Intelligent reluctance synchronous motor

Abstract

The invention relates to an intelligent reluctance synchronous motor which comprises a reluctance synchronous motor body, a cooperative detection mechanism, a wired video recording mechanism, a box type filtering device, a sharpening processing device, an artifact eliminating device, an intelligent identification device and an electric shock early warning device. The intelligent reluctance synchronous motor disclosed by the invention can be used for intelligent identification, so that the application prospect is wider.

Description

Technical Field

[0001] The present invention relates to the field of reluctance synchronous motors, and in particular to an intelligent reluctance synchronous motor. Background Art

[0002] The reluctance synchronous motor is evolved from the squirrel cage asynchronous motor. Its rotor has no cage winding, but is equipped with reaction slots corresponding to the number of stator poles (only the salient pole part is used, without excitation winding and permanent magnet), which is used to generate reluctance synchronous torque. Reluctance synchronous motors are mainly used in industrial and agricultural production, transportation, national defense, commercial and household appliances, medical electrical equipment and other fields.

[0003] In a high humidity or high acid environment, the reluctance synchronous motor needs the necessary supporting wooden frames to support the reluctance synchronous motor, so as to effectively prevent electric shock accidents of the reluctance synchronous motor in the high humidity or high acid environment. However, the prior art does not have a targeted and high-precision identification mechanism for whether the reluctance synchronous motor has the necessary supporting wooden frames in the above-mentioned specific scenarios. Summary of the invention

[0004] In order to solve the technical problems in the prior art, the present invention provides an intelligent reluctance synchronous motor, which determines whether there is a wooden frame for supporting the reluctance synchronous motor in the image area where each target is located, by inputting the binary numerical representation of the standard image corresponding to the wooden frame, multiple geometric features of the image area where each target is located, the signal-to-noise ratio of the eliminated processed image, and the area ratio occupied by the background area of ​​the eliminated processed image into a convolutional neural network model and running the convolutional neural network model, and when there is no wooden frame for supporting the reluctance synchronous motor in each image area where each target in the eliminated processed image is located, a wooden frame unrecognized signal is issued, otherwise, a wooden frame identification signal is issued, thereby realizing targeted intelligent identification of whether there is a necessary supporting wooden frame for the reluctance synchronous motor in a high humidity environment or a high acid environment, and effectively preventing electric shock accidents of the reluctance synchronous motor in a high humidity environment or a high acid environment.

[0005] According to the present invention, there is provided an intelligent reluctance synchronous motor, comprising a reluctance synchronous motor body and a scene target intelligent identification system connected to the reluctance synchronous motor body, wherein the scene target intelligent identification system comprises: A collaborative detection mechanism, which is arranged on the reluctance synchronous motor and has a built-in humidity sensor, an acid detection device and a main control device, wherein the humidity sensor is used to sense the on-site humidity data of the environment in which the reluctance synchronous motor is currently located, and the acid detection device is used to detect the real-time pH value of the environment in which the reluctance synchronous motor is currently located. The main control device is connected to the humidity sensor and the acid detection device respectively, and is used to send a first operation signal when the received on-site humidity value is greater than or equal to a set humidity threshold and the received real-time pH value is less than or equal to the set pH value; A wired video recording mechanism, connected to the cooperative detection mechanism, for performing a video recording operation on the scene where the reluctance synchronous motor is located upon receiving the first operation signal, so as to obtain an instant video frame corresponding to the current moment; A box filter device, connected to the wired video recording mechanism, is used to perform box filter processing on the received instant video frames to obtain and output corresponding box filter images; A sharpening processing device, connected to the box filter device, for performing high-pass filtering sharpening processing on the received image to obtain and output a corresponding sharpened processed image; An artifact removal device, connected to the sharpening processing device, is used to perform artifact removal processing on the received sharpening processed image to obtain and output a corresponding artifact removal processed image; an intelligent recognition device connected to the artifact removal device, and used to detect multiple geometric features of the image area where each target in the elimination processing image is located, the multiple geometric features include the number of pixels in the length direction of the corresponding image area, the number of pixels in the width direction, and the maximum curvature and the minimum curvature of the area edge curve, input the binary numerical representation of the standard image corresponding to the wooden frame, the multiple geometric features of the image area where each target is located, the signal-to-noise ratio of the elimination processing image, and the area ratio occupied by the background area of ​​the elimination processing image into the convolutional neural network model and run the convolutional neural network model to determine whether there is a wooden frame for supporting the reluctance synchronous motor in the image area where each target is located, and when there is no wooden frame for supporting the reluctance synchronous motor in each image area where each target in the elimination processing image is respectively located, a wooden frame unrecognized signal is issued, otherwise, a wooden frame recognition signal is issued; The electric shock warning device is connected to the intelligent identification device and is used to execute an electric shock warning action corresponding to the wooden frame unidentified signal when receiving the wooden frame unidentified signal.

