Intelligent safety door lock system for offshore wind power fan tower drum

Abstract

The invention relates to the technical field of offshore wind power, and discloses an intelligent safety door lock system for an offshore wind power fan tower drum. The face acquisition module is used for acquiring a to-be-recognized user face image and judging a matching relationship between the to-be-recognized user face image and a preset user face image; the fingerprint acquisition module is used for acquiring fingerprint information of a to-be-identified user and judging a matching relationship between the fingerprint information of the to-be-identified user and preset fingerprint information of the user; the control module is used for judging whether the door lock is opened or not according to judgment results of the face acquisition module and the fingerprint acquisition module; the user sensing module is used for detecting whether a to-be-recognized user exists or not, and if the to-be-recognized user does not exist, the power supply of the face acquisition module, the power supply of the fingerprint acquisition module and the power supply of the control module are disconnected; if the to-be-identified user exists, switching on a power supply; and the power supply module is used for supplying power to other modules, so that a worker with user authority can normally open the tower door lock of the offshore wind turbine, and the safety of the tower door lock is improved.

Description

Technical Field

[0001] The present invention relates to the field of offshore wind power technology, and in particular to an intelligent safety door lock system for an offshore wind turbine tower. Background Art

[0002] Offshore wind resources are abundant and stable, especially in deep sea and offshore areas, where wind speeds are higher and more consistent and the available area is vast, providing huge power generation potential and effectively reducing dependence on limited land wind energy resources. Offshore wind turbines do not need to occupy precious land resources, avoiding the impact on land for agriculture, forestry and urban development, and reducing land use conflicts caused by the construction of wind farms on land.

[0003] However, the harsh offshore environment, long-term seawater erosion, high and low temperature changes, and strong winds can easily damage and fail the mechanical locks of traditional wind turbine towers, resulting in the door locks being unable to be opened or closed normally, causing unauthorized entry and unnecessary casualties. The key collection and return process for traditional locks is cumbersome, and keys are easily lost or forgotten. When work tasks change temporarily, the required keys cannot be obtained in time, affecting work efficiency. In addition, some traditional tower door locks have a simple structure and are easily pried open, and the door lock status cannot be monitored in time, resulting in the theft of cables, transformers, motors and other property inside the wind turbine, causing economic losses. Summary of the invention

[0004] The embodiment of the present application solves the technical problem of low safety of offshore wind turbine tower door locks in the prior art by providing an offshore wind turbine tower intelligent safety door lock system, thereby achieving an effective solution to the safety problem of offshore wind turbine towers.

[0005] In order to achieve the above object, the present invention provides an offshore wind turbine tower intelligent safety door lock system, comprising:

[0006] Door locks;

[0007] A face acquisition module is used to acquire a face image of a user to be identified and determine the matching relationship between the face image of the user to be identified and a preset face image of the user;

[0008] The fingerprint collection module is used to collect the fingerprint information of the user to be identified and determine the matching relationship between the fingerprint information of the user to be identified and the fingerprint information preset by the user;

[0009] A control module, used for judging whether to open the door lock according to the judgment results of the face acquisition module and the fingerprint acquisition module;

[0010] A user sensing module is used to detect whether there is a user to be identified. If there is no user to be identified, the power supply of the face acquisition module, the fingerprint acquisition module and the control module is disconnected; if there is a user to be identified, the power supply of the face acquisition module, the fingerprint acquisition module and the control module is connected;

[0011] A power module is used to supply power to the face acquisition module, fingerprint acquisition module, control module and user sensing module.

