CN116916493A - LED lighting lamp operation monitoring data management system - Google Patents
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Abstract
The invention discloses an operation monitoring data management system of an LED lighting lamp, and belongs to the technical field of intelligent lamps; the accuracy of the subsequent abnormal feedback monitoring analysis can be improved by carrying out validity screening on feedback anomalies counted by different channel monitoring; the local influence analysis of the abnormal feedback in different aspects is realized by carrying out calculation and analysis of the influence of the abnormal type on the abnormal type of the different feedback; the overall operation states of the LED illumination lamp are analyzed and classified by carrying out association calculation on different local operation monitoring analysis data of the LED illumination lamp in different basic monitoring periods, so that the overall effect of the current operation of the LED illumination lamp can be intuitively and efficiently obtained; the method and the device are used for solving the technical problems that in the existing scheme, periodic abnormal monitoring analysis is not implemented on the operation of the LED lighting lamp, and the abnormal monitoring analysis results of different periodicity are integrated to analyze the whole operation state of the LED lighting lamp and dynamically manage the operation of the LED lighting lamp.
Description
Technical Field
The invention relates to the technical field of intelligent lamps, in particular to an LED lighting lamp operation monitoring data management system.
Background
The LED lamp is a light-emitting diode, adopts a solid semiconductor chip as a luminescent material, and has the advantages of energy conservation, environmental protection, good color rendering and response speed compared with the traditional lamp.
When the existing LED lighting lamp operation monitoring data management scheme is implemented, most of the operation monitoring data management schemes still stay in the aspect of the LED lighting lamp, such as monitoring, comparing, analyzing and alarming operation data in different aspects when the LED lighting lamp operates, and managing the operation state of the LED lighting lamp in the aspect of the LED lighting lamp; however, no periodic anomaly monitoring analysis is implemented for the operation of the LED lighting fixture, and the results of the anomaly monitoring analysis of different periodicity are integrated to analyze the overall operation state of the LED lighting fixture and dynamically manage the implementation thereof.
Disclosure of Invention
The invention aims to provide an LED lighting lamp operation monitoring data management system which is used for solving the technical problems that in the existing scheme, periodic abnormal monitoring analysis is not implemented on the operation of an LED lighting lamp, and the results of the abnormal monitoring analysis with different periodicity are integrated to analyze the whole operation state of the LED lighting lamp and dynamically manage the operation of the LED lighting lamp.
The aim of the invention can be achieved by the following technical scheme:
the LED lighting lamp operation monitoring data management system comprises an operation anomaly monitoring statistical module, a monitoring statistical module and a data preprocessing module, wherein the operation anomaly monitoring statistical module is used for implementing monitoring statistics and implementing data preprocessing on the abnormal operation of the LED lighting lamp to obtain abnormal operation statistical data;
the operation anomaly monitoring and analyzing module is used for carrying out anomaly influence analysis on monitoring statistics and preprocessed anomaly operation statistics data to obtain anomaly monitoring and analyzing data; comprising the following steps:
when type influence analysis is sequentially implemented on the abnormal types corresponding to all the abnormal types of the same lamp model, type influence coefficients Ly corresponding to different abnormal types fed back by the LED lighting lamp are sequentially calculated and obtained through a formula Ly=YQ×LS/XZ; wherein YQ is an abnormal type weight corresponding to an abnormal type, LS is the total feedback times of the type corresponding to feedback of the abnormal type, and XZ is the total sales number of the LED lighting lamp in a basic monitoring period;
sequentially arranging a plurality of abnormal types fed back in descending order according to the numerical value of the type influence coefficient, and sequentially comparing and judging the type influence coefficient of the plurality of abnormal types in order with the corresponding type influence threshold;
marking the abnormal type corresponding to the type influence coefficient larger than the type influence threshold as a high-influence abnormal type and generating a high-influence feedback label, and marking the abnormal type corresponding to the type influence coefficient not larger than the type influence threshold as a low-influence abnormal type and generating a low-influence feedback label;
the high-influence feedback labels or the low-influence feedback labels corresponding to all the abnormal types form abnormal monitoring analysis data and are uploaded to a lamp operation supervision platform;
the operation anomaly monitoring management module is used for carrying out stability evaluation on the overall operation states of the LED lighting fixtures in different basic monitoring periods according to all anomaly monitoring analysis data, and carrying out dynamic management on updating maintenance and iterative upgrading of the LED lighting fixtures in the later period according to evaluation results.
