signal to obtain a filtered signal corresponding to the first sensing signal; decomposing the filtered signal through a preset modal decomposition model to obtain decomposition information, wherein the decomposition information includes multiple intrinsic modal components; matching each intrinsic modal component in the decomposition information with the second sensing signal to obtain a matching signal of the revolving door; solving the matching signal of the revolving door and the volume information between adjacent revolving door leaves through a preset target rotation model to obtain an action response signal of the revolving door. The method reduces the amount of interference signals introduced by the microwave radar sensor and improves the sensing accuracy; on the other hand, the sensing signal is associated with the drive motor signal.

Description

Technical Field

[0001] The present invention relates to the field of signal processing, and in particular to a signal processing method and system for a pedestrian sensing revolving door. Background Art

[0002] In the prior art, the general structure of a pedestrian sensing revolving door is as follows: a sensing probe, a driving motor, a driving motor transmission chain, and a limit switch are arranged on the revolving door; when the revolving door is working, the sensing probe is used to obtain information data of personnel activities within a certain range, so that when someone enters or leaves, the driving motor drives the revolving door to perform corresponding actions. When the sensing probe is a microwave radar sensor, the existing signal processing method is single, and the microwave radar sensor is only used as a direct signal trigger source, and the interference signal introduced by the characteristics of the microwave radar sensor itself is not fully processed. The characteristics of microwave radar are that the higher the frequency, the stronger the diffraction ability, the more energy is absorbed, and the greater the proportion of interference signal influence. When the flow of people entering the revolving door is large, the interference signal introduced will increase sharply, affecting the sensing accuracy; on the other hand, the existing processing method ignores the correlation between the sensing signal of the microwave radar sensor and the driving motor signal. Therefore, a signal processing method for pedestrian sensing revolving door is urgently needed. On the one hand, it is necessary to reduce the amount of interference signals introduced by microwave radar sensors and improve the sensing accuracy; on the other hand, it is necessary to associate the sensing signal with the drive motor signal to facilitate directional adjustment of the drive motor speed of the revolving door. Summary of the invention

[0003] The purpose of the present invention is to provide a signal processing method and system for a pedestrian sensing revolving door to improve the above problems. In order to achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0004] In a first aspect, the present application provides a signal processing method for a pedestrian sensing revolving door, the method comprising:

[0005] Acquire a first sensing signal, a second sensing signal, and volume information between adjacent revolving door leaves, wherein the first sensing signal is a movement sensing signal in a preset area at the top of a revolving door post, and the second sensing signal is a fixed value sensing signal in a preset area at the bottom of a revolving door post, and the preset area at the top of the revolving door post and the preset area at the bottom of the revolving door post are calculated using a preset sensing interaction model;

[0006] Performing filtering processing on the first sensing signal to obtain a filtered signal corresponding to the first sensing signal;

[0007] Decomposing the filtered signal by using a preset modal decomposition model to obtain decomposition information, wherein the decomposition information includes a plurality of eigenmode components;

[0008] Performing signal matching on each of the intrinsic mode components in the decomposed information and the second sensing signal to obtain a matching signal of the revolving door;

[0009] The matching signal of the revolving door and the volume information between the adjacent revolving door leaves are solved through a preset target rotation model to obtain an action response signal of the revolving door, and the action response signal of the revolving door is used to trigger the adjustment of the rotation speed of the driving motor of the revolving door.

