CN111766799A - Big data analysis control method - Google Patents
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- 238000007405 data analysis Methods 0.000 title claims abstract description 48
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- 235000019504 cigarettes Nutrition 0.000 claims abstract description 7
- 238000012545 processing Methods 0.000 claims description 67
- 238000003384 imaging method Methods 0.000 claims description 42
- 238000004458 analytical method Methods 0.000 claims description 38
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- 238000009529 body temperature measurement Methods 0.000 claims description 16
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- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 claims description 6
- 229910052710 silicon Inorganic materials 0.000 claims description 6
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/24—Pc safety
- G05B2219/24215—Scada supervisory control and data acquisition
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Abstract
The invention relates to a big data analysis control method, which comprises the step of using a big data analysis control platform to stop executing the charging operation of a vehicle charging socket at a cigarette lighter position in a vehicle when the temperature of water in the vehicle is too low so as to avoid overload operation of power in the vehicle.
Description
Technical Field
The invention relates to the field of data analysis, in particular to a big data analysis control method.
Background
In the field of statistics, data analysis is divided into descriptive statistical analysis, exploratory data analysis and confirmatory data analysis; where exploratory data analysis focuses on finding new features among the data, while confirmatory data analysis focuses on validation or authentication of existing assumptions.
Exploratory data analysis refers to a method of analyzing data to form hypothesis-worthy tests, which is complementary to conventional statistical hypothesis testing approaches. The method is named by the american famous statistician John diagram base (John Tukey).
Qualitative data analysis, also known as "qualitative data analysis," "qualitative research," or "qualitative research data analysis," refers to the analysis of non-numerical data (or data) such as words, photographs, observations, and the like.
Disclosure of Invention
The present invention needs to have at least two important points:
(1) when the temperature of water in the vehicle is too low, the charging operation of a vehicle charging socket at the position of a cigarette lighter in the vehicle is executed, which causes the problems of power overload operation and vehicle starting and unsmooth operation, therefore, a power cut-off device is introduced, which is respectively connected with the fault detection device, the water temperature measurement device, the scale analysis device and the power output unit, and is used for introducing a water temperature reading based on customized image recognition to perform judgment control on whether to execute power cut-off when the water temperature measurement device is in fault, and performing judgment control on whether to execute power cut-off by using the water temperature reading of the water temperature measurement device when the water temperature measurement device is not in fault;
(2) and determining a morphological processing mechanism for executing different strategies to each color sub-image of the image based on different image similarity levels, thereby improving the morphological processing effect of the image.
According to an aspect of the present invention, there is provided a big data analysis control method including using a big data analysis control platform to stop performing a charging operation of a vehicle charging socket of an in-vehicle lighter location when an in-vehicle water temperature is too low to avoid an overload operation with in-vehicle power, the big data analysis control platform including:
the charging socket for the vehicle comprises a power input unit and a power output unit, wherein the power input unit is connected with the cigarette lighter socket, and the power output unit is connected with the equipment to be charged;
the in-vehicle imaging device is arranged in a cab of the vehicle and is used for carrying out imaging processing on the instrument panel so as to obtain and output an instrument panel imaging image;
the water temperature measuring device is arranged on one side of an engine of the vehicle and is used for measuring the water temperature of the engine of the vehicle so as to output field water temperature data;
the fault detection device is arranged on one side of the water temperature measurement device and used for carrying out fault detection on the water temperature measurement device and sending a first trigger instruction when the water temperature measurement device is detected to be in fault, otherwise, sending a second trigger instruction;
the similarity analysis equipment is connected with the in-vehicle imaging equipment and used for receiving the instrument panel imaging image, obtaining each appearance of each object in the instrument panel imaging image and carrying out appearance similarity analysis on each appearance of each object so as to obtain a corresponding similarity grade;