[0012] Furthermore, the face acquisition module is used to acquire a face image of a user to be identified and determine a matching relationship between the face image of the user to be identified and a preset face image of the user, and further includes:

[0013] Collect n facial images of the same user to be identified;

[0014] Normalize and grayscale all the collected face images of users to be identified, and expand each face image into an m-dimensional vector;

[0015] Construct the face matrix K of the user to be identified:

[0016]

[0017] Among them, X 1 is the m-dimensional vector after the first face image of the user to be identified is expanded, X n is the m-dimensional vector after the n-th face image of the user to be identified is expanded;

[0018] Calculate the covariance matrix of the face matrix of the user to be identified according to the following formula:

[0019]

[0020] Among them, C is the covariance matrix of the face matrix of the user to be identified, n is the total number of face images of the user to be identified, T is the matrix transpose symbol, K T Transpose the face matrix of the user to be identified;

[0021] Calculating eigenvectors of the covariance matrix;

[0022] Select the first k eigenvectors with cumulative contribution rate reaching 96% as principal components;

[0023] Project the expanded vector of each face image of the user to be identified onto the principal component to obtain the feature vector of the face image of the user to be identified:

[0024]

[0025] Among them, y i is the feature vector of the i-th user face image to be identified, is the eigenvector transpose of the covariance matrix of the first user face matrix to be identified, is the eigenvector transpose of the covariance matrix of the kth user face matrix to be identified, X i is the m-dimensional vector after the i-th face image of the user to be identified is expanded.

[0026] Furthermore, the face acquisition module is used to acquire a face image of a user to be identified and determine a matching relationship between the face image of the user to be identified and a preset face image of the user, and further includes:

[0027] Pre-set the Euclidean threshold of the face;

[0028] Presetting a user preset face image, and obtaining a feature vector of the user preset face image;

[0029] Calculate the Euclidean distance between the feature vector of the face image of the user to be identified and the feature vector of the user preset face image:

[0030]

[0031] Where d is the Euclidean distance between the feature vector of the face image of the user to be identified and the feature vector of the face image preset by the user, z i The i-th user preset face image feature vector;

[0032] When the Euclidean distance between the feature vector of the user face image to be identified and the feature vector of the user preset face image is less than the face Euclidean threshold, it is determined that the user face image to be identified matches the user preset face image.

[0033] Furthermore, the fingerprint collection module is used to collect fingerprint information of the user to be identified and determine the matching relationship between the fingerprint information of the user to be identified and the fingerprint information preset by the user, including:

[0034] Presetting user preset fingerprint information and obtaining a feature vector of the user preset fingerprint information;

[0035] Collecting fingerprint information of the user to be identified, normalizing the size and direction of the fingerprint information of the user to be identified, and obtaining a feature vector of the fingerprint information of the user to be identified;

[0036] Preset a fingerprint Euclidean threshold, and calculate the Euclidean distance between the fingerprint information feature vector of the user to be identified and the fingerprint information feature vector of the user preset;

[0037] When the Euclidean distance between the feature vector of the fingerprint information of the user to be identified and the feature vector of the preset fingerprint information of the user is less than the fingerprint Euclidean threshold, it is determined that the fingerprint information of the user to be identified matches the preset fingerprint information of the user.

[0038] Furthermore, the control module is used to determine whether to open the door lock according to the determination results of the face acquisition module and the fingerprint acquisition module, and further includes:

[0039] When the face image of the user to be identified matches the preset face image of the user, or the fingerprint information of the user matches the preset fingerprint information of the user, the door lock is opened.

[0040] Further, the user sensing module is used to detect whether there is a user to be identified. If there is no user to be identified, the power supply of the face acquisition module, the fingerprint acquisition module and the control module is disconnected; if there is a user to be identified, the power supply of the face acquisition module, the fingerprint acquisition module and the control module is connected, and also includes:

[0041] Presetting a first detection range and a second detection range, wherein the radius of the first detection range is greater than the radius of the second detection range;

[0042] If there is no user to be identified within the first detection range, the user sensing module disconnects the power supplies of the face acquisition module, the fingerprint acquisition module and the control module;

[0043] If there is a user to be identified within the first detection range, determine whether the user to be identified is close to the second detection range, and if so, calculate the proximity time factor of the user to be identified, and set the power-on time of the face acquisition module, fingerprint acquisition module and control module according to the proximity time factor;

[0044] When the user to be identified enters the second detection range, the user sensing module sends a detection instruction to the control module, and the control module controls the face acquisition module and the fingerprint acquisition module to enter the information acquisition state.