[0010] In a second aspect, the present application also provides a signal processing system for a pedestrian sensing revolving door, the system comprising:

[0011] an acquisition module, used to acquire a first sensing signal, a second sensing signal and volume information between adjacent revolving door leaves, wherein the first sensing signal is a movement sensing signal in a preset area at the top of a revolving door post, and the second sensing signal is a fixed value sensing signal in a preset area at the bottom of a revolving door post, and the preset area at the top of the revolving door post and the preset area at the bottom of the revolving door post are calculated using a preset sensing interaction model;

[0012] A first processing module, configured to filter the first sensing signal to obtain a filtered signal corresponding to the first sensing signal;

[0013] A second processing module, configured to decompose the filtered signal through a preset modal decomposition model to obtain decomposition information, wherein the decomposition information includes a plurality of eigenmode components;

[0014] a third processing module, configured to perform signal matching on each of the intrinsic mode components in the decomposed information and the second sensing signal to obtain a matching signal of the revolving door;

[0015] The fourth processing module is used to solve the matching signal of the revolving door and the volume information between the adjacent revolving door leaves through a preset target rotation model to obtain an action response signal of the revolving door, and the action response signal of the revolving door is used to trigger the adjustment of the speed of the driving motor of the revolving door.

[0016] The beneficial effects of the present invention are:

[0017] The present invention introduces a first induction signal and a second induction signal, wherein the second induction signal is a constant-value electromagnetic wave and is used to superimpose and amplify the first induction signal, so as to amplify the amount of interference signals introduced by the microwave radar sensor before signal processing, and then reasonably eliminate them during the subsequent signal processing; in addition, the method associates the induction signal with the drive motor signal, so as to facilitate directional adjustment of the speed of the drive motor of the revolving door.

[0018] Other features and advantages of the present invention will be set forth in the following description, and in part will become apparent from the description, or may be understood by practicing embodiments of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 Schematic diagram of the signal processing method of the pedestrian sensing revolving door described in an embodiment of the present invention;

[0021] Figure 2 is a schematic diagram of the arrangement position structure of the first sensor and the second sensor in an embodiment of the present invention;

[0022] Figure 3 A topological structure diagram of the signal processing system of the pedestrian sensing revolving door described in the embodiment of the present invention when in use;

[0023] Figure 4 Schematic diagram of the signal processing system of the pedestrian sensing revolving door described in an embodiment of the present invention;

[0024] Markings in the figure:

[0025] 1. First sensor; 2. Second sensor; 11. Acquisition module; 12. First processing module; 13. Second processing module; 14. Third processing module; 15. Fourth processing module. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0027] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0028] Embodiment 1:

[0029] This embodiment provides a signal processing method for a pedestrian sensing revolving door.

[0030] See also Figure 1 , the figure shows that the method includes steps S1 to S5, specifically:

[0031] S1: Obtaining a first sensing signal, a second sensing signal and volume information between adjacent revolving door leaves, wherein the first sensing signal is a moving sensing signal in a preset area at the top of a revolving door post, and the second sensing signal is a fixed value sensing signal in a preset area at the bottom of a revolving door post, and the preset area at the top of the revolving door post and the preset area at the bottom of the revolving door post are calculated using a preset sensing interaction model;

[0032] In step S1, the first sensing signal and the second sensing signal are both collected by a microwave radar sensor, such as Figure 2 As shown, the microwave radar sensor arranged in the preset area at the top of the revolving door post is the first sensor 1, and the microwave radar sensor arranged in the preset area at the bottom of the revolving door post is the second sensor 2. In this method, the second sensing signal is a fixed-value electromagnetic wave actively emitted and received by the second sensor itself, and the value range of the fixed-value electromagnetic wave can be set according to the preset human flow environment, so the second sensor is a fixed-value sensor; the first sensing signal is a composite electromagnetic wave collected after the first sensor and the second sensor work simultaneously for a preset time, that is, the composite electromagnetic wave is an electromagnetic signal after the electromagnetic wave actively emitted by the first sensor itself is superimposed on the fixed-value electromagnetic wave of the second sensor. Since the emission signal of the first sensor is variable, the first sensor is a motion sensor.