the data analysis device is connected with the similarity analysis device and used for starting receiving of an instrument panel imaging image from the similarity analysis device when the received similarity level is lower than a preset level threshold, adjusting the morphological processing intensity of a C color sub-image in CMYK space of the instrument panel imaging image based on the similarity level, adjusting the morphological processing intensity of an M color sub-image in CMYK space of the instrument panel imaging image based on the similarity level, adjusting the morphological processing intensity of a Y color sub-image in CMYK space of the instrument panel imaging image based on the similarity level and adjusting the morphological processing intensity of a K color sub-image in CMYK space of the instrument panel imaging image based on the similarity level;
the parallel processing equipment is connected with the data analysis equipment and is used for parallelly executing morphological processing of respective morphological processing intensity on the C color sub-image, the M color sub-image, the Y color sub-image and the K color sub-image in the CMYK space of the instrument panel imaging image so as to obtain three corresponding processed sub-images and superposing the three processed sub-images so as to obtain an instant superposed image;
the edge sharpening device is used for receiving the instant superposition image and carrying out edge sharpening processing on the instant superposition image so as to obtain and output an edge sharpened image;
the combined filtering device is connected with the edge sharpening device and is used for performing combined filtering processing of first recursive filtering and then Gaussian filtering on the edge sharpened image so as to obtain and output a corresponding combined filtering image;
the scale analysis equipment is connected with the combined filtering equipment and used for extracting the outline of the water temperature dial in the combined filtering image based on the imaging characteristic of the water temperature dial, extracting the outline of the water temperature dial pointer in the combined filtering image based on the imaging characteristic of the water temperature dial pointer, and analyzing a reference water temperature reading based on the relative position of the outline of the water temperature dial pointer in the outline of the water temperature dial;
the power cut-off equipment is respectively connected with the fault detection equipment, the water temperature measurement equipment, the scale analysis equipment and the power output unit and is used for determining whether to execute power cut-off action on the power output unit based on the reference water temperature reading when receiving the first trigger instruction;
wherein the power cut-off device is further configured to determine whether to perform a power cut-off action on the power output unit based on the field water temperature data upon receiving the second trigger instruction;
wherein determining whether to perform a power shut-off action on the power output unit based on the reference water temperature reading comprises: cutting off power supply to the power output unit when the reference water temperature reading is below a preset temperature threshold;
wherein determining whether to perform a power shut-off action on the power output unit based on the reference water temperature reading comprises: resuming power supply to the power output unit when the reference water temperature reading is equal to or higher than the preset temperature threshold;
wherein determining whether to perform a power shut-off action on the power output unit based on the site water temperature data comprises: cutting off power supply to the power output unit when the on-site water temperature data is lower than a preset temperature threshold;
wherein determining whether to perform a power shut-off action on the power output unit based on the site water temperature data comprises: when the on-site water temperature data is higher than or equal to the preset temperature threshold, the power supply to the power output unit is resumed.
The big data analysis control method is simple in design and convenient to control. When the water temperature measuring equipment breaks down, the water temperature reading based on the customized image recognition is introduced to judge and control whether to execute power cut-off, otherwise, the water temperature reading of the water temperature measuring equipment is used to judge and control whether to execute power cut-off, and therefore starting and running of the vehicle are guaranteed.
Detailed Description
Embodiments of the present invention will be described in detail below.
The vehicle-mounted charger is a vehicle-mounted charger which is powered by a conventional automobile battery (12V for cars and 24V for trucks), and is widely used in the field of lithium battery charging of various portable and handheld devices.
Handheld devices such as: cell phones, PDAs, GPS, etc. The vehicle-mounted charger not only considers the actual requirements of lithium battery charging (constant voltage CV, constant current CC and overvoltage protection OVP), but also considers the severe environment of the vehicle-mounted storage battery (transient spike voltage, system switch noise interference, EMI and the like); therefore, the power management IC selected by the vehicle charging scheme must simultaneously satisfy: high voltage resistance, high efficiency, high reliability and low frequency (beneficial to the design of EMI).