[0006] It can be seen that the present invention has at least the following three outstanding substantive features: First, the video images obtained by performing the video recording operation on the scene where the reluctance synchronous motor is located are subjected to customized enhancement processing including box filter processing, high-pass filter sharpening processing and artifact removal processing to obtain an eliminated processed image with higher image quality, thereby providing more valuable basic data for subsequent intelligent identification; Second, detecting and eliminating multiple geometric features of the image area where each target is located in the processed image, wherein the multiple geometric features include the number of pixels in the length direction and the width direction of the corresponding image area, and the maximum curvature and the minimum curvature of the area edge curve; Thirdly, the binary numerical representation of the standard image corresponding to the wooden frame, the multiple geometric features of the image area where each target is located, the signal-to-noise ratio of the eliminated image and the area ratio of the background area of ​​the eliminated image are input into the convolutional neural network model and the convolutional neural network model is run to determine whether there is a wooden frame for supporting the reluctance synchronous motor in the image area where each target is located, and when there is no wooden frame for supporting the reluctance synchronous motor in each image area where each target in the eliminated image is located, a wooden frame unrecognized signal is issued, otherwise, a wooden frame recognition signal is issued, thereby realizing targeted intelligent recognition of whether there is a necessary supporting wooden frame for the reluctance synchronous motor in a high humidity environment or a high acid environment, and effectively preventing electric shock accidents of the reluctance synchronous motor in a high humidity environment or a high acid environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The embodiments of the present invention will be described below with reference to the accompanying drawings, wherein:

[0008] Figure 1 It is a structural block diagram of a set scene target intelligent identification system for a reluctance synchronous motor according to implementation scheme A of the present invention.

[0009] Figure 2 It is a structural block diagram of a set scene target intelligent identification system for a reluctance synchronous motor according to implementation scheme B of the present invention.

[0010] Figure 3 It is a structural block diagram of a set scene target intelligent identification system for a reluctance synchronous motor according to implementation scheme C of the present invention. DETAILED DESCRIPTION

[0011] Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0012] The present invention provides an intelligent reluctance synchronous motor, comprising a reluctance synchronous motor body and a scene target intelligent identification system connected to the reluctance synchronous motor body. Here, the term "reluctance synchronous motor body" can be understood as a conventional reluctance synchronous motor body in the art, and no further description is required.