Preferably, the operation of the anomaly monitoring statistics module includes:
in a basic monitoring period, counting abnormal operation of the LED lighting lamp with a networking function through an online feedback channel and an offline after-sale channel, obtaining a lamp model and an abnormal type corresponding to the LED lighting lamp which is fed back abnormally, and carrying out effectiveness screening on feedback of the LED lighting lamp according to the abnormal type;
matching the exception types with all sample exception types prestored in a database; if the matching is successful, generating a feedback effective label; if the matching is unsuccessful, generating a feedback invalid tag.
Preferably, counting the total feedback times of abnormal operation of the corresponding LED lighting lamp, the total feedback valid tags and the total feedback invalid tags according to the lamp model; calculating the ratio of the total number of feedback invalid tags to the total number of feedback times, setting the ratio as an invalid influence coefficient, generating a first invalid influence signal if the invalid influence coefficient is larger than an invalid influence threshold value, and generating an update prompt of the LED lighting lamp networking operation description to a manufacturer according to the first invalid influence signal;
and if the invalid influence coefficient is not greater than the invalid influence threshold, generating a second invalid influence signal, and maintaining the prompt of the networking operation description of the existing LED lighting lamp according to the second invalid signal.
Preferably, counting the total number of type feedback corresponding to different abnormal types of the feedback of the same lamp model; performing digital processing on the abnormal type to obtain a corresponding weight of the abnormal type;
the LED lighting lamp is corresponding to all lamp models and abnormal types of abnormal feedback, and the corresponding total feedback times and the total feedback times of a plurality of types form abnormal operation statistical data.
Preferably, the operating steps of the abnormality monitoring management module include: traversing the abnormal monitoring analysis data, and acquiring the sales total XS and the sales total XE of the LED lighting lamp after being put into the market according to the high-influence feedback tags acquired through traversing, and the type influence coefficients Ly corresponding to all the high-influence feedback tags in all basic monitoring periods after the LED lighting lamp is put into the market; and extracting the value of the sales total number, the sales total number and the type influence coefficients corresponding to all the high-influence feedback tags, and obtaining the running state coefficient Yz corresponding to the LED lighting lamp through calculation.
Preferably, the calculation formula of the operation state coefficient Yz is:the method comprises the steps of carrying out a first treatment on the surface of the Wherein, alpha and beta are constant coefficients larger than zero, and alpha+beta=0.1; n is the total number of all high impact feedback tags.
Preferably, when the overall operation state of the LED lighting fixture after being put into the market is analyzed and evaluated according to the operation state coefficient, the operation state coefficient is compared with the operation state range corresponding to the LED lighting fixture, so as to obtain an evaluation result composed of the first state signal, the second state signal or the third state signal.
Preferably, when the later updating maintenance and iterative upgrading of the LED lighting lamp are dynamically managed according to the evaluation result, the evaluation result is traversed, and the existing updating maintenance scheme, the updating maintenance frequency increase or the time of advanced iterative upgrading are respectively implemented on the LED lighting lamp according to the first state signal, the second state signal or the third state signal obtained by traversing.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, through carrying out validity screening on feedback anomalies of monitoring statistics of different channels, the accuracy of subsequent anomaly feedback monitoring analysis can be improved, and meanwhile, the effect of the corresponding networking operation instruction of the LED lighting lamp can be obtained, so that the corresponding networking operation instruction of the LED lighting lamp can be updated and perfected in time; by calculating and analyzing the abnormal type influence of different feedback abnormal types, the method not only can realize the local influence analysis of different abnormal feedback, but also can provide reliable local influence analysis data support for the integral influence analysis and dynamic management of the subsequent LED lighting lamp, and improves the integral effect of the monitoring analysis of different abnormal types of operation feedback.
