CN111338298B - Intelligent production process monitoring system for health ring - Google Patents
Intelligent production process monitoring system for health ring Download PDFInfo
- Publication number
- CN111338298B CN111338298B CN202010089116.2A CN202010089116A CN111338298B CN 111338298 B CN111338298 B CN 111338298B CN 202010089116 A CN202010089116 A CN 202010089116A CN 111338298 B CN111338298 B CN 111338298B
- Authority
- CN
- China
- Prior art keywords
- pixel
- monitoring
- image
- information
- cluster head
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 124
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 48
- 230000036541 health Effects 0.000 title claims abstract description 42
- 238000001914 filtration Methods 0.000 claims abstract description 25
- 238000004458 analytical method Methods 0.000 claims abstract description 8
- 230000007613 environmental effect Effects 0.000 claims abstract description 5
- 241000854291 Dianthus carthusianorum Species 0.000 claims description 34
- 238000012545 processing Methods 0.000 claims description 21
- 238000001514 detection method Methods 0.000 claims description 17
- 241000196324 Embryophyta Species 0.000 claims description 10
- 230000014509 gene expression Effects 0.000 claims description 6
- 230000005540 biological transmission Effects 0.000 claims description 4
- 238000000034 method Methods 0.000 abstract description 14
- 230000008569 process Effects 0.000 abstract description 12
- 230000009286 beneficial effect Effects 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 15
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 11
- 150000002500 ions Chemical class 0.000 description 11
- 229910052799 carbon Inorganic materials 0.000 description 9
- 230000004060 metabolic process Effects 0.000 description 8
- 201000010099 disease Diseases 0.000 description 6
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 6
- 230000036039 immunity Effects 0.000 description 6
- 239000000843 powder Substances 0.000 description 6
- 239000008280 blood Substances 0.000 description 5
- 210000004369 blood Anatomy 0.000 description 5
- 239000011162 core material Substances 0.000 description 5
- 230000017531 blood circulation Effects 0.000 description 4
- 230000000694 effects Effects 0.000 description 4
- 239000000463 material Substances 0.000 description 4
- 229910052613 tourmaline Inorganic materials 0.000 description 4
- 239000011032 tourmaline Substances 0.000 description 4
- 229940070527 tourmaline Drugs 0.000 description 4
- 150000001768 cations Chemical class 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000006872 improvement Effects 0.000 description 3
- 229920000642 polymer Polymers 0.000 description 3
- 238000000197 pyrolysis Methods 0.000 description 3
- 150000003839 salts Chemical class 0.000 description 3
- 229910052723 transition metal Inorganic materials 0.000 description 3
- 150000003624 transition metals Chemical class 0.000 description 3
- 239000004215 Carbon black (E152) Substances 0.000 description 2
- PPBRXRYQALVLMV-UHFFFAOYSA-N Styrene Chemical compound C=CC1=CC=CC=C1 PPBRXRYQALVLMV-UHFFFAOYSA-N 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 2
- 150000001450 anions Chemical class 0.000 description 2
- -1 carbon-ammonia compound Chemical class 0.000 description 2
- 210000004027 cell Anatomy 0.000 description 2
- 150000001875 compounds Chemical class 0.000 description 2
- 229930195733 hydrocarbon Natural products 0.000 description 2
- 150000002430 hydrocarbons Chemical class 0.000 description 2
- NUJOXMJBOLGQSY-UHFFFAOYSA-N manganese dioxide Chemical compound O=[Mn]=O NUJOXMJBOLGQSY-UHFFFAOYSA-N 0.000 description 2
- 229910052751 metal Inorganic materials 0.000 description 2
- 239000002184 metal Substances 0.000 description 2
- 239000002086 nanomaterial Substances 0.000 description 2
- 229920003023 plastic Polymers 0.000 description 2
- 239000004033 plastic Substances 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 238000001179 sorption measurement Methods 0.000 description 2
- 239000002912 waste gas Substances 0.000 description 2
- 239000010920 waste tyre Substances 0.000 description 2
- KXGFMDJXCMQABM-UHFFFAOYSA-N 2-methoxy-6-methylphenol Chemical compound [CH]OC1=CC=CC([CH])=C1O KXGFMDJXCMQABM-UHFFFAOYSA-N 0.000 description 1
- 208000012260 Accidental injury Diseases 0.000 description 1
- 241000894006 Bacteria Species 0.000 description 1
- 235000017166 Bambusa arundinacea Nutrition 0.000 description 1
- 235000017491 Bambusa tulda Nutrition 0.000 description 1
- 102000001554 Hemoglobins Human genes 0.000 description 1
- 108010054147 Hemoglobins Proteins 0.000 description 1
- 206010061598 Immunodeficiency Diseases 0.000 description 1
- 206010024642 Listless Diseases 0.000 description 1
- 208000002720 Malnutrition Diseases 0.000 description 1
- 206010028980 Neoplasm Diseases 0.000 description 1
- 244000061176 Nicotiana tabacum Species 0.000 description 1
- 235000002637 Nicotiana tabacum Nutrition 0.000 description 1
- 244000082204 Phyllostachys viridis Species 0.000 description 1
- 235000015334 Phyllostachys viridis Nutrition 0.000 description 1
- 239000004698 Polyethylene Substances 0.000 description 1
- 230000003213 activating effect Effects 0.000 description 1
- 230000004913 activation Effects 0.000 description 1
- 239000013543 active substance Substances 0.000 description 1
- 230000004596 appetite loss Effects 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 210000000467 autonomic pathway Anatomy 0.000 description 1
- 239000011425 bamboo Substances 0.000 description 1
- 235000021168 barbecue Nutrition 0.000 description 1
- 201000011510 cancer Diseases 0.000 description 1
- 238000003763 carbonization Methods 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 239000003610 charcoal Substances 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000007791 dehumidification Methods 0.000 description 1
- 238000004332 deodorization Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000916 dilatatory effect Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 230000002124 endocrine Effects 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 206010016256 fatigue Diseases 0.000 description 1
- 229920002457 flexible plastic Polymers 0.000 description 1
- 210000005260 human cell Anatomy 0.000 description 1
- 230000036737 immune function Effects 0.000 description 1
