CO2 Tank Monitor
Monitor CO2 cylinder pressure and predict depletion times to prevent gas outages in cell culture incubators, particularly during weekends when laboratories are unmanned. Provides automated alerts and consumption tracking for proactive cylinder management.
Key Capabilities:
- - Pressure-Based Depletion Prediction: Calculate remaining cylinder life based on current pressure and consumption rates
- Weekend Risk Detection: Identify if depletion will occur during weekends when no staff is available
- Multi-Cylinder Support: Handle different cylinder sizes (10L, 40L) and specifications
- Automated Alert System: Generate status reports with actionable recommendations
- Simulation Mode: Test monitoring scenarios with randomized data for training
When to Use
✅ Use this skill when:
- - Monitoring cell culture CO2 incubators that require continuous gas supply
- Setting up automated daily checks for cylinder status (e.g., via cron jobs)
- Planning cylinder replacement schedules to avoid service interruptions
- Training new lab members on gas monitoring procedures (use simulation mode)
- Managing multiple incubators with different consumption rates
- Pre-holiday assessments to ensure adequate gas supply during lab closures
- Creating standard operating procedures (SOPs) for gas monitoring
❌ Do NOT use when:
- - Monitoring liquid nitrogen tanks for cryogenic storage → Use
freezer-sample-locator or specialized LN2 monitors - Tracking compressed air or N2 cylinders for non-CO2 applications → Adapt parameters but verify compatibility
- Real-time IoT sensor integration is available → Use actual sensor API instead of simulation
- Cylinder uses weight-based measurement instead of pressure → Modify calculation logic accordingly
- Emergency gas leak detection is needed → Use gas detection safety systems with alarms
- Managing bulk tank installations with automatic switchover → These systems have built-in monitoring
Related Skills:
- - 上游 (Upstream):
equipment-maintenance-log, INLINECODE2 - 下游 (Downstream):
eln-template-creator, INLINECODE4
Integration with Other Skills
Upstream Skills:
- -
equipment-maintenance-log: Track CO2 incubator maintenance history that affects consumption rates - INLINECODE6 : Monitor cylinder inventory and replacement schedules
- INLINECODE7 : Record calibration dates for pressure gauges
Downstream Skills:
- -
eln-template-creator: Generate experiment templates that include gas monitoring checklists - INLINECODE9 : Forecast CO2 gas costs based on consumption trends
- INLINECODE10 : Coordinate empty cylinder disposal with replacement
Complete Workflow:
Daily Morning Check → co2-tank-monitor → equipment-maintenance-log → lab-inventory-tracker → Replacement Scheduling
Core Capabilities
1. Pressure-Based Depletion Prediction
Calculate remaining cylinder lifetime based on current pressure readings and historical consumption patterns.
CODEBLOCK1
Parameters:
| Parameter | Type | Required | Description | Default |
|---|
| INLINECODE11 | float | Yes | Current cylinder pressure in MPa | 8.0 |
| INLINECODE12 |
float | Yes | Average daily consumption rate (MPa/day) | 1.5 |
|
capacity | int | No | Cylinder capacity in liters (10 or 40) | 40 |
Calculation Method:
CODEBLOCK2
Best Practices:
- - ✅ Calibrate consumption rate based on historical data (monitor for 1-2 weeks)
- ✅ Account for usage variations - higher on heavy culture days, lower on weekends
- ✅ Check pressure at consistent time (e.g., 9 AM daily) for accurate trends
- ✅ Update consumption rate seasonally - incubator usage may vary
Common Issues and Solutions:
Issue: Inaccurate consumption estimates
- - Symptom: Predicted depletion date consistently off by several days
- Solution: Monitor actual consumption over 2-4 weeks; adjust daily_consumption parameter
Issue: Pressure fluctuations causing false alerts
- - Symptom: Inconsistent pressure readings due to temperature changes
- Solution: Take readings at same time daily; allow cylinder to equilibrate after use
2. Weekend Depletion Risk Detection
Identify if cylinder depletion will occur during weekends when laboratory staff is unavailable.