[0045] Further, judging whether the user to be identified is close to the second detection range, and if so, calculating the proximity time factor of the user to be identified, and setting the power-on time of the face acquisition module, the fingerprint acquisition module and the control module according to the proximity time factor, including:

[0046] When a user to be identified appears within the first detection range, transmitting a first microwave signal to the user to be identified, and calculating a first return time of the microwave reflected wave signal;

[0047] Transmitting a second microwave signal to the user to be identified, and calculating a second return time of the microwave reflected wave signal;

[0048] Calculate a first return time difference between the first return time and the second return time;

[0049] When the first return time difference is greater than or equal to the preset return time difference, it is determined that the user to be identified is not close to the second detection range, and the power of the face acquisition module, the fingerprint acquisition module and the control module is not turned on;

[0050] When the first return time difference is less than the preset return time difference, it is determined that the user to be identified is close to the second detection range, and the product of the first return time and the first return time difference is calculated and used as the first return time factor;

[0051] Transmitting a third microwave signal to the user to be identified, and calculating a third return time of the microwave reflected wave signal;

[0052] transmitting a fourth microwave signal to the user to be identified, and calculating a fourth return time of the microwave reflected wave signal;

[0053] Calculate a second return time difference between the third return time and the fourth return time;

[0054] Calculate the product of the third return time and the second return time difference and use it as the second return time factor;

[0055] Calculating the approach time factor according to the first return time factor and the second return time factor;

[0056] The power-on time of the face acquisition module, the fingerprint acquisition module and the control module is set according to the proximity time factor and the proximity time factor-on time mapping table.

[0057] Further, the calculating the approach time factor according to the first return time factor and the second return time factor further includes:

[0058] A=t 1 ×a 1 +t 2 ×a 2 ;

[0059] Where A is the approach time factor; t 1 is the calculation weight of the first return time factor, a 1 is the first return time factor, t 2 is the calculation weight of the second return time factor, a 2 is the second return time factor, t 1 +t 2 =1,t 1 <t 2 .

[0060] Furthermore, the offshore wind turbine tower intelligent safety door lock system further includes:

[0061] The waterproof housing includes the face acquisition module, the fingerprint acquisition module, the control module, the user sensing module and the power supply module.

[0062] Furthermore, the offshore wind turbine tower intelligent safety door lock system further includes:

[0063] An alarm module is used to issue a reminder or warning through voice when the face collection module and the fingerprint collection module collect the user information to be identified for multiple times and the verification fails;

[0064] The alarm module is also used to record the facial image of the user to be identified and report it to the monitoring center when the door lock is opened abnormally.

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] The present invention discloses an intelligent safety door lock system for an offshore wind turbine tower. User-related information is entered in advance through a face acquisition module and a fingerprint acquisition module. In subsequent use, only the user to be identified whose user information is entered in advance is allowed to enter, so as to avoid unnecessary losses caused by the accidental entry of unrelated personnel. At the same time, the user sensing module controls the power module more intelligently, so as to better save energy. The waterproof shell is used to better extend the use time of the door lock. At the same time, an alarm module is added, so as to monitor and record illegal intruders in the first time, so as to ensure the safety inside the offshore wind turbine tower. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0068] Figure 1 A structural schematic diagram of an offshore wind turbine tower intelligent safety door lock system in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0069] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0070] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0071] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0072] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0073] The following is a description of preferred embodiments of the present invention with reference to the accompanying drawings.