- 210000000987 immune system Anatomy 0.000 description 1
- 208000015181 infectious disease Diseases 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 230000009545 invasion Effects 0.000 description 1
- 208000017971 listlessness Diseases 0.000 description 1
- 235000021266 loss of appetite Nutrition 0.000 description 1
- 208000019017 loss of appetite Diseases 0.000 description 1
- 229920002521 macromolecule Polymers 0.000 description 1
- 230000001071 malnutrition Effects 0.000 description 1
- 235000000824 malnutrition Nutrition 0.000 description 1
- 230000003340 mental effect Effects 0.000 description 1
- 150000002739 metals Chemical class 0.000 description 1
- 244000000010 microbial pathogen Species 0.000 description 1
- 230000004089 microcirculation Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 208000015380 nutritional deficiency disease Diseases 0.000 description 1
- 210000000056 organ Anatomy 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 230000020477 pH reduction Effects 0.000 description 1
- 244000052769 pathogen Species 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 229920001568 phenolic resin Polymers 0.000 description 1
- 230000035790 physiological processes and functions Effects 0.000 description 1
- 239000011033 pink tourmaline Substances 0.000 description 1
- 229920000573 polyethylene Polymers 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 230000001172 regenerating effect Effects 0.000 description 1
- 229920005989 resin Polymers 0.000 description 1
- 239000011347 resin Substances 0.000 description 1
- 208000019116 sleep disease Diseases 0.000 description 1
- 208000020685 sleep-wake disease Diseases 0.000 description 1
- 239000000779 smoke Substances 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
- 238000005728 strengthening Methods 0.000 description 1
- 238000007920 subcutaneous administration Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000005979 thermal decomposition reaction Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- 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
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4185—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by the network communication
-
- 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
- G05B2219/30—Nc systems
- G05B2219/31—From computer integrated manufacturing till monitoring
- G05B2219/31088—Network communication between supervisor and cell, machine group
Landscapes
- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Image Processing (AREA)
Abstract
The utility model provides a production process intelligent monitoring system for healthy circle, includes a plurality of temperature monitor module, a plurality of sensor monitor module, image acquisition module, intelligent management module, display screen and siren, temperature monitor module is used for monitoring the surface temperature of the production facility of healthy circle, sensor monitor module adopts sensor assembly to monitor the environmental information of the workshop of healthy circle, intelligent management module carries out filtering process and analysis to the monitoring information who obtains, works as make the siren report to the police when there is the monitoring information who is higher than given threshold value in the monitoring information to control image acquisition module basis the positional information of the monitoring information who is higher than given threshold value carries out image acquisition to this position. The invention has the beneficial effects that: the intelligent monitoring system is used for intelligently monitoring the production equipment of the health ring and the environment of a production workshop, and ensures the safe production of the health ring.
Description
Technical Field
The invention relates to the field of intelligent monitoring, in particular to an intelligent monitoring system for a production process of a health circle.
Background
After the physiological function of human body grows to the top, each organ declines with age and the increase of free radicals in the body, the metabolism slows down, the immunologic function declines, the adaptability to the change of external and internal environment declines, the physical strength declines and various diseases are produced. When the disease occurs, not only can great pain and affliction be brought to the individual, but also great pain is brought to the family. Meanwhile, huge losses are brought to the society and the country. The immune system, the most effective weapon of the human body to defend against the invasion of pathogens, is able to discover and eliminate the factors that cause the internal environment to fluctuate, such as: foreign bodies, foreign pathogenic microorganisms, and the like. Immunocompromised bodies are susceptible to infection or cancer; because of frequent illness, the consumption of the body is aggravated, so there are general manifestations of physical weakness, malnutrition, listlessness, fatigue, weakness, loss of appetite, sleep disorder, etc. As is well known whether the health level and state of the human body are understood by the strength and weakness of metabolism and immunity, the activity and regenerative capacity of cells must be the basis or core of metabolism and immunity; and a good tissue environment is needed to keep the activity of human cells to a certain degree.
The health ring is an anaerobic high-molecular health ring taking reasonable energy storage and transfer as a core, and MEGA as a core technology is used for acquiring and converting energy suitable for the physiological characteristics of a human body to act on the human body, so that the metabolism and the immunity of the human body are improved, and the improvement of the health level of the human body or the improvement of diseases is realized. Can produce high temperature and waste gas etc. in the production process of healthy circle, arouse accident easily carelessly a little, consequently, provide a production process intelligent monitoring system for healthy circle, carry out intelligent monitoring to the production facility of healthy circle and workshop's environment, in time early warning when appearing dangerous, can guarantee the safety in production of healthy circle.