CODEBLOCK3
Weekend Risk Scenarios:
| Scenario | Risk Level | Action Required |
|---|
| Depletion on Saturday/Sunday | 🔴 High | Immediate replacement or weekend duty |
| Depletion Monday morning |
🟡 Medium | Replace Friday afternoon |
| Depletion Friday evening | 🟡 Medium | Monitor closely; replace if possible |
| Depletion mid-week | 🟢 Low | Schedule routine replacement |
Best Practices:
- - ✅ Set alertdays = 2 for standard work weeks (alert by Wednesday for Friday replacement)
- ✅ Plan Friday replacements for any cylinder with <4 days remaining
- ✅ Create weekend duty roster for critical experiments during high-risk periods
- ✅ Consider holiday schedules - extend alertdays before long weekends
Common Issues and Solutions:
Issue: False weekend alerts for Monday depletion
- - Symptom: Alerts triggered for Monday morning depletion when lab reopens
- Solution: Adjust logic or manually review; Monday AM depletion may be acceptable
Issue: Missing Friday evening depletion risk
- - Symptom: Cylinder runs out Friday night after staff leaves
- Solution: Check Friday 5 PM status specifically; consider Friday evening as weekend
3. Multi-Cylinder Size Support
Support different CO2 cylinder specifications commonly used in laboratory settings.
CODEBLOCK4
Cylinder Specifications:
| Capacity | Typical Use | Full Pressure | Duration (@1.5 MPa/day) |
|---|
| 10L | Small incubators, backup | ~15 MPa | ~10 days |
| 40L |
Main incubators, heavy use | ~15 MPa | ~40 days |
Best Practices:
- - ✅ Use 40L cylinders for main incubators to reduce replacement frequency
- ✅ Keep 10L cylinders as emergency backup for critical experiments
- ✅ Record cylinder capacity in monitoring logs for accurate predictions
- ✅ Standardize on one size per facility when possible for simplified inventory
Common Issues and Solutions:
Issue: Wrong capacity setting causing prediction errors
- - Symptom: Predictions consistently off by 4x (10L vs 40L confusion)
- Solution: Verify cylinder label; update capacity parameter in monitoring script
Issue: Mixing cylinder sizes in same calculation
- - Symptom: Different incubators on different cylinder sizes
- Solution: Run separate monitoring instances for each cylinder/incubator pair
4. Automated Alert System with Status Levels
Generate color-coded status reports with specific recommendations based on urgency.
CODEBLOCK5
Status Levels:
| Code | Icon | Status | Condition | Action |
|---|
| 0 | 🟢 | Normal | Days > alertdays + 2 | No action needed |
| 1 |
🟡 | Caution | Days within alertdays + 2 | Monitor closely |
|
2 | 🔴 | Danger | Days ≤ alert_days or weekend depletion | Replace immediately |
Return Codes for Automation:
| Exit Code | Meaning | Automation Action |
|---|
| 0 | Normal | Continue routine monitoring |
| 1 |
Caution | Send email notification |
|
2 | Danger | Send urgent alert; page on-call staff |
Best Practices:
- - ✅ Integrate with alerting systems using return codes for automated notifications
- ✅ Customize recommendations for your lab's specific procedures
- ✅ Escalate based on status - email for caution, SMS/call for danger
- ✅ Log all status changes for trend analysis and audit trails
Common Issues and Solutions:
Issue: Alert fatigue from frequent caution alerts
- - Symptom: Too many caution-level notifications causing ignored alerts
- Solution: Adjust alert_days threshold; batch daily reports instead of immediate alerts
Issue: Missing critical weekend alerts
- - Symptom: Weekend depletions not detected when they span multiple days
- Solution: Ensure willdepleteon_weekend() logic covers multi-day weekend periods
5. Simulation Mode for Training
Generate randomized cylinder data for training staff without affecting real monitoring systems.
CODEBLOCK6
Training Applications:
| Use Case | Simulation Parameters | Learning Objective |
|---|
| New staff training | Various random scenarios | Recognize different alert levels |
| Weekend risk awareness |
Force weekend depletion scenarios | Understand critical timing |
|
Consumption calculation | Different pressure/consumption combos | Practice manual calculations |
|
Emergency response | Low pressure scenarios (<3 MPa) | Learn urgent procedures |
Best Practices:
- - ✅ Run simulations weekly to keep staff familiar with alert formats
- ✅ Create scenario library with specific training cases (weekend depletion, low pressure, etc.)