[0074] like Figure 1 As shown, an embodiment of the present invention discloses an intelligent safety door lock system for an offshore wind turbine tower, comprising:

[0075] Door locks;

[0076] The face acquisition module is used to acquire the face image of the user to be identified and determine the matching relationship between the face image of the user to be identified and the face image preset by the user;

[0077] The fingerprint collection module is used to collect the fingerprint information of the user to be identified and determine the matching relationship between the fingerprint information of the user to be identified and the fingerprint information preset by the user;

[0078] A control module, used to determine whether to open the door lock according to the judgment results of the face collection module and the fingerprint collection module;

[0079] The user sensing module is used to detect whether there is a user to be identified. If there is no user to be identified, the power supply of the face acquisition module, the fingerprint acquisition module and the control module is disconnected; if there is a user to be identified, the power supply of the face acquisition module, the fingerprint acquisition module and the control module is connected;

[0080] The power module is used to supply power to the face acquisition module, fingerprint acquisition module, control module and user sensing module.

[0081] In this embodiment, a face acquisition module and a fingerprint acquisition module are provided to verify the user who wants to enter the offshore wind turbine tower door lock, and a user sensing module is added to intelligently distribute the power supply.

[0082] In some embodiments of the present application, the face acquisition module is used to acquire a face image of a user to be identified and determine a matching relationship between the face image of the user to be identified and a face image preset by the user, and further includes:

[0083] Collect n facial images of the same user to be identified;

[0084] Normalize and grayscale all the collected face images of users to be identified, and expand each face image into an m-dimensional vector;

[0085] Construct the face matrix K of the user to be identified:

[0086]

[0087] Among them, X 1 is the m-dimensional vector after the first face image of the user to be identified is expanded, X n is the m-dimensional vector after the n-th face image of the user to be identified is expanded;

[0088] Calculate the covariance matrix of the face matrix of the user to be identified according to the following formula:

[0089]

[0090] Among them, C is the covariance matrix of the face matrix of the user to be identified, n is the total number of face images of the user to be identified, T is the matrix transpose symbol, K T Transpose the face matrix of the user to be identified;

[0091] Compute the eigenvectors of the covariance matrix;

[0092] Select the first k eigenvectors with cumulative contribution rate reaching 96% as principal components;

[0093] Project the expanded vector of each face image of the user to be identified onto the principal component to obtain the feature vector of the face image of the user to be identified:

[0094]

[0095] Among them, y i is the feature vector of the i-th user face image to be identified, is the eigenvector transpose of the covariance matrix of the first user face matrix to be identified, is the eigenvector transpose of the covariance matrix of the kth user face matrix to be identified, X i is the m-dimensional vector after the i-th face image of the user to be identified is expanded.

[0096] In this embodiment, a plurality of facial images of the user to be identified are collected to extract feature vectors, thereby improving the accuracy of the extracted facial feature vectors of the user to be identified.

[0097] In this embodiment, the face acquisition module is used to acquire the face image of the user to be identified and determine the matching relationship between the face image of the user to be identified and the face image preset by the user, and also includes:

[0098] Pre-set the Euclidean threshold of the face;

[0099] Presetting a user preset face image and obtaining a feature vector of the user preset face image;

[0100] Calculate the Euclidean distance between the feature vector of the face image of the user to be identified and the feature vector of the face image preset by the user:

[0101]

[0102] Where d is the Euclidean distance between the feature vector of the face image of the user to be identified and the feature vector of the face image preset by the user, z i Feature vector of the i-th user-preset face image;

[0103] When the Euclidean distance between the feature vector of the user face image to be identified and the feature vector of the user preset face image is less than the face Euclidean threshold, it is determined that the user face image to be identified matches the user preset face image.

[0104] In this embodiment, the method for extracting the feature vector of the user preset facial image is consistent with the method for extracting the feature vector of the user facial image to be identified. n user preset facial images are collected, and a user preset facial image matrix is ​​established to obtain the user preset facial image feature vector.