Disclosure of Invention
In view of the above problems, the present invention aims to provide an intelligent production process monitoring system for health circles.
The health circle is equipment which takes MEGA as a core technology to obtain and convert energy suitable for the physiological characteristics of a human body to act on the human body, so that the metabolism and the immunity of the human body are improved, and the improvement of the health level or diseases of the human body is realized. The health circle is a medical health product (applying for medical instrument certificate) sold by the applicant, and comprises the following main components: a nano-class oxygen-free high-molecular carbon prepared from hydrocarbon, tourmaline, and transition metal. The basic principle is that the oxygen-free high molecular polymer and a plurality of inorganic nano materials are scientifically and reasonably proportioned to prepare the oxygen-free nano material. The health circle has the functions of reducing water molecular groups, tourmaline, adsorbing positive ions (generating negative ions) and the like, and improves the blood system to a certain extent. The main effects are as follows: 1. the blood flow speed is accelerated; 2. the blood flow per unit time increases and hemoglobin increases; 3. enhanced cellular tissue permeability; 4. not only can improve blood microcirculation and promote metabolism, but also has the auxiliary effects of cleaning blood, generating negative ions, resisting acidification and the like. Can be used for treating diseases or diseases caused by metabolism and immunity decrease.
Specifically, a hydrocarbon (an artificial polymer compound other than phenol-formaldehyde resin and plant materials, such as waste tires and plastic products) is subjected to dry distillation (anaerobic thermal decomposition) and activation to obtain activated carbon. The active carbon comprises primary active carbon and secondary active carbon or primary and secondary active substances which are mixed and added into tourmaline. Adding transition metals, monovalent and divalent metals and oxides or salts thereof. A compound or salt.
The oxide or salt may be in powder form, or may be a component of a web, a fabric, a film, or a component of an impregnating material. When the powder is used as powder, the powder is packaged by a flexible hollow plastic tube, two ends of the powder are sealed, and a metal or other fixed connecting devices are arranged to form a ring shape, so that the powder is convenient to wear on all parts of a body. The linear section shape of the flexible plastic pipe can be round, oval, triangular or rectangular. The purpose is to increase the fluidity of human blood.
The purity of the active carbon obtained by the technology is more than 94.4 percent and is higher than that of bamboo charcoal and the like. The cation adsorption capacity is strong, and an environment with more anions is created. The material mixed by the formula and the process can generate negative ions, electromagnetic waves and far infrared rays. So as to increase blood flow and promote health. The electromagnetic wave and far infrared ray have the functions of raising the temperature of subcutaneous deep layer, dilating blood capillary and strengthening metabolism, and the negative ion has the functions of activating biological cell, regulating autonomic nerve, regulating endocrine and mental stabilization, raising immunity and relieving fatigue.
The active carbon has strong cation adsorption capacity due to its large specific surface area, especially plant carbide, and can deodorize, dehumidify, and prevent bacteria (mildew), and can generate negative ions, electromagnetic waves, and far infrared rays when being matched with tourmaline and transition metal. At present, relevant products which are sold on the market comprise products for plant carbonization, deodorization, dehumidification and mould prevention, have cation adsorbability and generate anions and far infrared rays. A generator for generating negative ions by high-voltage discharge. Clothes, bedding, mask, health products and the like which generate negative ions and far infrared rays. The optimal formula of the health ring is as follows: the mixture of oxygen-free dry distillation matter, pink tourmaline and manganese dioxide is called blood flow increasing material for short.
The core material is prepared by decomposing the artificial polymer (such as waste tire) of carbon-ammonia compound (except styrene resin) at 550 deg.C in the absence of oxygen, bagging the resultant with polyethylene bag (20 cm in length and 10cm in width), and comparing with ion energy in atmosphere of 3cm to 30cm around with ion detector (AC-I00 from Zuoteng Co.). The result is averaged for five times, the artificial macromolecule is one time higher than the active carbon generated by the plant and is 1.4 times of the tobacco carbon, the anaerobic method is more effective than the old barbecue dry distillation method, and the carbon content is high. Therefore, the negative ion generating power is strong.
It can be seen that high temperature and waste gas can be produced in the production process of the health ring, accidents are easily caused carelessly, and therefore, the intelligent production process monitoring system for the health ring is provided, intelligent monitoring is carried out on production equipment of the health ring and the environment of a production workshop, timely early warning is carried out when dangers occur, and safety production of the health ring can be guaranteed.
The purpose of the invention is realized by the following technical scheme:
an intelligent monitoring system for a production process of a health circle comprises a plurality of temperature monitoring modules, a plurality of sensor monitoring modules, an image acquisition module, an intelligent management module, a display screen and an alarm, wherein each temperature monitoring module comprises a temperature monitoring unit and a position detection unit, the temperature monitoring unit is used for monitoring the surface temperature of production equipment of the health circle, the position detection unit is used for acquiring the position information of the temperature monitoring unit, each sensor monitoring module comprises a sensor monitoring unit and a GPS positioning unit, the sensor monitoring unit adopts a sensor assembly to monitor the environmental information of a production workshop of the health circle, the GPS positioning unit is used for acquiring the position information of the sensor monitoring unit, and the temperature monitoring modules and the sensor monitoring modules send the acquired monitoring information and the position information to the intelligent management module, the intelligent management module carries out filtering processing and analysis on the received monitoring information, when the monitoring information higher than a given threshold value exists in the monitoring information, the intelligent management module enables the alarm to give an alarm, controls the image acquisition module to carry out image acquisition on the position according to the position information of the monitoring information higher than the given threshold value, sends the acquired image to the intelligent management module, and the intelligent management module processes the received image and then sends the processed image to the display screen for displaying.