In the prior art, when the temperature of water in a vehicle is too low, the charging operation of a vehicle charging socket at the position of a cigarette lighter in the vehicle is executed, which causes the problems of power overload operation and unsmooth vehicle starting and running.
In order to overcome the defects, the invention provides a big data analysis control method which comprises the step of using a big data analysis control platform to stop executing the charging operation of a vehicle charging socket at the position of a cigarette lighter in a vehicle when the temperature of water in the vehicle is too low so as to avoid overload operation of electric power in the vehicle, wherein the big data analysis control platform can effectively solve the corresponding technical problems.
The big data analysis control platform according to the embodiment of the invention comprises:
the charging socket for the vehicle comprises a power input unit and a power output unit, wherein the power input unit is connected with the cigarette lighter socket, and the power output unit is connected with the equipment to be charged;
the in-vehicle imaging device is arranged in a cab of the vehicle and is used for carrying out imaging processing on the instrument panel so as to obtain and output an instrument panel imaging image;
the water temperature measuring device is arranged on one side of an engine of the vehicle and is used for measuring the water temperature of the engine of the vehicle so as to output field water temperature data;
the fault detection device is arranged on one side of the water temperature measurement device and used for carrying out fault detection on the water temperature measurement device and sending a first trigger instruction when the water temperature measurement device is detected to be in fault, otherwise, sending a second trigger instruction;
the similarity analysis equipment is connected with the in-vehicle imaging equipment and used for receiving the instrument panel imaging image, obtaining each appearance of each object in the instrument panel imaging image and carrying out appearance similarity analysis on each appearance of each object so as to obtain a corresponding similarity grade;
the data analysis device is connected with the similarity analysis device and used for starting receiving of an instrument panel imaging image from the similarity analysis device when the received similarity level is lower than a preset level threshold, adjusting the morphological processing intensity of a C color sub-image in CMYK space of the instrument panel imaging image based on the similarity level, adjusting the morphological processing intensity of an M color sub-image in CMYK space of the instrument panel imaging image based on the similarity level, adjusting the morphological processing intensity of a Y color sub-image in CMYK space of the instrument panel imaging image based on the similarity level and adjusting the morphological processing intensity of a K color sub-image in CMYK space of the instrument panel imaging image based on the similarity level;
the parallel processing equipment is connected with the data analysis equipment and is used for parallelly executing morphological processing of respective morphological processing intensity on the C color sub-image, the M color sub-image, the Y color sub-image and the K color sub-image in the CMYK space of the instrument panel imaging image so as to obtain three corresponding processed sub-images and superposing the three processed sub-images so as to obtain an instant superposed image;
the edge sharpening device is used for receiving the instant superposition image and carrying out edge sharpening processing on the instant superposition image so as to obtain and output an edge sharpened image;
the combined filtering device is connected with the edge sharpening device and is used for performing combined filtering processing of first recursive filtering and then Gaussian filtering on the edge sharpened image so as to obtain and output a corresponding combined filtering image;
the scale analysis equipment is connected with the combined filtering equipment and used for extracting the outline of the water temperature dial in the combined filtering image based on the imaging characteristic of the water temperature dial, extracting the outline of the water temperature dial pointer in the combined filtering image based on the imaging characteristic of the water temperature dial pointer, and analyzing a reference water temperature reading based on the relative position of the outline of the water temperature dial pointer in the outline of the water temperature dial;
the power cut-off equipment is respectively connected with the fault detection equipment, the water temperature measurement equipment, the scale analysis equipment and the power output unit and is used for determining whether to execute power cut-off action on the power output unit based on the reference water temperature reading when receiving the first trigger instruction;
wherein the power cut-off device is further configured to determine whether to perform a power cut-off action on the power output unit based on the field water temperature data upon receiving the second trigger instruction;
wherein determining whether to perform a power shut-off action on the power output unit based on the reference water temperature reading comprises: cutting off power supply to the power output unit when the reference water temperature reading is below a preset temperature threshold;
wherein determining whether to perform a power shut-off action on the power output unit based on the reference water temperature reading comprises: resuming power supply to the power output unit when the reference water temperature reading is equal to or higher than the preset temperature threshold;
wherein determining whether to perform a power shut-off action on the power output unit based on the site water temperature data comprises: cutting off power supply to the power output unit when the on-site water temperature data is lower than a preset temperature threshold;
wherein determining whether to perform a power shut-off action on the power output unit based on the site water temperature data comprises: when the on-site water temperature data is higher than or equal to the preset temperature threshold, the power supply to the power output unit is resumed.