[0033] Since the installation positions of the first sensor and the second sensor determine the radio frequency characteristics, the method proposes to calculate the preset area at the top of the revolving door post and the preset area at the bottom of the revolving door post through a preset induction interaction model. Step S1 includes S11 to S14, specifically:

[0034] S11: Obtaining the height information of the revolving door post, the distance information of the preset detection target and the transmission power information;

[0035] S12: Calculate the power density according to the preset distance information and transmission power information of the detection target to obtain the electromagnetic wave power density of the mobile sensor and the electromagnetic wave power density of the fixed value sensor;

[0036] In step S12, the transmission power information includes the transmission power of the mobile sensor and the transmission power of the fixed value sensor, including steps S121 and S122, specifically:

[0037] S121: performing power density calculation according to the distance information of the preset detection target and the transmission power of the mobile sensor to obtain the electromagnetic wave power density of the mobile sensor;

[0038] In step S121, the calculation formula is:

[0039]

[0040] In the above formula (1), p u represents the electromagnetic wave power density of the mobile sensor, p1 represents the transmission power of the mobile sensor, G1 represents the preset radar antenna gain information of the mobile sensor, and r represents the preset distance information of the detection target.

[0041] S122: Perform power density calculation according to the distance information of the preset detection target and the transmission power of the fixed value sensor to obtain the electromagnetic wave power density of the fixed value sensor.

[0042] In step S122, the calculation formula is:

[0043]

[0044] In the above formula (2), p z represents the electromagnetic wave power density of the fixed value sensor, p2 represents the transmission power of the fixed value sensor, G2 represents the preset radar antenna gain information of the fixed value sensor, and r represents the preset detection target distance information.

[0045] S13: Calculating the height information of the revolving door post and the electromagnetic wave power density of the motion sensor through an induction interaction model to obtain first sensing area information, where the first sensing area information corresponds to a preset area on the top of the revolving door post;

[0046] In step S13, the induction interaction model is:

[0047]

[0048] In the above formula (3), S1 represents the first sensing area information, p u represents the electromagnetic wave power density of the motion sensor, H represents the height information of the revolving door post, Aeff Indicates the preset effective area of ​​the motion sensor's receiving antenna.

[0049] S14: Correct and calculate the first sensing area information, the electromagnetic wave power density of the fixed value sensor and the preset attenuation coefficient to obtain second sensing area information, where the second sensing area information corresponds to a preset area at the bottom of the revolving door post.

[0050]

[0051] In the above formula (4), S2 represents the second sensing area information, p z represents the electromagnetic wave power density of the fixed value sensor, S1 represents the first sensing area information, and λ represents the preset attenuation coefficient.

[0052] S2: Filter the first sensing signal to obtain a filtered signal corresponding to the first sensing signal;

[0053] In this method, since the first induction signal is a composite electromagnetic wave, filtering is required before decomposing the first induction signal to remove unnecessary induction signal components. The filtering method may adopt the existing limiting filtering method.

[0054] S3: Decomposing the filtered signal by a preset modal decomposition model to obtain decomposition information, wherein the decomposition information includes a plurality of eigenmode components;

[0055] In step S3, the modal decomposition model includes a first decomposition model and a second decomposition model, including steps S31 to S34, specifically:

[0056] S31: acquiring first white noise information and second white noise information, wherein the first white noise information is a maximum input signal corresponding to the driving motor of the revolving door when the revolving door operates normally, and the second white noise information is a minimum input signal corresponding to the driving motor of the revolving door when the revolving door operates normally;

[0057] S32: Decomposing and calculating the first white noise information and the filtered signal through a first decomposition model to obtain primary decomposition residual value information;

[0058] Step S32 includes steps S321 to S324, specifically:

[0059] S321: classifying the first white noise information to obtain a plurality of different first white noise classification signals;

[0060] In step S321, the calculation formula of the jth first white noise classification signal is:

[0061]

[0062] In the above formula (5), x j represents the jth first white noise graded signal, ε max Indicates the maximum amplitude information corresponding to the drive motor of the revolving door, 2 j represents the classification variable of the first white noise information, x represents the first white noise information, and j has a value range of 1 to m, wherein m represents the number of classifications after the first white noise information is classified.