- ✅ Include simulation in onboarding for new lab members
- ✅ Test alert pathways using simulation to verify notification systems
Common Issues and Solutions:
Issue: Simulation data too random for consistent training
- - Symptom: Trainees see different scenarios each session
- Solution: Set random seed for reproducible scenarios; create predefined training datasets
Issue: Confusion between simulation and real data
- - Symptom: Staff mistakes simulation for actual cylinder status
- Solution: Clearly label all simulation outputs; use distinct formatting
6. Automated Scheduling Integration
Integrate with cron jobs or task schedulers for automated daily monitoring.
CODEBLOCK7
Integration Patterns:
| Integration Type | Trigger | Action | Return Code Handling |
|---|
| Daily cron | 9:00 AM daily | Check status | Log results; alert if ≠0 |
| Pre-weekend |
Friday 5 PM | Weekend risk check | Force alert if weekend risk |
|
Real-time | Sensor threshold | Immediate check | Page on-call if danger |
|
Manual | Lab staff | Ad-hoc check | Display full report |
Best Practices:
- - ✅ Use --quiet mode for automated runs to reduce log noise
- ✅ Capture return codes for alerting and logging
- ✅ Test cron jobs manually before deploying to production
- ✅ Monitor the monitor - ensure scheduled checks are running
- ✅ Implement heartbeat - alert if monitoring script fails to run
Common Issues and Solutions:
Issue: Cron job not executing
- - Symptom: No monitoring logs or alerts
- Causes: Path issues, permissions, environment variables
- Solution: Use full paths; test manually first; check cron logs
Issue: Sensor data unavailable
- - Symptom: Cannot read pressure from sensor log
- Solution: Implement fallback to manual input; alert on sensor failure
Complete Workflow Example
From daily monitoring to replacement scheduling:
CODEBLOCK8
Python API Usage:
CODEBLOCK9
Expected Output Files:
CODEBLOCK10
Common Patterns
Pattern 1: Daily Morning Monitoring Routine
Scenario: Lab technician checks all CO2 cylinders every morning at 9 AM.
CODEBLOCK11
Workflow:
- 1. Read pressure gauges on all cylinders at 9 AM
- Run monitoring script for each cylinder
- Log status codes and any alerts
- If any cylinder shows status ≥1, notify lab manager
- Schedule replacements for caution-level cylinders
- For danger-level, initiate immediate replacement procedure
Output Example:
CODEBLOCK12
Pattern 2: Pre-Holiday Weekend Assessment
Scenario: Before a 3-day weekend (e.g., Memorial Day), ensure adequate gas supply.
CODEBLOCK13
Workflow:
- 1. On Friday before holiday, run assessment with extended alert_days (4)
- Check all cylinders with weekend risk detection
- For any cylinder with depletion during closure period:
- Prioritize immediate replacement
- Consider emergency weekend delivery
- Transfer critical cultures to backup incubator
- 4. Document gas status in holiday handoff notes
- Set up emergency contact for gas supplier
Output Example:
CODEBLOCK14
Pattern 3: New Lab Member Training
Scenario: Train new technician on CO2 monitoring using simulation mode.
CODEBLOCK15
Workflow:
- 1. Run simulation mode to generate 10 random scenarios
- For each scenario, trainee manually calculates remaining days
- Compare trainee calculation with script output
- Discuss appropriate actions for each status level
- Practice emergency procedures with "danger" scenarios
- Review actual monitoring logs from past month
- Shadow experienced technician for first week
Output Example:
CODEBLOCK16
Pattern 4: Multi-Incubator Facility Management
Scenario: Large facility with 6 incubators on different CO2 cylinders.