The beneficial effects created by the invention are as follows:
the invention is used for intelligently monitoring the environment of the production equipment and the production workshop of the health ring, the surface temperature of the production equipment of the health ring is monitored by the temperature monitoring unit, the state of the production equipment of the health ring in the production process is judged according to the surface temperature condition of the production equipment of the health ring, the abnormal phenomenon of the production equipment of the health ring can be found in time, the safety production of the health ring is ensured, the sensor monitoring module is used for monitoring the environment of the production workshop of the health circle, so that the environment condition of the production workshop of the health circle can be mastered in real time, the alarm is given in time when danger occurs, the image acquisition module is controlled to acquire images of dangerous positions, the acquired images are processed and then displayed on the display screen, so that workers can more visually know the dangerous conditions occurring in the production workshop of the health circle, the accidental injury caused by the fact that the vehicle enters the workshop without knowing the dangerous condition is avoided.
Drawings
The invention is further described with the aid of the accompanying drawings, in which, however, the embodiments do not constitute any limitation to the invention, and for a person skilled in the art, without inventive effort, further drawings may be derived from the following figures.
FIG. 1 is a schematic diagram of the present invention.
Reference numerals:
a temperature monitoring module; a sensor monitoring module; an image acquisition module; an intelligent management module; a display screen; an alarm.
Detailed Description
The invention is further described with reference to the following examples.
Referring to fig. 1, the system for intelligently monitoring the production process of a health circle in this embodiment includes a plurality of temperature monitoring modules, a plurality of sensor monitoring modules, an image acquisition module, an intelligent management module, a display screen, and an alarm, each temperature monitoring module includes a temperature monitoring unit and a position detection unit, the temperature monitoring unit is used for monitoring the surface temperature of the production equipment of the health circle, the position detection unit is used for acquiring the position information of the temperature monitoring unit, each sensor monitoring module includes a sensor monitoring unit and a GPS positioning unit, the sensor monitoring unit monitors the environmental information of the production workshop of the health circle by using a sensor component, the GPS positioning unit is used for acquiring the position information of the sensor monitoring unit, and the temperature monitoring module and the sensor monitoring module send the acquired monitoring information and position information to the intelligent management module, the intelligent management module carries out filtering processing and analysis on the received monitoring information, when the monitoring information higher than a given threshold value exists in the monitoring information, the intelligent management module enables the alarm to give an alarm, controls the image acquisition module to carry out image acquisition on the position according to the position information of the monitoring information higher than the given threshold value, sends the acquired image to the intelligent management module, and the intelligent management module processes the received image and then sends the processed image to the display screen for displaying.
This preferred embodiment is used for carrying out intelligent monitoring to the production facility of healthy circle and the environment of workshop, monitor the surface temperature of the production facility of healthy circle through the temperature monitoring unit, the state of the production facility of healthy circle in process of production is judged to the surface temperature condition of the production facility of healthy circle through the production facility of healthy circle, can in time discover the abnormal phenomenon of the production facility of healthy circle, monitor the environment of the workshop of healthy circle through sensor monitoring module, can master the environmental aspect of the workshop of healthy circle in real time, and in time early warning when dangerous appears, the safety in production of healthy circle has been guaranteed.
Preferably, the intelligent management module includes a data processing unit, a security analysis unit and an image processing unit, the data processing unit is configured to perform filtering processing on the received monitoring information, the security analysis unit compares the processed monitoring information with a given threshold, when monitoring information higher than the given threshold exists in the monitoring information, the alarm is enabled to alarm, the image acquisition module is enabled to perform image acquisition on the position according to the position information of the monitoring information higher than the given threshold, and the image processing unit is configured to process the received image.