[0013] Figure 1 The structure block diagram of the intelligent recognition system for setting scene targets of a reluctance synchronous motor according to embodiment A of the present invention is shown, and the system includes: A collaborative detection mechanism, which is arranged on the reluctance synchronous motor and has a built-in humidity sensor, an acid detection device and a main control device, wherein the humidity sensor is used to sense the on-site humidity data of the environment in which the reluctance synchronous motor is currently located, and the acid detection device is used to detect the real-time pH value of the environment in which the reluctance synchronous motor is currently located. The main control device is connected to the humidity sensor and the acid detection device respectively, and is used to send a first operation signal when the received on-site humidity value is greater than or equal to a set humidity threshold and the received real-time pH value is less than or equal to the set pH value; For example, the collaborative detection mechanism is arranged on the reluctance synchronous motor and has a built-in humidity sensor, an acid detection device and a main control device, the humidity sensor is used to sense the on-site humidity data of the current environment of the reluctance synchronous motor, the acid detection device is used to detect the real-time pH value of the current environment of the reluctance synchronous motor, the main control device is respectively connected to the humidity sensor and the acid detection device, and is used to send a first operation signal when the received on-site humidity value is greater than or equal to a set humidity threshold and the received real-time pH value is less than or equal to the set pH value, including: the SOC chip can be selected to implement the collaborative detection mechanism, which is arranged on the reluctance synchronous motor and has a built-in humidity sensor, an acid detection device and a main control device, the humidity sensor is used to sense the on-site humidity data of the current environment of the reluctance synchronous motor, the acid detection device is used to detect the real-time pH value of the current environment of the reluctance synchronous motor, the main control device is respectively connected to the humidity sensor and the acid detection device, and is used to send a first operation signal when the received on-site humidity value is greater than or equal to the set humidity threshold and the received real-time pH value is less than or equal to the set pH value; A wired video recording mechanism, connected to the cooperative detection mechanism, for performing a video recording operation on the scene where the reluctance synchronous motor is located upon receiving the first operation signal, so as to obtain an instant video frame corresponding to the current moment; A box filter device, connected to the wired video recording mechanism, is used to perform box filter processing on the received instant video frames to obtain and output corresponding box filter images; A sharpening processing device, connected to the box filter device, for performing high-pass filtering sharpening processing on the received image to obtain and output a corresponding sharpened processed image; An artifact removal device, connected to the sharpening processing device, is used to perform artifact removal processing on the received sharpening processed image to obtain and output a corresponding artifact removal processed image; an intelligent recognition device connected to the artifact removal device, and used to detect multiple geometric features of the image area where each target in the elimination processing image is located, the multiple geometric features include the number of pixels in the length direction of the corresponding image area, the number of pixels in the width direction, and the maximum curvature and the minimum curvature of the area edge curve, input the binary numerical representation of the standard image corresponding to the wooden frame, the multiple geometric features of the image area where each target is located, the signal-to-noise ratio of the elimination processing image, and the area ratio occupied by the background area of ​​the elimination processing image into the convolutional neural network model and run the convolutional neural network model to determine whether there is a wooden frame for supporting the reluctance synchronous motor in the image area where each target is located, and when there is no wooden frame for supporting the reluctance synchronous motor in each image area where each target in the elimination processing image is respectively located, a wooden frame unrecognized signal is issued, otherwise, a wooden frame recognition signal is issued; An electric shock warning device, connected to the intelligent identification device, is used to execute an electric shock warning action corresponding to the wooden frame unidentified signal when receiving the wooden frame unidentified signal; The collaborative detection mechanism is further configured to send a second operation signal when the received on-site humidity value is less than the set humidity threshold or the received real-time PH value is higher than the set PH value; Wherein, the wired recording mechanism is further used to stop performing the recording operation on the scene where the reluctance synchronous motor is located when receiving the second operation signal.

[0014] Figure 2 It is a structural block diagram of a set scene target intelligent identification system for a reluctance synchronous motor according to implementation scheme B of the present invention.

[0015] Compared with the A embodiment, the set scene target intelligent identification system of the reluctance synchronous motor shown in the B embodiment of the present invention may also include: a thickness sensor device, connected to the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device, respectively, for measuring the current real-time thickness values ​​of the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively; Wherein, the thickness sensor device is respectively connected with the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device, and is used to respectively measure the current real-time thickness values ​​of the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device, including: the thickness sensor device includes a plurality of thickness measurement units, which are respectively connected with the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device, so as to complete the measurement of the current real-time thickness values ​​of the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device; Wherein, the thickness sensor device includes a plurality of thickness measuring units, which are used to be connected to the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively, so as to complete the measurement of the current real-time thickness values ​​of the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively, including: the plurality of thickness measuring units are a plurality of thickness sensors, which are used to be connected to the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively, so as to complete the measurement of the current real-time thickness values ​​of the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively; Wherein, the plurality of thickness measuring units are a plurality of thickness sensors, which are used to be connected to the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively, so as to complete the respective measurement of the current real-time thickness values ​​of the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively, including: the plurality of thickness sensors have the same structure; Among them, the multiple thickness measurement units are multiple thickness sensors, which are used to be connected to the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively, so as to complete the separate measurement of the current real-time thickness values ​​of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively, and also include: the multiple thickness sensors have the same thickness measurement upper limit value and thickness measurement lower limit value.