[0105] The beneficial effect of the above technical solution is: using face unlocking instead of traditional mechanical unlocking, the door lock can be opened in time to cope with temporary changes in work tasks, thereby improving work efficiency.

[0106] In some embodiments of the present application, the fingerprint collection module is used to collect fingerprint information of the user to be identified and determine the matching relationship between the fingerprint information of the user to be identified and the fingerprint information preset by the user, including:

[0107] Presetting user preset fingerprint information and obtaining a feature vector of the user preset fingerprint information;

[0108] Collecting fingerprint information of the user to be identified, normalizing the size and direction of the fingerprint information of the user to be identified, and obtaining a feature vector of the fingerprint information of the user to be identified;

[0109] Preset the fingerprint Euclidean threshold, and calculate the Euclidean distance between the fingerprint information feature vector of the user to be identified and the fingerprint information feature vector preset by the user;

[0110] When the Euclidean distance between the feature vector of the fingerprint information of the user to be identified and the feature vector of the preset fingerprint information of the user is less than the fingerprint Euclidean threshold, it is determined that the fingerprint information of the user to be identified matches the preset fingerprint information of the user.

[0111] The beneficial effect of the above technical solution is: in conjunction with the face acquisition module, when the user to be identified wears a mask or other face obstructing objects, fingerprint verification can be used preferentially, thereby improving the applicability of the intelligent safety door lock system of the offshore wind turbine tower.

[0112] In some embodiments of the present application, the control module is used to determine whether to open the door lock according to the determination results of the face acquisition module and the fingerprint acquisition module, and further includes:

[0113] When the face image of the user to be identified matches the face image preset by the user, or the fingerprint information of the user matches the fingerprint information preset by the user, the door lock is unlocked.

[0114] In this embodiment, a door lock locking time is preset. After the control module opens the door lock, if the user exceeds the door lock locking time and still fails to open the offshore wind turbine tower safety door, the control module automatically closes the door lock, and the user needs to re-verify the unlocking; in addition, after the control module detects that the safety door is opened and closed again, the control module closes the door lock again, and the user outside the safety door needs to re-verify the unlocking.

[0115] In some embodiments of the present application, the user sensing module is used to detect whether there is a user to be identified. If there is no user to be identified, the power supply of the face acquisition module, the fingerprint acquisition module and the control module is disconnected; if there is a user to be identified, the power supply of the face acquisition module, the fingerprint acquisition module and the control module is connected, and further includes:

[0116] Preset a first detection range and a second detection range, wherein the radius of the first detection range is greater than the radius of the second detection range;

[0117] If there is no user to be identified within the first detection range, the user sensing module disconnects the power supply of the face acquisition module, the fingerprint acquisition module and the control module;

[0118] If there is a user to be identified within the first detection range, determine whether the user to be identified is close to the second detection range. If so, calculate the proximity time factor of the user to be identified, and set the power-on time of the face acquisition module, the fingerprint acquisition module and the control module according to the proximity time factor;

[0119] When the user to be identified enters the second detection range, the user sensing module sends a detection instruction to the control module, and the control module controls the face acquisition module and the fingerprint acquisition module to enter the information acquisition state.

[0120] In this embodiment, a first detection range and a second detection range are set to detect whether there is a user to be identified. When the user to be identified appears in the first detection range and tends to approach the second detection range, the power of each module is turned on and the user information pre-collection state is entered.

