fix: add period_ms to linear and drift models to prevent unbounded divergence

Without period, y=k*t+b and y=base+drift_rate*t grow infinitely, which is
unrealistic for industrial simulation. period_ms makes t wrap modulo the period,
producing sawtooth patterns that simulate per-cycle behavior (e.g. tension build-up
per coil, sensor drift per shift).

TestProject/RNG/README.md

@@ -100,10 +100,13 @@ y = k·t + b，b 取自 `defaultValue`。
 
 | 参数 | 含义 | 默认值 |
 |------|------|--------|
-| k | 斜率（每周期增量） | 0.0 |
+| k | 斜率（每 tick 增量） | 0.0 |
+| period_ms | 周期（ms），t 按周期取模 | 0（无限） |
+
+`period_ms > 0` 时，t = (实际 tick) % (period_ms / 20)，模拟每周期重复的线性过程（如带钢卷取时张力逐渐增大然后释放）。`period_ms = 0` 时不取模。
 
 ```json
-"linear_slow": { "mode": "linear", "params": { "k": 0.001 } }
+"linear_slow": { "mode": "linear", "params": { "k": 0.001, "period_ms": 600000 } }
 ```
 
 #### sine — 正弦波
@@ -147,7 +150,14 @@ y = base + drift_rate·t，base 取自 `defaultValue`。模拟传感器缓慢退
 
 | 参数 | 含义 | 默认值 |
 |------|------|--------|
-| drift_rate | 每周期漂移量 | 0.0 |
+| drift_rate | 每 tick 漂移量 | 0.0 |
+| period_ms | 周期（ms），t 按周期取模 | 0（无限） |
+
+`period_ms > 0` 时形成锯齿波漂移：每个周期内从 base 线性漂移到 base + drift_rate·period_ticks，然后复位，模拟每个生产周期内的退化-复位行为。
+
+```json
+"drift_slow": { "mode": "drift", "params": { "drift_rate": 0.0001, "period_ms": 3600000 } }
+```
 
 #### csv — CSV 数据回放
 

TestProject/RNG/json/rng_models.json

@@ -3,14 +3,14 @@
     "constant_zero":  { "mode": "constant",   "params": {} },
     "normal_tiny":    { "mode": "normal",     "params": { "sigma": 0.01 } },
     "normal_med":     { "mode": "normal",     "params": { "sigma": 0.5 } },
-    "linear_slow":    { "mode": "linear",     "params": { "k": 0.001 } },
+    "linear_slow":    { "mode": "linear",     "params": { "k": 0.001, "period_ms": 600000 } },
-    "linear_fast":    { "mode": "linear",     "params": { "k": 0.05 } },
+    "linear_fast":    { "mode": "linear",     "params": { "k": 0.05,  "period_ms": 120000 } },
     "sine_ecc1":      { "mode": "sine",       "params": { "A": 5.0, "omega": 0.314, "phi": 0 } },
     "sine_ecc2":      { "mode": "sine",       "params": { "A": 3.0, "omega": 0.628, "phi": 1.57 } },
     "spike_sharp":    { "mode": "spike",      "params": { "amplitude": 50,  "probability": 0.05 } },
     "spike_mild":     { "mode": "spike",      "params": { "amplitude": 10,  "probability": 0.15 } },
-    "drift_slow":     { "mode": "drift",      "params": { "drift_rate": 0.0001 } },
+    "drift_slow":     { "mode": "drift",      "params": { "drift_rate": 0.0001, "period_ms": 3600000 } },
-    "drift_fast":     { "mode": "drift",      "params": { "drift_rate": 0.005 } },
+    "drift_fast":     { "mode": "drift",      "params": { "drift_rate": 0.005,  "period_ms": 600000 } },
     "toggle_2s":      { "mode": "bool_toggle", "params": { "period_ms": 2000 } },
     "toggle_5s":      { "mode": "bool_toggle", "params": { "period_ms": 5000 } },
     "toggle_10s":     { "mode": "bool_toggle", "params": { "period_ms": 10000 } },

TestProject/RNG/model/DriftModel.h

@@ -5,7 +5,12 @@ using json = nlohmann::json;
 
 struct DriftModel : IModel {
   float base, drift_rate;
+  size_t period_ticks;
   DriftModel(const json& params, float defaultVal)
-    : base(defaultVal), drift_rate(params.value("drift_rate", 0.0f)) {}
+    : base(defaultVal), drift_rate(params.value("drift_rate", 0.0f))
-  float evaluate(size_t t) override { return base + drift_rate * t; }
+    , period_ticks(params.value("period_ms", 0) / 20) {}
+  float evaluate(size_t t) override {
+    if (period_ticks > 0) t %= period_ticks;
+    return base + drift_rate * t;
+  }
 };

TestProject/RNG/model/LinearModel.h

@@ -5,7 +5,12 @@ using json = nlohmann::json;
 
 struct LinearModel : IModel {
   float k, b;
+  size_t period_ticks;
   LinearModel(const json& params, float defaultVal)
-    : k(params.value("k", 0.0f)), b(defaultVal) {}
+    : k(params.value("k", 0.0f)), b(defaultVal)
-  float evaluate(size_t t) override { return k * t + b; }
+    , period_ticks(params.value("period_ms", 0) / 20) {}
+  float evaluate(size_t t) override {
+    if (period_ticks > 0) t %= period_ticks;
+    return k * t + b;
+  }
 };