[0016] Figure 3 It is a structural block diagram of a set scene target intelligent identification system for a reluctance synchronous motor according to implementation scheme C of the present invention.

[0017] Compared with the A embodiment, the set scene target intelligent identification system of the reluctance synchronous motor shown in the C embodiment of the present invention may also include: A value temporary storage mechanism, connected to the plurality of thickness measurement units of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device, respectively, for temporarily storing input data and output data of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively; Wherein, the temporary value storage mechanism is respectively connected to the plurality of thickness measuring units of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device, and is used to temporarily store the input data and output data of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively, including: the temporary value storage mechanism is a FLASH flash memory; Among them, the numerical temporary storage mechanism is respectively connected to multiple thickness measurement units of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device, and is used to temporarily store the input data and output data of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively, including: the numerical temporary storage mechanism is an MMC storage chip.

[0018] In addition, in the set scene target intelligent recognition system of the reluctance synchronous motor, the binary numerical representation of the standard image corresponding to the wooden frame, multiple geometric features of the image area where each target is located, the signal-to-noise ratio of the elimination processed image, and the area ratio occupied by the background area of ​​the elimination processed image are input into the convolutional neural network model and the convolutional neural network model is run to determine whether there is a wooden frame for supporting the reluctance synchronous motor in the image area where each target is located, including: the convolutional neural network model is a convolutional neural network that has completed multiple trainings and the number of trainings is inversely correlated with the contrast of the elimination processed image.

[0019] The intelligent scene target recognition system for the reluctance synchronous motor of the present invention can solve the technical problem in the prior art of lacking a targeted and high-precision identification mechanism for whether the reluctance synchronous motor has the necessary supporting wooden frames in specific scenarios. It can use an artificial intelligence identification mode to specifically identify whether there are wooden frames for supporting the reluctance synchronous motor in each image area where each target in the processed image is located, thereby achieving targeted analysis of whether there are necessary supporting wooden frames for the reluctance synchronous motor in a high-humidity or high-acid environment.

[0020] By examining the accompanying drawings and detailed description, other systems, methods, features and advantages of the present invention will be or will become apparent to those skilled in the art. All additional systems, methods, features and advantages should be included in the above description, fall within the scope of the present invention, and be protected by the appended claims.