According to the invention, the operation state coefficients are obtained by carrying out association calculation on different local operation monitoring analysis data of the LED lighting lamp in different basic monitoring periods, so that the association and expansion of the monitoring analysis data in different periods are realized, the overall operation state of the LED lighting lamp is analyzed and classified according to the operation state coefficients, the overall effect of the current operation of the LED lighting lamp can be intuitively and efficiently obtained, and the updating maintenance and iterative upgrading of the LED lighting lamp can be dynamically adjusted according to the overall operation state of the LED lighting lamp, so that the subsequent production and operation influence of different abnormal types on the LED lighting lamp can be timely and efficiently reduced, the expansion and extension of the operation monitoring analysis of the LED lighting lamp are realized, and the diversity and the expansion of the operation monitoring analysis of the LED lighting lamp are improved.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a block diagram of a system for managing operation monitoring data of an LED lighting fixture according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in fig. 1, the invention relates to an operation monitoring data management system of an LED lighting lamp, comprising an operation anomaly monitoring and counting module, an operation anomaly monitoring and analyzing module and a lamp operation supervision platform;
the operation anomaly monitoring and counting module is used for carrying out monitoring and counting on the abnormal operation of the LED lighting lamp and preprocessing implementation data to obtain abnormal operation statistical data; comprising the following steps:
in the basic monitoring period, the unit of the basic monitoring period is month, specifically can be three months, local data monitoring and analysis are implemented on the operation aspect of the LED lighting lamp through the setting of the basic monitoring period, abnormal operation of the LED lighting lamp with networking function is counted through an online feedback channel and an offline after-sales channel, lamp models and abnormal types corresponding to the LED lighting lamp with abnormal feedback are obtained, and effectiveness screening is implemented on the feedback of the LED lighting lamp according to the abnormal types;
it should be noted that, the LED lighting fixture in the embodiment of the present invention may implement intelligent control through networking, where the intelligent control includes but is not limited to voice control and software remote control; the on-line feedback channel can be APP for implementing remote control of the LED lighting lamp, or a public number and forum of a manufacturer corresponding to the LED lighting lamp; the off-line after-sales channel can be an after-sales service store corresponding to the LED lighting lamp;
furthermore, exception types include, but are not limited to, software exception types, hardware exception types, and network exception types; the feedback personnel automatically select and confirm the after-sales personnel;
matching the exception types with all sample exception types prestored in a database; if the matching is successful, generating a feedback effective label; if the matching is unsuccessful, generating a feedback invalid tag;
the purpose of performing validity screening on feedback of the LED lighting fixtures is to determine whether abnormality of the LED lighting fixtures is a self problem or an external problem, for example, if a sample abnormality type does not include a network abnormality type, determining that abnormality of feedback of the corresponding LED lighting fixtures is valid, and determining that abnormality of feedback of the corresponding LED lighting fixtures is a self problem; otherwise, determining that the abnormality fed back by the corresponding LED lighting lamp is an external network problem;
counting the total feedback times of abnormal operation of the corresponding LED lighting lamp according to the lamp model, and feeding back the total number of effective tags and the total number of invalid tags; calculating the ratio of the total number of feedback invalid tags to the total number of feedback times, setting the ratio as an invalid influence coefficient, generating a first invalid influence signal if the invalid influence coefficient is larger than an invalid influence threshold value, and generating an update prompt of the LED lighting lamp networking operation description to a manufacturer according to the first invalid influence signal; the invalid influence threshold value is determined through historical feedback big data corresponding to the LED lighting fixtures with similar models;
if the invalid influence coefficient is not greater than the invalid influence threshold, generating a second invalid influence signal, and maintaining the prompt of the networking operation description of the existing LED lighting lamp according to the second invalid signal;
according to the embodiment of the invention, the effectiveness screening is carried out on the feedback anomalies of the monitoring statistics of different channels, so that the accuracy of the follow-up anomaly feedback monitoring analysis can be improved, and meanwhile, the effect of the corresponding networking operation instruction of the LED lighting lamp can be obtained, so that the corresponding networking operation instruction of the LED lighting lamp can be updated and perfected in time.