[0121] In this embodiment, it is determined whether the user to be identified is close to the second detection range. If so, the proximity time factor of the user to be identified is calculated, and the power-on time of the face acquisition module, the fingerprint acquisition module and the control module is set according to the proximity time factor, including:

[0122] When a user to be identified appears within the first detection range, a first microwave signal is transmitted to the user to be identified, and a first return time of the microwave reflected wave signal is calculated;

[0123] Transmitting a second microwave signal to the user to be identified, and calculating a second return time of the microwave reflected wave signal;

[0124] Calculate the first return time difference between the first return time and the second return time;

[0125] When the first return time difference is greater than or equal to the preset return time difference, it is determined that the user to be identified is not close to the second detection range, and the power supply of the face acquisition module, the fingerprint acquisition module and the control module is not turned on;

[0126] When the first return time difference is less than the preset return time difference, it is determined that the user to be identified is close to the second detection range, and the product of the first return time and the first return time difference is calculated and used as the first return time factor;

[0127] transmitting a third microwave signal to the user to be identified, and calculating a third return time of the microwave reflected wave signal;

[0128] transmitting a fourth microwave signal to the user to be identified, and calculating a fourth return time of the microwave reflected wave signal;

[0129] Calculate the second return time difference between the third return time and the fourth return time;

[0130] Calculate the product of the third return time and the difference between the second return time and use it as the second return time factor;

[0131] Calculating a proximity time factor according to the first return time factor and the second return time factor;

[0132] The power-on time of the face acquisition module, the fingerprint acquisition module and the control module is set according to the proximity time factor and the proximity time factor-on time mapping table.

[0133] In this embodiment, the specific time node of radiating the fourth microwave signal is collected. For example, when the specific time node of transmitting the fourth microwave signal is 15:00, and according to the obtained proximity time factor and the data in the proximity time factor-connection time mapping table, it is found that the current proximity time factor corresponds to a connection time of 180 seconds, then the specific power-on time node of the face acquisition module, the fingerprint acquisition module and the control module is 15:00+180 seconds, that is, 15:03 minutes.

[0134] In this embodiment, calculating the approach time factor according to the first return time factor and the second return time factor further includes:

[0135] A=t 1 ×a 1 +t 2 ×a 2 ;

[0136] Where A is the approach time factor; t 1 is the calculation weight of the first return time factor, a 1 is the first return time factor, t 2 is the calculation weight of the second return time factor, a 2 is the second return time factor, t 1 +t 2 =1,t 1 <t 2 .

[0137] The beneficial effects of the above technical solution are: the proximity time factor is obtained according to the first return time factor and the second return time factor, and the proximity time factor-connection time mapping table can be set according to multiple experiments and test experience. The reasonable power-on time is calculated by the proximity time factor and the proximity time factor-connection time mapping table to avoid the phenomenon that the user moves too fast, turns on the power too late, or turns on the power prematurely and wastes power.

[0138] In some embodiments of the present application, it also includes:

[0139] The waterproof casing includes a face acquisition module, a fingerprint acquisition module, a control module, a user sensing module and a power module.

[0140] The beneficial effect of the above technical solution is that the waterproof shell can effectively isolate the internal electronic components from corrosion by environmental factors such as seawater, thereby improving durability.

[0141] In some embodiments of the present application, it also includes:

[0142] An alarm module is used to issue a reminder or warning through voice when the face collection module and the fingerprint collection module collect the user information to be identified for multiple times and the verification fails;

[0143] The alarm module is also used to record the facial image of the user to be identified and report it to the monitoring center when the door lock is opened abnormally.

[0144] The beneficial effect of the above technical solution is that when the door lock is opened by force, the illegal intruder is monitored and recorded immediately, so as to facilitate the subsequent verification of relevant personnel.

[0145] In the description of the above embodiments, specific features, structures, materials or characteristics may be combined in a suitable manner in any one or more embodiments or examples.

[0146] Although the present invention has been described above with reference to the embodiments, various modifications may be made thereto and parts thereof may be replaced with equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed by the present invention may be used in combination with each other in any manner, and the fact that these combinations are not fully described in this specification is only for the sake of omitting space and saving resources.