Next, the detailed structure of the big data analysis control platform of the present invention will be further described.
In the big data analysis control platform:
the combined filtering device comprises a recursive filtering sub-device and a Gaussian filtering sub-device, and the recursive filtering sub-device is connected with the Gaussian filtering sub-device;
wherein, in the data analysis device, the degree of change of the morphological processing intensity of the K color sub-image with the similarity level is the most drastic.
In the big data analysis control platform:
in the parallel processing device, the degree of change of the morphological processing intensity of the C color sub-image with the level of similarity, the degree of change of the morphological processing intensity of the M color sub-image with the level of similarity, and the degree of change of the morphological processing intensity of the Y color sub-image with the level of similarity are the same;
the degree of change of the morphological processing intensity of the C color sub-image along with the similarity level, the degree of change of the morphological processing intensity of the M color sub-image along with the similarity level, the degree of change of the morphological processing intensity of the Y color sub-image along with the similarity level, and the degree of change of the morphological processing intensity of the K color sub-image along with the similarity level are in inverse proportion.
In the big data analysis control platform:
in the similarity analysis device, performing outline similarity analysis on each outline of each object to obtain a corresponding similarity level includes: the more consistent the respective appearances of the respective objects are, the higher the corresponding degree of similarity obtained.
The big data analysis control platform can further comprise:
the multi-parameter detection device is respectively connected with the currently unused suspension pins of the similarity analysis device, the data analysis device and the parallel processing device so as to obtain the current temperature of the currently unused suspension pins of the similarity analysis device, the current temperature of the currently unused suspension pins of the data analysis device and the current temperature of the currently unused suspension pins of the parallel processing device.
The big data analysis control platform can further comprise:
and the MCU control chip is connected with the multi-parameter detection equipment and used for receiving the current temperature of the currently unused suspension pins of the similarity analysis equipment, the current temperature of the currently unused suspension pins of the data analysis equipment and the current temperature of the currently unused suspension pins of the parallel processing equipment, and performing weighted mean operation on the current temperature of the currently unused suspension pins of the similarity analysis equipment, the current temperature of the currently unused suspension pins of the data analysis equipment and the current temperature of the currently unused suspension pins of the parallel processing equipment to obtain a reference pin temperature, and the MCU control chip is also used for multiplying the obtained reference pin temperature by a weighing factor to obtain the silicon wafer entity temperature of the similarity analysis equipment.
The big data analysis control platform can further comprise:
the field storage device is used for storing three weight values in advance, wherein the three weight values are used for enabling the current temperature of the currently unused suspension pin of the similarity analysis device, the current temperature of the currently unused suspension pin of the data analysis device and the current temperature of the currently unused suspension pin of the parallel processing device to respectively participate in weighted mean calculation.
The big data analysis control platform can further comprise:
the speed adjusting equipment is respectively connected with the similarity analyzing equipment and the MCU control chip and is used for determining corresponding operation speed down-regulation multiples according to the entity temperature of the silicon wafer when the received entity temperature of the silicon wafer exceeds a limit;
the speed adjusting device is further used for executing downward adjustment execution operation on the current data processing speed of the similarity analyzing device based on the operation speed downward adjustment multiple;
in the field storage device, the current temperature of the currently unused suspension pin of the similarity analysis device, the current temperature of the currently unused suspension pin of the data analysis device and the current temperature of the currently unused suspension pin of the parallel processing device are different in size, and the three weight values of the current temperature of the currently unused suspension pin of the parallel processing device participate in weighted mean calculation respectively;
and the field storage device is connected with the MCU control chip and is used for pre-storing the weighing factors.