Counting the total number of type feedback corresponding to different abnormal types of the feedback of the same lamp model;
performing digital processing on the exception types, setting different exception types to correspond to different exception type weights, and performing traversal matching on the obtained exception types and all the exception types prestored in the database to obtain corresponding exception type weights;
the anomaly type weight is used for digitally representing different anomaly types so as to realize the subsequent differential calculation and analysis of different anomaly types, and the specific value of the anomaly type weight can be determined according to the after-sale overhaul price corresponding to the anomaly type;
the LED illumination lamp is corresponding to all lamp models and abnormal types of abnormal feedback, and the corresponding total feedback times and the total feedback times of a plurality of types form abnormal operation statistical data;
in the embodiment of the invention, the accuracy of the subsequent data calculation and analysis can be effectively improved by carrying out monitoring statistics and preprocessing on feedback anomalies of different channels.
The operation anomaly monitoring and analyzing module is used for carrying out anomaly influence analysis on monitoring statistics and preprocessed anomaly operation statistics data to obtain anomaly monitoring and analyzing data; comprising the following steps:
when type influence analysis is sequentially implemented on the abnormal types corresponding to all the abnormal types of the same lamp model, type influence coefficients Ly corresponding to different abnormal types fed back by the LED lighting lamp are sequentially calculated and obtained through a formula Ly=YQ×LS/XZ; wherein YQ is an abnormal type weight corresponding to an abnormal type, LS is the total feedback times of the type corresponding to feedback of the abnormal type, and XZ is the total sales number of the LED lighting lamp in a basic monitoring period; the type influence coefficient is a numerical value used for simultaneously calculating all feedback data of the same feedback abnormal type of the LED lighting lamp to evaluate feedback influence of the abnormal type corresponding to feedback;
sequentially arranging a plurality of abnormal types fed back in descending order according to the numerical value of the type influence coefficient, and sequentially comparing and judging the type influence coefficient of the plurality of abnormal types in order with the corresponding type influence threshold; the type influence threshold is determined by historical feedback big data of other similar types of LED lighting fixtures;
marking the abnormal type corresponding to the type influence coefficient larger than the type influence threshold as a high-influence abnormal type and generating a high-influence feedback label, and marking the abnormal type corresponding to the type influence coefficient not larger than the type influence threshold as a low-influence abnormal type and generating a low-influence feedback label;
and the high-influence feedback labels or the low-influence feedback labels corresponding to all the abnormal types form abnormal monitoring analysis data and are uploaded to the lamp operation supervision platform.
According to the embodiment of the invention, by calculating and analyzing the influence of the abnormal types of different feedback, the local influence analysis of the abnormal feedback in different aspects can be realized, and reliable local influence analysis data support can be provided for the integral influence analysis and dynamic management of the subsequent LED lighting lamp, so that the integral effect of the monitoring analysis of the different abnormal types of the operation feedback is improved.
Example 2
On the basis of the embodiment 1, the method further comprises the following steps:
the operation anomaly monitoring management module is used for carrying out stability evaluation on the overall operation states of the LED lighting fixtures in different basic monitoring periods according to all anomaly monitoring analysis data, and carrying out dynamic management on updating maintenance and iterative upgrading of the LED lighting fixtures in the later period according to the evaluation result; comprising the following steps:
traversing the abnormal monitoring analysis data, and acquiring the sales total XS and the sales total XE of the LED lighting lamp after being put into the market according to the high-influence feedback tags acquired through traversing, wherein the units of the sales total are ten thousands, the units of the sales total are ten thousands yuan, and the type influence coefficients Ly corresponding to all the high-influence feedback tags appearing in all the basic monitoring periods after the LED lighting lamp is put into the market; extracting the value of the type influence coefficient corresponding to the sales total number, sales total amount and all high influence feedback labels and passing through a formulaCalculating and obtaining an operation state coefficient Yz corresponding to the LED lighting lamp; wherein, alpha and beta are constant coefficients larger than zero, and alpha+beta=0.1, and the constant coefficients in the formula can be set by a person skilled in the art according to actual conditions or obtained through a large number of data simulation of the same type; n is the total number of all high-impact feedback tags; the running state coefficient is a numerical value for evaluating the overall running state of the LED lighting lamp by performing simultaneous calculation on sales aspect data and feedback aspect data after the LED lighting lamp is put into the market;
when the overall operation state of the LED illumination lamp after being put into the market is analyzed and evaluated according to the operation state coefficient, the operation state coefficient is compared with the operation state range corresponding to the LED illumination lamp; the operation state range is determined by historical operation big data of other similar LED lighting fixtures;
if the running state coefficient is smaller than the minimum value of the running state range, generating a first state signal;
if the running state coefficient is not smaller than the minimum value of the running state range and not larger than the maximum value of the running state range, generating a second state signal;
if the running state coefficient is greater than the maximum value of the running state range, generating a third state signal;
the running state coefficient and the corresponding first state signal, second state signal or third state signal form an evaluation result;
when the later updating maintenance and iterative upgrading of the LED lighting lamp are dynamically managed according to the evaluation result, traversing the evaluation result, and respectively implementing the existing updating maintenance scheme, increasing the updating maintenance frequency or advancing the time of iterative upgrading for the LED lighting lamp according to the first state signal, the second state signal or the third state signal obtained by traversing.
In the embodiment of the invention, the operation state coefficient is obtained by carrying out association calculation on different local operation monitoring analysis data of the LED lighting lamp in different basic monitoring periods, the association and expansion of the monitoring analysis data in different periods are realized, the overall operation state of the LED lighting lamp is analyzed and classified according to the operation state coefficient, the overall effect of the current operation of the LED lighting lamp can be intuitively and efficiently obtained, and the updating maintenance and the iterative upgrading of the LED lighting lamp can be dynamically regulated according to the overall operation state of the LED lighting lamp, so that the subsequent production and operation influence of different abnormal types on the LED lighting lamp can be timely and efficiently reduced, the expansion and extension of the operation monitoring analysis of the LED lighting lamp are realized, and the diversity and the expansibility of the operation monitoring analysis of the LED lighting lamp are improved.
In addition, the formulas related in the above are all formulas for removing dimensions and taking numerical calculation, and are one formula which is obtained by acquiring a large amount of data and performing software simulation through simulation software and is closest to the actual situation.
In the several embodiments provided by the present invention, it should be understood that the disclosed system may be implemented in other ways. For example, the above-described embodiments of the invention are merely illustrative, and for example, the division of modules is merely a logical function division, and other manners of division may be implemented in practice.
The modules illustrated as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module. The integrated modules may be implemented in hardware or in hardware plus software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the essential characteristics thereof.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (8)
1. The LED lighting lamp operation monitoring data management system is characterized by comprising an operation anomaly monitoring statistics module, a control module and a control module, wherein the operation anomaly monitoring statistics module is used for implementing monitoring statistics and preprocessing implementation data on the abnormal operation of an LED lighting lamp to obtain abnormal operation statistics data;
the operation anomaly monitoring and analyzing module is used for carrying out anomaly influence analysis on monitoring statistics and preprocessed anomaly operation statistics data to obtain anomaly monitoring and analyzing data; comprising the following steps:
when type influence analysis is sequentially implemented on the abnormal types corresponding to all the abnormal types of the same lamp model, type influence coefficients Ly corresponding to different abnormal types fed back by the LED lighting lamp are sequentially calculated and obtained through a formula Ly=YQ×LS/XZ; wherein YQ is an abnormal type weight corresponding to an abnormal type, LS is the total feedback times of the type corresponding to feedback of the abnormal type, and XZ is the total sales number of the LED lighting lamp in a basic monitoring period;
sequentially arranging a plurality of abnormal types fed back in descending order according to the numerical value of the type influence coefficient, and sequentially comparing and judging the type influence coefficient of the plurality of abnormal types in order with the corresponding type influence threshold;
marking the abnormal type corresponding to the type influence coefficient larger than the type influence threshold as a high-influence abnormal type and generating a high-influence feedback label, and marking the abnormal type corresponding to the type influence coefficient not larger than the type influence threshold as a low-influence abnormal type and generating a low-influence feedback label;
the high-influence feedback labels or the low-influence feedback labels corresponding to all the abnormal types form abnormal monitoring analysis data and are uploaded to a lamp operation supervision platform;
the operation anomaly monitoring management module is used for carrying out stability evaluation on the overall operation states of the LED lighting fixtures in different basic monitoring periods according to all anomaly monitoring analysis data, and carrying out dynamic management on updating maintenance and iterative upgrading of the LED lighting fixtures in the later period according to evaluation results.