[0063] S322: Mix each of the different first white noise classification signals with the filtered signal to obtain a plurality of first mixed signals;

[0064] S323: Decompose each of the first mixed signals in turn using a first decomposition model to obtain first intrinsic mode component information corresponding to each of the first mixed signals;

[0065] In step S323, the first decomposition model is:

[0066]

[0067] In the above formula (6), IMF i represents the first intrinsic mode component information corresponding to the i-th first mixed signal, M(z i ) represents the i-th first mixed signal, represents the mean envelope of the i-th first mixed signal, represents the upper envelope of the i-th first mixed signal, represents the lower envelope of the i-th first mixed signal, where i ranges from 1 to n, and n represents the total amount of decomposition of the first intrinsic mode component information.

[0068] S324: Calculate all the first eigenmode component information to obtain primary decomposition residual value information.

[0069] In step S324, the calculation formula for the primary decomposition residual value information is:

[0070]

[0071] In the above formula (7), r1 represents the residual value information of the first decomposition, M(z i ) represents the i-th first mixed signal, represents the mean information of all the first intrinsic mode component information, i ranges from 1 to n, n represents the total amount of decomposition of the first intrinsic mode component information, IMF i Represents the first intrinsic mode component information corresponding to the i-th first mixed signal.

[0072] S33: Decomposing and calculating the second white noise information and the first decomposition residual value information by using a second decomposition model to obtain second decomposition residual value information;

[0073] Step S33 includes steps S331 to S334, specifically:

[0074] S331: classifying the second white noise information to obtain a plurality of different second white noise classification signals;

[0075] In step S331, the calculation formula of the kth second white noise classification signal is:

[0076]

[0077] In the above formula (8), y k represents the kth second white noise hierarchical signal, ε min Indicates the minimum amplitude information corresponding to the drive motor of the revolving door, 2 k represents the classification variable of the second white noise information, y represents the second white noise information, and k ranges from 1 to q, where q represents the number of classifications after the second white noise information is classified.

[0078] In this method, in order to facilitate mapping processing of each classified signal, the number of classifications m of the first white noise information and the number of classifications q of the second white noise information may be the same.

[0079] S332: Mix each of the different second white noise hierarchical signals with the primary decomposition residual value information to obtain a plurality of second mixed signals;

[0080] S333: Decompose each of the second mixed signals in turn using a second decomposition model to obtain second intrinsic mode component information corresponding to each of the second mixed signals;

[0081] In step S333, the second decomposition model is:

[0082]

[0083] In the above formula (9), IMF′ b represents the second intrinsic mode component information corresponding to the bth second mixed signal, M′(z b ) represents the bth second mixed signal, represents the mean envelope of the b-th second mixed signal, represents the upper envelope of the b-th second mixed signal, represents the lower envelope of the bth second mixed signal, where b ranges from 1 to w, and w represents the total amount of decomposition of the second intrinsic mode component information.

[0084] S334: Calculate all the second eigenmode component information to obtain the secondary decomposition residual information.

[0085] In step S334, the calculation formula for the secondary decomposition residual information is:

[0086]

[0087] In the above formula (10), r2 represents the secondary decomposition residual information, M′(z b ) represents the b-th second mixed signal, represents the mean information of all the second eigenmode component information, and the value range of b is from 1 to w, where w represents the total amount of decomposition of the second eigenmode component information.

[0088] S34: When the secondary decomposition residual information meets the preset discrimination condition, stop the iterative decomposition to obtain the decomposition information.

[0089] In this method, the preset discrimination condition is: r2 < a, where a represents the preset residual signal judgment threshold. When the secondary decomposition residual information is less than a, stop the iterative decomposition, and construct the second eigenmode components obtained before stopping the iterative decomposition as the decomposition information.

[0090] S4: Match each eigenmode component in the decomposition information with the second induction signal to obtain the matching signal of the revolving door;

[0091] In step S4, when performing signal matching, an existing matching pursuit algorithm can be used. Since each eigenmode component is a one-dimensional signal and the second induction signal is a fixed-value electromagnetic signal, the second induction signal is used as the reference signal during matching pursuit. When the actual sparse value in the current eigenmode component is greater than the preset sparse value, then this eigenmode component is removed, where the actual sparse value represents the coincidence degree between the corresponding signal in the current eigenmode component and the second induction signal. When the coincidence degree is high, the sparse value is a zero element at this time. When the coincidence degree is poor, non-zero elements will appear; when the actual sparse value in the current eigenmode component is less than the preset sparse value, then this eigenmode component is saved to obtain the matching signal of the revolving door.

[0092] S5: Solve the matching signal of the revolving door and the volume information between adjacent revolving door leaves through a preset target rotation model to obtain the action response signal of the revolving door, and the action response signal of the revolving door is used to trigger the adjustment of the rotational speed of the driving motor of the revolving door.

[0093] In step S5, the preset target rotation model is:

[0094] f(t)={1-v×η(t)}×g(t); (11)

[0095] In the above formula (11), f(t) represents the action response signal of the revolving door, η(t) represents the preset unit signal response periodic function, v represents the volume information between adjacent revolving door leaves, g(t) represents the matching signal of the revolving door, and t represents the response time.

[0096] After the motion response f(t) of the revolving door is calculated, the response signal power is calculated based on f(t):

[0097]

[0098] In the above formula (12), P represents the response signal power, T represents the preset period, and f(t) represents the action response signal of the revolving door.

[0099] According to the size of the response signal power, it is matched with the graded drive motor power of the revolving door to obtain the corresponding drive motor power of the revolving door; when the drive motor torque of the revolving door is constant, the drive motor power is proportional to the drive motor speed, and the drive motor speed of the revolving door can be adjusted by changing the response signal power.

[0100] Embodiment 2:

[0101] like Figure 3 As shown, it is a topological structure diagram of the signal processing system of the present invention when it is applied. First, the signals corresponding to the first sensor and the second sensor are collected respectively; then the first sensing signal and the second sensing signal are input into the signal processing system, and finally the signal processed by the signal processing system is displayed.

[0102] like Figure 4 As shown, this embodiment provides a signal processing system for a pedestrian sensing revolving door, the system comprising:

[0103] An acquisition module 11 is used to acquire a first sensing signal, a second sensing signal and volume information between adjacent revolving door leaves, wherein the first sensing signal is a movement sensing signal in a preset area at the top of a revolving door post, and the second sensing signal is a fixed value sensing signal in a preset area at the bottom of a revolving door post, and the preset area at the top of the revolving door post and the preset area at the bottom of the revolving door post are calculated using a preset sensing interaction model;

[0104] A first processing module 12, configured to filter the first sensing signal to obtain a filtered signal corresponding to the first sensing signal;

[0105] The second processing module 13 is used to decompose the filtered signal through a preset modal decomposition model to obtain decomposition information, wherein the decomposition information includes a plurality of eigenmode components;

[0106] A third processing module 14 is used to perform signal matching on each of the intrinsic mode components in the decomposed information and the second sensing signal to obtain a matching signal of the revolving door;

[0107] The fourth processing module 15 is used to solve the matching signal of the revolving door and the volume information between the adjacent revolving door leaves through a preset target rotation model to obtain an action response signal of the revolving door, and the action response signal of the revolving door is used to trigger the adjustment of the speed of the driving motor of the revolving door.

[0108] In an implementation method disclosed in the present invention, the modal decomposition model in the second processing module 13 includes a first decomposition model and a second decomposition model, including:

[0109] a first acquisition unit, configured to acquire first white noise information and second white noise information, wherein the first white noise information is a maximum input signal corresponding to a driving motor of the revolving door when the revolving door operates normally, and the second white noise information is a minimum input signal corresponding to the driving motor of the revolving door when the revolving door operates normally;

[0110] A first calculation unit, configured to perform decomposition calculation on the first white noise information and the filtered signal through a first decomposition model to obtain primary decomposition residual value information;

[0111] A second calculation unit is used to perform decomposition calculation on the second white noise information and the first decomposition residual value information through a second decomposition model to obtain second decomposition residual value information;

[0112] The discriminating unit is used to stop iterative decomposition when the secondary decomposition residual value information meets a preset discriminating condition to obtain decomposition information.