CODEBLOCK17
Workflow:
- 1. Create monitoring dashboard tracking all 6 cylinders
- Run monitoring script for each cylinder daily
- Implement staggered replacement schedule to avoid all cylinders needing replacement simultaneously
- Track consumption trends to optimize delivery schedule
- Maintain 1-2 backup cylinders in inventory
- Negotiate bulk pricing with gas supplier based on usage patterns
- Monthly review of consumption trends and cost optimization
Output Example:
Facility CO2 Dashboard - 2026-02-09
====================================
Main Incubators (40L):
Inc-01: 🟢 18.2 days | Last replaced: 2026-01-22
Inc-02: 🟡 4.5 days | REPLACE THIS WEEK
Inc-03: 🟢 22.1 days | Last replaced: 2026-01-15
Inc-04: 🟢 15.8 days | Last replaced: 2026-01-28
Backup Incubators (10L):
Back-01: 🟢 6.2 days
Back-02: 🟢 8.4 days
This Week Actions:
- Replace Inc-02 cylinder by Wednesday
- Order replacement for delivery next week
Monthly Consumption: 42 MPa (28% under budget)
Quality Checklist
Pre-Monitoring Setup:
- - [ ] CRITICAL: Verify pressure gauge is calibrated and functional
- [ ] Confirm cylinder size (10L or 40L) matches monitoring parameters
- [ ] Establish baseline daily consumption rate through 1-2 weeks observation
- [ ] Set appropriate alert_days threshold (typically 2 for standard weeks)
- [ ] Configure automated scheduling (cron) for daily checks
- [ ] Set up alerting pathway (email, SMS) for danger-level status
- [ ] Create emergency contact list for gas supplier
- [ ] Ensure backup cylinder availability for critical incubators
During Daily Monitoring:
- - [ ] Take pressure readings at consistent time (e.g., 9:00 AM)
- [ ] CRITICAL: Record actual pressure value, not estimates
- [ ] Note any unusual consumption patterns (door openings, new cultures)
- [ ] Verify status code and understand implications
- [ ] Check for weekend depletion risk (especially on Thursdays/Fridays)
- [ ] Log all readings for trend analysis
- [ ] Update consumption rate if usage patterns change significantly
- [ ] Inspect cylinder and regulator for leaks or damage
Alert Response:
- - [ ] CRITICAL: Acknowledge danger-level alerts immediately
- [ ] For weekend depletion risk, arrange replacement before Friday 5 PM
- [ ] Notify lab manager of caution-level cylinders needing replacement
- [ ] Document all actions taken in response to alerts
- [ ] Verify replacement cylinder is available before removing empty one
- [ ] After replacement, verify incubator maintains proper CO2 concentration
- [ ] Update monitoring logs with replacement date and new cylinder info
- [ ] Return empty cylinder to storage area for pickup
Post-Replacement Verification:
- - [ ] CRITICAL: Verify new cylinder valve is fully open
- [ ] Check pressure gauge reading on new cylinder (should be ~15 MPa)
- [ ] Monitor incubator CO2 concentration for 30 minutes to verify stability
- [ ] Verify no gas leaks at regulator connections (soap bubble test)
- [ ] Update monitoring parameters with new cylinder start pressure
- [ ] Log replacement in inventory management system
- [ ] Notify relevant lab members of cylinder change
- [ ] Schedule next replacement based on predicted depletion date
Common Pitfalls
Monitoring Setup Issues:
- - ❌ Inconsistent reading times → Daily variations affect trend accuracy
- ✅ Take readings at same time each day (e.g., 9:00 AM ± 30 min)
- - ❌ Wrong consumption estimates → Inaccurate depletion predictions
- ✅ Calculate from actual usage over 2+ weeks; update seasonally
- - ❌ Ignoring temperature effects → Pressure varies with ambient temperature
- ✅ Allow cylinder to equilibrate to room temperature before reading
- - ❌ Not accounting for usage variations → Weekend vs weekday consumption differs
- ✅ Monitor separately for different usage patterns; use average
Alert and Response Issues:
- - ❌ Alert fatigue → Too many notifications cause important alerts to be missed
- ✅ Batch daily reports; only escalate urgent alerts immediately
- - ❌ Missing weekend alerts → Friday check doesn't catch Saturday depletion
- ✅ Always check weekend risk explicitly; use Friday 5 PM check
- - ❌ Delayed replacement → Waiting too long leads to actual depletion
- ✅ Replace when caution status triggered; don't wait for danger
- - ❌ No backup plan → Cylinder fails with no replacement available
- ✅ Maintain 1-2 backup cylinders; know emergency supplier contacts
Calculation and Data Issues:
- - ❌ Wrong cylinder capacity → 10L vs 40L confusion causes 4x error
- ✅ Always verify cylinder label; double-check capacity parameter
- - ❌ Pressure unit confusion → PSI vs MPa or Bar mixing
- ✅ Standardize on MPa; convert if gauge shows different units
- - ❌ Not tracking multiple cylinders → Mixing readings from different tanks
- ✅ Label cylinders clearly; use location-specific monitoring
- - ❌ Ignoring cumulative error → Small daily errors compound over weeks
- ✅ Verify predictions against actual depletion; calibrate regularly
Operational Issues:
- - ❌ Gauges not calibrated → Inaccurate readings lead to wrong predictions
- ✅ Calibrate pressure gauges annually or per manufacturer recommendation
- - ❌ Leaks undetected → Higher consumption than predicted
- ✅ Regular leak checks; sudden consumption increases indicate leaks
- - ❌ Regulator problems → Pressure drops even with adequate gas
- ✅ Replace regulators per schedule; check for ice buildup in flow
- - ❌ No documentation → Cannot track trends or troubleshoot issues
- ✅ Maintain detailed logs; review monthly for optimization
Troubleshooting
Problem: Predicted depletion date consistently wrong
- - Symptoms: Actual depletion 3-5 days earlier or later than predicted
- Causes:
- Incorrect consumption rate estimate
- Changing usage patterns (more/fewer cultures)
- Temperature variations affecting pressure readings
- Leaks in system
- Recalculate consumption rate from recent actual usage
- Monitor for 2+ weeks to establish accurate baseline
- Take readings at consistent temperature conditions
- Check for leaks using soapy water at connections
Problem: Frequent false alerts (alert fatigue)
- - Symptoms: Receiving caution/danger alerts that don't require action
- Causes:
- Alert threshold too sensitive
- Normal fluctuations triggering alerts
- Multiple notifications for same cylinder
- Adjust alert_days parameter (increase from 2 to 3)