Preferably, the image processing unit is configured to perform filtering processing on the received image, where I represents the received image, f (I, j) represents a gray value of a pixel I (I, j) at a coordinate (I, j) in the image I, and a filter function corresponding to the pixel I (I, j) is constructed as follows:
f′(i,j)=argmin{α(i,j)*α′(i,j)+β(i,j)*β′(i,j)}
α′(i,j)=(f′(i,j)-h(i,j))2
where f '(I, j) represents the filtered gray scale value of the pixel I (I, j), Ω (I, j) represents the local neighborhood of (2 ω +1) × (2 ω +1) centered on the pixel I (I, j), α' (I, j) represents the gray scale constraint factor of the pixel I (I, j), β '(I, j) represents the edge constraint factor of the pixel I (I, j), f' (x, y) represents the filtered gray scale value of the pixel at coordinate (x, y) in the local neighborhood Ω (I, j), f '(I, j +1) represents the filtered gray scale value of the pixel at coordinate (I, j +1) in the image I, f' (x, y +1) represents the filtered gray scale value of the pixel at coordinate (x, y +1) in the image I, f '(I +1, j) represents the filtered gray scale value of the pixel at coordinate (I, j +1) in the image I, f' (I +1, y +1) represents the filtered gray scale value of the pixel at coordinate (I +1) in the image I, j), f '(I +1) represents the filtered gray scale value of the pixel I + j) in the filtered gray scale value of the pixel I, y +1, f' (I + j) represents the filtered gray scale value of the pixel I +1, j), f +1, y +1, j) represents the filtered gray scale value of the pixel I, y +1And isThe expression of (a) is:
wherein L (Ω (i, j)) represents the number of pixels in the local neighborhood Ω (i, j), k (x, y) is a value-taking function, when | f (x, y) -f (i, j) | is less than or equal to W (i, j), k (x, y) | 1, when | f (x, y) -f (i, j) |>When W (i, j), k (x, y) is 0, where f (x, y) represents the local neighborhood ΩThe gray value of the pixel at coordinate (x, y) in (I, j), W (I, j) is the pixel detection threshold corresponding to the pixel I (I, j), andwherein,representing the mean, f, of the grey values of the pixels in the local neighborhood Ω (i, j)m(Ω (i, j)) represents the median of the gray values of the pixels in the local neighborhood Ω (i, j);
when in useThen the values of h (i, j), α (i, j) and β (i, j) are: α (i, j) is equal to 1, β (i, j) is equal to 0, whenThen h (i, j), α (i, j), and β (i, j) have values of h (i, j) to f (i, j),α (i, j) ═ 1- β (i, j); whenThen the values of h (i, j), α (i, j) and β (i, j) are:
the preferred embodiment is used for filtering the received image, constructing a filtering function of the pixel, and introducing a gray level constraint factor and an edge constraint factor into the filtering function, wherein the gray level constraint factorThe edge constraint factors are used for ensuring that the gray value of the noise pixel tends to be normal in the filtering process, the edge constraint factors are used for ensuring that the edge information in the image is kept in the filtering process, the pixel detection factors are defined, the pixel detection factors can effectively judge the attributes of the pixel, and the gray constraint reference value, the gray constraint weight value and the edge constraint weight value are determined according to different attributes of the pixel, when the value of the pixel detection factor belongs toWhen the pixel is a noise pixel, judging that the pixel is a noise pixel, taking the mean value of the gray values of other pixels which do not contain the noise pixel in the neighborhood pixels of the noise pixel as a gray constraint reference value of the gray constraint reference value in the filtering function, setting a gray constraint weight value to be 1, and setting a structural constraint weight value to be 0, wherein the gray constraint reference value is used for ensuring that the gray value of the noise pixel can be close to a normal value by the filtering function; when the value of the pixel detection factor belongs toWhen the pixel is judged to belong to the edge area, the filtering function is mainly used for reserving the edge information in the image at the moment, the gray level constraint reference value in the filtering function is set to be the gray level value of the pixel to be filtered, namely the gray level characteristic of the edge pixel is reserved, the larger the value of the pixel detection factor in the interval is, the closer the pixel is to the edge area of the image is shown, namely the structural constraint factor in the filtering function is set to be in a mode of increasing along with the increasing of the value of the pixel detection factor, and the structural constraint factor is used for ensuring that the filtering function can effectively reserve the edge information in the image in the filtering process; when the value of the pixel detection factor belongs toThen indicating that the gray value distribution of the pixel and the local neighborhood pixels is more balanced, and at the moment, the gray value constraint reference value in the filtering function adopts the gray value mean value of the pixels in the local neighborhood of the pixel to be filtered, and the gray value constraint weight and the structural constraint weight are both set to be the gray value constraint weight and the structural constraint weightSo that the filter function at this point ensures the smoothness of the pixel.
Preferably, let I denote the image received by the image processing unit, I ' denote the image after the filtering processing of the image I, perform information compensation on the filtered image I ', let z denote the filtered noise image, let z be I-I ', and let I bez(a, b) represents the pixel at coordinate (a, b) in the noisy image z, using the local neighborhood KzPixel-to-pixel I in (a, b)zAdjusting the gray values of (a, b), specifically:
in the formula, L (K)z(a, b)) represents a local neighborhood KzNumber of pixels in (a, b), fz' (a, b) denotes a pair of pixels IzThe adjusted gray-scale value of (a, b), fz(a, b) represents a pixel IzGrey scale value of (a, b), Kz(a, b) represents the pixel IzM centered on (a, b)z(a,b)×Nz(a, b) local neighborhood of where Mz(a, b) denotes a local neighborhood KzLength of (a, b), Nz(a, b) denotes a local neighborhood KzWidth of (a, b), and Mz(a, b) and NzThe expressions of (a, b) are respectively:
where M and N represent the length and width, Ω, respectively, of the noise image zz(a, b) represents the pixel Iz(2 ω +1) × (2 ω +1) local neighborhood centered at (a, b), 0<ω<M and 0<ω<N,fz(x, y) denotes the local neighborhood Ωz(a, b) the gray value of the pixel at coordinate (x, y), fz(x +1, y) is the gray value of the pixel at coordinate (x +1, y) in the noise image z, fz(x,y+1) Is the gray value, f, of the pixel at coordinate (x, y +1) in the noise image zz(max) and fz(min) representing the maximum and minimum values of the pixel grey values in the noise image z, respectively;
assuming that z 'represents an image in which the gray values of pixels in the noise image z are adjusted, and I ″ represents an image in which information compensation is performed on the image I', the expression of I ″ is: i ″ + I '+ z'.
