Method for automatically collecting and judging equipment abnormity based on state of alarm lamp of information equipment

Abstract

The invention discloses a method for judging equipment abnormity based on information equipment alarm lamp state automatic collection, and belongs to the field of equipment inspection. A camera is installed in the rack, and image information of equipment operation is collected when the machine operates; positioning the position of an alarm lamp in the image; performing color identification on the detected light area; and carrying out information equipment abnormity judgment according to different light types. According to the invention, a new automatic inspection method is provided for operation and maintenance personnel, the equipment in the machine room can be effectively monitored on a remote maintenance desktop, and the operation and maintenance cost of the system is greatly saved. Technically, the method is suitable for most of information equipment, the feasibility of batch deployment in an informatization machine room is high, and an existing machine room structure is not affected; the method has the characteristics of low economic investment, mature technology and the like, and has wide market popularization value.

Description

Technical Field

[0001] This invention relates to the field of equipment inspection technology, and in particular to a method for automatically collecting and determining equipment malfunctions based on the status of alarm lights on information equipment. Background Technology

[0002] Data center operation and maintenance is a core component of ensuring the stable operation of enterprise information systems, and its importance is self-evident. An efficient and standardized data center operation and maintenance system can ensure that critical infrastructure such as servers, network equipment, and storage systems are always under control, promptly detect and eliminate potential faults, and minimize the risk of system downtime and business interruption.

[0003] Traditional inspection methods rely heavily on engineers remotely logging into the system to check the status of information equipment, or on connection loss alarms after equipment failure to detect faults. This approach is not only inefficient, but also suffers from delays in fault detection. Summary of the Invention

[0004] The purpose of this invention is to provide a method for automatically collecting and determining equipment malfunctions based on the status of alarm lights in information devices, in order to solve the problems in the background art.

[0005] To address the aforementioned technical problems, this invention provides a method for automatically collecting and determining device malfunctions based on the status of alarm lights on information devices, comprising:

[0006] Step 1: Install a camera inside the rack to capture image information of the equipment during operation;

[0007] Step 2: Locate the warning light in the image;

[0008] Step 3: Perform color recognition on the detected light area;

[0009] Step 4: Determine the anomaly of the information equipment based on different lighting types.

[0010] In one embodiment, step 2 includes: processing the acquired image information by using Gaussian filtering, median filtering, and weighted averaging of the image with weights that simulate a normal distribution to reduce noise;

[0011] The alarm lights on information equipment are round or square, and have multiple light sources at the same time;

[0012] The positions of the light sources within the rack are fixed, and the region of interest for each alarm light is defined, either manually or through a configuration file.

[0013] The type of information technology equipment is determined by comparing and associating regional information with information about the equipment within the rack.

[0014] In one implementation, step 3 includes: using HSV values ​​to determine color, where the alarm light colors include red, green, and yellow; collecting and recording the current color state; and comparing it with the previous state, recording any changes.

[0015] HSV is a color model consisting of three parameters: hue, saturation, and value.

[0016] In one implementation, step 4 includes: transmitting the recorded light color information to the background system, collecting information, forming an information device alarm light status database, judging the status of the information device, and realizing abnormal alarms, thus completing an automatic inspection task.

[0017] This invention provides a method for automatically collecting and determining equipment anomalies based on the status of alarm lights on information devices. This offers maintenance personnel a new method for automated inspection, enabling effective monitoring of data center equipment from a remote maintenance desktop, significantly reducing system maintenance costs. Technically, it is applicable to the vast majority of information devices, has strong feasibility for batch deployment in information-based data centers, and does not affect the existing data center structure. It also features low economic investment, mature technology, and broad market potential. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of a method for automatically collecting and determining equipment malfunctions based on the status of alarm lights in information devices, provided by the present invention. Detailed Implementation

[0019] The following detailed description, in conjunction with the accompanying drawings and specific embodiments, provides a method for automatically collecting and determining device anomalies based on the status of alarm lights in information devices, as proposed in this invention. The advantages and features of this invention will become clearer from the following description. It should be noted that the accompanying drawings are all in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of this invention.

[0020] This invention provides a method for automatically collecting and determining equipment malfunctions based on the status of alarm lights in information devices, comprising the following steps:

[0021] Step 1: Install an industrial-grade camera with fixed focal length inside the rack to capture image information of the equipment during operation.

[0022] Step 2: Locate the position of the alarm light in the image. Generally, the position of the alarm light in a rack is relatively fixed and can be determined by detecting bright spots or fixed positions.

[0023] Step 3: Perform color recognition on the detected light area;

[0024] Step 4: Determine the anomaly of the information equipment based on different lighting types.

[0025] Step 1 specifically includes the following implementation methods:

[0026] This invention uses an industrial camera installed within a rack to capture server lighting images. Specifically designed for industrial environments, this camera offers significant advantages over consumer cameras in terms of stability, image quality, environmental adaptability, and functionality. It also exhibits excellent light adaptability and a wide spectral response range, making it suitable for 24 / 7 continuous operation.