- Implement alert aggregation (daily summary vs immediate)
- Use quiet mode for automated checks; manual for full reports
Problem: Weekend depletion not detected
- - Symptoms: Cylinder runs out Saturday/Sunday despite monitoring
- Causes:
- Friday check missed weekend risk
- Depletion spans multiple days
- Holiday weekends not considered
- Add explicit Friday 5 PM check for weekend risk
- Extend alert_days before long weekends
- Use will
depleteon_weekend() logic that checks multi-day periods
Problem: Cannot read pressure gauge accurately
- - Symptoms: Inconsistent or unclear pressure readings
- Causes:
- Gauge needle stuck or damaged
- Condensation or dirt on gauge face
- Parallax error reading needle position
- Replace faulty gauges immediately
- Clean gauge face regularly
- View needle straight-on to avoid parallax
- Consider digital pressure sensors for better accuracy
Problem: Cylinder depletes faster than expected
- - Symptoms: Predicted 10 days, actually depleted in 6 days
- Causes:
- Increased incubator usage (more cultures, frequent door openings)
- Gas leak in system
- Regulator malfunction
- Temperature increase (higher consumption)
- Check for leaks at all connections
- Verify incubator door seals
- Inspect regulator for proper function
- Update consumption rate to reflect actual usage
Problem: Monitoring script not running automatically
- - Symptoms: No daily logs or alerts despite cron setup
- Causes:
- Cron job misconfigured
- Path issues in script
- Permissions problems
- Script errors not logged
- Test cron job manually first
- Use full absolute paths in cron and script
- Check cron logs:
grep CRON /var/log/syslog
- Redirect stderr to log file for debugging
References
Available in references/ directory:
- - (No reference files currently available for this skill)
External Resources:
- - Cell Culture CO2 Guidelines: https://www.thermofisher.com/cellculture
- Gas Cylinder Safety: https://www.osha.gov/gascylinders
- CO2 Incubator Best Practices: https://www.sigmaaldrich.com/incubators
Scripts
Located in scripts/ directory:
- -
main.py - CO2 tank monitoring engine with prediction and alerting logic
Pressure Conversion Reference
| Unit | MPa | PSI | Bar |
|---|
| MPa | 1.0 | 145.0 | 10.0 |
| PSI |
0.0069 | 1.0 | 0.069 |
|
Bar | 0.1 | 14.5 | 1.0 |
Typical Cylinder Pressures:
- - Full cylinder: ~15 MPa (~2200 PSI)
- Working pressure: 8-10 MPa
- Replace threshold: ~3-5 MPa
- Empty: <1 MPa
Last Updated: 2026-02-09
Skill ID: 182
Version: 2.0 (K-Dense Standard)
CO2 储罐监测器
监测CO2钢瓶压力并预测耗尽时间,以防止细胞培养培养箱发生气体中断,特别是在实验室无人值守的周末。提供自动警报和消耗跟踪,实现主动的钢瓶管理。
关键能力:
- - 基于压力的耗尽预测:根据当前压力和消耗率计算钢瓶剩余使用时间
- 周末风险检测:识别耗尽是否会在无工作人员在场的周末发生
- 多钢瓶支持:处理不同规格的钢瓶(10L、40L)
- 自动警报系统:生成带有可操作建议的状态报告
- 模拟模式:使用随机数据进行监测场景测试,用于培训
使用场景
✅ 使用此技能的场景:
- - 监测需要持续供气的细胞培养CO2培养箱
- 设置钢瓶状态的自动每日检查(例如通过cron任务)
- 规划钢瓶更换计划以避免服务中断
- 培训新实验室成员掌握气体监测流程(使用模拟模式)
- 管理具有不同消耗率的多个培养箱
- 节前评估,确保实验室关闭期间有充足的气体供应
- 创建气体监测的标准操作程序(SOP)
❌ 不要使用此技能的场景:
- - 监测用于低温储存的液氮罐 → 使用freezer-sample-locator或专用LN2监测器
- 追踪用于非CO2应用的压缩空气或N2钢瓶 → 调整参数但需验证兼容性
- 已有实时的物联网传感器集成 → 使用实际传感器API而非模拟
- 钢瓶使用基于重量的测量而非压力 → 相应修改计算逻辑
- 需要紧急气体泄漏检测 → 使用带警报的气体检测安全系统
- 管理带有自动切换功能的大型储罐装置 → 这些系统自带监测功能
相关技能:
- - 上游:equipment-maintenance-log、lab-inventory-tracker