The preferred embodiment is used for performing information compensation on the filtered image, and a phenomenon of filtering weak texture detail information in the image may occur in the process of filtering the image; when information compensation is performed on an image, firstly, the gray value of a pixel in a filtered noise image is adjusted, the gray value of the pixel is adjusted by using a neighborhood pixel in a local neighborhood of the pixel, in the process of determining the neighborhood pixel participating in adjusting the gray value of the pixel, the preferred embodiment adaptively determines the range of the neighborhood pixel participating in adjusting the gray value of the pixel according to the attribute of the pixel, and when the pixel is the noise pixel, the local neighborhood K participating in adjusting the gray value of the pixel is adjustedz(a, b) is smaller, namely, the noise pixel can be effectively removed, when the pixel is the texture detail information, the local neighborhood K participating in the gray value adjustment of the pixel is enabledzAnd (a, b) is large, namely, the texture detail information can be effectively kept.
Preferably, the sensor monitoring unit adopts sensor assembly to monitor workshop environment information, sensor assembly still includes the convergent node including the monitoring node that is used for gathering workshop environment information, the cluster head node that is used for collecting the workshop environment monitoring information that the monitoring node sent in the cluster, the convergent node is with the workshop environment monitoring information that self acquireed and the transmission of received workshop environment monitoring information after fusing to the convergent node, by the convergent node with workshop environment monitoring information sends to intelligent management module.
Preferably, the sensor assembly comprises a temperature sensor, a humidity sensor, a dust concentration sensor and a smoke concentration sensor.
Preferably, the rate of collecting the workshop environment information by the sensor assembly is adaptively adjusted, and C is set0Indicating a cluster head node, K (C)0) Indicating cluster head node C0Set of monitoring nodes in the cluster, and K (C)0)={ki,i=1,2,…,N(C0) In which k isiRepresents the set K (C)0) The ith monitoring node in (1), N (C)0) Represents the set K (C)0) Number of monitoring nodes inIndicating cluster head node C0The rate at which the plant environment information is collected at time t,indicating a monitoring node kiThe rate of collecting the workshop environment information at time t, andandare all set to V0Defining a cluster head detection factorWherein d (C)0And t) represents a cluster head node C0Number of packets in buffer queue at time t, D (C)0) Indicating cluster head node C0The number of data packets that can be accommodated in the buffer queue;
when rho (C)0)>1 hour, cluster head node C0The speed of collecting the workshop environment information is adjusted as follows: wherein, S (C)0) Indicating cluster headPoint C0Number of packets successfully transmitted to the sink node, J (C)0) Indicating cluster head node C0Number of self-collected data packets, J (k)i,C0) Indicating a monitoring node kiSuccessful transmission to cluster head node C0The number of data packets; cluster head node C0Monitoring node k of the clusteriThe speed of collecting the workshop environment information is adjusted as follows: when rho (C)0) When the number of the cluster head nodes is less than or equal to 1, clustering the head nodes C0Rate of collecting plant environment informationAnd the monitoring node k of the clusteriRate of collecting plant environment informationRemain unchanged.
The preferred embodiment is used for adaptively adjusting the rate of acquiring the workshop environment information by the sensor component in the sensor monitoring unit, adjusting the rate of acquiring the workshop environment information by the cluster head node according to the transmission success rate of the cluster head node and the number of data packets in the cache queue of the cluster head node, and adjusting the rate of acquiring the workshop environment information by the monitoring node in the cluster where the cluster head node is located according to the number of data packets in the cache queue of the cluster head node, so that the number of data packets in the cache queue of the cluster head node is smaller than the number of data packets which can be accommodated by the monitoring node, and the congestion phenomenon in the process of transmitting the data packets by the cluster head node is avoided.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (4)
1. An intelligent monitoring system for a production process of a health circle is characterized by comprising a plurality of temperature monitoring modules, a plurality of sensor monitoring modules, an image acquisition module, an intelligent management module, a display screen and an alarm, wherein each temperature monitoring module comprises a temperature monitoring unit and a position detection unit, the temperature monitoring unit is used for monitoring the surface temperature of production equipment of the health circle, the position detection unit is used for acquiring the position information of the temperature monitoring unit, each sensor monitoring module comprises a sensor monitoring unit and a GPS positioning unit, the sensor monitoring unit adopts a sensor assembly to monitor the environmental information of a production workshop of the health circle, the GPS positioning unit is used for acquiring the position information of the sensor monitoring unit, and the temperature monitoring modules and the sensor monitoring modules send the acquired monitoring information and the acquired position information to the intelligent management module, the intelligent management module carries out filtering processing and analysis on the received monitoring information, when the monitoring information is higher than a given threshold value, the intelligent management module enables an alarm to give an alarm, controls the image acquisition module to carry out image acquisition on the position according to the position information of the monitoring information higher than the given threshold value, sends the acquired image to the intelligent management module, and sends the received image to the display screen for displaying after processing;