[0027] Step 2 specifically includes the following implementation methods:

[0028] The acquired image information is processed using Gaussian filtering and median filtering to reduce noise. Alarm lights on information equipment are typically circular or square, and often have multiple light sources. The positions of the light sources within the rack are relatively fixed. The Region of Interest (ROI) of the alarm lights to be monitored is defined, which can be done manually or using configuration files. The location information of the alarm lights is compared and correlated with the information about the equipment within the rack to determine the information equipment information. For example, the lighting status of the information equipment at rack position 12U (a common rack-mounted location calibration method) can be manually calibrated, and the information recorded in the background can be associated with the alarm light status of a company's OA server at this location. This method is also applicable to network device alarm lights, storage array alarm lights, hard drive alarm lights, external device alarm lights, and other information equipment.

[0029] Step 3 specifically includes the following implementation methods:

[0030] The color is determined using HSV values ​​(a color model composed of three parameters: hue, saturation, and value). Common colors for alarm lights include red, green, and yellow. For example, color can be determined using hue values. Data is collected every minute, recording the current color state and comparing it with the previous reading. Any changes are recorded or trigger an alarm.

[0031] Step 4 specifically includes the following implementation methods:

[0032] The recorded light colors are transmitted to the backend system for information collection, forming a database of alarm light statuses for information devices. This allows the system to assess the status of the devices and issue alarms for any anomalies. This completes one automated inspection task.

[0033] This invention uses the color of alarm lights on information devices to quickly locate the status of information devices and promptly detect faults.

[0034] like Figure 1 As shown, firstly, industrial cameras are deployed within the rack to acquire images, averaging once per minute, generating image information with the colors of the information equipment's lights. Then, using methods such as Gaussian filtering and median filtering, a weighted average is applied to simulate a normal distribution, effectively suppressing noise while preserving the image's structural information. Next, the information equipment type and light status are associated through the location of the alarm lights. Then, the HSV color space method is used to determine the status of the information equipment's alarm lights, collecting the corresponding light color information of the information equipment. Finally, this information is matched with the device alarm light status information recorded in the background to determine the device's status.

[0035] This invention relates to a method for automatically collecting and determining equipment anomalies based on the status of alarm lights in information equipment. The method uses an industrial camera to collect the status of alarm lights during equipment operation. It is applicable to the vast majority of information equipment, enabling timely detection of potential equipment problems and ensuring that critical infrastructure such as servers, network devices, and storage systems are always under control. This invention employs methods such as Gaussian filtering and HSV color space to collect the status of information equipment lights, and combines this with ROI calibration to establish a database of alarm light statuses for the corresponding information equipment, thereby completing the status detection of the information equipment.

[0036] The above is a detailed description of the method for automatically collecting and determining equipment anomalies based on the status of alarm lights on information devices. The above description is merely a typical example to clearly illustrate the present invention and is not intended to limit the implementation of the invention. Any modifications or equivalent substitutions made by those skilled in the art to the technical solutions of the present invention, and any obvious changes or variations derived from the technical solutions of the present invention, are still within the protection scope of the present invention.

Claims

1. A method for automatically collecting and determining an abnormality of an information device based on a state of an alarm lamp of the information device, characterized by, The method comprises the following steps: Step 1: install a camera in the rack, and collect image information of the running equipment when the information equipment is running; Step 2: locate the position of the alarm light in the image; Step 3: color recognition is performed on the detected light area; Step 4: information equipment abnormality judgment is performed according to different light types.

2. The method of automatically collecting and determining an abnormality of an information device based on a state of a warning light of the information device according to claim 1, wherein The step 2 comprises: processing the collected image information, using Gaussian filtering, median filtering, simulating the weight of normal distribution to perform weighted average on the image, and reducing noise points; The alarm light of the information equipment is circular or square, and there are multiple light sources at the same time; The light source position in the rack is fixed, the region of interest of each alarm light is defined, and manual or configuration file calibration is performed; The information equipment type is determined by comparing and associating the region information and the equipment information in the rack.

3. The method of automatically collecting and determining an abnormality of an information device based on a state of a warning light of the information device according to claim 2, wherein The step 3 comprises: color judgment is performed by using HSV value, the alarm light color includes red, green and yellow, the current color state is collected and recorded, and the change is recorded by comparison with the last time; wherein, HSV is a color model composed of hue H, saturation Saturation and brightness Value.

4. The method of automatically collecting and determining an abnormality of an information device based on a state of a warning light of the information device according to claim 3, wherein The step 4 comprises: the recorded light color condition is transmitted to the background system, information collection is performed, an information equipment alarm light state database is formed, state judgment is performed on the information equipment, abnormal alarm is realized, and thus one automatic inspection task is completed.

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