2. The LED lighting fixture operational monitoring data management system of claim 1 wherein the operational anomaly monitoring statistics module comprises:
in a basic monitoring period, counting abnormal operation of the LED lighting lamp with a networking function through an online feedback channel and an offline after-sale channel, obtaining a lamp model and an abnormal type corresponding to the LED lighting lamp which is fed back abnormally, and carrying out effectiveness screening on feedback of the LED lighting lamp according to the abnormal type;
matching the exception types with all sample exception types prestored in a database; if the matching is successful, generating a feedback effective label; if the matching is unsuccessful, generating a feedback invalid tag.
3. The system for managing operation monitoring data of an LED lighting fixture according to claim 2, wherein the total number of feedback effective tags and the total number of feedback ineffective tags corresponding to abnormal operation of the LED lighting fixture are counted according to the fixture model; calculating the ratio of the total number of feedback invalid tags to the total number of feedback times, setting the ratio as an invalid influence coefficient, generating a first invalid influence signal if the invalid influence coefficient is larger than an invalid influence threshold value, and generating an update prompt of the LED lighting lamp networking operation description to a manufacturer according to the first invalid influence signal;
and if the invalid influence coefficient is not greater than the invalid influence threshold, generating a second invalid influence signal, and maintaining the prompt of the networking operation description of the existing LED lighting lamp according to the second invalid signal.
4. The system for managing operation monitoring data of an LED lighting fixture according to claim 3, wherein the total number of type feedback corresponding to different anomaly types occurring in feedback of the same fixture model is counted; performing digital processing on the abnormal type to obtain a corresponding weight of the abnormal type;
the LED lighting lamp is corresponding to all lamp models and abnormal types of abnormal feedback, and the corresponding total feedback times and the total feedback times of a plurality of types form abnormal operation statistical data.
5. The LED lighting fixture operational monitoring data management system of claim 1 wherein the operating step of the operational anomaly monitoring management module comprises: traversing the abnormal monitoring analysis data, and acquiring the sales total XS and the sales total XE of the LED lighting lamp after being put into the market according to the high-influence feedback tags acquired through traversing, and the type influence coefficients Ly corresponding to all the high-influence feedback tags in all basic monitoring periods after the LED lighting lamp is put into the market; and extracting the value of the sales total number, the sales total number and the type influence coefficients corresponding to all the high-influence feedback tags, and obtaining the running state coefficient Yz corresponding to the LED lighting lamp through calculation.
6. The system of claim 5, wherein the operational state coefficient Yz is calculated by the formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein, alpha and beta are constant coefficients larger than zero, and alpha+beta=0.1; n is the total number of all high impact feedback tags.
7. The system for managing operation monitoring data of an LED lighting fixture according to claim 5, wherein when the overall operation state of the LED lighting fixture after being put on the market is analyzed and evaluated according to the operation state coefficient, the operation state coefficient is compared with the operation state range corresponding to the LED lighting fixture, so as to obtain an evaluation result composed of the first state signal, the second state signal or the third state signal.
8. The system of claim 7, wherein when dynamically managing the later update maintenance and the iterative upgrade of the LED lighting fixture according to the evaluation result, the evaluation result is traversed, and the existing update maintenance scheme, the increase update maintenance frequency, or the time of the advanced iterative upgrade are respectively implemented for the LED lighting fixture according to the first status signal, the second status signal, or the third status signal obtained by the traversing.
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| CN117291555A (en) * | 2023-11-24 | 2023-12-26 | 南通钜盛数控机床有限公司 | Cooperative control system for manufacturing mechanical parts |
| CN117291555B (en) * | 2023-11-24 | 2024-04-16 | 南通钜盛数控机床有限公司 | Cooperative control system for manufacturing mechanical parts |
| CN118193927A (en) * | 2024-03-27 | 2024-06-14 | 核工业金华勘测设计院有限公司 | Geotechnical engineering geological investigation system and geotechnical engineering geological investigation method |
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