the intelligent management module comprises a data processing unit, a safety analysis unit and an image processing unit, wherein the data processing unit is used for filtering the received monitoring information, the safety analysis unit compares the processed monitoring information with a given threshold value, when the monitoring information with the threshold value higher than the given threshold value exists, an alarm is given out, the image acquisition module is used for acquiring the image of the position according to the position information of the monitoring information with the threshold value higher than the given threshold value, and the image processing unit is used for processing the received image;
the image processing unit is used for performing filtering processing on the received image, wherein I represents the received image, f (I, j) represents the gray value of a pixel I (I, j) at the coordinate (I, j) in the image I, and the filter function corresponding to the pixel I (I, j) is constructed as follows:
f′(i,j)=argmin{α(i,j)*α′(i,j)+β(i,j)*β′(i,j)}
α′(i,j)=(f′(i,j)-h(i,j))2
where f '(I, j) represents the filtered gray scale value of the pixel I (I, j), Ω (I, j) represents the local neighborhood of (2 ω +1) × (2 ω +1) centered on the pixel I (I, j), α' (I, j) represents the gray scale constraint factor of the pixel I (I, j), β '(I, j) represents the edge constraint factor of the pixel I (I, j), f' (x, y) represents the filtered gray scale value of the pixel at coordinate (x, y) in the local neighborhood Ω (I, j), f '(I, j +1) represents the filtered gray scale value of the pixel at coordinate (I, j +1) in the image I, f' (x, y +1) represents the filtered gray scale value of the pixel at coordinate (x, y +1) in the image I, f '(I +1, j) represents the filtered gray scale value of the pixel at coordinate (I, j +1) in the image I, f' (I +1, y +1) represents the filtered gray scale value of the pixel at coordinate (I +1) in the image I, j), f '(I +1) represents the filtered gray scale value of the pixel I + j) in the filtered gray scale value of the pixel I, y +1, f' (I + j) represents the filtered gray scale value of the pixel I +1, j), f +1, y +1, j) represents the filtered gray scale value of the pixel I, y +1And isThe expression of (a) is:
wherein L (Ω (i, j)) represents the local neighborhood Ω (i, j)K (x, y) is a value-taking function, when | f (x, y) -f (I, j) | is less than or equal to W (I, j), k (x, y) is 1, when | f (x, y) -f (I, j) | > W (I, j), k (x, y) is 0, wherein f (x, y) represents a gray-scale value of a pixel at coordinate (x, y) in a local neighborhood Ω (I, j), W (I, j) is a pixel detection threshold corresponding to pixel I (I, j), andwherein,representing the mean, f, of the grey values of the pixels in the local neighborhood Ω (i, j)m(Ω (i, j)) represents the median of the gray values of the pixels in the local neighborhood Ω (i, j);
when in useThen the values of h (i, j), α (i, j) and β (i, j) are: α (i, j) is equal to 1, β (i, j) is equal to 0, whenThen h (i, j), α (i, j), and β (i, j) have values of h (i, j) to f (i, j),α (i, j) ═ 1- β (i, j); whenThen the values of h (i, j), α (i, j) and β (i, j) are:
2. the system according to claim 1, wherein I represents an image received by the image processing unit, I ' represents an image obtained by filtering the image I, information compensation is performed on the filtered image I ', z represents a filtered noise image, and z is I-I ', I isz(a, b) represents the pixel at coordinate (a, b) in the noisy image z, using the local neighborhood KzPixel-to-pixel I in (a, b)zAdjusting the gray values of (a, b), specifically:
in the formula, L (K)z(a, b)) represents a local neighborhood KzNumber of pixels in (a, b), f'z(a, b) represents the pixel IzThe adjusted gray-scale value of (a, b), fz(a, b) represents a pixel IzGrey scale value of (a, b), Kz(a, b) represents the pixel IzM centered on (a, b)z(a,b)×Nz(a, b) local neighborhood of where Mz(a, b) denotes a local neighborhood KzLength of (a, b), Nz(a, b) denotes a local neighborhood KzWidth of (a, b), and Mz(a, b) and NzThe expressions of (a, b) are respectively:
where M and N are the length and width, Ω, respectively, of the noise image zz(a, b) represents the pixel Iz(a, b) a local neighborhood of (2 ω +1) × (2 ω +1) centered 0 < ω < M and 0 < ω < N, fz(x, y) denotes the local neighborhood Ωz(a,b) Grey value of pixel at medium coordinate (x, y), fz(x +1, y) represents the gray value of the pixel at coordinate (x +1, y) in the noise image z, fz(x, y +1) represents the gray value of the pixel at coordinate (x, y +1) in the noise image z, fz(max) and fz(min) representing the maximum and minimum values of the pixel grey values in the noise image z, respectively;
assuming that z 'represents an image in which the gray values of pixels in the noise image z are adjusted, and I ″ represents an image in which information compensation is performed on the image I', the expression of I ″ is: i ″ + I '+ z'.
3. The intelligent production process monitoring system for the health circle as claimed in claim 2, wherein the sensor monitoring unit monitors the workshop environment information by using a sensor component, the sensor component comprises monitoring nodes for collecting the workshop environment information, cluster head nodes for collecting the workshop environment monitoring information sent by the monitoring nodes in the cluster, and sink nodes, the cluster head nodes transmit the workshop environment monitoring information acquired by the cluster head nodes and the received workshop environment monitoring information to the sink nodes after being fused, and the workshop environment monitoring information is sent to the intelligent management module by the sink nodes.