- 下游:eln-template-creator、lab-budget-forecaster
与其他技能的集成
上游技能:
- - equipment-maintenance-log:跟踪影响消耗率的CO2培养箱维护历史
- lab-inventory-tracker:监测钢瓶库存和更换计划
- equipment-maintenance-log:记录压力表的校准日期
下游技能:
- - eln-template-creator:生成包含气体监测检查清单的实验模板
- lab-budget-forecaster:根据消耗趋势预测CO2气体成本
- waste-disposal-guide:协调空钢瓶处理与更换
完整工作流程:
每日早晨检查 → co2-tank-monitor → equipment-maintenance-log → lab-inventory-tracker → 更换计划
核心能力
1. 基于压力的耗尽预测
根据当前压力读数和历史消耗模式计算钢瓶剩余使用时间。
python
from scripts.main import calculateremainingdays, calculatedepletiontime
from datetime import datetime
当前钢瓶状态
current_pressure = 8.0 # MPa
daily_consumption = 1.5 # MPa/天
计算剩余时间
remaining
days = calculateremaining
days(currentpressure, daily_consumption)
print(f剩余天数: {remaining_days:.1f})
计算耗尽时间点
depletion
time = calculatedepletion
time(remainingdays)
print(f预计耗尽时间: {depletion_time.strftime(%Y-%m-%d %H:%M)})
公式: remainingdays = pressure / dailyconsumption
参数:
| 参数 | 类型 | 必填 | 描述 | 默认值 |
|---|
| pressure | float | 是 | 当前钢瓶压力(MPa) | 8.0 |
| daily_consumption |
float | 是 | 平均每日消耗率(MPa/天) | 1.5 |
| capacity | int | 否 | 钢瓶容量(升,10或40) | 40 |
计算方法:
remainingdays = currentpressure / daily_consumption
最佳实践:
- - ✅ 校准消耗率:基于历史数据(监测1-2周)
- ✅ 考虑使用变化:培养量大时消耗高,周末消耗低
- ✅ 在固定时间检查压力(例如每天上午9点)以获得准确趋势
- ✅ 季节性更新消耗率:培养箱使用情况可能变化
常见问题及解决方案:
问题:消耗估算不准确
- - 症状:预测的耗尽日期持续偏差数天
- 解决方案:监测2-4周的实际消耗;调整daily_consumption参数
问题:压力波动导致误报
- - 症状:因温度变化导致压力读数不一致
- 解决方案:每天同一时间读取数据;使用后让钢瓶平衡
2. 周末耗尽风险检测
识别钢瓶耗尽是否会在实验室工作人员不在场的周末发生。
python
from scripts.main import isweekend, willdepleteonweekend, calculatedepletiontime
from datetime import datetime
计算耗尽时间
remaining_days = 3.5
depletion
time = calculatedepletion
time(remainingdays)
检查耗尽是否在周末
if is
weekend(depletiontime):
print(f⚠️ 警告:耗尽时间在 {depletion_time.strftime(%A)})
else:
print(f✅ 耗尽时间在工作日:{depletion_time.strftime(%A)})
使用警报阈值检查周末风险
alert_days = 2
weekend
risk = willdeplete
onweekend(depletion
time, alertdays)
if weekend_risk:
print(🔴 严重:钢瓶将在周末耗尽!)
print( 操作:在周五前更换或安排周末值班)
周末风险场景:
| 场景 | 风险等级 | 所需操作 |
|---|
| 周六/周日耗尽 | 🔴 高 | 立即更换或安排周末值班 |
| 周一早上耗尽 |
🟡 中 | 周五下午更换 |
| 周五晚上耗尽 | 🟡 中 | 密切监测;如可能则更换 |
| 周中耗尽 | 🟢 低 | 安排常规更换 |
最佳实践:
- - ✅ 设置alertdays = 2:适用于标准工作周(周三前预警,周五更换)
- ✅ 计划周五更换:任何剩余时间<4天的钢瓶
- ✅ 创建周末值班表:用于高风险期间的关键实验
- ✅ 考虑假期安排:在长周末前延长alertdays
常见问题及解决方案:
问题:周一耗尽的错误周末警报
- - 症状:实验室重新开放时,周一早上耗尽触发警报
- 解决方案:调整逻辑或手动复核;周一早上耗尽可能可接受
问题:遗漏周五晚上耗尽风险
- - 症状:工作人员离开后,钢瓶在周五晚上耗尽
- 解决方案:特别检查周五下午5点的状态;将周五晚上视为周末
3. 多钢瓶规格支持
支持实验室环境中常用的不同CO2钢瓶规格。
python
from scripts.main import simulatesensordata
钢瓶规格
CYLINDER_SPECS = {
10: {
name: 便携式(10L),
full_pressure: 15.0, # MPa
typical_usage: 小型培养箱、备用,
duration
15_mpa: ~10天
},
40: {
name: 标准型(40L),
full_pressure: 15.0, # MPa
typical_usage: 主培养箱、高用量,
duration
15_mpa: ~40天
}
}
选择合适的钢瓶
capacity = 40 # 升
specs = CYLINDER_SPECS[capacity]
print(f钢瓶:{specs[name]})
print(f满瓶压力:{specs[full_pressure]} MPa)
print(f典型用途:{specs[typical_usage]})
计算基于容量的估算
full_pressure = 15.0 # MPa(典型满瓶压力)
daily_consumption = 1.5 # MPa/天
max
days = fullpressure / daily_consumption
print(f在{daily
consumption} MPa/天下的最大持续时间:{maxdays:.1f}天)
钢瓶规格:
| 容量 | 典型用途 | 满瓶压力 | 持续时间(@1.5 MPa/天) |
|---|
| 10L | 小型培养箱、备用 | ~15 MPa | ~10天 |
| 40L |
主培养箱、高用量 | ~15 MPa |