In addition, a Micro Control Unit (MCU), also called a single chip Microcomputer (single chip Microcomputer) or a single chip Microcomputer (MCU), properly reduces the frequency and specification of a Central Processing Unit (CPU), and integrates peripheral interfaces such as a memory (memory), a counter (Timer), a USB, an a/D converter, a UART, a PLC, a DMA, and the like, and even an LCD driving circuit on a single chip to form a chip-level computer, which performs different combination control for different applications. Such as mobile phones, PC peripherals, remote controls, to automotive electronics, industrial stepper motors, robotic arm controls, etc., see the silhouette of the MCU.
The 32-bit MCU can be said to be the mainstream of the MCU market, the price of a single MCU is between 1.5 and 4 dollars, the working frequency is mostly between 100 and 350MHz, the execution efficiency is better, and the application types are also multiple. However, the length of the program code with the same function of the 32-bit MCU is increased by 30-40% compared with that of the 8/16-bit MCU due to the increase of the operand and the length of the memory, which causes that the capacity of the embedded OTP/FlashROM memory cannot be too small, and the number of external pins of the chip is greatly increased, thereby further limiting the cost reduction capability of the 32-bit MCU.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: Read-Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A big data analytics control method, the method comprising using a big data analytics control platform to stop performing charging operations to a vehicle charging receptacle of an in-vehicle lighter location when in-vehicle water temperatures are too low to avoid overloading operations with in-vehicle power, the big data analytics control platform comprising:
the charging socket for the vehicle comprises a power input unit and a power output unit, wherein the power input unit is connected with the cigarette lighter socket, and the power output unit is connected with the equipment to be charged;
the in-vehicle imaging device is arranged in a cab of the vehicle and is used for carrying out imaging processing on the instrument panel so as to obtain and output an instrument panel imaging image;
the water temperature measuring device is arranged on one side of an engine of the vehicle and is used for measuring the water temperature of the engine of the vehicle so as to output field water temperature data;
the fault detection device is arranged on one side of the water temperature measurement device and used for carrying out fault detection on the water temperature measurement device and sending a first trigger instruction when the water temperature measurement device is detected to be in fault, otherwise, sending a second trigger instruction;
the similarity analysis equipment is connected with the in-vehicle imaging equipment and used for receiving the instrument panel imaging image, obtaining each appearance of each object in the instrument panel imaging image and carrying out appearance similarity analysis on each appearance of each object so as to obtain a corresponding similarity grade;
the data analysis device is connected with the similarity analysis device and used for starting receiving of an instrument panel imaging image from the similarity analysis device when the received similarity level is lower than a preset level threshold, adjusting the morphological processing intensity of a C color sub-image in CMYK space of the instrument panel imaging image based on the similarity level, adjusting the morphological processing intensity of an M color sub-image in CMYK space of the instrument panel imaging image based on the similarity level, adjusting the morphological processing intensity of a Y color sub-image in CMYK space of the instrument panel imaging image based on the similarity level and adjusting the morphological processing intensity of a K color sub-image in CMYK space of the instrument panel imaging image based on the similarity level;
the parallel processing equipment is connected with the data analysis equipment and is used for parallelly executing morphological processing of respective morphological processing intensity on the C color sub-image, the M color sub-image, the Y color sub-image and the K color sub-image in the CMYK space of the instrument panel imaging image so as to obtain three corresponding processed sub-images and superposing the three processed sub-images so as to obtain an instant superposed image;
the edge sharpening device is used for receiving the instant superposition image and carrying out edge sharpening processing on the instant superposition image so as to obtain and output an edge sharpened image;
the combined filtering device is connected with the edge sharpening device and is used for performing combined filtering processing of first recursive filtering and then Gaussian filtering on the edge sharpened image so as to obtain and output a corresponding combined filtering image;
the scale analysis equipment is connected with the combined filtering equipment and used for extracting the outline of the water temperature dial in the combined filtering image based on the imaging characteristic of the water temperature dial, extracting the outline of the water temperature dial pointer in the combined filtering image based on the imaging characteristic of the water temperature dial pointer, and analyzing a reference water temperature reading based on the relative position of the outline of the water temperature dial pointer in the outline of the water temperature dial;
the power cut-off equipment is respectively connected with the fault detection equipment, the water temperature measurement equipment, the scale analysis equipment and the power output unit and is used for determining whether to execute power cut-off action on the power output unit based on the reference water temperature reading when receiving the first trigger instruction;
wherein the power cut-off device is further configured to determine whether to perform a power cut-off action on the power output unit based on the field water temperature data upon receiving the second trigger instruction;
wherein determining whether to perform a power shut-off action on the power output unit based on the reference water temperature reading comprises: cutting off power supply to the power output unit when the reference water temperature reading is below a preset temperature threshold;
wherein determining whether to perform a power shut-off action on the power output unit based on the reference water temperature reading comprises: resuming power supply to the power output unit when the reference water temperature reading is equal to or higher than the preset temperature threshold;
wherein determining whether to perform a power shut-off action on the power output unit based on the site water temperature data comprises: cutting off power supply to the power output unit when the on-site water temperature data is lower than a preset temperature threshold;
wherein determining whether to perform a power shut-off action on the power output unit based on the site water temperature data comprises: when the on-site water temperature data is higher than or equal to the preset temperature threshold, the power supply to the power output unit is resumed.
2. The method of claim 1, wherein:
the combined filtering device comprises a recursive filtering sub-device and a Gaussian filtering sub-device, and the recursive filtering sub-device is connected with the Gaussian filtering sub-device;
wherein, in the data analysis device, the degree of change of the morphological processing intensity of the K color sub-image with the similarity level is the most drastic.
3. The method of claim 2, wherein:
in the parallel processing device, the degree of change of the morphological processing intensity of the C color sub-image with the level of similarity, the degree of change of the morphological processing intensity of the M color sub-image with the level of similarity, and the degree of change of the morphological processing intensity of the Y color sub-image with the level of similarity are the same;
the degree of change of the morphological processing intensity of the C color sub-image along with the similarity level, the degree of change of the morphological processing intensity of the M color sub-image along with the similarity level, the degree of change of the morphological processing intensity of the Y color sub-image along with the similarity level, and the degree of change of the morphological processing intensity of the K color sub-image along with the similarity level are in inverse proportion.
4. The method of claim 3, wherein:
in the similarity analysis device, performing outline similarity analysis on each outline of each object to obtain a corresponding similarity level includes: the more consistent the respective appearances of the respective objects are, the higher the corresponding degree of similarity obtained.
5. The method of claim 4, wherein the platform further comprises:
the multi-parameter detection device is respectively connected with the currently unused suspension pins of the similarity analysis device, the data analysis device and the parallel processing device so as to obtain the current temperature of the currently unused suspension pins of the similarity analysis device, the current temperature of the currently unused suspension pins of the data analysis device and the current temperature of the currently unused suspension pins of the parallel processing device.
6. The method of claim 5, wherein the platform further comprises:
and the MCU control chip is connected with the multi-parameter detection equipment and used for receiving the current temperature of the currently unused suspension pins of the similarity analysis equipment, the current temperature of the currently unused suspension pins of the data analysis equipment and the current temperature of the currently unused suspension pins of the parallel processing equipment, and performing weighted mean operation on the current temperature of the currently unused suspension pins of the similarity analysis equipment, the current temperature of the currently unused suspension pins of the data analysis equipment and the current temperature of the currently unused suspension pins of the parallel processing equipment to obtain a reference pin temperature, and the MCU control chip is also used for multiplying the obtained reference pin temperature by a weighing factor to obtain the silicon wafer entity temperature of the similarity analysis equipment.
7. The method of claim 6, wherein the platform further comprises:
the field storage device is used for storing three weight values in advance, wherein the three weight values are used for enabling the current temperature of the currently unused suspension pin of the similarity analysis device, the current temperature of the currently unused suspension pin of the data analysis device and the current temperature of the currently unused suspension pin of the parallel processing device to respectively participate in weighted mean calculation.
8. The method of claim 7, wherein the platform further comprises:
the speed adjusting equipment is respectively connected with the similarity analyzing equipment and the MCU control chip and is used for determining corresponding operation speed down-regulation multiples according to the entity temperature of the silicon wafer when the received entity temperature of the silicon wafer exceeds a limit;
the speed adjusting device is further used for executing downward adjustment execution operation on the current data processing speed of the similarity analyzing device based on the operation speed downward adjustment multiple;
in the field storage device, the current temperature of the currently unused suspension pin of the similarity analysis device, the current temperature of the currently unused suspension pin of the data analysis device and the current temperature of the currently unused suspension pin of the parallel processing device are different in size, and the three weight values of the current temperature of the currently unused suspension pin of the parallel processing device participate in weighted mean calculation respectively;
and the field storage device is connected with the MCU control chip and is used for pre-storing the weighing factors.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR19980085851A (en) * | 1997-05-30 | 1998-12-05 | 양재신 | Low temperature starting method of car and its device |
| CN101397969A (en) * | 2007-09-25 | 2009-04-01 | 三菱电机株式会社 | Combustion engine control device |
| CN102512075A (en) * | 2011-12-19 | 2012-06-27 | 江苏罗思韦尔电气有限公司 | Vehicular heating bottle |
| CN207526590U (en) * | 2017-10-20 | 2018-06-22 | 华晨汽车集团控股有限公司 | A kind of vehicle water temp represents the too low fault detect of number and processing unit |
| CN108256524A (en) * | 2018-01-24 | 2018-07-06 | 国家电网公司 | A kind of automatic reading method of multilist index formula instrument |
| CN109063608A (en) * | 2018-07-17 | 2018-12-21 | 苏海英 | Volume amplitude cloud handles acquisition platform |
| CN109445527A (en) * | 2018-12-21 | 2019-03-08 | 李银花 | Tablet computer data conversion storage system |
| CN109544569A (en) * | 2018-11-30 | 2019-03-29 | 宁波泽锦电器科技有限公司 | Automatic de-icing formula simple gate refrigerator |
-
2019
- 2019-04-02 CN CN201910263210.2A patent/CN111766799A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR19980085851A (en) * | 1997-05-30 | 1998-12-05 | 양재신 | Low temperature starting method of car and its device |
| CN101397969A (en) * | 2007-09-25 | 2009-04-01 | 三菱电机株式会社 | Combustion engine control device |
| CN102512075A (en) * | 2011-12-19 | 2012-06-27 | 江苏罗思韦尔电气有限公司 | Vehicular heating bottle |
| CN207526590U (en) * | 2017-10-20 | 2018-06-22 | 华晨汽车集团控股有限公司 | A kind of vehicle water temp represents the too low fault detect of number and processing unit |
| CN108256524A (en) * | 2018-01-24 | 2018-07-06 | 国家电网公司 | A kind of automatic reading method of multilist index formula instrument |
| CN109063608A (en) * | 2018-07-17 | 2018-12-21 | 苏海英 | Volume amplitude cloud handles acquisition platform |
| CN109544569A (en) * | 2018-11-30 | 2019-03-29 | 宁波泽锦电器科技有限公司 | Automatic de-icing formula simple gate refrigerator |
| CN109445527A (en) * | 2018-12-21 | 2019-03-08 | 李银花 | Tablet computer data conversion storage system |
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