4. The intelligent monitoring system for the production process of the health circle as claimed in claim 3, wherein the rate of the sensor assembly acquiring the workshop environment information is adaptively adjusted, and C is set0Indicating a cluster head node, K (C)0) Indicating cluster head node C0Set of monitoring nodes in the cluster, and K (C)0)={ki,i=1,2,...,N(C0) In which k isiRepresents the set K (C)0) The ith monitoring node in (1), N (C)0) Represents the set K (C)0) Number of monitoring nodes inIndicating cluster head node C0The rate at which the plant environment information is collected at time t,indicating a monitoring node kiThe rate of collecting the workshop environment information at time t, andandare all set to V0Defining a cluster head detection factorWherein d (C)0And t) represents a cluster head node C0Number of packets in buffer queue at time t, D (C)0) Indicating cluster head node C0The number of data packets that can be accommodated in the buffer queue;
when rho (C)0) When the number is more than 1, the cluster head node C is connected0The speed of collecting the workshop environment information is adjusted as follows:wherein, S (C)0) Indicating cluster head node C0Number of packets successfully transmitted to the sink node, J (C)0) Indicating cluster head node C0Number of self-collected data packets, J (k)i,C0) Indicating a monitoring node kiSuccessful transmission to cluster head node C0The number of data packets; cluster head node C0Monitoring node k of the clusteriThe speed of collecting the workshop environment information is adjusted as follows:when rho (C)0) When the number of the cluster head nodes is less than or equal to 1, clustering the head nodes C0Rate of collecting plant environment informationAnd the monitoring node k of the clusteriRate of collecting plant environment informationRemain unchanged.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010089116.2A CN111338298B (en) | 2020-02-12 | 2020-02-12 | Intelligent production process monitoring system for health ring |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010089116.2A CN111338298B (en) | 2020-02-12 | 2020-02-12 | Intelligent production process monitoring system for health ring |
Publications (2)
Publication Number | Publication Date |
---|---|
CN111338298A CN111338298A (en) | 2020-06-26 |
CN111338298B true CN111338298B (en) | 2020-09-11 |
Family
ID=71183871
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202010089116.2A Active CN111338298B (en) | 2020-02-12 | 2020-02-12 | Intelligent production process monitoring system for health ring |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN111338298B (en) |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112540635B (en) * | 2020-12-03 | 2021-08-17 | 华润三九(枣庄)药业有限公司 | Traditional chinese medicine production intelligence quality control system based on artificial intelligence |
CN113436824B (en) * | 2021-07-07 | 2024-08-16 | 上海圣石生物医学科技有限公司 | Magnetic wave-absorbing material, preparation method, application and health-care product thereof |
Family Cites Families (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104331869B (en) * | 2014-11-25 | 2017-10-27 | 南京信息工程大学 | The image smoothing method that gradient is combined with curvature |
KR101801460B1 (en) * | 2016-03-25 | 2017-11-27 | 박노창 | Greenhouse monitoring system |
CN206554978U (en) * | 2017-03-09 | 2017-10-13 | 中国矿业大学(北京) | Underground coal mine sensor positioning alarm system |
CN109640032B (en) * | 2018-04-13 | 2021-07-13 | 河北德冠隆电子科技有限公司 | Five-dimensional early warning system based on artificial intelligence multi-element panoramic monitoring detection |
CN109460945A (en) * | 2018-12-26 | 2019-03-12 | 广东北斗翔晨科技有限公司 | Cultivation information monitoring method based on Internet of Things |
CN110458839B (en) * | 2019-10-09 | 2020-01-14 | 江西太平洋电缆集团有限公司 | Effective wire and cable monitoring system |
CN110458157B (en) * | 2019-10-14 | 2020-01-07 | 江西太平洋电缆集团有限公司 | Intelligent monitoring system for power cable production process |
-
2020
- 2020-02-12 CN CN202010089116.2A patent/CN111338298B/en active Active
Also Published As
Publication number | Publication date |
---|---|
CN111338298A (en) | 2020-06-26 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN111338298B (en) | Intelligent production process monitoring system for health ring | |
DE602005017755D1 (en) | COLLECTION OF INFORMATION ON ACTIVITY AND SLEEP QUALITY WITH A MEDICAL PRODUCT | |
CN201698561U (en) | Prompting device for correcting sitting postures of computer users | |
CN106369751A (en) | Fresh air exchange control method | |
CN1811645A (en) | Intelligent anti-snoring sleeping pillow | |
CN102824168B (en) | Flexible physiological dry electrode and preparation method thereof | |
CN107617149A (en) | The disturbance of consciousness promotees wake up system and its application method | |
CN103446683A (en) | Five-prevention oxygen-enriched mask | |
CN109481164A (en) | A kind of electric wheelchair control system based on EEG signals | |
CN103418018A (en) | Tea fungus synthesized bacterial cellulose pressure sore dressing as well as preparation method and application thereof | |
CN205108639U (en) | Intelligent malleation respiratory therapy machine that conveniently carries | |
CN208130251U (en) | A kind of external diaphragm pacemaker of the medium frequency electric stimulation of low frequency modulations | |
CN115295161B (en) | Recuperation monitoring method and system based on millimeter wave radar | |
CN203341947U (en) | Full-isolation and multifunctional intensive care type ambulance | |
CN208048720U (en) | A kind of high altitude localities human body physiological parameter monitoring and warning wearable device | |
CN105879134A (en) | Monitor for ventricular assist apparatus and monitoring method of monitor | |
CN206767376U (en) | A kind of efficient sterilizing taste removal lift car for wisdom building | |
CN108836316A (en) | A kind of R wave of electrocardiosignal extracting method based on BP neural network | |
CN213849673U (en) | Air-purifying posture-correcting chair based on Internet of things control | |
CN204076989U (en) | Water-proof breathable properties foil electret | |
WO2005074809A1 (en) | Device for measuring the function of a lung | |
CN209713244U (en) | A kind of animal auditory detection is heat insulating bed with fixation | |
Tran et al. | Snoring detection sleep pillow | |
CN201789980U (en) | Autopsy respirator special for legal medical experts | |
AU2021105118A4 (en) | An intelligent auxiliary decision-making platform for the treatment of large-scale casualty incidents |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |