A dry burning risk early warning method based on fouling coefficient inversion

Abstract

The present application relates to the technical field of chiller safety monitoring, and particularly relates to a dry burning risk early warning method based on fouling coefficient inversion. The present application is based on a prediction formula early warning scheme of thermal model normalized fouling inversion: only using the existing electrical quantity of the chiller controller and the existing environment temperature of the main machine, according to the water tank energy balance model, the influence of the environment temperature and the water tank volume on the warming process is attributed to the calculation of the expected warming time, and then the ratio of the measured value and the expected value is used to invert the fouling coefficient and extrapolate the remaining available time, so that the early warning of the dry burning risk is realized without additional sensors. The present application constructs a predictive rather than reactive dry burning early warning mechanism, sets a typical early warning time to avoid the dry burning risk by constructing and extrapolating the remaining available time based on the fouling coefficient trend, and actively arranges cleaning and replacement, thereby effectively preventing the occurrence of dry burning phenomenon.

Description

Technical Field

[0001] This invention relates to the field of chiller safety monitoring technology, specifically to a method for early warning of dry burning risk based on scaling coefficient inversion. Background Technology

[0002] To meet the cooling requirements of different components in equipment with complex operating conditions, such as lasers, the cooling circulation loop of the accompanying chiller typically includes at least one low-temperature cooling loop and multiple ambient-temperature cooling loops. The ambient-temperature cooling loops are mainly generated by electrically heating the cooling water in the low-temperature loops. Due to impurities in the cooling water, scale can form on the electric heating rods in the loops, leading to insufficient local flow. When the flow is blocked or the water is evaporated and dried out, it can easily cause melting, tube rupture, or even fire. To address this issue, current chillers have implemented a reactive shut-off operation after dry burning, primarily relying on additional sensors, such as the nitrogen heating method used in existing patent CN223942844U. The expansion-triggered mechanical disconnection mechanism cuts off the power supply in the early stages of dry burning, achieving purely hardware-based reactive protection, but it lacks the ability to prevent and predict in advance; CN102563884A judges dry burning by the rate of temperature rise, requiring the addition of a sensor to the temperature-sensing blind tube; CN108180595A judges dry burning of the electric heater by collecting the outlet air temperature, requiring the addition of a temperature acquisition unit and a contactor; CN105700451A judges dry burning by detecting the actual time it takes for the heating wire to reach the preset resistance from the initial resistance, requiring a resistance detection circuit. The above solutions are either "reactive" protection (acting only after dry burning has occurred) or require the addition of a dedicated sensor, and none of them can provide predictive warnings before scaling leads to dry burning. Summary of the Invention

[0003] The purpose of this invention is to propose a predictive early warning scheme based on normalized scaling inversion using a thermal model: by utilizing only the existing electrical quantities of the chiller controller and the existing ambient temperature of the host, and according to the water tank energy balance model, the influence of ambient temperature and water tank volume on the heating process is incorporated into the calculation of the expected heating time. Then, the scaling coefficient is inverted by the ratio of the measured value to the expected value, and the remaining available time is extrapolated, thereby achieving early warning of dry burning risk without the need for additional sensors.

[0004] To achieve the above objectives, the present invention adopts the following technical solution.

[0005] A method for early warning of dry-burning risk based on scaling coefficient inversion includes the following steps:

[0006] Step 1: Data Collection

[0007] During the healthy operation of the target chiller, the electric heating is activated to execute multiple complete heating cycles, and the electric heating power of each heating cycle is collected. 1. Room temperature water tank water temperature ;

[0008] Obtain the reference temperature for water tank heat dissipation , This refers to the heat sink temperature corresponding to the heat dissipation from the cooling circuit to the surrounding area;

[0009] The measured water temperature in the room temperature water tank was from the initial temperature. Heat to target temperature Measured heating time ;

[0010] Calculate the thermal inertia of the water tank ,in , This refers to the density of water. This refers to the real-time working volume of the water tank. This refers to the specific heat capacity of water;

[0011] Step 2: Draw a healthy baseline, determine the equivalent heat dissipation coefficient and the water tank thermal inertia reference curve.