[0147] Those skilled in the art can understand that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An offshore wind turbine tower intelligent safety door lock system, characterized in that: include: Door locks; A face acquisition module is used to acquire a face image of a user to be identified and determine the matching relationship between the face image of the user to be identified and a preset face image of the user; The fingerprint collection module is used to collect the fingerprint information of the user to be identified and determine the matching relationship between the fingerprint information of the user to be identified and the fingerprint information preset by the user; A control module, used for judging whether to open the door lock according to the judgment results of the face acquisition module and the fingerprint acquisition module; A user sensing module is used to detect whether there is a user to be identified. If there is no user to be identified, the power supply of the face acquisition module, the fingerprint acquisition module and the control module is disconnected; if there is a user to be identified, the power supply of the face acquisition module, the fingerprint acquisition module and the control module is connected; A power module is used to supply power to the face acquisition module, fingerprint acquisition module, control module and user sensing module.

2. The offshore wind turbine tower intelligent safety door lock system according to claim 1 is characterized in that: The face acquisition module is used to acquire the face image of the user to be identified and determine the matching relationship between the face image of the user to be identified and the face image preset by the user, and further includes: Collect n facial images of the same user to be identified; Normalize and grayscale all the collected face images of users to be identified, and expand each face image into an m-dimensional vector; Construct the face matrix K of the user to be identified: Among them, X1 is the m-dimensional vector after the first face image of the user to be identified is expanded, X n is the m-dimensional vector after the n-th face image of the user to be identified is expanded; Calculate the covariance matrix of the face matrix of the user to be identified according to the following formula: Among them, C is the covariance matrix of the face matrix of the user to be identified, n is the total number of face images of the user to be identified, T is the matrix transpose symbol, K T Transpose the face matrix of the user to be identified; Calculating eigenvectors of the covariance matrix; Select the first k eigenvectors with cumulative contribution rate reaching 96% as principal components; The expanded vector of each face image of the user to be identified is projected onto the principal component to obtain the feature vector of the face image of the user to be identified: Among them, y i is the feature vector of the i-th user face image to be identified, is the eigenvector transpose of the covariance matrix of the first user face matrix to be identified, is the eigenvector transpose of the covariance matrix of the kth user face matrix to be identified, X i is the m-dimensional vector after the i-th face image of the user to be identified is expanded.

3. The offshore wind turbine tower intelligent safety door lock system according to claim 2 is characterized in that: The face acquisition module is used to acquire the face image of the user to be identified and determine the matching relationship between the face image of the user to be identified and the face image preset by the user, and further includes: Pre-set the Euclidean threshold of the face; Presetting a user preset face image, and obtaining a feature vector of the user preset face image; Calculate the Euclidean distance between the feature vector of the face image of the user to be identified and the feature vector of the user preset face image: Where d is the Euclidean distance between the feature vector of the face image of the user to be identified and the feature vector of the face image preset by the user, z i The i-th user preset face image feature vector; When the Euclidean distance between the feature vector of the user face image to be identified and the feature vector of the user preset face image is less than the face Euclidean threshold, it is determined that the user face image to be identified matches the user preset face image.

4. The offshore wind turbine tower intelligent safety door lock system according to claim 1 is characterized in that: The fingerprint collection module is used to collect fingerprint information of the user to be identified and determine the matching relationship between the fingerprint information of the user to be identified and the fingerprint information preset by the user, including: Presetting user preset fingerprint information and obtaining a feature vector of the user preset fingerprint information; Collecting fingerprint information of the user to be identified, normalizing the size and direction of the fingerprint information of the user to be identified, and obtaining a feature vector of the fingerprint information of the user to be identified; Preset a fingerprint Euclidean threshold, and calculate the Euclidean distance between the fingerprint information feature vector of the user to be identified and the fingerprint information feature vector of the user preset; When the Euclidean distance between the feature vector of the fingerprint information of the user to be identified and the feature vector of the preset fingerprint information of the user is less than the fingerprint Euclidean threshold, it is determined that the fingerprint information of the user to be identified matches the preset fingerprint information of the user.