[0113] It should be noted that, regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

Claims

1. A signal processing method for a pedestrian sensing revolving door, characterized in that: include: Acquire a first sensing signal, a second sensing signal, and volume information between adjacent revolving door leaves, wherein the first sensing signal is a movement sensing signal in a preset area at the top of a revolving door post, and the second sensing signal is a fixed value sensing signal in a preset area at the bottom of a revolving door post, and the preset area at the top of the revolving door post and the preset area at the bottom of the revolving door post are calculated using a preset sensing interaction model; Performing filtering processing on the first sensing signal to obtain a filtered signal corresponding to the first sensing signal; Decomposing the filtered signal by using a preset modal decomposition model to obtain decomposition information, wherein the decomposition information includes a plurality of eigenmode components; Performing signal matching on each of the intrinsic mode components in the decomposed information and the second sensing signal to obtain a matching signal of the revolving door; The matching signal of the revolving door and the volume information between the adjacent revolving door leaves are solved through a preset target rotation model to obtain an action response signal of the revolving door, and the action response signal of the revolving door is used to trigger the adjustment of the rotation speed of the driving motor of the revolving door.

2. The signal processing method for a pedestrian sensing revolving door according to claim 1, characterized in that: The preset area at the top of the revolving door post and the preset area at the bottom of the revolving door post are calculated by a preset induction interaction model, including: Obtain the height information of the revolving door post, the distance information of the preset detection target and the transmission power information; The power density is calculated according to the preset detection target distance information and transmission power information to obtain the electromagnetic wave power density of the mobile sensor and the electromagnetic wave power density of the fixed value sensor; The height information of the revolving door post and the electromagnetic wave power density of the motion sensor are calculated by using an induction interaction model to obtain first induction area information, where the first induction area information corresponds to a preset area at the top of the revolving door post; The first sensing area information, the electromagnetic wave power density of the fixed value sensor and the preset attenuation coefficient are corrected and calculated to obtain the second sensing area information, and the second sensing area information corresponds to the preset area at the bottom of the revolving door column.

3. The signal processing method for a pedestrian sensing revolving door according to claim 2, characterized in that: The power density is calculated according to the preset detection target distance information and the transmission power information to obtain the electromagnetic wave power density of the mobile sensor and the electromagnetic wave power density of the fixed value sensor, wherein the transmission power information includes the transmission power of the mobile sensor and the transmission power of the fixed value sensor, including: Performing power density calculation according to the distance information of the preset detection target and the transmission power of the mobile sensor to obtain the electromagnetic wave power density of the mobile sensor; The power density is calculated according to the distance information of the preset detection target and the transmission power of the fixed value sensor to obtain the electromagnetic wave power density of the fixed value sensor.

4. The signal processing method for a pedestrian sensing revolving door according to claim 2, characterized in that: The height information of the revolving door post and the electromagnetic wave power density of the motion sensor are calculated through an induction interaction model to obtain first induction area information, where the first induction area information corresponds to a preset area at the top of the revolving door post. The induction interaction model is: The induction interaction model is: In the above formula, S1 represents the first sensing area information, p u represents the electromagnetic wave power density of the motion sensor, H represents the height information of the revolving door post, A eff Indicates the preset effective area of ​​the motion sensor's receiving antenna.