[0012] Establish a water tank energy balance model ;

[0013] in This refers to the equivalent heat dissipation coefficient of a chiller;

[0014] make Transform the model into ;

[0015] Separate variables and from Points to The water tank temperature was obtained from Heat up to Expected time calculation model ;

[0016] Based on the measured data from step one, the measured temperature rise time for each cycle under healthy operating conditions is used as an example. The mean values ​​are used to plot the health baseline under various working conditions. ;

[0017] When the system's health status changes, by Inverse calculation of the equivalent heat dissipation coefficient U;

[0018] Step 3: Real-time Operating Condition Analysis

[0019] Based on the equivalent heat dissipation coefficient U calibrated in step two and the thermal inertia of the water tank And real-time collected operating condition parameters, to test the real-time temperature rise time under the current operating conditions. ;

[0020] Based on the health baseline corresponding to the current operating conditions Calculate the scaling coefficient ;

[0021] Based on the scaling coefficient K, early warning conditions are set to issue early warnings of dry burning risk and perform corresponding maintenance actions according to the preset level.

[0022] In a further or preferred embodiment of the aforementioned dry-burning risk early warning method based on scaling coefficient inversion, step three, setting early warning conditions and issuing a dry-burning risk early warning in advance, includes:

[0023] ①According to the most recent Scaling coefficient per heating cycle The rate of decrease, linearly extrapolated, decreases to a preset critical scaling threshold. Estimate the remaining available days based on the time available. ;

[0024] ② When the scaling coefficient And the heating time is relatively long Delay exceeds preset ratio The system will issue an alert and push a maintenance work order in a timely manner.

[0025] ③Based on the remaining available days Warning value for less than preset available days Timely push of maintenance work orders;

[0026] A further or preferred embodiment of the aforementioned dry-burning risk early warning method based on scaling coefficient inversion, , , , .

[0027] In a further or preferred embodiment of the aforementioned dry-burning risk early warning method based on scaling coefficient inversion, step three, which involves executing corresponding maintenance actions according to preset levels, includes establishing a three-level response and baseline maintenance mechanism, specifically referring to:

[0028] ① Warning level: Corresponds to K≤0.85, or relatively long heating time If the delay exceeds 18%, maintenance actions will include logging and issuing a warning pop-up.

[0029] ② Warning level: Corresponds to K≤0.70, or a relatively long heating time. Delay exceeding 43%, or remaining available days For periods of ≤14 days, maintenance actions include automatic load reduction / power limiting, and the delivery of maintenance work orders.

[0030] ③ Protection level: For K≤0.55 or when overheating / dry burning threshold is detected, maintenance actions include controlled shutdown and locking restart permissions.

[0031] A further or preferred embodiment of the aforementioned dry-burning risk warning method based on scaling coefficient inversion is to establish reference curves for different life cycles by repeating steps one and two within different life cycles of the chiller; and to issue warnings based on the chiller system attributes at different life cycles.

[0032] In a further or preferred embodiment of the aforementioned dry-burning risk warning method based on scaling coefficient inversion, in step three, for chillers based on constant power heating, the frequency of over-temperature protection and the degree to which the steady-state target temperature is not reached are used as the basis to convert them into an equivalent extension of heating time, and the scaling coefficient K is obtained by inversion.

[0033] Its beneficial effects are as follows:

[0034] This application constructs a predictive rather than reactive dry-burning early warning mechanism. By constructing and extrapolating the remaining available time based on the scaling coefficient trend, a typical early warning time is set to avoid the risk of dry burning, and cleaning and replacement are proactively arranged, effectively preventing the occurrence of dry burning.

[0035] This application analyzes and tracks the basic electrical control or detection quantities (power, water temperature) and the inherent parameter water tank heat dissipation reference temperature within the existing control system of the chiller. It does not require the addition of new sensors or monitoring mechanisms. Industrial deployment can be achieved by upgrading the firmware within the existing chiller control system.

[0036] This application does not rely on external environment or other mechanisms. The thermal model based on the water tank heat dissipation reference temperature makes the scaling coefficient calculation and analysis unaffected by changes in weather and working conditions, and has good compatibility and universality. Attached Figure Description

[0037] Figure 1 This is a flowchart illustrating the principle of a dry-burning risk early warning method based on scaling coefficient inversion.