Claims

1. An intelligent reluctance synchronous motor, comprising a reluctance synchronous motor body and a scene target intelligent identification system connected to the reluctance synchronous motor body, characterized in that: The scene target intelligent recognition system comprises: A collaborative detection mechanism, which is arranged on the reluctance synchronous motor and has a built-in humidity sensor, an acid detection device and a main control device, wherein the humidity sensor is used to sense the on-site humidity data of the environment in which the reluctance synchronous motor is currently located, and the acid detection device is used to detect the real-time pH value of the environment in which the reluctance synchronous motor is currently located. The main control device is connected to the humidity sensor and the acid detection device respectively, and is used to send a first operation signal when the received on-site humidity value is greater than or equal to a set humidity threshold and the received real-time pH value is less than or equal to the set pH value; A wired video recording mechanism, connected to the cooperative detection mechanism, for performing a video recording operation on the scene where the reluctance synchronous motor is located upon receiving the first operation signal, so as to obtain an instant video frame corresponding to the current moment; A box filter device, connected to the wired video recording mechanism, is used to perform box filter processing on the received instant video frames to obtain and output corresponding box filter images; A sharpening processing device, connected to the box filter device, for performing high-pass filtering sharpening processing on the received image to obtain and output a corresponding sharpened processed image; An artifact removal device, connected to the sharpening processing device, is used to perform artifact removal processing on the received sharpening processed image to obtain and output a corresponding artifact removal processed image; an intelligent recognition device connected to the artifact removal device, and used to detect multiple geometric features of the image area where each target in the elimination processing image is located, the multiple geometric features include the number of pixels in the length direction of the corresponding image area, the number of pixels in the width direction, and the maximum curvature and the minimum curvature of the area edge curve, input the binary numerical representation of the standard image corresponding to the wooden frame, the multiple geometric features of the image area where each target is located, the signal-to-noise ratio of the elimination processing image, and the area ratio occupied by the background area of ​​the elimination processing image into the convolutional neural network model and run the convolutional neural network model to determine whether there is a wooden frame for supporting the reluctance synchronous motor in the image area where each target is located, and when there is no wooden frame for supporting the reluctance synchronous motor in each image area where each target in the elimination processing image is respectively located, a wooden frame unrecognized signal is issued, otherwise, a wooden frame recognition signal is issued; The electric shock warning device is connected to the intelligent identification device and is used to execute an electric shock warning action corresponding to the wooden frame unidentified signal when receiving the wooden frame unidentified signal.

2. The intelligent reluctance synchronous motor according to claim 1, characterized in that: The collaborative detection mechanism is also used to send a second operation signal when the received on-site humidity value is less than the set humidity threshold or the received real-time pH value is higher than the set pH value; Wherein, the wired recording mechanism is further used to stop performing the recording operation on the scene where the reluctance synchronous motor is located when receiving the second operation signal.

3. The intelligent reluctance synchronous motor according to claim 2, characterized in that: The system further comprises: a thickness sensor device, connected to the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device, respectively, for measuring the current real-time thickness values ​​of the box-type filter device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively; Among them, the thickness sensor device is respectively connected to the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device, and is used to respectively measure the current real-time thickness values ​​of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device. The thickness sensor device includes multiple thickness measurement units, which are respectively connected to the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device to complete the measurement of the current real-time thickness values ​​of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device.

4. The intelligent reluctance synchronous motor according to claim 3, characterized in that: The thickness sensor device includes multiple thickness measurement units, which are used to be connected to the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively to complete the measurement of the current real-time thickness values ​​of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively. The multiple thickness measurement units are multiple thickness sensors, which are used to be connected to the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively to complete the measurement of the current real-time thickness values ​​of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively.

5. The intelligent reluctance synchronous motor according to claim 4, characterized in that: The multiple thickness measuring units are multiple thickness sensors, which are used to be connected to the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively, so as to complete the measurement of the current real-time thickness values ​​of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively, including: the structures of the multiple thickness sensors are the same.

6. The intelligent reluctance synchronous motor according to claim 5, characterized in that: The multiple thickness measurement units are multiple thickness sensors, which are used to be connected to the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively to complete the measurement of the current real-time thickness values ​​of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively, and also include: the multiple thickness sensors have the same thickness measurement upper limit value and thickness measurement lower limit value.

7. The intelligent reluctance synchronous motor according to any one of claims 3 to 6, characterized in that: The system further comprises: The numerical temporary storage mechanism is respectively connected to the multiple thickness measurement units of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device, and is used to temporarily store the input data and output data of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively.

8. The intelligent reluctance synchronous motor according to claim 7, characterized in that: The numerical temporary storage mechanism is respectively connected to the multiple thickness measurement units of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device, and is used to temporarily store the input data and output data of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively. The numerical temporary storage mechanism includes: the numerical temporary storage mechanism is a FLASH flash memory.

9. The intelligent reluctance synchronous motor according to claim 7, characterized in that: The numerical temporary storage mechanism is respectively connected to the multiple thickness measurement units of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device, and is used to temporarily store the input data and output data of the box-type filtering device, the sharpening processing device, the artifact elimination device and the intelligent identification device respectively. The numerical temporary storage mechanism includes: the MMC storage chip.

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