5. The offshore wind turbine tower intelligent safety door lock system according to claim 3 or 4, characterized in that: The control module is used to determine whether to open the door lock according to the determination results of the face acquisition module and the fingerprint acquisition module, and further includes: When the face image of the user to be identified matches the preset face image of the user, or the fingerprint information of the user matches the preset fingerprint information of the user, the door lock is opened.

6. The offshore wind turbine tower intelligent safety door lock system according to claim 1 is characterized in that: The user sensing module is used to detect whether there is a user to be identified. If there is no user to be identified, the power supply of the face acquisition module, the fingerprint acquisition module and the control module is disconnected; if there is a user to be identified, the power supply of the face acquisition module, the fingerprint acquisition module and the control module is connected, and further includes: Presetting a first detection range and a second detection range, wherein the radius of the first detection range is greater than the radius of the second detection range; If there is no user to be identified within the first detection range, the user sensing module disconnects the power supplies of the face acquisition module, the fingerprint acquisition module and the control module; If there is a user to be identified within the first detection range, determine whether the user to be identified is close to the second detection range, and if so, calculate the proximity time factor of the user to be identified, and set the power-on time of the face acquisition module, fingerprint acquisition module and control module according to the proximity time factor; When the user to be identified enters the second detection range, the user sensing module sends a detection instruction to the control module, and the control module controls the face acquisition module and the fingerprint acquisition module to enter the information acquisition state.

7. The offshore wind turbine tower intelligent safety door lock system according to claim 6 is characterized in that: Determining whether the user to be identified is close to the second detection range, and if so, calculating the proximity time factor of the user to be identified, and setting the power-on time of the face acquisition module, the fingerprint acquisition module, and the control module according to the proximity time factor, including: When a user to be identified appears within the first detection range, transmitting a first microwave signal to the user to be identified, and calculating a first return time of the microwave reflected wave signal; Transmitting a second microwave signal to the user to be identified, and calculating a second return time of the microwave reflected wave signal; Calculate a first return time difference between the first return time and the second return time; When the first return time difference is greater than or equal to the preset return time difference, it is determined that the user to be identified is not close to the second detection range, and the power of the face acquisition module, the fingerprint acquisition module and the control module is not turned on; When the first return time difference is less than the preset return time difference, it is determined that the user to be identified is close to the second detection range, and the product of the first return time and the first return time difference is calculated and used as the first return time factor; Transmitting a third microwave signal to the user to be identified, and calculating a third return time of the microwave reflected wave signal; transmitting a fourth microwave signal to the user to be identified, and calculating a fourth return time of the microwave reflected wave signal; Calculate a second return time difference between the third return time and the fourth return time; Calculate the product of the third return time and the second return time difference and use it as the second return time factor; Calculating the approach time factor according to the first return time factor and the second return time factor; The power-on time of the face acquisition module, the fingerprint acquisition module and the control module is set according to the proximity time factor and the proximity time factor-on time mapping table.

8. The offshore wind turbine tower intelligent safety door lock system according to claim 7 is characterized in that: The calculating the approach time factor according to the first return time factor and the second return time factor also includes: A=t1×a1+t2×a2; Among them, A is the approach time factor; t1 is the calculation weight of the first return time factor, a1 is the first return time factor, t2 is the calculation weight of the second return time factor, a2 is the second return time factor, t1+t2=1, t1<t2.

9. The offshore wind turbine tower intelligent safety door lock system according to claim 1 is characterized in that: Also includes: The waterproof housing includes the face acquisition module, the fingerprint acquisition module, the control module, the user sensing module and the power supply module.

10. The offshore wind turbine tower intelligent safety door lock system according to claim 1, characterized in that: Also includes: An alarm module is used to issue a reminder or warning through voice when the face collection module and the fingerprint collection module collect the user information to be identified for multiple times and the verification fails; The alarm module is also used to record the facial image of the user to be identified and report it to the monitoring center when the door lock is opened abnormally.

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