[0038] Figure 2 This is a diagram showing the alarm action settings based on the scaling coefficient K;

[0039] Figure 3 This is a normalized illustration of the thermal model (at different ambient temperatures). As Ta changes synchronously, K remains stable.

[0040] Figure 4 This is a flowchart of the early warning and alarm action based on the scaling coefficient K. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0042] This application is used to provide early warning before dry burning occurs (typical lead time is about 14 days, depending on water quality, operating load and control strategy), and does not require additional sensors for scaling, temperature or resistance; it uses existing electrical quantities and the existing ambient temperature of the host to invert the scaling coefficient based on the energy balance model and extrapolate the remaining available time, and normalizes the influence of ambient temperature and volume on the heating process through the model, and intervenes in stages to avoid fire and pipe burst, while taking into account continuous operation.

[0043] The failure mechanism of scale buildup and dry burning in chillers can be analyzed as follows: high water hardness → scale buildup on the heating element surface → decreased heat exchange efficiency → slower heating and increased surface temperature at the same power → localized dry burning → melting and bursting of the tube. If a warning is given before scale buildup leads to dry burning, cleaning and replacement can be arranged to avoid fire and production line interruption.

[0044] This invention is implemented in four phases: targeted testing → baseline drawing → reference data acquisition → comparative analysis. Figure 1 As shown.

[0045] Example 1

[0046] Step 1: Testing (Actual Data Collection)

[0047] To establish the inherent parameter model of the target chiller, the electric heating rod was activated to perform multiple complete heating cycles during the first month of operation (under known cleanliness and normal control) and the subsequent operation period, based on the chiller's own controller. The heating power P and the ambient temperature water tank temperature were collected for each heating cycle from the chiller's independent control system. And obtain the reference temperature for water tank heat dissipation. ;

[0048] Water tank heat dissipation reference temperature It refers to the heat sink temperature corresponding to the heat dissipation of the cooling circuit to the surrounding area, that is, the air temperature surrounding the circuit; it is one of the core parameters of the chiller operation monitoring system, and this parameter is provided by the chiller's own condition monitoring system.

[0049] The measured water temperature in the room temperature water tank was from the initial temperature. Heat to target temperature Measured heating time ;

[0050] pass Calculate the mass of cooling water to obtain the thermal inertia of the water tank. ;

[0051] This refers to the working volume. For closed water tanks, the volume is considered constant. For open water tanks, the real-time volume is determined by the liquid level monitoring data in the chiller monitoring system. This refers to the specific heat capacity of water;

[0052] Step 2: Draw a health baseline

[0053] Determine the equivalent heat dissipation coefficient and the reference curve of the water tank's thermal inertia.

[0054] An energy balance model for the water tank is established based on the heat circulation process within the water tank. ;

[0055] in It refers to the equivalent heat dissipation coefficient of a chiller, which is one of the basic parameters of a chiller. For the same model of chiller, its equivalent heat dissipation coefficient U under the initial healthy state has been calibrated and determined at the factory or under healthy operating conditions, and is a constant of the initial healthy baseline.

[0056] make Transform the model into ;

[0057] Separate variables and from Points to The water tank temperature was obtained from Heat up to Expected time calculation model ;

[0058] The aforementioned expected time incorporates both the water tank's heat dissipation reference temperature and volumetric thermal inertia, ensuring that it changes synchronously with variations in ambient temperature and volume.

[0059] Based on the measured data from step one, the measured temperature rise time for each cycle under healthy operating conditions is used as an example. The mean values ​​are used to plot the health baseline under various working conditions. ;

[0060] In subsequent execution, reference curves for different lifecycle stages of the chiller are established by repeating steps one and two; early warnings are issued based on the chiller system attributes at different lifecycle stages, and... The equivalent heat dissipation coefficient U is calculated and calibrated in reverse to achieve real-time updates of the health baseline at different life cycles;

[0061] Step 3: Real-time Operating Condition Analysis

[0062] Based on the equivalent heat dissipation coefficient U calibrated in step two and the thermal inertia of the water tank And real-time collected operating condition parameters, to test the real-time temperature rise time under the current operating conditions. ;

[0063] Based on the health baseline corresponding to the current operating conditions Calculate the scaling coefficient ;

[0064] To analyze the scaling condition of the heater, the scaling coefficient is used. Under healthy conditions, with the heater clean and properly controlled, the actual heating time is... ≈ At this point, K≈1.0; when scaling on the heater reduces its effective heat transfer capacity, the actual heating time... As K increases, K decreases. This coefficient is derived from the deviation of the chiller's inherent detection parameter, heating time, from the physical model, without relying on additional scaling or temperature monitoring devices.

[0065] Then, warning conditions can be set according to the scaling coefficient K to issue a dry burning risk warning in advance, and corresponding maintenance actions can be performed according to the preset level.

[0066] Example 2

[0067] This second embodiment involves setting early warning conditions based on the scaling coefficient K, issuing an early warning of dry-burning risk, and performing corresponding maintenance actions according to the preset level. The core process is as follows: Figure 4 As shown, its parameter curve is as follows Figure 2 As shown, the general early warning and maintenance mechanism for chillers designed based on the technical solution of this application includes:

[0068] ①According to the most recent Scaling coefficient per heating cycle The rate of decrease, linearly extrapolated, decreases to a preset critical scaling threshold. Estimate the remaining available days based on the time available. ;

[0069] ② When the scaling coefficient And the heating time is relatively long Delay exceeds preset ratio The system will issue an alert and push a maintenance work order in a timely manner.

[0070] ③Based on the remaining available days Warning value for less than preset available days Timely push of maintenance work orders;

[0071] To ensure data validity and maintain effective cooling water functionality while reducing the risk of scaling, the data collection cycle for general cold reagent equipment should be [not specified]. Critical scaling threshold Delay ratio Number of days of advance warning .

[0072] Example 3

[0073] This embodiment builds upon embodiments one and two by further establishing a three-level response and baseline maintenance mechanism, specifically referring to:

[0074] ① Prompt level: Corresponding Or the heating time is relatively long If the delay exceeds 18%, maintenance actions will include logging and issuing a warning pop-up.

[0075] ② Warning level: corresponding to Or the heating time is relatively long Delay exceeding 43%, or remaining available days The maintenance actions include automatic load reduction / power limiting and pushing maintenance work orders.

[0076] ③ Protection level: corresponding to If overheating / dry burning threshold is detected, maintenance actions include controlled shutdown and locking restart permissions.

[0077] This invention is applicable to chiller systems with various heating control modes:

[0078] (a) For control systems where the surface temperature of the traditional heating element is limited.

[0079] Scale buildup in heaters is manifested as an increase in heating time / duty cycle, which is directly reflected by K, as shown in Table 1.

[0080] Table 1 Variable Power Heating Control

[0081]

[0082] The table analysis shows that the initial warming time is about 18% longer in winter when the ambient temperature is lower than in summer, but due to the longer warming time... As Ta increases synchronously, the scaling coefficient K remains consistent under different ambient temperatures, achieving output consistency and stability under different working conditions and environments, and effectively simplifying the logical approach of system analysis and processing.

[0083] (b) For constant power unrestricted control systems

[0084] For constant power unrestricted control, scaling will also reduce the effective heat exchange between the heating rod and the water, causing the rod to overheat, the frequency of overheat protection actions to increase, and the steady-state target temperature to be not reached. Since the intervention of the protection action will flatten the acceleration curve, the frequency of overheat protection and the degree to which the steady-state target temperature is not reached are used as the main criteria, and converted into an equivalent heating time extension to obtain the same scaling coefficient. Based on the scaling coefficient, the chiller dry burning warning and early maintenance are completed, as shown in Table 3.

[0085] Table 2 Constant Power Heating Control

[0086]

[0087] In Table 2, the scaling conditions in the first two operating conditions are the same, only the ambient temperature is different, and the scaling coefficient K varies. To synchronize with and remain consistent with it, such as Figure 1 As shown;

[0088] (c) For variable volume chiller systems, as shown in Table 3

[0089] Table 3 Normalized Changes in Working Volume

[0090]

[0091] The scaling conditions are the same in the first three operating conditions, only the working volume V (i.e., thermal inertia) is the same. The scaling coefficient K varies depending on the specific characteristics of the scale. Follow The volume expands and contracts synchronously with the changes, while K remains constant; the same applies to scenarios involving water replenishment / liquid level changes.