5. The signal processing method for a pedestrian sensing revolving door according to claim 1, characterized in that: The filtered signal is decomposed by a preset modal decomposition model to obtain decomposition information, wherein the decomposition information includes a plurality of eigenmode components, and the modal decomposition model includes a first decomposition model and a second decomposition model, including: Acquire first white noise information and second white noise information, wherein the first white noise information is a maximum input signal corresponding to the driving motor of the revolving door when the revolving door operates normally, and the second white noise information is a minimum input signal corresponding to the driving motor of the revolving door when the revolving door operates normally; Decomposing and calculating the first white noise information and the filtered signal through a first decomposition model to obtain primary decomposition residual value information; Decomposing and calculating the second white noise information and the first decomposition residual value information through a second decomposition model to obtain second decomposition residual value information; When the secondary decomposition residual value information meets the preset judgment condition, the iterative decomposition is stopped to obtain the decomposition information.

6. The signal processing method for a pedestrian sensing revolving door according to claim 5, characterized in that: Decomposing and calculating the first white noise information and the filtered signal through a first decomposition model to obtain primary decomposition residual value information includes: Classifying the first white noise information to obtain a plurality of different first white noise classification signals; Mixing each of the different first white noise classification signals with the filtered signal to obtain a plurality of first mixed signals; Decomposing each of the first mixed signals in turn by using a first decomposition model to obtain first intrinsic mode component information corresponding to each of the first mixed signals; All the first eigenmode component information is calculated to obtain primary decomposition residual value information.

7. The signal processing method for a pedestrian sensing revolving door according to claim 6, characterized in that: Decompose each of the first mixed signals in turn through a first decomposition model to obtain first intrinsic mode component information corresponding to each of the first mixed signals, wherein the first decomposition model is: In the above formula, IMF i represents the first intrinsic mode component information corresponding to the i-th first mixed signal, M(z i ) represents the i-th first mixed signal, represents the mean envelope of the i-th first mixed signal, represents the upper envelope of the i-th first mixed signal, represents the lower envelope of the i-th first mixed signal, where i ranges from 1 to n, and n represents the total amount of decomposition of the first intrinsic mode component information.

8. The signal processing method for a pedestrian sensing revolving door according to claim 6, characterized in that: All the first eigenmode component information is calculated to obtain the primary decomposition residual value information, wherein the calculation formula of the primary decomposition residual value information is: In the above formula, r1 represents the residual value information of the first decomposition, M(z i ) represents the i-th first mixed signal, represents the mean information of all the first intrinsic mode component information, i ranges from 1 to n, n represents the total amount of decomposition of the first intrinsic mode component information, IMF i Represents the first intrinsic mode component information corresponding to the i-th first mixed signal.

9. The signal processing method for a pedestrian sensing revolving door according to claim 1, characterized in that: The matching signal of the revolving door and the volume information between the adjacent revolving door leaves are solved by a preset target rotation model to obtain an action response signal of the revolving door, wherein the preset target rotation model is: f(t)={1-v×η(t)}×h(t); In the above formula, f(t) represents the action response signal of the revolving door, η(t) represents the preset unit signal response periodic function, v represents the volume information between adjacent revolving door leaves, g(t) represents the matching signal of the revolving door, and t represents the response time.

10. A signal processing system for a pedestrian sensing revolving door, characterized in that: include: an acquisition module, used to acquire a first sensing signal, a second sensing signal and volume information between adjacent revolving door leaves, wherein the first sensing signal is a movement sensing signal in a preset area at the top of a revolving door post, and the second sensing signal is a fixed value sensing signal in a preset area at the bottom of a revolving door post, and the preset area at the top of the revolving door post and the preset area at the bottom of the revolving door post are calculated using a preset sensing interaction model; A first processing module, configured to filter the first sensing signal to obtain a filtered signal corresponding to the first sensing signal; A second processing module, configured to decompose the filtered signal through a preset modal decomposition model to obtain decomposition information, wherein the decomposition information includes a plurality of eigenmode components; a third processing module, configured to perform signal matching on each of the intrinsic mode components in the decomposed information and the second sensing signal to obtain a matching signal of the revolving door; The fourth processing module is used to solve the matching signal of the revolving door and the volume information between the adjacent revolving door leaves through a preset target rotation model to obtain an action response signal of the revolving door, and the action response signal of the revolving door is used to trigger the adjustment of the speed of the driving motor of the revolving door.

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