[0092] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A method for early warning of dry-burning risk based on scaling coefficient inversion, characterized in that, Includes the following steps: Step 1: Data Collection During the healthy operation of the target chiller, the electric heating is activated to execute multiple complete heating cycles, and the electric heating power of each heating cycle is collected.

1. Room temperature water tank water temperature ; Obtain the reference temperature for water tank heat dissipation , This refers to the heat sink temperature corresponding to the heat dissipation from the cooling circuit to the surrounding area; The measured water temperature in the room temperature water tank was from the initial temperature. Heat to target temperature Measured heating time ; Calculate the thermal inertia of the water tank ,in , This refers to the density of water. This refers to the real-time working volume of the water tank. This refers to the specific heat capacity of water; Step 2: Draw a healthy baseline and determine the equivalent heat dissipation coefficient and the reference curve for the thermal inertia of the water tank; Establish a water tank energy balance model ; in This refers to the equivalent heat dissipation coefficient of a chiller; make Transform the model into ; Separate variables and from Points to The water tank temperature was obtained from Heat up to Expected time calculation model ; Based on the measured data from step one, the measured temperature rise time for each cycle under healthy operating conditions is used as an example. The mean values ​​are used to plot the health baseline under various working conditions. ; When the system's health status changes, by Inverse calculation of the equivalent heat dissipation coefficient U; Step 3: Real-time Operating Condition Analysis Based on the equivalent heat dissipation coefficient U calibrated in step two and the thermal inertia of the water tank And real-time collected operating condition parameters, to test the real-time temperature rise time under the current operating conditions. ; Based on the health baseline corresponding to the current operating conditions Calculate the scaling coefficient ; Based on the scaling coefficient K, early warning conditions are set to issue early warnings of dry burning risk and perform corresponding maintenance actions according to the preset level.

2. The method for early warning of dry burning risk based on scaling coefficient inversion according to claim 1, characterized in that, In step three, setting early warning conditions and issuing a warning of dry burning risk in advance includes: ①According to the most recent Scaling coefficient per heating cycle The rate of decrease, linearly extrapolated, decreases to a preset critical scaling threshold. Estimate the remaining available days based on the time available. ; ② When the scaling coefficient And the heating time is relatively long Delay exceeds preset ratio The system will issue an alert and push a maintenance work order in a timely manner. ③Based on the remaining available days Warning value for less than preset available days Maintenance work orders should be pushed out in advance.

3. The method for early warning of dry burning risk based on scaling coefficient inversion according to claim 2, characterized in that, ， ， ， 。 4. The method for early warning of dry burning risk based on scaling coefficient inversion according to claim 3, characterized in that, In step three, the execution of corresponding maintenance actions according to preset levels includes establishing a three-level response and baseline maintenance mechanism, specifically referring to: ① Prompt level: Corresponding Or the heating time is relatively long If the delay exceeds 18%, maintenance actions will include logging and issuing a warning pop-up. ② Warning level: corresponding to Or the heating time is relatively long Delay exceeding 43%, or remaining available days The maintenance actions include automatic load reduction / power limiting and pushing maintenance work orders. ③ Protection level: corresponding to If overheating / dry burning threshold is detected, maintenance actions include controlled shutdown and locking restart permissions.

5. The method for early warning of dry burning risk based on scaling coefficient inversion according to claim 1, characterized in that, By repeating steps one and two throughout the different lifecycles of the chiller, reference curves for different lifecycles are established; early warnings are issued based on the chiller system attributes at different lifecycle stages.

6. The method for early warning of dry burning risk based on scaling coefficient inversion according to claim 1, characterized in that, In step three, for chillers based on constant power heating, the frequency of over-temperature protection and the degree to which the steady-state target temperature cannot be reached are used as the basis to convert them into an equivalent extension of heating time, and the scaling coefficient K is obtained by inversion.

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